The Tech Humanist Show

How can deeper, more intentional listening help us stay human in an age of algorithm-driven music and AI-generated sound? Topics Covered: The connection between music and the human experience Defining and democratizing “musicality” Listening for versus listening to music The impact of corporate consolidation and streaming platforms on music discovery The difference between musical genres and industry formats How categories shape who gets heard Design flaws in music streaming and stunted musical literacy Bluegrass as a model for musical ecosystems Authenticity, AI, and the challenges of provenance in modern music The civic and democratic roles of music Practical tips for cultivating a healthy musical life Connect with Craig HavighurstWebsiteSubstack – StringTheories Episode Chapters:00:04 – Welcome and introduction to Craig Havighurst01:22 – The relationship between music and being human 04:15 – Craig’s first memorable music experience 07:28 – What is musicality and why does it matter? 11:03 – Listening for vs. listening to music 14:41 – The concept of a healthy musical diet 19:09 – The effect of industry shifts on music access 20:51 – Genres, formats, and who gets heard 25:17 – How streaming platforms affect musical literacy 33:20 – Bluegrass as a healthy musical ecosystem 34:38 – AI, authenticity, and musical provenance 44:13 – Music, empathy, and democracy 48:26 – Practical steps for intentional listening 51:34 – Closing thoughts and where to find Craig Havighurst

Are leaders thinking big enough—and human enough—in the AI era? Explore how AI and technology shape the human experience with Kate O’Neill and guest Brian Solis, Head of Global Innovation at ServiceNow. Discover the concept of cognitive Darwinism, AI transformation stories, leadership in the AI era, and how to drive growth while staying human-centric. Topics Covered:AI augmentation vs. automationCognitive Darwinism and self-awarenessCapacity and capability overhang in AI adoptionTransformation as a human storyPurposeful iteration vs. intentional innovationReturn on intelligence vs. return on ignoranceReskilling and workforce transformation case studies (IKEA & Walmart)Human-centric leadership and psychological safetyPersonal relationship with technology & digital attentionMind shifts required for future-ready leadership Connect with Brian SolisServiceNowLinkedInBrian Solis, Author at Workflow® Episode Chapters:00:04 Introduction & Guest Welcome01:00 Transformation as a Human Story02:24 The Human Story Leaders Miss in the AI Era03:06 AI’s Anti-Human Trajectory & Cognitive Darwinism04:28 AI Tax and Brain Fry05:49 AIQ: Artificial vs. Augmented Intelligence Quotient09:16 Agentic AI & Process Reinvention11:11 Grand Strategy and Leadership Mindsets15:55 Mind Shifts and Self-Awareness17:18 Book Inspiration and Becoming a Leader of the Moment20:13 Unlearning Disruption Myths in Enterprise25:16 Innovation: Creating New Value26:59 Evaluating AI Use: Efficiency vs. Net New Value31:13 Psychological Safety and Human-Centric Leadership32:28 IKEA & Walmart: Augmentation and Reskilling Case Studies38:00 Personal Relationship with Technology & Life Scale41:48 Closing Thoughts: Questions for Embracing Change43:05 Episode Wrap-Up and Farewells

Are you overwhelmed by nonstop change and wondering how to truly thrive in a world shaped by AI and information overload?Tune into the latest Tech Humanist Show episode, where Kate sits down with Frederick Marshall—gardener, CEO, and author of Thrive: The Antidote to Future Shock—to unearth how we can cultivate clarity, resilience, and actual human thriving in our tech-saturated world. Topics covered: Future shock in 2026 and its effects Common leadership misdiagnoses of burnout and overwhelm Strategies for managing information overload and uncertainty The Thrive framework: Priorities, obligations, and noise Observations from top performers across industries Design by subtraction and life “ecosystems” The Super 8 factors for thriving AI as collaborator and human-AI symbiosis Responsible and human-centered AI adoption at work Building thriving business and personal ecosystems Meaning, contribution, and human adaptability Connect with Fred Marshall Episode Chapters: 00:04 Introduction and future shock today01:11 Fred Marshall’s background and philosophy02:07 Defining future shock in the modern era04:10 How leaders misdiagnose overwhelm05:31 AI tools and strategic alignment08:07 Design by subtraction—managing time and attention11:05 What top performers do differently12:57 Assumptions, autopilot, and learning15:11 The problem Thrive solves for leaders16:06 Role of AI and personalizing technology for growth18:47 Accelerating learning with AI—cognitive friction21:20 Systems thinking for complexity22:04 The “Super 8” life factors27:02 Meaning, contribution, and purpose30:46 Thriving organizations and business ecosystems33:08 Speed vs. thoughtful strategy in fast-changing times41:43 Human-AI partnership and neural net overlap44:03 What leaders should believe about humans46:51 Why people give hope for the future48:38 Closing and where to find Thrive

How can leaders harness AI in their communication without losing their authentic human touch? Topics covered: The meaning and value of authenticity in leadership The risks and rewards of using AI for executive communication Building trust and executive presence in an AI-mediated world The difference between confidence and certainty for leaders Coaching for on-camera executive presence Communicating vulnerability and clarity under uncertainty The “anti-pitch” approach to introductions Ethical use of AI in relationship building Practical steps for leaders to leverage AI responsibly Connect with: Allison ShapiraWebsiteLinkedInInstagram Episode Chapters: 00:04 Introduction and overview of the Tech Humanist Show00:32 Allison Shapira’s background: Opera to executive communication03:39 Why AI for the Authentic Leader—leadership problems and urgency of the moment06:09 Defining authenticity in a leadership and AI context08:40 AI’s impact on executive presence—when the tools are “better than us”11:27 Tension between what AI rewards and what leadership requires14:37 Navigating ambiguity and nuance in leadership communication18:33 Projecting confidence versus certainty as a leader20:40 Communicating clarity and maintaining trust amid uncertainty22:27 Over-explaining, under-explaining, and AI’s potential impact23:49 Executive presence on camera and its evolving demands26:27 Societal expectations of leaders’ communication skills28:42 Bringing authority and warmth on camera; avoiding “performance” of leadership31:09 The “anti-pitch” idea—rethinking introductions in a tech-driven world34:51 Ethical use of AI in relationship building and values alignment37:18 Practical steps: What leaders should start (and stop) doing with AI38:56 Final takeaways and how to lead authentically in an AI-shaped world40:01 Outro and credits

How can organizations confront their histories of harm before being forced to reckon with them? In this episode, Kate O’Neill is joined by Sarah Federman as they explore the crucial difference between deferred and acknowledged harm, and what real accountability can look like—especially amid today’s AI boom. Topics covered: Reckoning work vs. apologies, CSR, and ESG Corporate accountability for historical harm Inaction versus action in organizational ethics Power asymmetry in AI data center expansion Community impact and responsible leadership The pattern of corporate reckoning across eras Acceleration of accountability in the digital age Building an ethical frame within organizations First moves toward genuine corporate reckoning Maintaining hope while working in harm and accountability Connect with Sarah FedermanWebsiteLinkedInInstagramSarah’s new book: Corporate Reckoning: How Businesses Can Address Historical Wrongs Episode Chapters: 00:04 Introduction and Host Welcome00:35 Guest Introduction: Sarah Federman01:47 Defining Reckoning Work03:00 The Interval Between Harm and Reckoning04:15 The Personal Connection to Reckoning05:27 Deferred Harm and Corporate Inaction06:57 Action, Inaction, and Neutrality08:20 AI Data Centers, Power Asymmetry, and Community Impact10:45 Protest, Creativity, and Avoiding Lazy Solutions12:18 Patterns of Reckoning Across Industries13:03 Ethical Acceleration and Real-Time Accountability15:13 Emergent Accountability Mechanisms16:05 Practical Steps for Responsible Tech Leadership18:22 Institutional Change vs. Performing Change21:11 History, Hope, and The Long Arc of Accountability22:54 Book Details and Where to Connect23:59 Closing and Credits

Are you overwhelmed at work but can’t pinpoint why? Discover how “thought load”—not just workload—may be sabotaging productivity, innovation, and well-being in the tech-driven workplace. Kate O’Neill sits down with Liane Davey—the brilliant mind behind the new book Thought Load—to unpack why work isn’t working for so many of us. Topics covered: The concept of thought load and its core components Differences between workload, cognitive load, and thought load How technology and AI impact cognitive and emotional burdens The productivity trap and measuring outcomes vs. outputs Effects of constant digital interruptions on attention and energy The role of feedback and judgment in corporate settings Emotional and cognitive impacts of always-on workplace culture Energy reserves as an operational constraint Organizational interventions to reduce thought load The outcome of conflict debt in high thought load environments Designing safer, more productive workplace conflict Tech tools as both solution and source of mental drain Hope for more innovative and present organizations Connect with Liane DaveyWebsiteInstagramLinkedIn Episode Chapters:00:00 – Introduction and background 00:43 – What is “thought load”? 02:15 – Equation: Cognitive and emotional demands over energy reserves 03:38 – The neuroscience of “treacherous triad” 04:05 – Why workload and thought load are not the same 05:22 – AI’s surprising effects on thought load 06:27 – Rethinking productivity: The activity-output-outcome framework 09:08 – Technology’s role in multiplying and draining cognitive demand 10:30 – Why managers reward “responsiveness”—and why that’s a trap 13:14 – When tech reduces vs. increases cognitive demands 15:57 – Tech as an emotional burden amplifier 17:02 – The misunderstanding of feedback vs. judgment 18:54 – Social pain and at-scale judgment in digital workplaces 23:20 – The operational significance of energy reserves 28:06 – High-leverage interventions for organizational energy 33:36 – Conflict debt as an outcome of high thought load 35:20 – Making conflict safer and more productive 40:15 – What a tech humanist organization could look like 42:19 – Closing thoughts and hope for the future 43:26 – Book release and where to connect

Are we truly understanding global trade, or just reacting to headlines? Step into a timely, eye-opening conversation on trade, geopolitics, and the systems shaping our global economy with Dmitry Grozoubinski, hosted by Kate O’Neill. Topics Covered: Why global trade is more misunderstood than ever The real forces driving today’s trade tensions and disruptions How policy, politics, and economics intersect in trade decisions Common misconceptions about tariffs, supply chains, and globalization The role of trade experts vs. media narratives How trade impacts everyday life more than we realize The challenge of communicating complex global systems simply What recent global events reveal about the fragility of trade systems The future of globalization: shifting, not disappearing Why understanding trade is critical in today’s world Connect with Dmitry GrozoubinskiWebsiteLinkedInDmitry’s Book: Why Politicians Lie About Trade Episode Chapters: [00:00:04] Introduction to the Tech Humanist Show [00:00:30] Guest Introduction: Dmitry Grozoubinski [00:01:15] Why Trade Is Suddenly Front and Center [00:03:40] Misconceptions About Global Trade [00:06:05] How Trade Policy Actually Works [00:08:50] Tariffs, Politics, and Public Perception [00:12:10] Media Narratives vs. Trade Reality [00:15:25] Supply Chains and Global Interdependence [00:18:40] Trade Tensions and Geopolitical Shifts [00:22:05] Why Trade Is Hard to Communicate [00:26:30] The Fragility of Global Systems [00:30:10] The Future of Globalization [00:33:45] Why Trade Literacy Matters [00:36:20] Where to Connect with Dmitry Grozoubinski [00:36:45] Closing and Credits

Are we letting technology shape our lives, or are we actively choosing how it fits in? Dive into an essential conversation about techno-chauvinism, AI’s real-world impacts, and what responsible innovation looks like with Meredith Broussard. Topics Covered: The difference between technological and social decisions The AI hype cycle and shifting perceptions of AI Techno chauvinism and using the right tool for the task The limits of technology in daily life and digital detox trends Hollywood’s influence on how we imagine AI Generative AI: how it works, dataset concerns, and hallucinations Unshedification and the realities of deploying generative AI The challenges of responsible AI and data governance Environmental impacts of data centers and generative AI Accountability and diffused responsibility in tech What “better” looks like for technology and society Connect with Meredith BroussardWebsiteLinkedIn Meredith’s book: ”More than a Glitch – Confronting Race, Gender, and Ability Bias in Tech” Episode Chapters: [00:00:04] Introduction to the Tech Humanist Show[00:00:30] Guest Introduction: Meredith Broussard[00:01:22] Stories We Tell Ourselves about AI[00:03:50] Biases Embedded in Technology & Techno Chauvinism[00:05:27] The Digital Shift and the Rise of Tech Dependency[00:08:48] Bans, Restrictions, and Nuanced AI Policy[00:10:44] AI Misconceptions vs. Hollywood Influences[00:14:14] Explaining Generative AI in Plain Language[00:17:37] Decision Making and the Fragility of AI Systems[00:20:11] The Realities of Generative AI in the Workplace[00:23:26] Responsible AI and Governance[00:29:03] Longevity and Constant Change in AI Models[00:31:25] AI Safeguards and Global Concerns[00:33:00] Accountability in Distributed Technology[00:34:43] Environmental Impact of Data Centers[00:38:49] What “Better” Looks Like for Tech & Society[00:41:21] Where to Connect with Meredith Broussard[00:41:40] Closing and Credits

What happens when AI makes us more creative—does it also make us more human? Dive into this episode to explore how blending technology and creativity can unlock new potential for individuals, teams, and businesses. Topics covered: Super Creativity: Augmenting human creativity with AI Unlocking creativity in “hidden figures” and backstage roles AI’s impact on solo creators vs. teams and executives Examples of AI expanding creative possibilities (beyond speed) Ethical questions around AI, data, and compensation Skill atrophy and organizational trends AI-powered empathy and psychometrics for presentations The importance of curiosity and space for creativity Practical ways to be more super creative Global perspectives and learning from diverse industries Connect with James TaylorWebsiteYouTubeLinkedInInstagram Episode Chapters: 00:00 – Welcome and Introduction 00:17 – The Promise of AI: What Will We Do with More Time? 00:28 – Meet James Taylor and “Super Creativity” 01:43 – What Is Super Creativity? 03:12 – Human, Team, and Human+Machine Creativity 03:36 – Aha Moment: Highlighting Backstage Creative Heroes 05:14 – Expanding Creativity through AI—Real World Examples 06:13 – Centaur and Cyborg Work Models 07:25 – The Future: Billion Dollar One-Person Businesses 08:20 – Purpose, Ethics, and Creating the Future 09:15 – Solo vs. Teams: Where Is AI Unlocking Creativity? 10:08 – AI Use Cases—from Coding to Healthcare 11:27 – The Transformative Potential of AI 12:52 – Essential Human Skills: Creativity and Critical Thinking 13:16 – AI + Psychometrics in Presentations 14:48 – Using AI for Data-Informed Empathy 16:18 – Digital Twins, Creative Abrasion, and AI Mentoring 18:37 – Boundaries: What James Taylor Won’t Use AI For 20:21 – Skill Atrophy and Tools of Consumption 21:41 – Physical Environment’s Impact on Creativity 23:05 – Values, Ethics, and AI Data Sovereignty 26:09 – AI in Organizations: Productivity, Headcount, and Ethics 27:56 – Practical Norms: Guardrails for AI, Facial Recognition, and Smart Glasses 29:47 – Creativity and Global Perspectives 30:42 – Staying Original and Leveraging AI as a Team 32:14 – Cross-Industry Learning and Boundary Crossing 33:44 – Super Creativity Applied 34:56 – Learning from Domain Experts and Other Speakers 35:26 – Books as Powerful Information Devices 36:40 – Practical Steps for Super Creativity 40:12 – Where to Find James Taylor and Closing Remarks

What does it really mean to build ethical and inclusive AI—and who gets to decide which problems we solve with technology?Dive into this conversation with Tess Posner as she and Kate O’Neill explore how education, ethics, and diverse voices shape the future of AI. Topics covered:The intersection of AI, education, and responsible technology Early experiences shaping ethical perspectives in tech Critical thinking versus just coding Unintended consequences and ethical frameworks Representation, diversity, and AI bias Organizational approaches to AI ethics Incentives and policies for responsible AI Scaling and challenges of AI literacy Adapting education for future AI challenges Building adaptive organizational cultures Hopeful signals and the next generation of technologists Connect with Tess PosnerAI 4 All WebsiteLinkedIn Episode Chapters:Exploring the Heart of Responsible AI [00:00:05]Early Influences and Tech for Human Flourishing [00:01:16]The Role of Ethics in Technology Education [00:03:33]Embedding Critical Thinking Over Code [00:06:58]Asking Unintended Consequence Questions [00:10:29]Lived Experience Shaping AI Projects [00:13:20]How Diversity Shapes Problem-Solving in AI [00:14:39]Organizational Incentives and Systemic Change [00:18:30]AI Literacy: Scaling, Challenges, and Surprises [00:28:34]Adapting Education and Future Perspectives [00:35:25]Hope, Human Alignment, and Signals to Watch [00:42:14]

What happens when technology doesn’t just restore light sensitivity, but actually brings back the ability to perceive forms, patterns, and meaning for those who’ve lost their sight? Dive into this episode as we explore how breakthroughs in retinal prostheses are reshaping human experience. Topics covered: The difference between light sensitivity and form vision How the Prima retinal prosthesis works Wireless design and integration with natural vision Selective stimulation and preserving retinal code Challenges in encoding vision and lessons from animal to human trials Patient perspectives and life impact Upgrading implants and future breakthroughs Comparing biological and electronic restoration approaches The meaning of vision for identity, independence, and connection The hope and future of vision restoration worldwide Connect with Professor Daniel PalankerStanford MedicineLinkedIn Episode Chapters: 00:05 Introduction to The Tech Humanist Show 00:17 Surprises in clinical trials and complexity of vision 00:41 The impact of vision and restoration 01:14 Episode arc and Professor Palanker’s breakthrough 02:02 Welcoming Professor Daniel Palanker 02:10 Prima system restores form vision 02:55 Distinct lived experience between light sensitivity and form vision 03:10 Examples of restored capability and simultaneous vision 04:49 How Prima works at the chip-glasses-human interface 05:01 Disease background: Age-related macular degeneration 07:01 External augmented reality glasses explained 08:21 Why Prima is wireless 10:13 Implant design and surgical simplicity 11:21 Preserving peripheral vision and the “don’t fix what’s not broken” philosophy 12:53 Selective retinal stimulation and proper encoding 14:37 Vision processing features and their importance 17:54 Brain’s interpretation of signals and meaning 19:22 Challenges of encoding further from the source 21:58 Journey: Concept to clinical implementation 26:17 Impact for patients—stories and real-world uses 28:03 Resolution, experience, and what higher resolution unlocks 31:20 Testing new indications and upgradable implants 32:32 Biological vs. electronic approaches and collaboration 35:13 Philosophical meaning of vision for identity and connection 37:26 Hope for the future of vision restoration 40:06 Market future and product evolution 40:39 Episode wrap-up and gratitude

What does it truly mean to see—and how close are we to restoring sight for those who have lost it? Dr. Lauren Ayton shares her journey at the frontier of vision restoration, from leading Australia’s first bionic eye trial to navigating the ethical, scientific, and personal dimensions of bringing sight back. Topics covered: The meaning of “seeing” and how the brain constructs vision Personal motivations behind vision restoration research The evolution of bionic eyes and retinal implants From basic science to technological intervention in vision Ethical dilemmas in emerging vision restoration technologies Patient experiences regaining sight and decision-making in trials Challenges of public perception vs. scientific reality Incremental innovation vs. paradigm shifts in medical science Importance of access, equity, and foundational care Designing technology for real human needs and capabilities Connect with Dr. Lauren AytonLinkedInCentre for Eye Research Australia Episode Chapters:00:00 – Introduction: What does it mean to see?01:45 – Dr. Lauren Ayton’s personal journey and driving questions03:35 – Career: Academia, startup life, and innovation in vision science05:27 – The complexity and subjectivity of vision07:08 – What happens when vision is restored? Patient experiences08:52 – Scientific breakthroughs that made sight restoration imaginable10:37 – The science behind bionic eyes, retinal implants, and gene therapy12:30 – Suprachoroidal approach in Australia’s first in-human bionic eye trial13:59 – Ethics of risk, hope, and consent in experimental medicine15:56 – Supporting patients through uncertainty and high-stakes decisions17:26 – Managing expectations: Public perception vs. current scientific reality20:08 – Incremental change, paradigm shifts, and multidisciplinary collaboration22:00 – Translation: From brilliant ideas to real-world impact24:06 – Access, equity, and the bigger picture of vision care25:48 – Human-driven innovation: Designing for dignity, capability, and real needs27:30 – Lessons from vision science about clarity, perception, and what we miss28:52 – The future: What’s possible in 10–20 years of vision restoration30:19 – Ethical reminders for the path ahead31:44 – Dr. Lauren Ayton’s takeaways: Centering humans and aiming high32:57 – How to support or get involved in vision research33:45 – What’s keeping Dr. Lauren Ayton hopeful34:46 – Closing and credits

What does it truly mean to see—and how can technology restore one of our most essential human senses? In this episode, Dr. José-Alain Sahel joins Kate O’Neill to reveal the breakthroughs in vision restoration, and how these innovations are shaping the future of human experience. Topics Covered: Optogenetic therapy and vision restoration Artificial retina technology Scientific and patient journey of regaining sight Convergence of AI, neuroscience, and medical devices Philosophy of sight and perception Natural vs. artificial boundaries in biotech Balancing innovation and patient safety Strategies for treating different stages of blindness Meaning and legacy of vision technologies Connect with: Dr. José-Alain SahelThe Eye & Ear Foundation of PittsburghUPMC Enterprises Episode Chapters: 00:00:05 – Welcome to the Tech Humanist Show 00:01:14 – Introduction of Dr. José-Alain Sahel 00:02:29 – 2021 Optogenetic Vision Restoration Breakthrough 00:02:46 – Recent Artificial Retina Breakthrough (2025) 00:03:47 – The First Patient’s Experience 00:06:31 – Explaining the Technology: Algae Proteins & Retinal Cells 00:09:00 – Scientific Process: Failures, Persistence, and Progress 00:10:13 – How the Goggles Work 00:11:03 – Training the Brain to Interpret New Visual Input 00:11:24 – The Patient’s Story: From Blindness to Seeing Again 00:16:07 – Philosophical Perspective on Sight and Perception 00:20:02 – Measuring Human Experience in Vision Restoration 00:23:26 – Natural vs. Artificial: Ethics and Human Augmentation 00:26:19 – Balancing Innovation with Patient Safety in Clinical Trials 00:29:53 – Complementary Strategies for Blindness Treatment 00:31:34 – Vision, Meaning, and Human Flourishing 00:34:41 – Where to Find More About Dr. Sahel’s Work 00:35:49 – Episode Credits & Outro

What if the real future-of-work crisis isn’t about technology replacing humans—but organizations pushing out workers just when their wisdom is needed most? In this episode, Kate O’Neill and Dan Pontefract explore the urgency of rethinking age in the workplace, longevity, and designing meaningful work for six-decade careers. Topics covered: Age and longevity in the workforce Fluid vs. crystallized intelligence The demographic “age debt” challenge AI and human intelligence collaboration Multidirectional, time-flexible careers Rethinking succession planning and wisdom transfer Designing learning ecosystems Evolution of purpose throughout a career Concrete steps leaders can take to turn age debt into dividends Connect with Dan PontefractWebsiteLinkedInYouTubeInstagramTikTokDan’s new book – “The Future is Grey” Episode Chapters:00:05 Welcome and Introduction00:36 The Real Crisis: Age and Work02:01 Dan’s Wake-Up Call: Fired at 5003:39 Longevity vs Organizational Blind Spots06:10 Lessons from Japan: The Age Canary07:14 Chief Longevity Officers: Action or Gray Washing?09:42 Fluid & Crystallized Intelligence in the Age of AI14:10 Rivers, Rocks, and Rubies: Beyond Generational Stereotypes18:09 Building Multi-Directional Careers22:00 “Gray” Means Embracing the In-Between22:44 Succession Planning vs Wisdom Transfer26:46 Learning Ecosystems for All Ages30:06 How Purpose Evolves Over Time33:01 3 Steps for Leaders: Actionable Guidance37:11 How to Use Rivers, Rocks, & Rubies in Practice39:11 Dan’s Personal “Gray” Future42:01 What’s Next for Dan and Final Thoughts43:26 Closing and Where to Connect

What if the “soft skills” we often overlook are actually the most strategic—and essential—in the age of AI? In this episode, leadership expert Dr. Bushra Khan and host Kate O’Neill explore the power and business impact of emotional intelligence, challenging outdated leadership myths and redefining what skills matter most for future-ready teams. Topics Covered: Why “soft skills” should be called “strategic skills” Emotional intelligence as a leadership framework Evidence-based emotional intelligence in organizations Critical thinking, persuasion, and influence for tech leaders Challenging the myth of micromanagement Culture’s impact on leadership assumptions Candor vs. bluntness in high-stakes communication Balancing bravery and kindness in decision making Practical approaches to EI skill-building in companies Finding hope and optimism in leadership Connect with: Dr. Bushra KhanLinkedinWebsite Episode Chapters: 00:00:05 – Welcome & redefining soft skills 00:00:37 – Emotional intelligence as leadership 00:01:20 – Reframing skills for a tech-driven world 00:01:55 – Why “soft” is inadequate and damaging 00:02:49 – Strategic skills vs. technical expertise 00:04:33 – Critical thinking & real-life practice 00:05:43 – Evidence-based EI: Research & impact 00:06:05 – Describing great leaders (EI in action) 00:08:47 – EQ vs. IQ & technical skills 00:11:06 – The emotional intelligence framework 00:12:34 – Making EI accessible in everyday life 00:13:24 – The myth of micromanagement 00:15:46 – Coaching, mentoring, and trust 00:17:13 – Cross-context skills: work, life, community 00:17:43 – Leadership mental models across cultures 00:18:35 – Cultural differences in trust and hierarchy 00:22:23 – Candor, clarity, and high-stakes communication 00:23:14 – Building trust for high-pressure moments 00:26:33 – Balancing bravery and kindness 00:29:29 – EI is not just being nice—using frameworks 00:31:34 – Practical “how” for applying EI 00:32:07 – Why companies should invest in human skills 00:32:41 – Making skills training bite-sized and evidence-based 00:35:44 – Key takeaways & actionable advice 00:36:23 – Finding hope and optimism in leadership 00:39:53 – Gratitude and closing remarks

What are the questions only humans can ask in an age where AI seems to have all the answers? In this episode, Kate O’Neill and futurist Ben Pring dive deep into the uniquely human skills and judgments that technology can’t replicate, and explore how leaders and organizations can navigate uncertainty, ask better questions, and shape a more human-centered future. Topics covered:Placing today’s AI advancements in historical context How technology replaces skill with judgment The value of asking better questions in an AI-driven world Why leaders avoid tough decisions about humans vs. machines How incentives and alignment shape organizational outcomes The policy gaps at the intersection of technology, strategy, and labor Distinguishing human creativity from AI-generated “slop” How to maintain humanity and funkiness in a synthetic content flood Hope and optimism for the future of work and technology Connect with Ben Pring: benpring.com Episode Chapters:00:00:05 – Welcome to the Tech Humanist Show 00:00:18 – The Human Ability to Ask the Next Best Question 00:00:32 – Computers Are Useless: Asking the Right Questions 00:01:05 – Introducing Ben Pring 00:02:21 – Historical Context for Today’s AI Moment 00:04:47 – Technology: Replacing Skill with Judgment 00:08:14 – What Leaders Should Be Asking in an AI-Powered World 00:13:08 – Why Leaders Avoid Tough Questions About Automation 00:16:13 – Decision-Making in Times of Uncertainty 00:19:10 – Distinguishing Priorities from Trivialities 00:24:22 – Aligning Incentives and Unintended Consequences 00:25:41 – Have We Gotten Better at Taming the Monster? 00:29:26 – The Most Important Policy Questions We’re Not Asking 00:33:59 – The Car as a Parallel: Infrastructure and Human-Centric Design 00:36:21 – What Remains Distinctly Human in a Synthetic Content World 00:41:01 – Invention, Funkiness, and Problem-Solving 00:42:46 – Hope and Optimism for the Future 00:49:03 – Closing and Where to Find Ben Pring

What if climate action and economic growth aren’t at odds—but actually deeply aligned? In this episode, Kate O’Neill sits down with Tom Chi to challenge conventional thinking about climate solutions, innovation, and the future of planetary restoration. Topics Covered: The emotional impact of witnessing coral reef collapse Reimagining climate action through the lens of both ecology and economy Lessons from Google X: rapid prototyping and low-cost innovation How Google Glass shaped the understanding of visual information and human experience Insights into planetary restoration and urgent timelines for action The concept of “Climate Capital” and investment strategies for sustainability Aligning ecological wins with economic incentives Overcoming barriers in climate-tech: capex inertia and effective policy Interconnectedness and its influence on business and technology Innovative approaches for sustainable material management Connect with Tom Chi:LinkedInAt One Ventures Website Episode Chapters: 00:00:05 – Welcome & Introduction to the Tech Humanist Show 00:00:15 – Tom Chi on Reef Collapse and Global Tragedy 00:00:43 – Rethinking Climate Action: Ecology vs. Economy 00:02:15 – Conversation Kickoff: Meet Tom Chi 00:02:36 – Google X, Rapid Prototyping, and Hardware Innovation 00:06:24 – Augmenting Human Vision: Google Glass Discoveries 00:13:08 – From Tech Innovator to Planetary Restoration 00:16:33 – The Gravity of Coral Loss & Civilization-Scale Decisions 00:19:47 – Becoming Net Positive to Nature: NE Ventures Approach 00:21:01 – What “Climate Capital” Really Means 00:27:01 – Structuring Climate-Tech Investments & Timelines 00:28:57 – Advice for Funders: Overcoming Green Premiums 00:33:15 – Interconnectedness: Tech, Nature, and Business 00:38:43 – Building Lasting Systems with Nature 00:39:13 – The One Law to Accelerate Climate Solutions 00:47:21 – Empowering Change: Rates Not States 00:47:30 – Book Release: Climate Capital 00:48:17 – Closing Remarks & How to Connect

What if the secret to solving your organization’s toughest problems was thinking like a 10-year-old? Discover how childlike creativity and fun can reframe complex business challenges, spark innovation, and drive real results. Topics Covered: Childlike thinking for organizational problem-solvingPlayful penalties to boost accountabilityStorytelling and translating complex issues for kidsChange management through unbiased perspectivesDementia care and deepfake technology solutionsMechanisms for creativity: no rules, have fun, do good, no shameDesigning inclusive, impactful brainstorming sessionsBridging playfulness and business gravitasApplying kid-inspired thinking to AI and executive decisionsKeeping curiosity and creative practice alive in organizations Connect with Bas Warmerdam:ConsultingKids.comLinkedIn Episode Chapters00:00:05 – Welcome & Intro to the Tech Humanist Show00:00:17 – “Playful Penalties” concept and team accountability00:00:41 – Bas Warmerdam’s work with Consulting Kids00:01:50 – Approach and methodology using children as junior consultants00:03:38 – Reframing collaboration problems through childlike solutions00:04:24 – Implementing playful penalties and organizational impact00:06:02 – The “Thinking Like a Child for Professionals” process00:08:27 – Bringing executives into the classroom and change management benefits00:09:23 – Storytelling for complex issue translation00:12:14 – Mechanisms for leaders to use childlike thinking in their teams00:15:09 – Four key thinking mechanisms from kids00:15:50 – Example: Dementia care and “no rules” thinking00:18:28 – How professionals can integrate fun and purpose00:19:55 – Embracing “no shame” in creative business solutions00:20:41 – Creating inclusion for quiet and underrepresented voices00:22:03 – Reintegration: Bringing creative ideas into business practice00:24:21 – Childlike thinking for AI-related decisions00:26:55 – Using kid-driven creativity to challenge AI authority00:28:40 – Sustaining childlike thinking post-consulting00:30:41 – Keeping curiosity sharp and connecting at home00:32:19 – How to connect with Bas Warmerdam and Consulting Kids00:32:55 – Closing remarks and credits

What if the future of work means being present without actually “being” there? In this episode, Kate O’Neill and Cortney Harding dig into how AI, spatial computing, and XR are quietly reshaping both our work and our very definition of human value, beyond the headlines and hype. Topics covered:The transformative power of spatial computing and XR beyond the AI buzz How enterprises are quietly adopting XR for training and productivity “Metaverse” vs. “Metaphysical”: the next evolution of immersive tech Redefining human strengths and “non-machine premiums” in the AI era How AI and XR can foster inclusion and overcome workplace bias Practical pilots for leaders: headset days, policies, and workflow innovations Why employee and consumer satisfaction metrics matter more than ever Predictions for seamless, reality-blending experiences in the next five years Connect with: Cortney Harding Episode Chapters00:00:05 – Welcome to The Tech Humanist Show 00:00:17 – Premium human strengths in an AI-driven workplace 00:00:28 – Cortney Harding on underestimating XR’s impact 00:01:32 – What’s quietly evolving in XR beyond AI hype? 00:02:01 – XR in the mainstream and the interconnected tech ecosystem 00:04:05 – The underreported impact of XR in enterprise and education 00:05:32 – From “metaverse” to “metaphysical”: reframing the future 00:09:00 – Extended reality, AI, and rethinking collaboration 00:11:25 – Developing non-machine premiums to stay ahead of AI 00:13:47 – Four “E”s where humans have the edge: Emotion, Enhancement, Experience, Ego 00:18:10 – Meeting people where they are: designing human-centered spatial experiences 00:21:01 – Frictionless experiences, seamless recommendations, and what’s next 00:22:24 – When AR/VR is actually worth it (and when a website is plenty) 00:24:31 – Aligning AI with organizational and human goals 00:26:11 – Creating a permission structure for meaningful AI use at work 00:31:11 – The shift from hours worked to task-based value 00:36:45 – One pilot for the future: “Headset day” at work 00:39:18 – Inclusion, avatars, and telling the tech story differently 00:40:29 – Lightning round: best, worst, and most promising XR use cases 00:42:53 – Five-year forecast: immersive experiences as everyday reality 00:43:51 – Where to find “The Spatial Race” and final thoughts

What’s stopping legacy companies from becoming the next Airbnb or Amazon—and how can they unlock platform thinking to transform their assets into thriving ecosystems? Dive into how established organizations can use the “Digital Phoenix” effect to fuel innovation, leverage their existing advantages, and reshape value creation with cutting-edge insights from the world of platforms. Topics covered: Platform business models and value creationPlatform thinking vs. traditional business models The “Digital Phoenix” effect and leveraging idle assets Case studies: Telepass, EasyPark, airports, and Chipotle Overcoming barriers to platform transformation Internal platforms and cross-functional collaboration The impact of AI and generative AI on organizations Employee engagement and organizational change Shifting from customer-centricity to value architecture Scaling, flexibility, and regeneration benefits of platforms Connect with Daniel & Tommaso:Website: PlatformThinking.EULinkedIn: Daniel Trabucchi // Tommaso Buganza Episode Chapters00:00:05 – Introduction and welcome 00:00:33 – The rise of platform companies and industries reshaped 00:01:38 – AI’s role in internal platforms and collaboration 00:02:02 – Guests’ background and partnership 00:02:29 – The Digital Phoenix Effect and business transformation 00:04:16 – The Phoenix analogy and legacy company opportunities 00:04:43 – Telepass case study: from legacy to platform 00:05:58 – Overcoming the chicken-and-egg problem 00:07:39 – Idle assets: a startup advantage for legacy firms 00:08:47 – Defining platforms: do both sides need to be tech-centric? 00:09:18 – Types of users and value creation differences 00:10:09 – Legacy firms, tech, and two-sided value 00:12:36 – Nontraditional examples: airports and value creation 00:14:12 – Chipotle’s farmer market: a pandemic case 00:17:11 – Mindset shifts: sustainability, regeneration, and platform transformation 00:19:09 – Barriers to platform adoption: mindset, complexity, and value 00:23:57 – From customer shoes to value architect’s perspective 00:25:10 – Reshaping organizations: multiple customer mindsets 00:27:23 – Common worries of business leaders 00:29:41 – Benefits for companies making the leap 00:33:25 – Organizational change and employee engagement 00:34:14 – Leading innovation and internal platform value 00:36:12 – Creating a win-win within organizations 00:38:26 – AI’s evolving role in platform thinking 00:40:57 – Internal collaboration and GenAI’s sliding doors 00:42:49 – Where to find the guests and resources 00:44:03 – Show credits and closing

How can AI and innovation transform not just the business side of sports, but create truly human-centered fan experiences? In this episode, Christa Stout, the Chief Strategy and Innovation Officer for the Portland Trailblazers, talks with Kate O’Neill about building people-first strategies in professional sports, using AI to impact real human experiences, and lessons in innovation from around the world. Topics covered: The evolving role of Chief Strategy and Innovation Officer in sports Balancing business value with fan, community, and employee impact Approaches to meaningful innovation and international development lessons Building and implementing AI strategy in a sports organization Change management and centering real people in organizational change How generative AI unlocks human potential and personalizes fan engagement Organizational metrics for innovation, inclusion, and impact Upskilling employees and culture change for AI adoption Creating frictionless, joyful fan experiences with technology Connect with Christa StoutPortland Trailblazers WebsiteLinkedIn Episode Chapters00:00:05 – Introduction to the Tech Humanist Show & Guest Overview00:01:33 – The Scope of Strategic and Innovation Leadership in Pro Sports00:02:58 – The Rise of Strategy Roles & Future-Focused Planning00:05:42 – What Makes an Innovative Sports Team?00:07:23 – Lessons in Innovation from International Experience00:09:16 – Change Management: Combining Theory and Impact00:14:54 – Embedding AI Strategy: From Curiosity to Company-Wide Change00:19:15 – Real-World Results: AI’s Impact on Employee and Fan Experiences00:22:38 – Humanizing AI: Where Tech Enables Personal Touch00:26:18 – Redefining “Value” in Sports Organizations00:29:38 – Evolving Metrics and Exponential Possibilities with AI00:32:42 – Building Employee Buy-In and Upskilling for AI Adoption00:35:01 – Tools & Anticipated Changes for the Future of Sports Innovation00:37:25 – What True Innovation Could Mean for the Sports Experience00:39:46 – Closing Thoughts, Where to Connect, and Outro

What does it really take for organizations to thrive in an era of constant disruption and rapid technological change? In this insightful episode of the Tech Humanist Show, host Kate O’Neill sits down with innovation strategist Greg Verdino to explore the critical role of adaptability in modern business. Drawing from their experiences with digital transformation and the development of the ADAPT Manifesto, Greg Verdino shares hard-won lessons on why “always-on” adaptation, curiosity, and investing in future-readiness are more essential than ever. Topics Covered:The origins and goals of the ADAPT Manifesto Why most transformation projects fail The essential values and principles of adaptability Common barriers to organizational adaptation The importance of investing in both technology and people How AI is reshaping organizational structures and workflows The difference between reaction and strategic response Balancing innovation and tradition (“the power of and”) The need for systems thinking in leadership Practical tips for fostering adaptability, curiosity, and unlearning Connect with Greg Verdino:WebsiteLinkedInYouTube“Never Normal: Uncommon Ideas for Leaders Who Won’t Settle for the Status Quo” Episode Chapters00:00:05 – Welcome to The Tech Humanist Show – Kate O’Neill introduces the show00:00:51 – How Kate and Greg met: the “Super Team” and curiosity for new technology 00:02:53 – Why adaptability is the key business skill today 00:03:30 – Why digital transformations fail and the birth of the ADAPT Manifesto 00:06:14 – The ADAPT Manifesto values and principles explained 00:10:01 – “Fund the future”: investing in people, processes, and tech 00:11:36 – Common pitfalls in funding innovation and transformation 00:15:13 – Structuring for change in the era of AI 00:21:33 – What gets in the way of adaptation? 00:25:59 – Transformation vs. innovation and keeping up with change 00:30:31 – The lesson of Jenny’s Ice Cream: balancing novelty and consistency 00:32:01 – “The power of and” and avoiding either/or thinking 00:34:12 – The danger of chasing every shiny object (reaction vs. response) 00:36:31 – Trends shaping the next waves of adaptation 00:41:06 – Practical tips: being curious, unlearning, and hands-on learning 00:47:13 – Personal examples of unlearning 00:52:39 – Where to connect with Greg Verdino 00:53:44 – Show credits and wrap-up

What truly separates successful AI adoption from mere “execution theater”? In this episode host Kate O’Neill sits down with AI transformation leader Deepika Chopra to explore the critical—and often overlooked—dimension of human readiness in AI adoption. Drawing from her experience leading major AI and digital initiatives at Fortune 500 companies and startups alike, Deepika Chopra breaks down the “alignment gap”—the persistent disconnect between what AI can deliver and what organizations are actually prepared to embrace. Topics covered: AI literacy and organizational trust The “alignment gap” in AI transformation Execution theater vs. genuine adoption Measuring human readiness: The HAAS (Human AI Alignment Score) Culture’s role in successful AI implementation Differences between startups and enterprises in AI adoption Practical frameworks for leaders to assess and cultivate readiness Hopeful outlooks on AI’s human impact Connect with Deepika Chopra Website: movefirstalignfast.comLinkedIn: Deepika Chopra Episode Chapters00:00:05 – Welcome and show introduction 00:00:17 – Getting AI literacy and trust within organizations 00:02:18 – The alignment gap: definitions and implications 00:03:38 – Why do organizations get stuck in the alignment gap? 00:04:51 – Real-world example of AI adoption hesitancy 00:05:38 – Execution theater vs. genuine transformation 00:07:38 – The misalignment spiral and its risks 00:08:25 – The power of metaphors in shaping AI trust 00:09:27 – Deepika’s tech journey: failures and insights 00:13:35 – Measuring human readiness: HAAS score explained 00:15:05 – Organizational response to HAAS score 00:16:29 – Practical tips for cultivating AI readiness 00:18:26 – Operationalizing human-centric innovation 00:20:26 – What separates thriving and struggling AI transformations? 00:23:32 – Startups vs. enterprises: alignment gap challenges 00:24:29 – First steps for leaders to break out of execution theater 00:25:57 – The one mindset shift leaders need: Align before you automate 00:27:28 – Hopeful perspectives: the people at the center of AI 00:28:29 – Connect with Deepika Chopra 00:28:50 – Episode wrap and credits

How can technology and indigenous wisdom come together to help humanity solve the climate crisis? In this episode, Kate O’Neill sits down with Tullio Andrade, chief strategist for COP30, as Brazil prepares to host the first UN climate conference in the Amazon. Dive into a dynamic conversation about the intersection of digital innovation, indigenous knowledge, and global climate action. Learn how satellite monitoring, AI, and community-driven solutions are reshaping our fight against climate change—and how YOU can help build a future that’s both human-centered and planet-centered. Don’t miss this inspiring look at the tech-powered path to a more sustainable world! Topics Covered: Interdisciplinary climate strategy Role of indigenous wisdom Integrating technology with traditional knowledge Satellite forest monitoring and AI Community participation in climate solutions Inclusion and accessibility at COP 30 Scaling climate finance with tech Mindset shifts in tech and climate sectors Connect with: Tulio AndradeLinkedInCOP30 Brasil Episode Chapters00:00:05 – Introduction and episode overview 00:00:17 – Tullio Andrade’s interdisciplinary background 00:00:41 – Role at COP 30 and Brazil’s climate strategy 00:02:04 – Impact of philosophy, cybernetics, and complexity in climate negotiations 00:06:24 – Indigenous wisdom and the People’s COP 00:13:16 – Synthesis of traditional knowledge and technology 00:19:00 – Brazil’s satellite forest monitoring 00:24:55 – Ensuring community-led climate solutions 00:29:28 – Barriers and digital democratization at COP 00:35:52 – Importance of scaling climate finance 00:41:57 – Call to action for the tech community 00:46:33 – Closing thoughts: intentionality and agency 00:47:40 – Outro and credits

What’s at stake when our personal data becomes a tool of power? In this episode, Dr. Carissa Véliz explores how privacy shapes democracy, technology, and our day-to-day lives—asking what ethical guardrails are needed as AI and digital surveillance expand. Topics Covered: The primal importance of privacyPersonal data as a toxic asset Privacy as a collective good Examples of data re-identification risks Power dynamics in data and surveillance AI ethics and governance Differences in global AI policy Links between privacy, surveillance, and democracy Social media’s impact on discourse Practical tips for digital privacy Hopeful trends among younger generations Essential AI guardrails Policy change to ban personal data trade Connect with Dr. Carissa VélizWebsiteLinkedIn Episode Chapters 00:00:05 – Introduction to Tech Humanist Show 00:00:15 – Identifying individuals by phone data 00:00:34 – Dr. Carissa Véliz’s background and book 00:01:46 – International perspectives on privacy 00:02:30 – Privacy as collective and ecological harm 00:05:02 – Netflix data science competition example 00:07:26 – Risks of genetic and location data 00:08:50 – Uniqueness of phone data and battery patterns 00:09:49 – Privacy as power and societal vulnerability 00:13:37 – Knowledge asymmetry and profiling 00:14:07 – Ethical concerns in AI 00:16:45 – Digitizing the analog world and surveillance 00:17:22 – AI as a barrier to knowledge 00:20:57 – Exceptions in algorithms and human judgment 00:21:29 – Global differences in AI governance 00:23:32 – Privacy, surveillance, and democracy 00:24:55 – Social media’s influence on democracy 00:26:40 – Digital fatigue and detox trends 00:27:49 – Practical steps to protect privacy 00:30:07 – Optimism from young people 00:31:04 – Ethical AI guardrails 00:32:04 – Banning the trade in personal data 00:32:56 – Closing remarks and optimism

What if one of the world’s most game-changing tech products—Amazon Alexa—started with a plan so ambitious, it nearly involved building a real-life Star Trek holodeck? In this episode of the Tech Humanist Show, host Kate O’Neill dives deep with Edward Crump, the cofounder and co-inventor of Amazon Alexa, to uncover the untold origin story behind Alexa, how voice technology leapt from science fiction to our living rooms, and why the original vision involved challenges most engineers would have walked away from. With a storied career spanning Amazon, Netflix, Nike, and leading Champion Venture Partners, Ed brings rare, behind-the-scenes insights into human-centered AI, privacy, and the next frontier of truly personal devices. Topics Covered:The Genesis of Amazon AlexaTechnical Challenges in Voice AI DevelopmentUser Experience PrototypingThe Evolution and Human Impact of Voice AISecurity and Privacy in Connected DevicesResponsible AI & Data Protection PrinciplesApplying Privacy & Security Expertise Across IndustriesCareer Progression & Interdisciplinary InnovationVenture Investment & the Future of InnovationCommon Startup PitfallsHope for a Human-Centered Tech Future Connect with Edward Crump:LinkedIn: Ed CrumpInstagram: InstagramWebsite: Champion Management Company Episode Chapters 00:00 Joining Bezos’s Innovative Team06:12 Solving Product Development Challenges07:03 Early Voice Recognition Challenges11:55 Voice-Activated WiFi Setup Concept14:58 “Voice Simplicity vs. Tech Complexity”17:56 Personal AI: Future of Wallets21:30 “Entrepreneurial Journey: From Mainframes to Netflix”25:36 “Privacy and Trust in Public Sharing”28:24 “Isolation Principles in Data Security”31:28 Nike’s Tech and Data Innovation35:53 Future of Smart Sports Technology36:55 Innovative Smart Tech and Athlete Futures41:07 Hope for Human-Centered Tech Future

What if the words we use to describe AI are misleading us—and even shaping how we regulate, trust, and collaborate with technology itself? In this revelatory episode of the Tech Humanist Show, host Kate O’Neill sits down with Anna Mills and Nate Angell, co-authors of a provocative new paper arguing that the term “AI hallucination” may be doing more harm than good. Together, they explore why “mirage” is a much better metaphor for those times AI gets things wrong—one that empowers human users and encourages critical thinking, rather than mystifying the technology or making it seem almost sentient. Topics Covered:Background and Motivation for the AI “Mirage” PaperOrigins and Issues with the Term “AI Hallucination”The Case for “AI Mirage” as a Better MetaphorDeep Dive into the Mirage MetaphorPower Dynamics, Language, and Metaphors in AI DiscourseImplications for Educators, Technologists, and PolicymakersThe Publication Process and Interdisciplinary CollaborationAdoption, Use, and Evolution of AI TerminologyHuman Agency, Hope, and Creativity in AI’s Future Connect with Anna Mills and Nate Angell:LinkedIn: Anna Mills + Nate AngellPaper: Are We Tripping? The Mirage of AI Hallucinations Episode Chapters 00:00:05 – Welcome and introductions: Why language matters in AI00:02:24 – Anna and Nate introduce their work and the AI Mirage paper00:05:07 – Where did “hallucination” come from—and why is it problematic?00:08:49 – How metaphors shape policy, public understanding, and AI design00:10:18 – The problematic implications of “hallucination”: Stigma and technical misconceptions00:11:48 – Unpacking the “mirage” metaphor: Origins, process, and collaborative input00:18:44 – Why “mirage” works: Human judgment, desire, and skepticism00:22:02 – The complexity of AI “mirages” versus human interpretation00:25:49 – Language, power dynamics, and shaping critical AI literacy00:32:05 – Advice for educators and technologists: Building agency and literacy00:33:08 – What would change if “mirage” replaced “hallucination”?00:35:21 – Interdisciplinary collaboration and the importance of social discourse00:38:33 – Practical tips for adopting better language about AI00:39:23 – Staying hopeful and humanistic in a rapidly evolving tech landscape00:41:30 – When AI “mirages” are actually “rainbows”: Embracing creative delight00:42:37 – Closing thanks and reflections

What if one-third of the world’s internet users are actually children—children whose data is being harvested, who are being exposed to manipulation, and whose classrooms are now testing grounds for unproven tech? In this eye-opening episode of the Tech Humanist Show, host Kate O’Neill sits down with Leanda Barrington-Leach, a leading advocate and spokesperson for children’s rights in the digital realm through the UK-based 5Rights Foundation. Together, they pull back the curtain on how today’s digital landscape—shaped by “persuasive design,” addictive algorithms, and fast-moving unregulated technology—creates unique and urgent risks for young people online. Leanda issues a wake-up call: Children are not only the first adopters of major tech platforms, but they’re vulnerable to designs that keep them glued to screens, expose them to inappropriate content, and exploit their personal data. The conversation covers how these challenges have evolved with the introduction of generative AI in the classroom, why traditional regulation hasn’t kept pace, and the surprising lack of evidence for EdTech’s positive impact on learning. Topics Covered:The Mission and Work of the 5Rights FoundationPersuasive Design and Children’s VulnerabilityEvolving Risks and Challenges for Children OnlineThe State of Educational Technology (EdTech)The Role and Promise of Generative AI in EducationRegulation Versus Industry Self-RegulationChildren’s Participation and Voices in PolicyAdvice and Support for Parents, Educators, and PolicymakersAwareness Campaigns: The Twisted Toys InitiativeOptimism and Concerns for the Future Connect with Leanda Barrington-LeachLinkedIn: Leanda Barrington-LeachWebsite: 5Rights Foundation Episode Chapters 00:00 Persuasive Design Patterns Explained05:44 Children’s Online Vulnerability Crisis09:29 Unproven Educational Tech Risks13:35 Flawed AI Reading System Unveiled15:50 Digital Tech Requires Regulation19:16 “Policy Framework and Self-Regulation Required”21:52 Balancing Parental Control and Privacy26:33 Parents Demand Action Against Tech Giants31:11 “Twisted Toys: Digital Dangers Exposed”36:18 “Age-Appropriate Design Code Advocacy”37:08 Advocate: Educate, Complain, Influence

What if trust was the secret ingredient to thriving in the age of AI? In this eye-opening episode of The Tech Humanist Show, host Kate O’Neill sits down with Stephen M. R. Covey, celebrated author of Trust & Inspire and The Speed of Trust, to reveal how trust is at the heart of successful leadership in today’s technology-driven world. Covey shares powerful personal stories—including a formative lesson from his father, Stephen Covey of 7 Habits fame—that show how trust transforms people and organizations. You’ll get exclusive insights on why trust isn’t just a “soft” virtue, but a pivotal driver of speed, innovation, and economic performance—especially as AI and digital tools rapidly reshape the workplace. Covey breaks down how leaders can replace old-school command-and-control with a partnership approach that values people first, and he introduces the game-changing concept of “stewardship agreements” for managing remote teams, digital transformation, and ethical technology use.Topics Covered:Introduction and Framing of the ConversationFoundational Influences and the “Green and Clean” StoryEvolution of Work on TrustTrust as an Economic and Business ImperativeThe Role of Trust in Technological Change and AIBlended Intelligence: Human and AI CollaborationBuilding Trust in Remote and Digital Work EnvironmentsParadigm Shift: Manager to CoachCommunication and Trust During Technological TransformationReal-World Examples of Trust-Led Leadership in Tech TransformationConnect with Stephen M.R. CoveyLinkedIn: Stephen M.R. Coveytrustandinspire.com Episode Chapters 00:00 “Green and Clean” Yard Lessons04:22 Unkept Yard: A Life Lesson08:10 Building Trust After Merger11:49 AI: Replace or Augment Jobs?13:30 Harnessing Human-Centered Potential19:44 “Agreement with Accountability and Guidelines”22:27 “Empowerment Through Stewardship Agreements”27:19 Lead with Transparency28:58 “Trust and Influence Through Understanding”34:17 “Trust-Based Management Shift”37:02 “Trust Leadership for a Changing World”40:23 Tech Humanist Show Outro

Are you ready to rethink how AI shapes our human experience? On this episode of the Tech Humanist Show, we’re diving into a captivating conversation with Maria Luciana Axente, a leader in AI ethics and responsible technology. What if AI’s rush for dominance is overshadowing crucial aspects of humanity and ethics? Get ready to explore this and much more. In this episode, Maria shares her journey, from growing up in communist Romania to becoming a prominent voice in AI ethics at PwC UK and her involvement in NATO’s advisory group. We discuss the necessity of AI to be human-centered—created for, with, and about people. Maria sheds light on the implementation gaps companies face when integrating AI ethically and practically, and the critical importance of upskilling everyone on AI’s impact, including users. Maria’s optimism shines through as she expresses hope in humanity’s capability to create a balanced world where technology enhances the human experience. Follow-ups for listeners include reflecting on how your organization approaches AI, considering new upskilling initiatives, and engaging in conversations around AI’s ethical impact, addressing not just business needs but societal implications too. Are you ready to make AI work for us all? Tune in to be part of the change.Topics Covered:Discussion on AI and TechnologyExplanation of what human-centered AI means.Co-editing of “Human-Centered AI: A Multidisciplinary Perspective”.AI Implementation Gaps in OrganizationsResponsible AI ToolkitDiscussion on Agentic AI and Rapid Technological AdvancementsPolicy and RegulationDifferences between UK and US in terms of AI regulation and policy.Children’s Rights in the Age of AIThe Future and Hopeful Outlook Connect with Maria AxenteX: @maria_axenteLinkedIn: Maria Axente Episode Chapters 00:00 Welcoming AI Ethics Leader04:23 “From Star Wars to Star Trek”08:14 “Structuring Program for C-Suite Discussions”11:32 Bridging Academia and Industry Design16:06 AI: Savior or Doom Debate17:10 Chatbot Risks Gain Global Attention20:17 “Responsible AI: A Team’s Journey”25:50 “AI’s Hurdles in a Messy World”27:57 AI Nationalism Gains Political Focus31:04 Navigating Global Cooperation Challenges34:49 Prioritizing Humanity in Children’s AI38:40 “The Hope in Humanity’s Potential”

What if the real danger of AI isn’t bad code or rogue bots—but our own willingness to mistake simulated intelligence for true understanding? In this essential episode of the Tech Humanist Show, host Kate O’Neill welcomes Hamilton Mann—digital innovator, business instructor, and author of Artificial Integrity—to tackle the urgent question: How can we build AI systems that are not only smart, but also trustworthy, fair, and aligned with human values? Hamilton introduces the concept of “artificial integrity”—a framework for embedding ethical principles directly into AI systems rather than treating ethics as an afterthought. Through compelling case studies and practical insights, he demonstrates how businesses and developers can move beyond AI anxiety toward AI systems that enhance rather than replace human judgment. The conversation explores the unpredictable nature of AI, the critical importance of transparency in algorithmic decision-making, and Hamilton’s innovative Artificial Integrity Index. You’ll discover the four cognitive zones that define human-AI interaction and learn actionable strategies for integrating integrity into AI development across different industries and applications.Whether you’re a business leader navigating AI implementation, a developer building the next generation of AI tools, or simply someone concerned about technology’s impact on society, this episode offers a roadmap for creating AI that serves humanity’s best interests.Ready to move from AI anxiety to AI integrity? Listen in for an episode that might just change the way you look at artificial intelligence—and your own place in the future. Follow up by checking out Hamilton Mann’s book, “Artificial Integrity,” and exploring resources and past episodes at thetechhumanist.com. Don’t forget to share your reflections on how you’re building integrity into your own tech journey!Topics Covered:The Concept of Artificial IntegrityImportance and Application of Artificial Integrity in SocietyExamples and Case Studies of AI with IntegrityAI’s Unpredictability and the Need for Embedded IntegrityThe Artificial Integrity IndexThe Conceptual Framework of Artificial IntegrityApplicability Across Different AI ModalitiesChallenges for Business Leaders in Integrating Integrity into AIThe Four Critical Cognitive Zones for Human-AI InteractionHope and the Future of AI and Humanity Connect with Hamilton MannInstagram: @hamilton.mannLinkedIn: @hamiltonmannBook: Artificial Integrity: The Paths to Leading AI Toward a Human-Centered Future Episode Chapters 00:00 Integrity Essential in AI Systems05:00 “Artificial Integrity in AI Design”07:59 “AI Integrity in Modern Systems”10:12 “Ethical AI Systems for Safety”15:11 “Three Pillars of AI Integrity”16:30 AI Ethics and Integrity Framework21:38 Human-AI Synergy: Interconnected Intelligence25:54 AI and Human Integration Challenges29:48 “Navigating Four Cognitive Zones”33:00 “Automation Frames Behavior”37:32 AI for Enhancing Reflection and Critique40:46 “Human Strengths Over Machine Intelligence”45:41 “Equitable Responsibility Provides Hope”46:53 “Tech Humanist Show Closing”

What if everything you think you know about civic engagement is stuck in the past—and the real power lies in everyday actions between elections, not just in the voting booth or the halls of government? In this revealing episode of The Tech Humanist Show, host Kate O’Neill sits down with Mila Atmos—creator of the Future Hindsight podcast—to explore how technology, culture, and ordinary people are reshaping the future of democracy. Drawing from her own journey across continents, Mila shares eye-opening insights on what it truly means to be a “global citizen” and how shifting social contexts and digital tools are breaking down (and sometimes reinforcing) barriers to community and civic action. Topics Covered: Concept of Global CitizenshipFormation of Community AwarenessTechnology and Community BuildingThe Birth and Focus of “Future Hindsight” PodcastCitizen Change MakersTechnology’s Role in Civic EngagmentInformation Asymmetry and Media ConsumptionZCross-Cultural Civic Engagement InsightsThe Role of Place and In-Person EngagementEnvisioning Future-Ready CitiesContent Creation and Fostering DialogueResponsible Consumption and Civic DutyConnect with Mila AtmosInstagram: @milaatmosLinkedIn: @milaatmos Episode Chapters 00:00 “Digital Democracy Insights with Mila”05:04 “Identity and Belonging in Indonesia”08:18 “Civic Engagement Beyond Voting”10:11 “Effective Communication by Ocasio-Cortez”14:40 “Legacy Media’s Decline and Asymmetry”19:02 Read History for Contextual News22:00 Headscarf Acceptance in Schools25:42 Future-Ready City Engagement27:16 Future City Vision: Housing & Transit31:08 “Unified Viewing’s Impact on Society”33:37 American Resilience Amid Information ChallengesZ37:14 Comedic News as Information Bridge40:19 “Future of Civic Engagement”44:29 Civic Engagement and Local Politics46:18 “Future Hindsight Insights”

In this episode of The Tech Humanist Show on Lou Diamond, join host Kate O'Neill and guest Bärí Williams as they explore the intersections of technology, diversity, and AI's impact on the workplace. Bärí shares insights from her book "Seeing Yet Unseen" and reveals experiences building Meta's supplier diversity program. Discover the challenges and hope for black and brown workers in the age of innovation.

In this insightful episode of The Tech Humanist Show, host Kate O’Neill welcomes Wendy Smith, the Dana J. Johnson Professor of Management at the University of Delaware. Wendy is an expert in strategic paradoxes and brings a wealth of knowledge from her groundbreaking work and acclaimed book, “BOTH/AND Thinking.” Wendy dives deep into the pitfalls of “either/or” thinking, a mindset that often leads organizations and individuals to swing between extremes without finding effective middle grounds. Instead, she advocates for embracing “both/and” thinking, highlighting how this approach helps organizations balance competing priorities, avoid polarization, and uncover more holistic solutions. The episode features compelling case studies, including Unilever under the leadership of Paul Polman and Southwest Airlines with Herb Kelleher and Colleen Barrett. These examples illustrate how “both/and” thinking can integrate financial success with social and environmental well-being, as well as improve customer experience and financial outcomes through people-centric strategies. Wendy also brings attention to the impact of automation and the significance of reskilling and reengaging employees rather than merely replacing them with technology. Kate and Wendy explore how leaders can use paradoxical thinking to navigate the complexities posed by emerging technologies like AI. Listeners will learn about strategic frameworks for addressing competing demands, the importance of “tightrope walking” in decision-making, and the relevance of “both/and” thinking in personal relationships. Wendy touches upon the development of a paradox mindset inventory, and the unique challenges faced by women in leadership roles are discussed, with insights into how they might naturally adopt a “both/and” thinking approach. Join Kate O’Neill and Wendy Smith as they delve into how embracing complexity and contradiction can lead to more innovative, sustainable, and human-centric solutions. This episode provides a treasure trove of practical insights and strategies for leaders and organizations aiming to thrive in an increasingly complex world. Topics Covered: The downside of “either/or” thinking and the benefits of “both/and” thinking. Case studies on Unilever and Southwest Airlines. Addressing automation through reskilling, not displacement. Strategies for navigating competing demands with a higher purpose. Exploring the paradox mindset inventory. Insights into gender roles and leadership. Guest Contact Information: Website: BothAndThinking.netBoth/And Thinking book: On AmazonInstagram: @Prof.WendySmithX.com: @ProfWendySmithLinkedIn: Wendy K. Smith Episode Chapters 00:00 Wendy Smith: Embrace complexity, balance innovation, human-centricity.03:23 We misframe challenges as either-or dilemmas.07:36 Work-life balance: competing demands, conflicting choices.12:13 Commitment: Double profits through social, environmental focus.14:51 Southwest Airlines prioritized people, boosting service success.16:58 Empower agency, embrace automation, enable responsible growth.20:21 Enable skill growth; address individual-managerial challenges.24:15 Discussing women’s leadership styles and SEO challenges.27:48 Women face unique leadership challenges due to stereotypes.31:05 Seeking insights on tech-driven competitive innovation.36:13 Paul Polman: Separate, understand, integrate sustainability and business.39:17 Balanced scorecard integrates multiple metrics for decisions.43:12 Balancing competing demands in organizational decisions.48:15 Embrace nuanced thinking over binary choices.50:03 Sign up for Tech Humanist Show newsletter.

In this enlightening episode of The Tech Humanist Show, host Kate O’Neill dives deep into a thought-provoking conversation with Greg Epstein, the humanist chaplain at Harvard and MIT, and a New York Times best-selling author. Known for his impactful role as the Twitter chaplain during the pandemic, Greg now channels his passions through LinkedIn and his personal website, gregmepstein.com. Joining us to discuss his latest book, “Tech Agnostic: How Technology Became the World’s Most Powerful Religion and Why it Desperately Needs a Reformation,” Greg offers a unique perspective on the intersection of technology and human values. He challenges us to think critically about the ways in which technology mimics religious structures and calls for a metaphorical “reformation.” Greg and Kate explore essential themes, such as the ethical balance of addressing future generations while correcting present inequities, and the role of democracy in the tech landscape. Greg’s book is more than just a critique; it’s a roadmap for a more ethically grounded tech future. The conversation also delves into the comedic elements of his writing, the notion of “new shit,” and the spiritual dimensions of creating technology that prioritizes human connection over capitalist gains. In addition, Kate O’Neill is interviewed within it! The episode also touches on the indigenous principle of considering seven generations ahead, and features rich discussions on responsible tech movements. Kate and Greg reflect on efforts to encode positive human values into technology while cautioning against the dogmatic prophecies of tech luminaries. Tune in to hear insights about fostering community resilience, the importance of vulnerability, and how technologists can balance professional success with personal fulfillment. Plus, get a sneak peek into Kate’s upcoming book, “What Matters Next,” which tackles these pressing ethical dilemmas. Guest Contact Information: Greg Epstein’s websiteInstagram: @GregMEpsteinX.com: @GregMEpsteinLinkedIn: Greg M Epstein Topics Covered: The Role of Emotions in Human VoiceImpact of AI on Voice CommunicationHuman Voice vs. AI CommunicationMisconceptions about Human VoiceThe Business Context and Emotional DesensitizationCommunication of MeanningAI and Voice SimulationBiases in AI-Generated VoicesVoice Technology and SocietyDigital Age and Effective CommunicationSense Making and the Human Experience Episode Chapters 00:00 Exploration of tech as modern religion’s reformation.06:11 Appreciating self-critical believers and technologists.08:49 Book advocates reform, blending tradition with modernity.13:20 Shift mindset towards fulfillment and connectedness.16:36 Tech futurism equated to theology or prophecy.19:36 Balancing future focus with current ethical responsibilities.23:39 Appreciation for book’s exploration of community support.27:54 Embrace imperfections, connect meaningfully, reject techno perfection.32:39 Balancing professional success with personal integrity.33:57 Tech whistleblowers face risks; courage is essential.38:11 Get “Tech Agnostic” book; connect via LinkedIn.

In this engaging episode of The Tech Humanist Show, host Kate O’Neill sits down with the multifaceted Casey Erin Clark, co-founder of Vital Voice Training, to explore the profound connections between voice, human communication, and technology. With AI and voice technologies becoming increasingly prevalent, Casey shares her unique perspective on how these developments impact our understanding and utilization of the human voice. From examining the biases inherited by AI voice assistants to discussing the complex interplay between emotions, body, and voice, Casey and Kate delve deep into how we can harness our embodied experiences to communicate more authentically and effectively in an AI-driven world. Casey passionately argues for the importance of acknowledging our human messiness as a crucial component that sets us apart from machines. Tune in to discover how emotions manifest in our voices, the societal implications of gendered voice technologies, and how we can embrace our full human potential in an age of rapid technological advancement. Whether you’re intrigued by vocal performance, interested in AI ethics, or simply curious about the future of human-machine interaction, this episode promises to offer valuable insights and thought-provoking discussions. Join us for this thought leadership conversation, and learn how to find your Vital Voice in a technological world. Guest Contact Information: Website:CaseyErinClark.comInstagram: @CaseyErinClarkX.com: @CaseyErinClarkLinkedIn: Casey Erin Clark Topics Covered: The Role of Emotions in Human Voice Impact of AI on Voice Communication Human Voice vs. AI Communication Misconceptions about Human Voice The Business Context and Emotional Desensitization Communication of Meanning AI and Voice Simulation Biases in AI-Generated Voices Voice Technology and Society Digital Age and Effective Communication Sense Making and the Human Experience Episode Chapters 00:00 AI amplifies human biases; exploit human advantages.06:42 People ignore emotions to remain composed professionally.10:05 Emotions last 90 seconds unless prolonged internally.14:09 Technology’s impact isn’t neutral; voice selections matter.15:20 AI assistants default to feminine; choice impacts perception.19:03 Embrace your body’s sensory and emotional awareness.23:10 Kitten’s insights vs AI’s sense-making contrasted.25:44 Embrace human uniqueness alongside intelligent machines.

Renowned AI ethicist and philosopher, Ravit Dotan joins host Kate O’Neill as they dive deep into the world of artificial intelligence and ethics. The conversation covers the significant changes in public perception of AI, sparked by direct interaction and the influence of sci-fi-like misconceptions. Dotan addresses the ethical pitfalls of large language models, including the rise of deepfakes and misinformation, especially pertinent with upcoming elections. She elucidates the dangers of anthropomorphizing AI using terms like “hallucinations,” advocating instead for more accurate language to describe AI behaviors. Furthermore, the episode underscores the digital divide exacerbating global inequalities and delves into the complex challenge of forming global policies on AI ethics amidst diverse cultural and legislative landscapes. Dotan shares insights from a collaborative project aimed at tackling ethical risks in AI, and discusses shifting education paradigms to integrate technology like ChatGPT for solving modern problems. Listeners will also gain a nuanced understanding of the current AI climate, ethical AI governance, and the practical alignment of academia and industry. Join Kate and Ravit for a thought-provoking discussion that promises to redefine how we interact with and think about technology and ethics in our digital age. Don’t miss this comprehensive examination of AI’s role in our lives and the urgent need for responsible and inclusive approaches to its development and deployment. Guest Contact Information: Website:TechBetter.aiX.com: @DotanRavitLinkedIn: Ravit Dotan Topics Covered: User Interaction with AI Misleading Terminology and AI Hype Ethical Concerns with Large Language Models Digital Divide Cultural and Ethical Challenges Philosophical Perspective Ravit Dotan’s background and expertise in AI ethics AI Metaphors and Terminology Public Perception of AI Reflections on Current AI Climate Challenges in Humanities Education Principles in AI Ethics Interdisciplinary Approach Academia vs. Private Sector Gap AI in Education Episode Chapters 00:00 Misleading AI metaphors cause public confusion.06:32 Replace “hallucinations” with “misinformation” for accuracy.07:29 AI’s public engagement surge raises speculation.11:22 Technologists’ language humanizes AI, fueling hype.15:58 Risk of inequality; leapfrogging tech challenges/opportunities.20:55 Focus on AI governance, stakeholder engagement, accountability.25:01 Academic knowledge gap in responsible technology development.26:45 Balance incentives for responsible AI across sectors.31:13 Focus education on problem-solving using disciplinary tools.32:21 Collaboration addressing company risks with students’ help.

Kate O’Neill is joined by Cortney Harding— a visionary leader in virtual and augmented reality (VR and AR), founder, and CEO of Friends with Holograms. Together, they explore how immersive technologies are transforming human experiences and the innovative projects that Harding’s agency has spearheaded. Cortney shares insights into Friends with Holograms’ award-winning work, including a groundbreaking VR training program for social workers that has gained widespread adoption across nearly 30 states. She discusses how continuous learning, artificial intelligence, and natural language processing play crucial roles in the development and iteration of VR/AR projects. The conversation delves deep into the metaverse’s potential, avatars’ ethical considerations, and the necessity for robust governance and privacy measures. Harding underscores the importance of meeting users “where they are” in VR experiences to truly engage and impact them, while Kate challenges listeners to think about the future implications of these technologies in our daily lives. Listeners will also hear about the power of anonymous avatars in promoting equal participation within organizational problem-solving exercises and the broader societal benefits of technological advancements like universal basic income. This episode is filled with dynamic discussions on the future of AR/VR, insights into creating impactful digital experiences, and the chance for brands to think beyond physical replications in the digital world. It’s a must-listen for tech enthusiasts, industry professionals, and anyone curious about the rapidly evolving digital landscape. Join Kate and Cortney to explore the future of immersive experiences and their lasting impact on society. Tune in for a compelling conversation on the forefront of virtual reality technology and its profound impact on society. Guest Contact Information: Website:https://cortney-harding.com/ X.com: @CortneyHarding LinkedIn: Cortney Harding Topics Covered: Cortney harding and Friends with Holograms Continuous Learning and Iteration in VR/AR Projects: Meeting Users “Where They Are” in VR: Avatars and the Metaverse Fandoms and Celebrities in the Metaverse Trust and Governance in the Metaverse Insight on a Personalized Small Language Model (SLM) or Avatar Broad Implications and Support for Universal Basic Income Augmented and Extended Reality Future of AR/VR Technologies Opportunities for Brands in the Metaverse Digital Transformation Strategy Creating Successful Metaverse Experiences Advice for Aspiring VR/AR Practitioners Ethical and Global Considerations Episode Chapters 00:00 Courtney Harding discusses VR and AR advancements.06:18 VR as empathy machine: impactful but limited simulation.07:40 Meeting people as themselves creates impactful experiences.12:43 Transparency and governance critical for metaverse trust.14:15 Ensuring safe, accountable spaces in the metaverse.18:45 AR is the mega opportunity for future entertainment.22:45 Start with purpose, not technology, for transformation.27:05 Start with Spatial: build, invite, explore, learn.29:07 Developing world positive; West negative towards technology.30:39 Desires personal small language model for AI talk.34:03 Avatars manage tasks, enhancing personal productivity.37:11 Thanks for listening to the Tech Humanist Show.

In this insightful episode of The Tech Humanist Show, host Kate O’Neill sits down with Noah Giansiracusa, an associate professor of mathematics at Bentley University and visiting scholar at Harvard, to unravel the fascinating interplay between mathematics, social media algorithms, and their impact on society. Noah dives into his journey, which began during the pandemic, sparking his transition from pure mathematics to applied data science. He discusses his first book aimed at a general audience, delving into the role of social media algorithms and their profound yet often misunderstood influence on our daily lives. The conversation highlights the dual nature of mathematics, both as an art form and a practical tool, exploring the aesthetic beauty of pure math and the crucial applicability of applied math in fields such as epidemiological modeling. Noah shares his personal struggles during the pandemic, reflecting on the relevance of non-useful mathematical pursuits while others fought critical real-world issues. A significant portion of the discussion is dedicated to artificial intelligence and the mechanics of algorithms. Noah demystifies AI, clarifies the basic functionalities of social media algorithms, and addresses common misconceptions about AI’s omniscience and ability to infer truthfulness. Listeners will gain valuable insights into how AI and algorithms collect and use data, amplify societal issues, and shape user experiences on platforms driven by engagement metrics. Noah emphasizes the importance of digital literacy and understanding these technologies to better navigate the information ecosystem and protect oneself from misinformation. Kate and Noah also touch on the ethical considerations and need for greater transparency in algorithmic operations, advocating for regulatory measures to enhance public trust and user engagement. As a preview to Noah’s upcoming book “Robin Hood Math,” due in summer 2025, the episode offers a deep dive into the world of algorithms, math, and their overarching impact on society. Don’t miss this enlightening discussion that bridges the gap between complex mathematical concepts and everyday technology, making it accessible and relevant for everyone. Tune in and empower yourself with the knowledge to understand and navigate the data-driven world. Topics Covered: Noah Giansiracusa’s career and academic journey The role of pure mathematics as artistic expression Applied mathematics and its practical applications The impact of the COVID-19 pandemic on perceptions of math’s utility Understanding social media algorithms and their societal implications AI, deep learning, and the data that fuels them The necessity of transparency and regulation in algorithmic design Practical tips for managing digital experiences Upcoming book: “Robin Hood Math” by Noah Giansiracusa Tune in for an episode that promises to enrich your understanding of the invisible algorithms shaping your world! Guest Contact Information: Website:www.noahgian.com Twitter:@NoahGiansiracusa LinkedIn:Noah Giansiracusa Episode Chapters 00:00 Noah Giansiracusa: Math professor, author, public speaker.04:48 Enjoyed diverse interaction; different, practical educational approach.07:38 Pandemic inspired math book and broader discussions.13:03 Connecting math’s beauty to AI’s meaningful impact.14:53 Data competitions test methods; neural networks are brain-inspired.17:51 AI thrives on data from surveillance capitalism.21:49 Understanding algorithms is essential for informed citizenship.26:44 Engagement data drives your social media experience.28:23 Social media engagements don’t always reflect truth.31:15 AB tests yield practical data unlike open web.37:22 Simplify algorithms, improve social media experiences.38:32 Social media uses AI for weighted engagement sums.44:21 Curate content wisely; leaders make trustworthy AI decisions.47:16 Thoughtful communication and transparency in using tools.48:28 Transparency and regulation needed for algorithm insights.

When we talk about the metaverse as we imagine it taking shape, we don’t always have the vocabulary to describe how we should be able to navigate it safely and enjoyably. Join host Kate O’Neill on The Tech Humanist Show as she engages in an enlightening conversation with technology critic and industry analyst Sara M. Watson. In this episode, Sara delves into the intricate relationship between humans and emerging technologies, offering profound insights using metaphors like BDSM and deep-sea diving to explain VR transitions. Highlighting the paramount importance of a smooth VR offboarding experience, Sara shares her personal challenges and collaboration efforts to make VR safer and more user-friendly. They explore the significance of prompts, critical thinking, and user creativity in navigating AI tools, drawing inspiration from Diana Kimball’s idea of AI as engines of imagination. They also broach privacy concerns and the ethical implications of AI and generative content, with Sara reflecting on historical media manipulation and consumer responsibility. This episode is a must-listen for anyone interested in the future of immersive technologies, the evolving trust dynamics with AI, and the quest for ethical and humane innovation in technology. Tune in to explore Sara’s thoughts on the juxtaposition of physical and digital worlds, and how they shape our collective tech experience. Host: Kate O’Neill Guest: Sara M. Watson Don’t miss this thought-provoking discussion on the tech-human frontier! #TheTechHumanistShow #SaraMWatson #VR #AI #Technology #Ethics #Innovation #Privacy #HumaneTech Key Topics Metaphorical Understanding and VR: Sara M. Watson uses metaphors such as BDSM and diving tables to explain VR transitions and the importance of a smooth off-boarding experience. Critical Thinking and AI Tools: Emphasis on critical thinking and using AI tools as partners for thought, highlighting human creativity in the prompting process. Generative AI and Imagination: Discussion on generative AI as tools for imagination and creativity, including examples like generating a Lego set prompt of the Mar-a-Lago FBI search. Privacy and Data Protection in AI: Concerns about the privacy and data protection implications of large language models and corporate security in AI data handling. Trust in AI: Exploration of trust dynamics in AI integration by tech and non-tech companies, and the need for clear signals and explicit statements of intent. VR User Safety and Aftercare: Sara’s experience with nausea from VR use and the discussion on making VR environments safer, inspired by practices from the BDSM community and psychedelics. Media Literacy and Technological Disruption: Episode Chapters00:00 Excitement to write about future tech interfaces.07:00 VR uses novel controls, requiring significant learning curve.10:41 Virtual experiences need better off-boarding for re-acclimation.12:46 BDSM concepts integrated into safer VR experiences.18:15 Metaphors for technology highlight human linguistic creativity.23:00 Big data’s privacy, security, and output concerns.26:18 Consumer interactions evolving; trust and transparency critical now.30:21 Responsibility of digital literacy lies with consumers.34:45 Implications for democracy, humanity, and technology’s future.37:17 Brilliant insights on The Tech Humanist Show. The Tech Humanist Show is a multi-media-format program exploring how data and technology shape the human experience. Hosted by Kate O’Neill. To watch full interviews with past and future guests, or for updates on what Kate O’Neill is doing next, subscribe to The Tech Humanist Show hosted by Kate O’Neill channel on YouTube.

In this compelling episode of The Tech Humanist Show, host Kate O’Neill sits down with Dr. Joel Mier, former head of marketing at Netflix, to explore the complex intersection of data, empathy, and customer-centricity in business. The conversation opens with a deep dive into the challenges of quantifying empathetic understanding and the importance of tying data analysis to emotional connection for impactful results. Dr. Mier shares invaluable insights from his rich career, including his transformative move to Netflix from Adobe and his experiences working with influential leaders like Tom Dillon and Leslie Kilgore. The episode takes a thoughtful look at Netflix’s success, attributed to key factors like ambidexterity, scalability, and a relentless focus on customer centricity. Kate and Joel also discuss the importance of a balanced perspective within academia and the challenges of cultural change within large organizations. Listeners will find Dr. Mier’s anecdotes about early career decisions, including his pivotal interview with Mark Randolph at Netflix, both entertaining and enlightening. His reflections on Netflix’s democratic approach to data and its enduring impact offer a unique perspective on fostering innovation. Additionally, the episode addresses current student concerns about environmental sustainability and the rise of AI technology, with practical advice on how to navigate these pressing issues. With thought-provoking discussions on strategic reinvention, local content prioritization, and the significance of human-centric data, this episode is a must-listen for anyone interested in the synergy between technology, data, and the human experience. Tune in to discover how empathetic leadership and data-driven decisions can harmonize to drive meaningful change in today’s fast-paced world. Key Topics: Quantifying empathetic understanding in business Role of data analytics as a catalyst for change Insights from Netflix’s cultural and operational success Challenges in implementing customer-centric approaches Importance of ambidexterity, scalability, and customer focus Balancing academic and practical perspectives Navigating environmental sustainability and AI technology Join Kate O’Neill and Dr. Joel Mier as they delve into these topics and much more, providing insights that bridge the gap between technology and the human experience. Episode Chapters 00:00 Summary: Interview with Dr. Joel Meyer, marketing expert.04:38 Understanding power of deconstructing averages, data’s impact.06:39 Advancing internet affected office space in valley.10:14 Importance of forward thinking in leadership teams.14:43 Netflix culture and metrics influence career significantly.18:30 Reflection on former employer’s innovative culture.22:04 Drucker: Success comes through customer recognition, listening.24:10 Exploring decision making and empowerment in companies.28:48 Transparency and openness in financial meetings.32:48 Company prioritizes local stories and global impact.35:46 Netflix created a valuable, accidental genius queue.38:37 Data and individual stories are essential. Netflix Friends allowed social connections and recommendations.40:51 Excited about big data and human connection.43:27 Insightful pondering on empathy and human connection.49:21 Moved to Richmond, Virginia, began college teaching.52:19 Addressing existential concerns and fears about AI.54:04 AI as a tool for those who learn.

In this riveting episode of The Tech Humanist Show, Kate O’Neill sits down with Aimee’ Killeen and Chuck Greely, two pivotal figures in the water sector, to explore the confluence of technology, environmental science, and water management. Aimee’ Killeen, President of the Water Environment Federation (WEF) and COO of Providence Engineering and Environmental Group, shares her personal connection to the Gulf Coast and how it fuels her commitment to ensuring clean water for all. She discusses the challenges of water scarcity, the impact of infrastructure funding, and the importance of public awareness in the water sector. Chuck Greely, Assistant Division Leader of DUDEK’s Engineering Group and President of the California Water Environment Association, brings his insights on the future of water sustainability in the face of climate change. From the “silver tsunami” of retiring water professionals to the potential of AI to revolutionize the water industry, Chuck offers a hopeful yet pragmatic view of what lies ahead. Together, they paint a vivid picture of the water challenges we face, the technological innovations that could help overcome them, and the vital role of mentorship and community engagement in building a sustainable water future. Dive into this episode to discover how the water sector is navigating its way towards a future where the best thing since clean water is the technology and human ingenuity preserving it. Episode Chapters (00:00) The Tech Humanist Show explores how data and technology shape the human experience(01:06) Aimee’ majored in environmental science at LSU; she now works in water conservation(03:27) Over 2 million Americans live without basic access to safe drinking water and sanitation(07:58) Almost 2 million Americans without clean water and sewer service to their home(10:16) Providence helps industries deal with wastewater and water treatment challenges(15:50) Water leaders need to increase visibility of their sector through effective communication(23:02) Ways the sector can help people recognize water value(25:38) Community building, mentorship, and raising up new leaders in water quality is important(29:02) Chuck Greely, president of the California Water Environment Association(31:49) Climate change is having negative effects on both surface water and groundwater(34:50) What kind of life are humans looking at if we don’t achieve sustainable water goals(36:43) How has working in the Colorado River Basin shaped Chuck’s ideas about water future(40:37) Every industry is grappling with workers workforce growing pains(42:25) CWEA is looking at ways to attract and train new water workforce members(45:50) CWEA members advocate for the association through networking and educational opportunities(47:56) Kate O’Neill: CWEA annual conference is coming up very quickly Join us for this wide-ranging and thoughtful episode, which serves not only as a platform for discussing critical environmental issues but also a call to action for listeners to engage with and contribute to the efforts towards achieving a sustainable water future. The intersection of technology, water, and climate change presents complex challenges, but as our guests have shown, it also offers the opportunity for profound, impactful solutions.

In this episode of The Tech Humanist Show, we welcome Yanis Varoufakis, an economist, politician, author, and former Minister of Finance in Greece. Known for his insightful critique on the state of capitalism, Yanis opens up important dialogues that challenge our contemporary understanding of the economy. Our discussion centers around his new book, “Technofeudalism: What Killed Capitalism,” in which he explores the evolving landscape of our economy and society in the era of data monopolies and “cloud capital.” Cloud capital, as Yanis defines it, is a new form of capital that has emerged with the advent of big tech companies and data-driven economies. It represents the power and wealth accumulated through the control and exploitation of data and digital resources. In essence, it’s the capital that big tech companies like Google, Amazon, and Facebook have accrued through their vast networks, platforms, and the data they collect from their users. Yanis argues that the current power dynamics in the digital economy, where a handful of tech giants control a majority of the world’s data, is leading to a form of ‘technofeudalism.’ He suggests that the unchecked power of these data monopolies is reshaping our society and economy, often exacerbating inequality and undermining democracy. In our conversation, we delve into the role of democracy in this new era and discuss how changes in the ownership structures within companies could bring about a more equitable society. Join us for this thought-provoking episode as we explore these complex issues and envision a future where technology better serves humanity. Listen to the full episode on Apple Podcasts or Spotify.

Cities are like test beds for how data and tech can empower citizen experience. So it’s interesting to consider leading a growing city as someone with a background in technology. In this episode, Kate talks with her old friend Freddie O’Connell about his run for mayor of Nashville, and about how data and technology figures into the way he thinks about governance and citizen experience. The Tech Humanist Show is a multi-media-format program exploring how data and technology shape the human experience. Hosted by Kate O’Neill. To watch full interviews with past and future guests, or for updates on what Kate O’Neill is doing next, subscribe to The Tech Humanist Show hosted by Kate O’Neill channel on YouTube. Full Transcript Kate O’Neill:

Dive deep with us into the world of mining, sustainability, and the delicate balance between economic needs, environmental responsibility, and future potential. Our interview with Dana Bennett, president of the Nevada Mining Association, sheds light on the complex landscape of the mining industry, in Nevada but also globally, and its implications for communities and technology. As we explore topics ranging from the demand for critical minerals to the role of advanced technology in mining, we uncover Nevada’s pioneering efforts in stewardship and how it sets an example for other regions. Join us as we navigate the dialogue around responsible mining practices and the exciting advancements in tech the industry is exploring. About our guest Dana Bennett: Dana Bennett, Ph.D., is the Interim President of the Nevada Mining Association, where she previously served as the organization’s first female President. Bennett implemented the NVMA’s first strategic plan and increased membership. She is a lifelong Nevadan with 30 years of experience in public policy in Nevada and a Ph.D. in history. Bennett has authored three books and numerous articles and has served as a consultant for companies doing business in Nevada as well as policymakers in the Silver State. About The Tech Humanist Show and host Kate O’Neill: The Tech Humanist Show is a multi-media-format program exploring how data and technology shape the human experience. Hosted by Kate O’Neill. To watch full interviews with past and future guests, or for updates on what Kate O’Neill is doing next, subscribe to The Tech Humanist Show hosted by Kate O’Neill channel on YouTube.

Women figure heavily into the tech humanist story. So for International Women’s Day — and to kick off our new season, Season 3! — we’re celebrating with an episode highlighting just a few of the brilliant women tech and futurist thinkers who’ve been guests on our show: Vanessa Mason, Dr. Safiya Noble, Giselle Mota, and Dr. Oluwakemi Olurinola. They’ve all made significant contributions to the conversation around women and technology. The Tech Humanist Show is a multi-media-format program exploring how data and technology shape the human experience. Hosted by Kate O’Neill. To watch full interviews with past and future guests, or for updates on what Kate O’Neill is doing next, subscribe to The Tech Humanist Show hosted by Kate O’Neill channel on YouTube. Full Transcript: Kate O’Neill 0:04International Women’s Day is celebrated on March 8, and it’s a day of commemoration for the many social, economic, cultural and political achievements and contributions of women around the globe. It’s also a rallying cry for accelerating women’s equality in issues like pay equity, education, access, health care and reproductive rights, and a host of other topics. Today we’re celebrating International Women’s Day by discussing the impact of technology on women and girls, feminist issues, gender inequities, and biases directed at women. Women figure heavily into the tech humanist story. As a veteran of the tech space and a woman myself, I want to highlight the importance of acknowledging and addressing the ways in which emerging technology can perpetuate existing inequalities and biases. By bringing awareness to these issues, we can work towards a more equitable future for all. So in the spirit of International Women’s Day, we’ll hear from a few women tech humanists you should be following. They include Vanessa Mason, Dr. Safiya Noble, Giselle Mota, and Dr. Oluwakemi Olurinola, all of whom have made significant contributions to the conversation around women in technology. So let’s dive in. First, let’s talk about the ways in which technology can impact women and girls. From the gender gap in STEM fields to the rise of cyber bullying and online harassment. Women and girls face unique challenges in the tech world. The lack of diversity in the tech industry, and the perpetuation of gender stereotypes in AI and other technologies can have serious consequences for women and marginalized communities. As tech humanists, it’s our responsibility to advocate for more inclusive and ethical practices in the development and implementation of emerging technologies. Vanessa Mason is a futurist and expert in belonging, and works to ensure that emerging technologies are inclusive of women’s experiences. We talked about belonging, and how the push for data-fication behind algorithmic experiences, which very often are designed and developed largely by men, overlook women’s experiences, whether or not they are measurable, or don’t attempt to understand or measure them. Vanessa Mason 2:33When I think about gender, and what can be quantified some of it is you know that there are experiences of women that just aren’t measured, because like they aren’t considered, there are some experiences being a woman that aren’t easily measured. So I think every woman can relate to you’re walking down a dark street at night, the fear that you feel that someone either might pop out in front of you, or suddenly run after you or something is something that is real, it’s a real experience. But you can’t really, there aren’t necessarily ways to fully designed for how you either account for that, or how you sort of design around that like that has a felt sense of built experience, but by millions of women all over the world. But nonetheless, every time I’ve ever taken an Uber or Lyft no one ever accounts for that, you know, to make sure for example, that maybe the car always stops under a streetlight that the car always has its flashers on, for example. So you know, you’re getting in the right vehicle, like some of these are just protocols that would account for that experience that aren’t accounted for. Kate O’Neill 3:31It’s true. Remember, for example, when Apple’s health app included things like tracking blood alcohol level, but forgot to include any kind of period tracker. Many of these experiences that are commonplace for women are not taken into consideration in design, simply because tech design, development and leadership has been historically dominated by men, white men specifically. And that brings up another issue. Dr. Safiya Umoja Noble 3:58That’s really it. And you’re also creating social structure through those categories. And what we know is that those categories have always existed, at least in a western context, as hierarchical. Kate O’Neill 4:12Dr. Safiya Umoja Noble is the author of algorithms of oppression, and a scholar who has done extensive research on how algorithms misrepresent black people and women, and further the oppression of marginalized groups. During our conversation, she pointed out that society is ordered in many ways around hierarchy, which affects issues of race as well as gender. So if your categorization system puts, you know, it has you have a racial classification system, like we have the United States and many other parts of the world where white is the highest valued and most resourced and most powerful and black is the antithesis of that and the binary and everything in between is vying for its relationship to power or powerlessness. Dr. Safiya Umoja Noble 5:01that those systems become real. So the question is, you know, how do we create systems that aren’t hierarchical, and where power is not distributed along those lines of classification or categorization. And we have not solved that. Instead, we are reinforcing those systems of power over and over and over again. Kate O’Neill 5:23During our conversation, which you can listen to in full at season one, episode five, she talks about how she gets students to really witness the impact of the oppression she’s written about. Dr. Safiya Umoja Noble 5:35On a basic level around search, I’ll often have my students do their own searches on Google and you know, other large commercial search engines. And I’ll ask them to look for identities that matter to them that are kind of like either their own identities or identities they care about. And it’s interesting to see the kinds of searches they do. So though I say, you know, go do these searches. Come back. Next class session, we’re going to discuss everybody’s going to get a chance to talk about what they found and what it means to them. And, you know, for some people, they you know, I’ll never forget what I was teaching at the University of Illinois at Urbana Champaign, I had just like a disproportionately high number of white women in predominantly white sororities. And I think almost all of them had done a search on sorority girl, and we’re pissed. So we’re, I don’t think like, necessarily, that like searches on black girls and Latina girls and Asian girls that would surface porn at the, in those years, meant that much to them, or they could think that they were sympathetic but not empathic. When they looked for their own identity, they were disgusted. So you know, often it’s just those kinds of experiences that are really helpful to help students feel the impact. Kate O’Neill 7:00The thing is, technology has the potential to both exacerbate and alleviate gender inequities. From the gender pay gap to the lack of access and technology in developing countries. There’s plenty of work to be done to ensure that women have equal opportunities and access to the benefits of technology. But a fair few of these gender inequities might be alleviated by a more meaningful representation and visibility of women already in these fields, at least as far as young girls are concerned when they’re weighing their future career options. Dr. Oluwakemi Olurinola is an educator in Nigeria who is passionate about getting girls interested in stem the acronym in case you’re not familiar for science, technology, engineering and math, as she discussed with me in the first episode of season two, a brighter future for education. The problem so often is simply helping girls to recognize that they can pursue careers in engineering and other science and tech fields. Dr. Oluwakemi Olurinola 8:00And you walk into those science classes, and then you ask for their career paths. And you have like 98% of them wanting to be medical doctors or nurses or pharmacists. And I realized that basically, it’s isn’t that they loved science, but they didn’t know what other career options were available to them. So you have the problem of awareness, apart from gender stereotyping. And so I remember that a particular time I ran a program during the girls in science and I invited girls from science classes, I had almost 70 girls in the hall. And I asked how many of them wanted to be medical doctors and he had everybody’s hands up, I had only one person in that room of almost 70 girls who was considering a career in engineering. Kate O’Neill 8:42Giselle Mota is a futurist who brings simplicity, humanity and an innovative perspective to the sometimes abstract and complex topic of all things future of work. And she maintains an emphasis on inclusion. Giselle Mota 8:58We really need to think about being more inclusive of all right, I read a recent article that was talking about gender equity. So we talked a lot about pay equity, but sometimes we forget about gender equity. And we forget that, for example, what if you don’t identify as a man or a woman, for example? And what about your pay equity? Right? Isn’t that we don’t often talk about that we talk about like, men versus women’s pay. And we talk about like minorities and race and ethnicity but we forget about like other groups of people who What about their pay and their representation? And what about their leadership opportunities and things like that promotion? So there’s that and then there’s like men who also are are at home and their caregiving and therefore they’re taking care of the children. And like we forget about them. So it’s like there’s there’s so much that we often overlook because we we hyper focus on what we think inclusion means. We forget that it’s about all and I’m all about an inclusive future of work. And that means taking everybody with us, everyone. Kate O’Neill 9:58More inclusive of all indeed. In fact, as we discuss technology and gender issues, we’d be remiss not to acknowledge the growing recognition that gender is not binary. And many people’s experiences of technology are made worse because they don’t conform to the idea of that binary. There’s work to do here as well. These women are just a few of the many voices working to create a more equitable and inclusive tech world. By amplifying their voices and following their work, we can help ensure that women and girls are better represented and valued in the tech industry. That’s all we have time for today. But I hope this conversation has inspired you to think critically about the impact of technology on women and girls. Remember, as tech humanists, we have the power to shape the future of technology in a way that is equitable, inclusive and beneficial. And what was that Giselle? Giselle Mota 10:52And that means taking everybody with us, everyone. Kate O’Neill 10:56Thank you for listening to the tech humanist show. This episode was produced with help from our extended team, including research by Ashley Robinson and Erin Daughtery at Interrobang. You can find more information about the show’s guests and links to their projects at thetechhumanist.com where you can also find more episodes, or you can subscribe at iTunes or wherever you get your podcasts. Special thanks to all of our guests for lending their voices and ideas to help make the future a brighter place. I’m Kate O’Neill and you’ve been listening to the Tech Humanist Show from KO Insights.

It’s the end of the year, which means we’re all starting to wrap up our work years and turn our attention to other things… like Spotify Unwrapped! As fun as Spotify Unwrapped is (and it is—I share some of my own Spotify data in the episode), it speaks to the fact that we’re all slowly willing to accept more and more tech companies gathering huge amounts of data on all of us. In this case, that data seems harmless—and wrapped in a pretty bow!—but in a lot of cases, that isn’t true. My guests today help me unpack and explore what the world of excessive data collection has to do with the new age of surveillance, as well as how that data is used, and what businesses and tech leaders might be able to do to make products and services safer for customers, employees, and users. This week’s guests are Albert Fox Cahn and Kim Crayton. The Tech Humanist Show is a multi-media-format program exploring how data and technology shape the human experience. Hosted by Kate O’Neill. Produced and edited by Chloe Skye, with research by Ashley Robinson and Erin Daugherty at Interrobang. To watch full interviews with past and future guests, or for updates on what Kate O’Neill is doing next, subscribe to The Tech Humanist Show hosted by Kate O’Neill channel on YouTube, or head to KOinsights.com. Full Transcript to come.

Algorithmic bias has been a major topic over the last few years, but for many decision makers, the problem seems remote, confusing, or not a top concern. Even if you’ve been working at removing the bias from your business or technology, decades of bias in the data that got us here means we still have a ways to go, and we’re going to need everyone on board. In this episode, my guests and I explore what algorithmic bias is, where it comes from, how we may be unintentionally making the problem worse, and most importantly, what we can do about it. Guests this week include Dr. Dorothea Baur, Ana Milicevic, Dr. Chris Gilliard, Renee Cummings, Dr. Safiya U. Noble, Abhishek Gupta, Dr. Rumman Chowdhury, Calli Schroeder, and Giselle Mota. The Tech Humanist Show is a multi-media-format program exploring how data and technology shape the human experience. Hosted by Kate O’Neill. Produced and edited by Chloe Skye, with research by Ashley Robinson and Erin Daugherty at Interrobang. To watch full interviews with past and future guests, or for updates on what Kate O’Neill is doing next, subscribe to The Tech Humanist Show hosted by Kate O’Neill channel on YouTube, or head to KOinsights.com. Full Transcript Kate O’Neill: Perhaps it’s easy to hear “algorithmic bias” and assume we’re only talking about racism or sexism encoded into our data. “Only…” Those certainly are two very real and very relevant implications of the term, but they don’t tell the whole story. In fact—everyone who interacts with technology in any way is either affected by or directly affecting algorithmic bias on a daily basis, and most of it is invisible to us. Some people, of course, are affected more profoundly than others. Depending on your circumstances, that bias might even sometimes help you: if you happen to be in a demographic that trends toward higher credit scores, you may be more likely to get approved for a loan than someone from a different demographic with an identical credit history. But sometimes, and not all that rarely, the bias in algorithms can hurt you, and in surprising ways: the car insurance calculation algorithm, for example, is likely to quote you a higher premium if you’re a man. The problem overall is that, algorithmically, the individual doesn’t matter—it’s all about the aggregate. Decisions are made for you based on the average of all the available data across all of your demographic attributes, often whether these attributes are relevant or not to the decision at hand. Which would be one thing if we could see and impact the way these algorithms function, but as individuals, we don’t have that ability. We have no way of knowing what decisions they’re making for us, or how. Dorothea Baur, a leading expert & advisor on ethics, responsibility, and sustainability in finance, technology, and beyond, has some strong feelings about that. Dorothea Baur: One of the biggest achievements is two-hundred and forty years ago when the Enlightenment set in in Europe. Emmanuel Kant said, ‘hey, people! Dare to use your own mind!’ It was like a wake-up call, because up ‘til then…we didn’t really make an effort to explore the world because we thought everything was determined by God. By stepping out and using our own brains, we liberated ourselves from the shackles of religion or other authorities. And so now, are we just taking it too far? Have we used our brains so far that we are eventually creating machines that are smarter than us and kind of imposing their decisions, again, upon us,…that are equally as intransparent as God’s decisions, if you look at certain algorithms. Kate: Even if the algorithms weren’t biased, they would still impact our lives on a daily basis. But biased they indeed are. Which means more and more, the status quo—even the ugly parts of it—is being made permanent. The bright side is that people are talking more about the risks inherent in algorithmic decision-making, which means the bias baked into our data is at least an addressable problem. So that’s what I’m talking about today: algorithmic bias, where it comes from, how it affects you and your business, and how we can use strategic big-picture thinking to mitigate and erase the harm it causes. PODCAST INTRO Ana Milicevic: We talk about algorithms so much, but we talk about them as if they’re some magical entity that does something, and it’s not! Human programmers put in inputs and put in constraints and reflect their perspective of the world, and then machine language interprets that and channels it back to us. I just want everybody who has said something along the lines of ‘well, the algorithm does this,’ to replace that with, ‘the people who programmed this algorithm have done so and so.’ Because I think it removes responsibility from us as authors.” Kate: That was Ana Milicevic, a longtime digital media executive who is principal and co-founder of Sparrow Digital Holdings, discussing a trend she’s seen in the way we talk about the algorithms that run our apps, technology, and AI systems. We act like they are unknowable and beyond our control, when in truth, they’re just codifications of data models. The bias in these systems often stems from bias within the original data that was used to code them. This is what’s known as ‘data bias,’ one of the two types of bias in AI, where algorithms are trained using data that is itself already biased. This type of bias is frequently caused by the other type, ‘societal bias,’ which deals with how that data is collected, based on our assumptions and norms as a society. Faulty assumptions create blind spots or expectations that may not reflect reality, which leads to us gathering excess information that doesn’t matter (but that we believe does), or failing to collect data about things we believe we already understand. What that means is the data isn’t always the problem—it’s the top-level business decisions made before data is collected that have a massive impact on where it comes from and how it’s used. Solving the problem means challenging assumptions, which isn’t something a person—or team of people—unaware of their biases is capable of doing. Part of the issue is that the tech industry is still struggling to become genuinely diverse in ways that would make these underlying biases less hidden. Dr. Chris Gilliard, a writer, professor and speaker whose scholarship concentrates on digital privacy and the intersections of race, class, and technology, explains what that looks like at a company like Facebook. Dr. Chris Gilliard: The headline said something like, ‘Facebook inching towards their diversity goals.’ I don’t know the exact number, and they had gone from 4% to 5%, or something like that…They’ve offered many different excuses for why their diversity numbers are what they are, including blaming it on like a pipeline issue and things like that. These companies, on the one hand want us to believe that they can achieve the impossible through code, but on the other hand, it’s like super impossible to find black people who can work here. Kate: Beyond race, there’s a lack of diversity in class, thought, and ability. Ana Milicevic explains further. Ana Milicevic: Technology is still very homogenous. The people who get to build it, overwhelmingly, across the world, come from a certain background and think very similarly to one another. And unless we can figure out how to democratize this, we’re always gonna have an inherent bias reflected in the algorithms, even if the authors of software have the most noble intentions ever. Kate: Because even “nobly-intentioned” coders have to take shortcuts to get products out on time. Rather than attempt to collect new data, it’s easier—and faster—to borrow data from old sources. If there’s no one around with a different perspective or life experience, the coders may believe they’ve removed any bias or harm from their new system—because they weren’t able to recognize the bias that was already there. They may not have thought to check whether the data was collected fairly—or even be able to consider the motivations and intentions of those who initially collected it. Renee Cummings, AI ethicist, criminal psychologist, and Data Activist at UVA’s School of Data Science, explained one issue that keeps cropping up in the criminal justice system. Renee Cummings: So if you’re using data that has been gathered from communities that have been over-policed, of course the data is not going to be as accurate as you want that data to be. When you look at the history in the country of enslavement—when you think about things like the slave codes, and the Fugitive Slave Act, or you think of the 13th Amendment, or the one-drop rule, or the Three-Fifths Compromise, and Jim Crow, and segregation… how do you remove that from the data? How do you take that history of systemic racism out of that data? And if that history is baked into your data sets, what are you going to produce with that? Kate: It turns out… a lot of biased and harmful decisions. Renee Cummings: Risk-assessment tools were being used to give a score as to whether or not someone was going to re-offend, attaching risk-assessment tools to recidivism rates. And what we saw with this criminal justice is that many of the high-impact decisions happened there—when it comes to life or liberty, when it comes to life or death. And if you’re planning to use an AI or an algorithmic decision-making tool in the criminal justice system, you cannot be using a tool that is so opaque, or a tool that’s providing predictions that are overestimating recidivism. And I felt that what I was seeing was not a conscience when it came to the use of artificial intelligence, because too many of the tools were being designed from a place of biased data. And this is happening in every industry, anywhere processes or decisions are being digitized — which is pretty much everywhere. Once biased data has been used, the resulting output often becomes the building blocks of new code. With each generation of development, these layers upon layers of legacy bias and harm become more entrenched in the way our technology functions, and become more baked in, more permanent. We’ve been doing this so long it’s all but impossible to excavate the generations-removed biases layered underneath today’s code. One way this is happening is in the arena of crime, where we’ve been conditioned to think of crime in a particular way for so long, our technology evolved to do the same thing. Renee Cummings: I did a lot of work on investigating white-collar crime, and profiling white-collar criminals, and this is why I’m saying that so many of the tools that are being designed are all focused on the street. Let’s use the technology to really look at other spaces where crime is happening. Kate: The social bias that ‘street-crime’ is the only crime that needs policing is centuries old, but that assumption was rarely questioned, and now we have algorithms deciding where to deploy police officers. Lo and behold, they’re being dispatched to low-income, minority neighborhoods, because that’s where older crime data tended to come from, and where it tended to focus. And because people who aren’t living in those neighborhoods aren’t seeing the problems that ensue, they have a hard time believing or even imagining the consequences. Here’s Dr. Gilliard again to elaborate. Dr. Chris Gilliard: A big part of the problem is that a lot of these effects are invisible, they disproportionately or disparately impact marginalized populations. So, I’ve talked, spoken, and written about Amazon Ring a lot. Part of the problem with talking about it is that most people who would invest in a Ring only think of law enforcement in terms of a institution or body that works for them, never as one that’s going to work against them. So it’s very hard; they often place the safety of their packages as more important than the safety of black lives. Even if you explicitly ask them, they would still say, ‘well, I need to get, y’know, whatever product it is.’ And so until that changes, some of these probably aren’t going to change. Kate: Basically, we have a lot of work to do. Part of that work might start with reframing how we talk about these issues. Dr. Safiya Noble, Professor of Gender and African American Studies at UCLA and author of Algorithms of Oppression: How Search Engines Reinforce Racism, asserts that using the word ‘bias’ exacerbates the problem by removing responsibility. Safiya U. Noble: The real critique of the implications of the work is getting defamed and depoliticized. How you see that now is instead of talking about algorithmic discrimination or oppression, which are kinds of words I use, people are talking about things like ‘bias.’ One of the things that does is it neutralizes the power of the critique by devolving it into a set of arguments that, y’know, everybody is biased, everything is biased, and that’s not helpful! These things are structural, they’re not just living at the individual level of how a coder or how a programming team thinks. All forms of classification and categorization have implications. Most of the ways the technology is oriented is around, like, binary classification systems, and that already is a problem. It certainly is a problem around gender, it’s a problem around race… And you’re also creating social structure through those categories. And what we know is that those categories have always existed, at least in a Western context, as hierarchical. So if you have a racial classification system like we have in the United States, where White is the highest valued, most resourced, and most powerful, and Black is the antithesis of that, and everything in between in vying for its relationship to power or powerlessness, those systems become real! So the question is, how do we create systems that are not hierarchical, and where power is not distributed along those lines of classification or categorization? Instead, we are reinforcing those systems of power over and over and over again. Kate: Regardless of whether the intent is to harm, the fact is that these algorithms do cause it. Too often, decisions around AI, tech, and algorithms are based on cost-efficiency and timeliness of product release, or worse, a vacuum of ignorance, which is the case when the top-level decision-makers hear about the importance of a new technology and decide to integrate it into their product launch without any practical purpose, prioritizing ‘popularity’ over practicality. In either case, so long as there is inequality, algorithmic bias and its oppressive consequences are inevitable, and the technical debt increases yet again. But bias and oppression aren’t only coded into our lives by tech developers and coders. As individuals, we encode bias into technology as well. When it comes to search engines, tons of data goes into aggregating the best results for a search query, using information on which links past users clicked upon seeing similar results. Dr. Noble helps teach her students how this information is biased by having them search the Internet for an identity of their choosing. The results help them realize that algorithmic bias affects everyone—which was made all too clear at the University of Illinois… Safiya U. Noble: I had a disproportionately high number of white women in predominantly white sororities. I think almost all of them had done a search on ‘sorority girl,’ and were pissed. Kate: Because what turned up? Safiya U. Noble: Porn. Kate: Because porn was most commonly associated algorithmically with their identity. But those biases didn’t suddenly start their existence with the advent of the Internet. These are cultural biases, which Dr. Noble reinforces another way. Safiya U. Noble: I don’t think, like, searches on black girls, and latina girls and asian girls that would surface porn meant that much to them, when they looked for their own identity, they were disgusted. I also have them go look for the same people and communities in the library. This is a place where they see the subjectivity of knowledge. Where they start to realize, y’know, ‘I was looking up my sexuality, and it was in a cluster of books about sexual deviance, and I’m not feeling that.’ And so then they start to see that knowledge is subjective, and it’s political…Those experiences help students feel the impact of the work that you’re talking about. Kate: Even if you’re aware of these cultural biases and make efforts to control for them, there may be more bias in your data than you think. Some people input bias into new systems intentionally, through a process known as data poisoning. Abhishek Gupta, machine learning engineer, founder of the Montreal AI Ethics Institute, and board member of Microsoft’s CSE Responsible AI board warned about data poisoning when we spoke. Abhishek Gupta: If you in all earnestness put bias mitigation efforts in place as you were developing an ML system, if I was to compromise the model through an attack like data poisoning, I could negate the effect of that bias mitigation measure, and basically render useless that effort that you put in, and create this situation where I’m slowly able to compromise all of these different aspects of the ethical considerations that you put in place for that system. Kate: Which is how a well-known example like Microsoft’s Tay twitter account happens. Tay was an artificially intelligent social chatbot designed to interact on Twitter in 2016 and learn from its interactions with the denizens of that platform. Within very short order, it had become corrupted with racist, Nazi, anti-Semitic hate speech. But this phenomenon goes well beyond Tay or chatbots. Any algorithmic system can become corrupted through abuse, misuse, and the limits of inadequate guardrails. Dr. Chris Gilliard explained how platforms like Facebook’s advertising model make that easy to do. Dr. Chris Gilliard: Pro-Publica essentially found that if you wanted to, that it was possible to target a housing ad and have certain groups not see that ad. One of the most pernicious parts of this is that, people don’t know what they’re not seeing! Someone using Facebook wouldn’t know that they’re not seeing an ad for housing. Facebook would call it a ‘mistake,’ but I think it’s incumbent upon us to realize that these are the products of decisions that Facebook made.” Kate: And it isn’t just Facebook’s data that can be poisoned. It’s everyone’s data. And if you use data for any part of your business, whether you generate it yourself or buy it from another company, some percentage of it may be poisoned, and there’s probably no way to figure out how much. Even if you never wrote another line of code that discriminated against your users or customers based on their demographics, it’s probably happening anyway. There’s also the question of bias showing up due to the origin of a technology. Dr. Rumman Chowdhury: The origin of technology absolutely does matter. Things that are built for military use, even if it is moved into the commercial space—which is, by the way, a lot of technology—will still hold with it the vestiges of, let’s say, surveillance, or monitoring, because it is ultimately built assuming the world is a particular way. In other words, there are ‘good people’ and ‘bad people.’ There’s the people I’m protecting, and the people I’m fighting, ‘cause that’s just how the military is structured. Kate: That’s Dr. Rumman Chowdhury, currently the Director of the Machine Learning Ethics, Transparency, and Accountability team at Twitter. Our tech today is coded with vestigial data collected by people with a specific understanding of the world, which leads to repeating issues that could have been prevented. Dr. Rumman Chowdhury: Fundamentally, your view of the world will impact the technology that you build…And this has kind of been some of the critiques of the way some of these research firms have been trying to arrive at sentient AI, is by having them play games. And they have them play combative games, rather than collaborative games. And your objective function matters! If my function is to win a game where I have to kill everybody, or it’s a zero-sum world in which I have to have the most amount of points to win, that sets up a very different system than one in which I’m training it to play a game where we have to be collaborative and collectively succeed. Kate: So let’s bring it back to you! Collective success is a worthy goal, so how do we get there? How can you make efforts to lessen or eradicate bias within your company? What choices can you make to reduce your business’s negative social and global impacts? First, don’t collect data just for the sake of collecting data. Start by asking yourself the big picture question: what is the purpose of our business? What matters to our customers or users, and to how we operate in alignment with that? For more advice on that front, check out our recent episode “Why Human Experience?” Once you’ve determined what matters, you can determine what data you actually need, rather than just collecting and storing data for the sake of it. Calli Schroeder, an attorney specializing in privacy, security, and technology law and member of the Global Privacy Council at EPIC Privacy, elaborates. Calli Schroeder: People collect so much just because they can. You should evaluate with this costs you in effort, versus what you’re getting from it. ‘Collect it just so you have it just in case’—that’s such an irresponsible perspective. The more information you have, the more risk you have of a breach, and the more liability you have. If you have a data breach and all you’ve collected about your clients is name and mailing address for the services, that’s hugely different than if you’ve also collected race, and gender, and income, and financial account information, and sexual orientation, and—why do you need that? Why do you want that? Kate: The best way not to discriminate against your employees, customers, or users on the basis of their identifying characteristics? Don’t have that information about them. However, there are industries where that information can be valuable—namely, healthcare. Here’s Dorothea Baur again. Dorothea Baur: So, you talk about precision medicine, you get the right treatment based on all your specific characteristics—with the help of AI, patterns can be evaluated better. So there it’s like a reverting of the ethical problem, it’s like, ‘please discriminate me!’ I want you to take into account all my characteristics. I want you to know how many veggie burgers I eat, I want you to know how much I sleep, whatever I do, all my risk factors, etc., because if this helps me to get the right treatment, I’m willing to lay it bare. Kate: Beyond medicine, there’s the environment. Dorothea Baur: The whole problem of pattern recognition in machine learning, where if it’s applied to humans, it is full of biases, and it kind of confuses correlation and causation, and it’s violating privacy, etc. There are a lot of issues that you don’t have when you use the same kind of technology in a natural science context, you know? Where you just observe patterns of oceans and clouds and whatever, or when you try to control the extinction of species. I mean, animals don’t have a need for or a right to privacy, so why not use AI in contexts where it doesn’t violate anyone’s moral rights? Kate: If you’re in an industry where you can provide better service by collecting additional information, there are still actions you can take to reduce bias. Most notably, hire employees and bring on experts and consultants that are every bit as diverse as and reflective of the stakeholders and communities you are serving, and listen when they explain any ramifications or consequences affecting their communities that you may have overlooked. Giselle Mota, Principal Consultant on the Future of Work at ADP, joined me to discuss exactly that. Giselle Mota: Diverse minds are needed at the table. So we need designers, policymakers, data scientists, that don’t only look the same, and are not the traditional people who’ve always been building the same stuff—we need to address the data itself. You have to be accountable to what it is that you’re doing and how you’re using people’s data, what data’s going into how you’re training your algorithms, from when you’re allowing that algorithm to determine candidate relevancy, if you’re gonna hire someone, if you’re gonna determine somebody’s credit, or image classification, standards that we apply on people… like, you have to mix up that data with a mix of representation. Kate: Renee Cummings echoed that sentiment, reiterating that simply talking about mitigating bias isn’t enough, because again—we don’t know what our biases are. We can’t know what we don’t know. Renee Cummings: I think there are many companies right now, particularly at this moment, where systemic racism seems to be on the front burner—there are many designers who are presenting tools that are detecting and monitoring and managing risks, and they have bias and discrimination in there, and racism—but it’s bigger than that. You’ve got to go back to the subconscious. What we really need are not only data scientists designing tools for criminal justice, but criminologists, and criminalists, and criminal psychologists, and other individuals involved in the criminal justice system working alongside those data scientists. Why use new technology to amplify historic biases that have kept us trapped? It’s going to take a combination of thinking, a new type of consciousness that we’ve got to develop, vigilance—because you’ve got to be constantly aware, and we all have biases, we all have prejudices—but it also calls for diversity, and equity, and inclusion, as a risk-management strategy. Diversity in itself just doesn’t create an AI system that’s perfect, but at least we will know that certain checks and balances have been applied. Kate: There’s also no shame in just calling for a do-over. Certain technologies have so much bias embedded within them, and allow further bias to cause harm to people and communities in the real world, that it might make sense to just… get rid of them and try again. Dr. Gilliard thinks that’s what we should do with Facial Recognition, where bias has been responsible for immense harm in the lives of many, and especially people of color. Dr. Chris Gilliard: Many people for years have been saying that Facial Recognition should either not exist, or should be heavily regulated. And those people have been told, ‘the horse is already out of the barn,’ like, once a tech is out in society, like, you can’t take it back. But we’re seeing different cities, townships, municipalities ban facial recognition. We’re seeing companies step back in one form or another. We’re seeing cracks, and having some victories. As a society, we’re not just stuck, like, once some clown puts something out there. One of the things I’ve seen that does give me a little bit of hope is there are more and more people not only saying that we have to do that work, but being inside these companies and holding them accountable for doing it. Not after the harm is done, right, not after the toxin’s been released, but before it’s released. Kate: And that’s what we need to do. Wherever possible, decisions need to be made to mitigate bias before products are released. In the short term, it may seem more cost effective or efficient to get your product out as soon as possible, but if it’s released and ends up causing more harm than it’s worth, it might also cost you more money in the long-run. It’s a lot harder to recall a product or have make changes to an operational system than it is to do that work ahead of time. So whether you’re a CEO or you have the ear of one, know that there are things you don’t know. Bring in intelligent people to collaborate and elevate your product or service. Be aware of your own biases—at least as aware as you can be—and be open to hearing from people about things you might have missed. Be aware of data poisoning methods and make efforts to counteract or prevent them. Decide on a big-picture level what data is essential to your business, and don’t collect anything beyond that. This will make you less likely to suffer a data breach and save you money in both data storage and processing power. The more problems you catch ahead of time, the less bias will be present in your final product, and the more future-proofed your business becomes. An added bonus is that will likely attract more customers and users as well. If we can do all of these things, our future technologies might do better than ‘reduce harm.’ They might even move society in a more positive direction. I’m Kate O’Neill. Thank you for joining me on this deep dive into algorithmic bias, harm, and oppression, and what we can do to change it. [PODCAST OUTRO]

“Supply chain issues” has become a catch-all term for a lot of frustrations these past few years, but it doesn’t paint a full picture of the situation, leaving out a key element: the humans who make it function. In this episode, my guests and I explore exactly how interconnected we all are, who the people keeping the supply chain running are, and how every decision (no matter how small) has global impact. We even examine how in the end, all of us, whether we’re individuals or business leaders, have the ability to alleviate some of the pressures on the supply chain by making small changes to the way we live. Join me as I explore how to make the future a brighter place. Guests this week include Christopher Mims, AJ Jacobs, Charlie Cole, and John C. Havens. The Tech Humanist Show is a multi-media-format program exploring how data and technology shape the human experience. Hosted by Kate O’Neill. Produced and edited by Chloe Skye, with research by Ashley Robinson and Erin Daugherty at Interrobang. To watch full interviews with past and future guests, or for updates on what Kate O’Neill is doing next, subscribe to The Tech Humanist Show hosted by Kate O’Neill channel on YouTube, or head to KOinsights.com. Full Transcript Kate: The term ‘supply chain’ was popularized in the 1980s, and has been in use since The Independent coined it in 1905. But in the past few years, especially since the onset of the COVID pandemic, it’s become a household term. And with its growing popularity, it might be time to address something I feel is missing from that language. Michael Gibb summarized this quite nicely in a piece he wrote for Aeon: “The image of a supply chain has…become so entrenched in our thinking that we find it hard to describe the process in any other way…The success of the supply chain metaphor is now holding us back, limiting our capacity to solve the problems plaguing the global economic system. Like all good metaphors it has pared back complexity in order to expose something fundamental, but in this case, that complexity is us. As products and their journeys have taken centre-stage, we – the people who use and make them – are recast as mere stagehands, guided by economic forces that are ultimately beyond our control.” This may come as no surprise to followers of my work, but what’s missing from the term is the humans that make the supply chain run, and in a sense—keep it alive. Christopher Mims: I really wanted to understand the scale of global shipping because it is the physical manifestation of the world economy…it’s weird how we have this blindness, I think, to what I would call the global industrial metabolism. If you think of the earth and human civilization as a big unified system, y’know, it’s an ecosystem. And all of that extraction of material and its transformation into physical goods, and its shipment to us, it really is, y’know it’s like… the leviathan. And this is its metabolism. And we’re a part of it. Kate: That quote comes from Tech Humanist Show guest Christopher Mims, tech columnist at the Wall Street Journal and author of Arriving Today: From Factory to Front Door — Why Everything Has Changed About How and What We Buy. We’re starting with it because the biological metaphor he makes helps illustrate the importance of the living beings that built and operate every step along the chain. It’s become too easy to think of it as just a technological marvel, or something too complex to understand, but if we think of it as a living organism, we can find our place in the greater whole. Just as a single white blood cell is part of a larger system that helps fight off infection inside our bodies, each of us is one part of an ever-moving and ever-changing whole that we impact on a daily basis. You might think your personal decisions don’t have much of an impact on the world around you. But every decision, no matter how small, has global impact: which brand of coffee to stock your break room with, whether to print invoices or send digital copies, where you buy groceries, what brand you buy, who files your taxes—it all plays into the global-scale digital economy that animates the supply chain. As the world is increasingly digitized, those decisions become data, which is then used to code predictive algorithms that shape the future of our world. So that’s what we’re talking about today: how you affect the supply chain, and how you can make decisions that help build the best future for both technology and humanity. AJ Jacobs, author of Thanks a Thousand about his quest to thank every person involved in the process of making his morning coffee, came on the show to discuss what he learned about what goes into a single seemingly-simple “cup of coffee.” AJ Jacobs: It doesn’t take a village to make a cup of coffee, it takes the world. I chose coffee, ‘cause I love to drink coffee, but I could have done the exact same thing for a pair of socks, a pen, this chair I’m sitting on…It takes an incredible amount of technology, and it takes humans! The obvious one I knew about was the barista. And I probably, if I thought about it, I was like, ‘oh yeah, there’s a farmer who grows this,’ but in-between there are hundreds of people! There’s the people who drive the truck that holds the coffee beans, and they couldn’t have done their job if someone didn’t build the road, and make the asphalt, and paint the lines on the road. And government plays a huge part in getting these products to us, ‘cause it’s the government that built the roads, and has the firefighters who will put out the fire if my coffee shop catches on fire… Kate: Or perhaps that made the regulations that said that there should not be bugs in your coffee. AJ Jacobs: Right, yeah! I couldn’t believe, when looking at the history of food, how disgusting it was before government regulation. And it has given me quite an appreciation, it’s made me more grateful, because you realize, every product—it’s like a story, and it’s filled with both joy and sadness. As part of my project, I thanked a thousand people, but I could have expanded it. I could have thanked 10,000, or 100,000. Kate: 100,000 people having a hand in a single cup of coffee may sound extreme, but it’s probably not far off. Globally, almost half a billion people work in the supply chain somehow—which is a number that’s greater than the population of every country in the world except China and India. And when you have that many people involved in anything, it becomes incredibly difficult to keep track of how individuals are being treated, or the global impacts of each tiny decision being made, something AJ had to confront on his journey of gratitude. AJ Jacobs: A huge issue that I struggled with is, not all the people on the supply chain are necessarily making the world a better place. A lot of the labor is done in developing countries where they don’t earn as much. And one entity that I had to thank was Exxon, because they provide the fuel for the coffee truck, probably for the ships that take it from Columbia to the United States… It was a little bit of an ethical dilemma because I wouldn’t have my coffee without them, but I also think that they are short-term thinkers who are doing incredible damage. I still believe that the positive effects of globalization outweigh the negative, and that it will eventually lift everyone up—’lift all boats’—but it’s… there’s no black and white answer. Kate: AJ also points out in his book that if everyone along the supply chain was paid a living wage, a single cup of coffee would cost over $25. This is because many workers are extremely underpaid, and in some cases, aren’t paid at all—which is the case with coal miners in North Korea. There, the job of a miner is inherited, rather than chosen, and recent defectors have expressed that those workers are unpaid and aren’t allowed to leave. Those who try to escape are captured and punished at labour training camps. If that sounds like modern slavery, it’s because it is. You may think, ‘Well, I wouldn’t order anything made in North Korea!’ but due to the complex nature of the supply chain, you may be wrong. 98% of North Korean coal exports go to China, who is one of the world’s largest coal exporters. So if you get your coal—or your electricity—from a company who gets any amount of coal from China, there’s no way to say for certain that it wasn’t provided at least in part by slave labor. Even if you can say for certain that slave labor had no hand in anything that you buy or produce, the supply chain is rife with child labour, sexual violence, restrictions on trade unions, and often inadequate or a complete lack of job safety. This issue is a growing concern, as G20 countries account for roughly 85% of the world’s GDP and 80% of global trade, which means that while those countries may not be directly responsible for human rights violations within their borders, the vast majority of their wealth comes from the exploitation of human labor abroad. When we look at the problems on this scale, it can be depressing, overwhelming, and seemingly impossible to make or suggest improvements without crumbling or backing up the entire chain, as Christopher Mims lamented. Christopher Mims: Step one is really describing the problem, and what I have found again and again is, we haven’t even gotten to step one. Even people who are supposedly experts on supply chains, there can be a tunnel vision—they’re unaware of what goes on in other links in the supply chain. As we saw during the pandemic, trying these sort of ‘point’ solutions doesn’t work. Classic example, Joe Biden gets on TV, he’s like, ‘we’re gonna make the Port of LA Long Beach—where 40% of all goods imported into the US come through—operate 24 hours a day.’ Sounds great! …It doesn’t work. Because if you make that port run 24 hours a day and you want more through it, you have to find a way to incentivize all of the truckers who are taking those shipping containers out of the port to operate 24 hours a day. Then you have to get all the warehouses that they’re taking the shipping containers to to operate 24 hours a day. Also, by the way, there aren’t enough truckers or warehouse space even if you had those ports operating 24 hours a day. Kate: This is the macro-version of a problem that exists at every stage in production and shipping. If we zoom in and look at an Amazon fulfillment center, for example, we can see the same issue cropping up at every point in the process. Part of the problem is the way these facilities are run, with every action and moment optimized for peak efficiency, turning humans into cogs in an algorithmic machine. Christopher Mims calls this trend “Bezosism.” Christopher Mims: Bezosism, it’s like the modern-day version of Taylorism or Fordism… the bottom line is, this is how you optimize the repetitive work that people do. Amazon is the best at doing this, but every other company that can is trying to do the same thing: make workers more productive by managing them with software and algorithms, kind of whatever the consequence is. Whether it’s an Amazon warehouse, or any fast-food restaurant you can name, or a call center… all of these places are now managed by algorithm, and the workers are monitored by software. Instead of a boss telling them to work faster, it’s the software cracking the whip and being like, ‘you’re not working fast enough, you need to pick packages faster’ in this Amazon warehouse, or ‘you need to flip burgers faster’ if you work at a McDonald’s. But this is becoming the dominant way that work is organized if you don’t have a college degree, if you’re an hourly worker… we’ll just let the software do it! Kate: If a task, say, placing an object into a box and sending that box to the next station, is designed and optimized to take, ideally, 7.6 seconds, it cannot take any more or less than 7.6 seconds. If it takes longer, there will eventually be a backup at the station. If the person working at that station sacrifices a safety protocol and takes just 7.5 seconds, the people ahead of them will have to speed up their actions as well, even if that means sacrificing their own safety or physical well-being. Even bathroom breaks are reportedly timed and optimized, with disastrous effects on other workers if someone takes too long to wash up. Put simply: even a fraction of a second multiplied a few thousand times can warp the entire system. If it turns out that 7.5 seconds is more optimal, the algorithms that run the facility may decide that this is the new normal, and future workers at that terminal will be expected to meet this new quota, regardless of whether they can do so safely. And with Amazon operating around 2,150 fulfillment centers globally, a single person’s action can affect tens of thousands of people worldwide. Algorithmic decision-making was designed to optimize speed and efficiency, but not necessarily human well-being. In fact, most businesses are designed to continue growing, regardless of the consequences. John C. Havens, Executive Director of the IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems, explains further. John C. Havens: Often times, value is framed in exponential growth, right? Not just profit. Exponential Growth is an ideology that’s not just about getting some profit or speed, it’s about doing this. But when you maximize any one thing, other things by definition take less of a focus. And especially with humans, that can be things like mental health. This is not bad or evil, but it is a decision. And in this case it’s a key performance indicator decision, the priority is to get something to market, versus, how can we make innovation about mental health? The answer is outside of the technology. I think if we eschew, and give away—and when I’m saying ‘give away,’ is more like the ultimate sense of why looking at our values are so critical. But the metrics are critical here, because we tend to focus on productivity. So we ignore the now. Most of gratitude is just being able to look at what you have now and say, ‘this is stuff I really treasure and value.’ If parenting, for instance, is one of those things, well then I’m going to allocate time with my kids, even though that half an hour at dinner I could be doing more work. Kate: Most businesses along the supply chain, at least today, aren’t driven by our values or by maximizing human well-being. They aren’t asking what humans are giving away to meet the expectation of productivity. And in a macro sense, we don’t see what we’re asking other humans to give away so that we are able to get our packages the day after we order them. Ironically, the early days of the birth of the assembly line didn’t look this way. Those days, human input was still valued, which perhaps can give us hope that it might be able to be again. Christopher Mims explains. Christopher Mims: The Toyota production system was developed in a context of extreme worker agency, of complete loyalty between employer and employee, lifelong employment in Japan, and workers who had the ability to stop the assembly line the instant they noticed that something was not working, and were consulted on all changes to the way that they work. Honestly, most companies in the US cannot imagine functioning in this way, and they find it incredibly threatening to imagine their hourly workers operating this way. Frankly, it is just disrespectful. Kate: While researching his book, he also had a chance to do a ride-along with a UPS driver, and got a chance to experience the importance of worker agency firsthand—and the consequences of losing it. Christopher Mims: My host, Jenny Rosato, she’s been a driver for more than 30 years, she’s the only woman driver at her delivery station in Stanford, CT. She knows all of the methods that UPS drivers use to do the same thing over and over again but stay safe. I had this experience of just kind of doing a couple things wrong, spending the whole day with her, my knees were hurting because of the like hard steel stairs that I was kind of leaping down in the wrong way, and I was starting to get sore in other ways because I wasn’t really picking up packages correctly. So, really beginning to understand how those processes have been developed at UPS over so many years, and how much it matters that those drivers do have agency. And it’s because last model delivery is a skilled profession! If human beings are able to develop that skill and their labor is optimized in concert with them, so they have agency, they can get better and better at it, and produce the highest quality ‘goods,’ which in the end is just getting your packages from point A to point B. Kate: But in the interest of ongoing automation and, again, exponential growth, in general businesses are looking at ways to replace humans as much as possible. Every time this happens, the methods we’ve used along the supply chain become more entrenched and harder to change. Once a machine has been designed for a specific task, that task can’t be altered without also altering everything that comes before and after it, or the new, and probably costly, machine will become obsolete. And because of the way the system was designed, we just don’t have time for that! Today, the sequence of events that starts with the ingestion of a shipping container into a port from a barge, truck, or train happens more than a million times a day, roughly 13 times a second. That means things can’t be drastically altered without halting or slowing down the entire supply chain. One thing that does leave room for potential change is that right now, robots are not very good at fine-motor functions, meaning there are still roles for humans. But with every day that passes, today’s status quo gets closer to becoming permanent, and rethinking the way we do things becomes less and less possible. One thing we should all be able to agree on is that the current system of global shipping is not perfect, so locking in the way it works today will mean trapping ourselves in a system that is not only actively harmful to a good many humans, it’s also inefficient. Charlie Cole, CEO of flower delivery website FTD.com, spoke to me about one of the reasons our system is as inefficient as it is. Charlie Cole: The real interesting aspect—and this isn’t unique to flowers, it’s actually true for a lot of businesses and a lot of businesses in the supply chain experienced this during the cargo ship fiasco off of Long Beach port—the source is remarkably centralized. The New York Times did a piece, and they estimated that 90-92% of roses that are bought in America for Valentine’s Day come from Columbia and Ecuador. Kate: When a single good that is meant to be sent everywhere on the planet comes from a single location, the amount of shipping required goes up dramatically. A famous example is cod: these fish are caught off the coast of Scotland, shipped to China to be filleted, and then sent back to Scotland to be put on the shelves in grocery stores. And yet, this wildly unnecessary 20,000-mile journey is a drop in the ocean compared to how complicated it is to build a single smartphone. A single device contains batteries, which are made in Korea out of lithium from Australia. It also contains microchips, which are first harvested as quartz in Appalachia, merged with silicon grown in Japan, and finally forged into their final form in Taiwan. The internal lasers are manufactured in Texas. The shatterproof glass comes from sand mines in Minnesota that’s shipped to Kentucky to be blown… each phone contains more than 300 components, and each of those has a journey that is just as complex and irrational, all in the name of cost saving and… efficiency? Even the digital aspects of this business model can be convoluted, as more and more companies shipping the same products outsource to other companies to fulfill their deliveries. Charlie Cole explained how he learned this during a snowstorm, while he was hand-delivering flowers to customers to make up for weather-related supply chain delays in Seattle. Charlie Cole: The second guy, I was holding a dozen beautiful long-stem roses, and he opens the door and he’s like, ‘wait a minute… there’s supposed to be three dozen.’ And what had happened is, he ordered from a third party that then outsourced one of the three orders to us, and the other two were coming from FedEx. And I was like, ‘woah, that’s a technological challenge.’ Kate: So now that we’ve briefly touched on how complicated the supply chain is, and how hard it can be on the individual humans working within it, let’s get back to you — and all of us. What can we do to make things better? AJ Jacobs: All you can do is live your life but try to improve anything that you see along the supply chain. Kate: Every purchasing decision you make has wide-reaching effects on the global supply chain. You may not be able to erase the human rights abuses happening in distant countries, but you can lessen the demand for goods and services that thrive on those cruelties. When you’re due for a phone upgrade, but your phone still works… maybe don’t replace it right away. Even delaying that purchase lessens the burden of demand throughout the supply chain. If you have something you want to buy on Amazon, maybe think about whether you actually need it ‘by tomorrow,’ or if you can wait, maybe even just until you have a few more items in your cart. These are very small changes of habit that can benefit us all to adopt. And if you’re making purchasing decisions for a medium to large sized business, have someone do research on where the products you’re buying are coming from, where their materials are sourced, and see if there is an alternative. It may cost a bit more, but if it doesn’t put as much pressure on the system and the humans that keep it moving, that’s a win for humanity. Charlie Cole has another way he helps lessen pressure on the supply chain. Charlie Cole: I think COVID shined a light on this: small businesses are the core of our communities. Right? They are the absolute core, and I think it was always nice to say that, but now we know it…I think to actually effectively run a marketplace which is fulfilled by small businesses, you need to invest as much in helping them win their local market independent of you. Kate: Patronizing and helping small businesses—especially those utilizing locally-sourced products—is another excellent way to lessen pressures on the supply chain. Go to your local farmer’s market instead of shopping at a massive retail chain! Use a tax service from down the street who you know works with other professionals in the neighborhood, rather than using the massively popular firm that has optimized every step in the process. And it doesn’t just apply to what you buy—you can also make positive changes by shifting the way you participate in philanthropy. Here’s AJ again with an example. AJ Jacobs: I of course had to thank the people who provide water to New York City, because coffee is 98.8% water. So I went up and met some of the hundreds of people who work for—the engineers, the chemists, the people who wade out into the reservoir to test it in the middle of winter, and it made me realize just how crazy it is that I’m able to turn a little knob and get drinkable water. And I have to remind myself that this was not true for 99% of human history, it’s still not true for billions of people around the world. So I donated to a charity that provides containers that make safe water for people in developing countries. You gotta look at the big picture when giving to charity—the most effective charities are as much as 100 times as effective than the least effective. Kate: Do your research and invest in a charity that you know will be effective. Or, if you don’t have time to do that research, AJ recommended an organization called GiveWell, which is associated with the Effective Altruism movement. Their focus is on researching charities for you to determine which ones will do the most good with your money. When we zoom out to look at the biggest picture, we can see both how massive the system is and how we’re all connected by it. The good news there is that every one of us has the ability to take small actions in how and what we buy, and those small actions, over time, can lead to better outcomes for an awful lot of people. Being intentional about how we engage in the supply chain can also help us feel more appreciative of what we consume, as AJ Jacobs demonstrated so well, and can lead us to make choices even more meaningfully. It’s an amazing thing, this global supply chain, and even if it’s not always easy to be cognizant of it, when we are, it’s very easy to be grateful for it, and for every human being that plays a part in supplying us with what we need and want.

This week, we’re exploring why it behooves businesses and business leaders to look at their users, consumers, customers, etc., as humans first. Slightly shifting perspective to consider the humanity behind purchasing decisions can lead to greater loyalty, more frequent use, and genuinely happier users, all of which add up to more business success and better outcomes for the world. Together with my guests, we discuss how human-centric decisions apply to various industries and how you can build better relationships that lead to success for all of humanity. Guests this week include Charlie Cole, Neil Redding, Dr. Rumman Chowdhury, Ana Milicevic, Cathy Hackl, Marcus Whitney, and David Ryan Polgar. The Tech Humanist Show is a multi-media-format program exploring how data and technology shape the human experience. Hosted by Kate O’Neill. Produced and edited by Chloe Skye, with research by Ashley Robinson and Erin Daugherty at Interrobang and input from Elizabeth Marshall. To watch full interviews with past and future guests, or for updates on what Kate O’Neill is doing next, subscribe to The Tech Humanist Show hosted by Kate O’Neill channel on YouTube, or head to KOInsights.com. Full Transcript Kate O’Neill: When you buy something, you’re a customer. But — to paraphrase a line from the movie Notting Hill — you’re also just a person, standing in front of a business, asking it to treat you like a human being. Over the last two decades plus working in technology, I’ve often held job titles that were centered on the experience of the user, the consumer, or the customer. In fact, the term ‘customer experience’ has been in use since at least the 1960s, and has become so common that a recent survey of nearly 2,000 business professionals showed that customer experience was the top priority over the next five years. And while generally speaking this emphasis is a good thing, my own focus over the past decade or so has shifted. I’ve realized that the more macro consideration of human experience was a subtle but vital piece missing from the discussion at large. Because when we talk about experience design and strategy, no matter what word we use to qualify it—customer, user, patient, guest, student, or otherwise—we are always talking about humans, and the roles humans are in relative to that experience. In order to refocus on human experience instead of customer, you have to change the way you think about your buyers. You owe it to yourself to think not just about how people can have a better experience purchasing from your company, but also what it means to be fully human within the journey that brings them to that moment, and the uniquely human factors that drive us to make decisions leading to purchase or loyalty. A recent piece by Deloitte shared in the Wall Street Journal echoes this idea and offers five ways to be more human-centric in business: 1) be obsessed by all things human, 2) proactively identify & understand human needs before they are expressed, 3) execute with humanity, 4) be authentic, and 5) change the world. That’s what today’s episode is about: using empathy and strategic business-savvy to understand what it means to be human, and how that intersects with the worlds of technology and business. Neil Redding: “When you look at everything that has to do with buying and selling of things, it’s so closely tied with what we care about, what we value most, value enough as humans to spend our hard-earned money on. And so, the realm of retail reflects something really deeply human, and profoundly human.” Kate: That was Neil Redding, brand strategist and self-described “Near Futurist” focused on the retail space. He’s right—buying and selling things has become deeply entwined with humanity. But when we purchase something, it’s not because we think of ourselves as “customers” or “end users.” We buy because we have a need or desire to fulfill, and sometimes that need is purely emotional. A ‘customer’ buys your product—a human buys your product for a reason. 84% of consumers say that being treated like a person instead of a number is an important element to winning their business. It does seem like business professionals are catching on, as 79% say it’s impossible to provide great service without full context of the client and their needs. But understanding something isn’t the same as putting it into practice—only 34% of people say they feel like companies actually treat them as individuals. One major difference is the question of framing. Customer experience frames the motivator as, ‘how effectively the business operates the events related to a purchase decision.’ It drives companies to focus on improving their own metrics, like bringing down call center wait times. These may yield worthwhile outcomes, but they’re inherently skewed to the business perspective and aligned to the purchase transaction. Focusing instead on human experience shifts the perspective to the person outside the business, and what they want or need. It allows consideration of the emotional state they may be bringing to the interaction, which leaves greater room for empathy and context. A human experience mindset suggests that each individual’s unique circumstances are more important than aggregate business metrics, because the reason why that person is interacting with your company probably can’t be captured by measuring, say, how long they might have to wait on the phone. You could bring that wait time to zero and it still may not have any impact on whether the person feels heard, respected, or satisfied with the outcome — or whether they want to engage with you again. But as fuzzy as it is to talk about human experience, we know that measurement is fundamental to business success, so we have to find a way to define useful metrics somehow. For each business, that number is likely a bit different. So how do you know whether your customers feel like they’re being treated as humans instead of just numbers? Charlie Cole, CEO of the flower delivery website ftd.com, believes one answer is obsessing over customer satisfaction metrics. Charlie Cole: “The best way to win this industry is just kick ass with the customer. We obsess over NPS scores, uh, as kind of leading indicators of LTV scores.” Kate: If you’re not familiar with the acronyms, allow me to decipher: NPS stands for Net Promoter Score, which measures how likely the customer is to recommend the business, and LTV in this context means ‘lifetime value,’ or the amount a customer may spend at your business over the course of their lifetime. Charlie Cole: “But remember, it’s not the receiver’s lifetime, it’s the sender’s lifetime. I mean, think about it. My stepmom is—just had a birthday April 9th, and I sent her a plant. If I went on a website and picked out a Roselia, and she received an Azelia, she’s gonna be like, ‘thank you so much, that was so thoughtful of you,’ and I’m gonna be pissed, right? And so like, we have to make sure we optimize that sender NPS score. It was shocking to us when we looked into the NPS, when we first got to FTD, our NPS, Kate, was in like the teens! My CTO looked at it and he goes, ‘how is this possible? We send gifts, who doesn’t like receiving gifts?’ And so we were looking at this stuff and we realized like, this is how you win. And I think when people look at the world of online delivery, there’s very few companies that are extremely customer-centric… and in our world it matters. It’s births, it’s deaths, it’s birthdays, it’s Mother’s Days… it’s the most emotional moments of your life that you’re relying on us for, so I think that gravitas just goes up to the next level.” Kate: Net Promoter Score offers directional insight about the customer experience, but it still isn’t quite measurement of the broader human experience. The typical NPS question is phrased, “How likely is it that you would recommend [company X] to a friend or colleague?”, which forces customers to predict future actions and place themselves into hypothetical or idealistic scenarios. It is also measured on a 1-10 scale, which is pretty arbitrary and subjective — one person’s 9 would not be another person’s 9. A clearer way to ask this and gain more useful human-centric data would be with simple yes/no questions, asking people about actual past behaviors. For instance, “in the past 6 weeks, have you recommended [company X] to a friend or colleague?” Other alternative measures include PES, or Product Engagement Score, which measures growth, adoption, and stickiness of a given product or service, and doesn’t require directly asking customers questions about their past or future habits. Instead, data comes in in real-time and allows for a clear measurement of success relative to a product’s usage. While these metrics are useful in various ways, one thing missing from them is emotion. As humans, we are animals deeply driven by our emotions: research from MIT Sloan finds that before humans decide to take an action—any action, including buying something—the decision must first go through a filtering process that incorporates both reason and feelings. Reason leads to conclusions, but emotion leads to action. And if a customer feels frustrated by the customer service they’re experiencing—perhaps they feel like they are being treated like a number, and not a person—they’ll file a complaint, share on social media, and tell their friends and family to avoid the business. These actions can be quite time-consuming, but people will give up their time to right a wrong they feel they’ve experienced. All this is to say that if you want to retain human loyalty or attract new people to your business, you have to create a positive emotional response in your customers, which means understanding more about who they are than simply what product they might want. Many businesses have discovered that one of the best ways to create an emotional connection with people is through branding. A great brand image can forge a permanent bond with someone who feels strongly that the company shares their values and practices what they preach. Once someone has connected a brand to their own identity, it becomes much more difficult to convince them to switch to another company—even if that company provides the same product at lower cost—because switching companies feels like losing a part of them. Dr. Rumman Chowdhury, Director of the Machine Learning Ethics, Transparency, and Accountability team at Twitter, explored the concept of branding with me when she came on my show last year. Rumman Chowdhury: “Human flourishing is not at odds with good business. Some of what you build, especially if you’re a B2C company, it’s about brand. It’s about how people feel when they interact with your technology or your product. You are trying to spark an emotion. Why do you buy Coke vs Pepsi? Why do you go to McDonald’s vs Burger King? Some of this is an emotional decision. It’s also this notion of value. People can get overly narrowly focused on value as revenue generation—value comes from many, many different things. People often choose less ‘efficient’ outcomes or less economically sound outcomes because of how it makes them feel. A frivolous example but an extreme example of it would be luxury brands. Apple spends so much money on design. Opening every Apple product is designed to feel like you’re opening a present. That was intentional. They fully understand the experience of an individual, in interacting with technology like a phone or a computer, is also an emotional experience.” Kate: If you’re able to understand what people connect to about your brand, you can invest into magnifying that image. If your customer loves that you invest into clean energies, it becomes less important how much time they spend on the phone waiting for a service rep. Operational metrics can’t show you this emotional resonance, so instead you have to think about what makes you stand out, and why people are attracted to you. Sometimes, however, human emotion has nothing to do with the product or brand in question, and more to do with the circumstances surrounding it. There’s perhaps no better example of this than flowers, which can be given for myriad reasons, and usually at the extreme ends of the emotional spectrum. I’ll let Charlie Cole explain. Charlie Cole: “For us, it’s buyer journey by occasion. So, you are sending flowers for the birth of a newborn. You are sending flowers for the tragic death of a teenager. You are sending flowers for the death of your 96 year old great grandfather. You are sending flowers for your wife’s birthday. I would argue that even though the end of all those buyer journeys is ‘flowers,’ they are fundamentally different. And you have to understand the idiosyncrasies within those buyer journeys from an emotional component. You have to start with the emotions in mind. You’re buying running shoes. The buying journey for like a runner, for like a marathoner, a guy who runs all the time, is emotionally different than someone who just got told they need to lose weight at the doctor. Someone who travels for business all the time versus someone who’s taking their first ever international…travel. Like, my wife retold a story the other day to my aunt about how her first European trip was when she won a raffle to go to Austria when she was 17. And her, like, single mom was taking her to Europe, and neither of them had ever been to Europe. That’s a different luggage journey than me, who used to fly 300,000 miles a year. And I think that if you take the time to really appreciate the emotional nuance of those journeys, yes there’s data challenges, and yes there’s customer recognition challenges, so you can personalize it. But I would urge every brand to start with like the emotional amino-acid level of why that journey starts, and then reverse-engineer it from there. Because I think you’ll be able to answer the data challenges and the attribution challenges, but I think that’s a place where we sometimes get too tech-y and too tactical, as opposed to human.” Kate: Another challenge unique to flowers and other products usually given as gifts is that there are two completely different humans involved in the transaction, each with different expectations and emotions riding on it. Charlie Cole: “There’s two people involved in every one of our journeys, or about 92% of them: the buyer, and the receiver. So how do I message to you, I don’t want to ruin the surprise! But I need to educate you, and oh yeah, I’m a really really nervous boyfriend, right? I wanna make sure everybody’s doing it right, and it’s gonna be there on time, and I need to make sure it’s going to the right place… So the messaging pathways to the sender and receiver are fundamentally different. If you kind of forget about your buying journey, and imagine everything as a gifting buyer journey, it just changes the messaging component. Not in a nuanced way, but darn near in a reciprocal way.” And while some businesses struggle to connect emotionally with the humans that make up their customer base, the tech industry—and specifically social media companies—seem to fundamentally understand what it is that humans crave, in a way that allows them to use it against us. They thrive because they take something that is quintessentially human—connecting with people and sharing our lives—and turn it into a means for data collection that can then be used to sell us products that feel specifically designed for us. Like most of us, Neil Redding has experienced this phenomenon firsthand. Neil Redding: “We spend more and more of our time in contexts that we are apparently willing to have commercialized, right? Instagram is kind of my go-to example, where almost all of us have experienced this uncanny presentation to us of something that we can buy that’s like so closely tied to… I mean, it’s like how did you know that this is what I wanted? So myself and people close to me have just said, ‘wow, I just keep buying this stuff that gets presented to me on Instagram that I never heard of before but gets pushed to me as like, yeah it’s so easy, and it’s so aligned with what I already want. So there’s this suffusion of commercial transaction—or at least discovery—of goods that can be bought and sold, y’know, in these moments of our daily lives, y’know, so that increasingly deep integration of commerce and buying and selling of things into our self-expression, into our communication, works because what we care about and what we are willing to buy or what we are interested in buying are so intertwined, right? They’re kind of the same thing at some deep level.” Kate: Part of the reason this works is that humans crave convenience. Lack of convenience adds friction to any process, and friction can quickly lead to frustration, which isn’t a mind state that leads to more business. The internet and social media has made keeping up with friends and gathering information incredibly convenient, so an advertisement here or there—especially one that looks and feels the same as everything else on our feed—doesn’t bother us like it might in other contexts. And when those advertisements have been tailored specifically to our interests, they’re even less likely to spark a negative emotion, and may in fact encourage us to buy something that we feel is very “us.” The big question for business leaders and marketers then is how do you digitize your business so that it emphasizes the richness of the human experience? How do you know which technologies to bring into your business, and which to leave aside? There are plenty of established and emerging technologies to choose from: Interactive email helps marketers drive engagement and also provides an avenue for additional data collection. Loyalty marketing strategies help brands identify their best customers and customize experiences for them. Salesforce introduced new features to help humanize the customer service experience with AI-powered conversational chatbots that feel pretty darn close to speaking with an actual human. Virtual and Augmented Reality website options allow customers to interact with products and see them in their hands or living rooms before they buy. With all the choice out there, it can be overwhelming. And t oo often, businesses and governments lean into the “just buy as much tech as possible!” approach without thinking integratively about the applications of said technology. Many companies are using that technology to leverage more data than ever before, hoping to customize and personalize experiences. David Ryan Polgar, a tech ethicist and founder of All Tech Is Human, explains why this method may not yield the results you think—because humans aren’t just a collection of data points. David Ryan Polgar: “Are we an algorithm, or are we unique? I always joke, like, my mom always said I’m a, a snowflake! I’m unique! Because, when you think about Amazon and recommendations, it’s thinking that your past is predicting your future. And that, with enough data, we can accurately determine where your next step is. Or even with auto-suggestion, and things like that. What’s getting tricky is, is that true? Or is it subtly going to be off? With a lot of these auto-suggestions, let’s say like text. Well the question I always like to think about is, how often am I influenced by what they said I should say? So if I wanna write, like, ‘have a…’ and then it says ‘great day,’ well, maybe I was gonna say great day, but maybe I was gonna say good day. And it’s subtly different, but it’s also influencing kinda, my volition. Now we’re being influenced by the very technology that’s pushing us is a certain direction. And we like to think of it, ‘well, it’s already based on you,’ but then that has a sort of cyclical nature to actually extending—” Kate: “Quantum human consciousness or something.” David: “Exactly! Exactly.” Kate: “Like, the moment you observe it, it’s changed.” Kate: It’s so easy, especially when you work with data, to view humans as output generators. But we’re living in an age where people are growing increasingly wary of data collection, which means you may not know as much about the people whose data you’ve collected as you think you do. Becoming dependent on an entirely data-driven model for customer acquisition may lead to faulty decisions — and may even be seen as a huge mistake five years from now. Instead, I always talk about “human-centric digital transformation,” which means the data and tech-driven changes you make should start from a human frame. Even if you’re already adopting intelligent automation to accelerate your operations, in some cases, very simple technologies may belong at the heart of your model. Here’s Neil Redding again. Neil Redding: “Using Zoom or FaceTime or Skype is the only technology needed to do what a lot of stores have done during COVID, where their customers expect the store associate interaction when they come to the stores, they just create a one-on-one video call, and the shopper just has this interaction over videochat, or video call, and kind of does that associate-assisted shopping, right? And so you have that human connection, and again, it’s nowhere near as great as sitting across a table and having coffee, but it’s better than, y’know, a 2-dimensional e-commerce style shopping experience.” Kate: As a parallel to video conferencing, Virtual Reality has opened up avenues for new human experiences of business as well. Cathy Hackl, a metaverse strategist and tech futurist, explained a new human experience she was able to have during COVID that wouldn’t have been possible without VR. Cathy Hackl: “I’ll give you an example, like with the Wall Street Journal, they had the WSJ Tech Live, which is their big tech conference, and certain parts of it were in VR, and that was a lot of fun! I mean, I was in Spatial, which is one of the platforms, hanging out with Joanna Stern, and with Jason Mims, and like, in this kind of experience, where like I actually got to spend some 1-on-1 time with them, and I don’t know if I would have gotten that if I was in a Zoom call, and I don’t know if I would have gotten that in person, either.” Kate: Virtual Reality and video technologies have also opened up new avenues for healthcare, allowing patients to conference with doctors from home and only travel to a hospital if absolutely necessary. Marcus Whitney is a healthcare investor and founder of the first venture fund in America to invest exclusively in Black founded and led healthcare innovation companies; he explains that these virtual experiences allow for better happiness, healing, and comfort. Marcus Whitney: “Going forward, telehealth will be a thing. We were already on the path to doing more and more healthcare in the home. It was something that they were trying to stop because, is the home an appropriate place for healthcare to take place? Lo and behold, it’s just fine. Patients feel more secure in the home, and it’s a better environment for healing, so you’re gonna see a lot more of that. I think we’re finally gonna start seeing some real breakthroughs and innovation in healthcare. Most of the lack of innovation has not been because we didn’t have great thinkers, it has largely been regulatory barriers. Remote patient monitoring was a huge one that came up in the last year, so now we have doctors caring about it. What moves in healthcare is what’s reimbursable. They were always trying to regulate to protect people, but then they realized, well, we removed the regulatory barriers and people were fine, so that regulation makes actually no sense, and people should have more choice, and they should be able to do telehealth if they want to.” Kate: And that’s just it: humans want choice. We want to feel seen, and heard, and like our opinions are being considered. There’s another technology on the horizon that could give people more power over their technology, and therefore freedom and choice, that will likely cause massive change in the marketplace when it is more widely available: Brain-computer interface. Cathy Hackl explains. Cathy Hackl: “So I’m very keen right now on brain-computer interface. The way I’m gonna explain it is, if you’ve been following Elon Musk, you’ve probably heard of neuro-link—he’s working on BCI that’s more internal, the ones I’ve been trying are all external devices. So I’m able to put a device on that reads my brainwaves, it reads my intent, and it knows that I wanna scroll an iPad, or I’ve been able to turn on lights using just my thoughts, or play a video game, or input a code… I’ve been able to do all these things. And I’m very keen on it, very interested to see what’s going on… I think the biggest thing that’s stuck with me from studying all these technologies and trying them out from an external perspective, is that my brain actually really likes it. Loves the workout. Like, I’m thinking about it, and I’m like, the receptors here, pleasure receptors are like lighting up, I’m like ‘ohmygosh!’ So I’m still sitting with that. Is that a good thing? Or a bad thing? I don’t know, but I think these technologies can allow us to do a lot of things, especially people with disabilities. If they don’t have a hand, being able to use a virtual hand to do things in a virtual space. I think that’s powerful.” Kate: That story also illuminates the fact that there are many different types of people, each with different needs. Digital transformation has given people with disabilities a new way to claim more agency over their lives, which creates a brand new potential customer-base, filled with humans who desire freedom and choice as much as the next person. Now, let’s talk about some companies who are doing at least a few q things right when it comes to the digital transformation of human experience. Starbucks, for instance. One of the worst parts of shopping in-store was waiting in line, and then the social pressure from the people behind you wishing you would order faster. If you weren’t a regular customer, the experience could be overwhelming. When they launched their mobile order app, it tapped into a number of things that made the experience of buying coffee faster and easier, with all sorts of fun customization options that I never knew existed when I only ordered in-store. Now, even brand new customers could order complex coffee drinks — meaning in that one move the company may have brought in new customers and allowed the cost per coffee to increase — all without people feeling pressure from other shoppers, and without the inconvenience of waiting in line. Then there’s Wal-Mart, who during the pandemic instituted ‘Wal-Mart pickup,’ a service where people can shop online and pick up their goods without ever having to step into the store. The service is technically operating at a financial loss, but Wal-Mart understands that solid branding and convenience are worth more to their company’s bottom-line in the long run than the amount of money they’re losing by investing into this particular service. Of course, some businesses are better suited for the online-only world than others. As more companies attempt to digitize their businesses, it’s incredibly important to tap into the human reasons that people wanted to engage with your business in the first place. In some cases, businesses have failed to make this connection, assuming that “if people liked us as a physical product, then they’ll continue using us when we’re digital,” or worse, “if we simply make people aware of us, they will become customers!” This assumption ignores human nature, as Ana Milicevic, a longtime digital media executive who is principal and co-founder of Sparrow Digital Holdings, explains. Ana Milicevic: “To be relevant in this direct to consumer world, you also have to approach awareness and customer acquisition differently. And this is the #1 mistake we see a lot of traditional companies make, and not really understand how to pitch to a digital-first, mobile-first consumer or a direct subscriber. They’re just not wired to do it that way, and often times the technology stacks that they have in place just aren’t the types of tools that can facilitate this type of direct interaction as well. So they’re stuck in this very strange limbo where they are committed to continuing to acquire customers in traditional ways, but that’s just not how you would go about acquiring a direct customer.” Kate: Acquiring those direct customers requires an understanding of what humans want—a large part of which is meaning. And how people create meaning in their lives is changing as well. Long before the pandemic, trends were already pointing toward a future where we live more of our lives online, but those trends have also been accelerated. So beyond digitizing your business, it may also be useful to invest time, money, and energy into discovering how the humans of the future will create meaning in their lives. Cathy Hackl discussed some of the trends she’s seen in her own kids that show how today’s children will consume and make purchasing decisions in a very different way than most modern businesses are used to. Cathy Hackl: “Something else that I’m noticing… y’know we’re going to brick and mortar, but we’re going to brick and mortar less. So you start to see this need for that virtual try-on to buy your makeup, or to buy clothes, and it’s also transitioning not only from the virtual try-on into what I’m calling the direct-to-avatar economy. Everything from virtual dresses that you’re buying, or custom avatars, y’know you’re starting to create this virtualized economy. And this is the reason I always talk about this now, is my son recently did his first communion, and when we said, ‘hey, what do you want as a gift?’ he said, ‘I don’t want money, I want a Roblox gift card that I can turn into Robucks,’—which is the currency they use inside Roblox—’so that I can buy—whichever gamer’s skin.’ And, y’know, when I was growing up, my brother was saving up to buy AirJordans. My son doesn’t want that, y’know, he wants Robucks, to buy something new for his avatar. This is direct-to-avatar; is direct-to-avatar the next direct-to-consumer?” Kate: Our online avatars represent us. We can customize them to directly express who we feel we are. Part of the reason this idea is so attractive is that many people—increasingly so in the context of online interaction—seek out meaningful experiences as our ‘aspirational’ selves. We gravitate to the communities that align with facets of who we wish we were. And perhaps less productively, we may also choose to present the idealized version of ourselves to the world, omitting anything we’re embarrassed by or that we feel may paint us in a negative light. But honestly, all of this makes sense in the context of making meaning, because humans are generally the most emotionally fulfilled when we feel empowered to control which ‘self’ we present in any given interaction. With this much freedom of choice and expression, and with the complications of the modern supply chain—which I will talk about more in depth in our next episode—it’s important to acknowledge that creating convenience and improving human satisfaction aren’t going to be easy tasks. Behind the scenes, there is a tremendous amount of work that goes into providing a satisfying customer experience. Let’s go back to the example of flowers and see what Charlie Cole has to say. Charlie Cole: “If it’s too cold they freeze, if it’s too hot they wilt, if UPS is a day late they die. And then, the real interesting aspect—and this isn’t unique to flowers—the source is remarkably centralized. So the New York Times estimated that 90-92% of roses that are bought in America for Valentine’s Day come from Columbia and Ecuador. And so, if anything goes wrong there, then you really don’t have a chance. Imagine the quintessential Valentine’s Day order: A dozen long-stem roses, New York City. Easy, right? I used to live on 28th and 6th, so let’s say Chelsea. Okay, I’ve got 7 florists who could do it. Who has delivery capacity? Roses capacity? The freshest roses? The closest to proximity? The closest to the picture in the order? Who has the vase that’s in the order? Did they buy roses from us? Because I like to be able to incentivize people based on margins they already have. And so without exaggeration, Kate, we have about 11-12 ranking factors that educate a quality score for a florist, and that’s how it starts the process. But then there’s all the other things, like how do we know somebody didn’t walk into that florist that morning and buy all the roses, right? And so there’s this real-time ebb-and-flow of demand because our demand is not ours! They have their own store, they have their own B2B business, they might take orders from some of our competitors. They might have their own website. We have no idea what any given florist happens in real time because they are not captive to us. What we’ve learned is the place we have to get really really really really good is technology on the forecasting side, on the florist communication side, and the customer communication side. Because I can’t control the seeds on the ground in Columbia, but I can really control the communication across the entire network as far as we go, as well as the amounts the we need in various places.” Kate: Creating that small-scale, emotional human moment where someone receives flowers requires immense computing power and collaboration between multiple businesses and workers. Which is part of why Charlie Cole also believes that in some cases, the best way to help your business succeed is to invest in helping other businesses that yours interacts with. Charlie Cole: “Small businesses… I think it’s our secret sauce. And I think COVID has shined a light on this: small businesses are the core of our communities. Right? They are the absolute core, and I think it was always nice to say that, but now we know it. And so here’s what I think we do better than anybody else: we’ve invested more in helping our florists run their own small business independently of us than we have about optimizing our marketplace. We launched new POS software. We launched a new local website product where we’re like the first person ever to become a reseller for Shopify because we made a custom platform for florists. We’re just their website provider. They’re actually competing with FTD.com in a lot of ways—but I think that’s where we’re gonna differentiate ourselves from all the other people that are perceived as, by small businesses, (their words not mine) leeches. Right? I think to actually effectively run a marketplace which is fulfilled by small businesses, you need to invest as much in helping them win their local market independent of you.” Kate: You could make the case that there is no more evolved human experience than choosing to help others. So if your business is engaged in activities that allow other businesses—and therefore humans—to thrive, you may also be building your brand in a direction that creates more customer loyalty than any exit survey or great service interaction ever could. Beyond understanding human emotions and needs, you can help your business by leaning into understanding how we create meaning. At our core, we are compelled to make meaning. Whether we realize it or not, meaningful experiences and interactions are the driving force behind many of our decisions, financial or otherwise. Meaning is different for everyone, but having it is vital to our happiness. If you are able to engage with potential customers in a way that helps them create meaning, or allows them to use your product to make meaning on their own, you are aligning your success with your customers’ success, and that bodes well for the long term. At the end of the day, making any of these changes starts at the very top of your business. Leadership needs to set the tone, creating a culture that allows room for workers at every level to engage more meaningfully with customers, and with each other. (By the way, for more discussion on creating or changing work culture, you can check out our last episode, “Does the Future of Work Mean More Agency For Workers?”) Your effort will benefit not only your business, but society as a whole. Remember the Deloitte piece in the Wall Street Journal I mentioned at the start of the episode, with ways to be more human-centric in business? Number 5 on that list was “change the world,” and research from Frontiers suggests that the well-being of any society is directly linked to how the people living within it feel about their lives and purpose. How we do that may be as simple — and as complicated — as helping people to experience meaning at any level. While the technologies around us keep changing, the opportunity becomes increasingly clear for people who work around creating customer experiences and user experiences to open up the aperture to see humanity through a fuller lens. This way, as you set your business up for longterm success, you also advocate for making human experiences as meaningful as possible — and you just might be changing the world for the better. Thanks for joining me as I explored what it means to think of customers as human. Next time, I’ll be exploring the supply chain and how, despite the vast technology involved, the closer you look the more you realize: the economy is people.