Cyber-Resilience Act: What Now?

Welcome to Benevolent Bots

Release Date: 01/13/2022

Authors: stories@amazemedialabs.com (Daniel Schreiber, Tulsee Doshi)

Description: Welcome to the intricate world of AI and Insurance, brought to you by hosts Daniel Schreiber and Tulsee Doshi. Experts from both fields will address the major questions facing the industry, shed light on some of the myths about AI, and discuss how AI ethics can be put in place in insurance. Join us for conversations on fairness, AI ethics, data ethics, transparency, accountability, privacy, and putting AI ethics into practice.

Explicit: No

Building creative restrictions to curb AI abuse

Release Date: 09/06/2022

Description: Along with all the positive, revolutionary aspects of AI comes a more sinister side. Joining us today to discuss ethics in AI from the developer’s point of view is David Gray Widder. David is currently doing his Ph.D. at the School of Computer Science at Carnegie Mellon University and is investigating AI from an ethical perspective, honing in specifically on the ethics-related challenges faced by AI software engineers. His research has been conducted at Intel Labs, Microsoft, and NASA’s Jet Propulsion Lab. In this episode, we discuss the harmful uses of deep fakes and the ethical ramifications thereof in proprietary versus open source contexts. Widder breaks down the notions of technological inevitability and technological neutrality, respectively, and explains the importance of challenging these ideas. Widder has identified a continuum between implementation-based harms and use-based harms and fills us in on how each is affected in the open source development space. Tune in to find out more about the importance of curbing AI abuse and the creativity required to do so, as well as the strengths and weaknesses of open source in terms of AI ethics. Full transcript. Key points from this episode: Introducing David Gray Widder, a Ph.D. student researching AI ethics. Why he chose to focus his research on ethics in AI, and how he drives his research. Widder explains deep fakes and gives examples of their uses. Sinister uses of deep fakes and the danger thereof. The ethical ramifications of deep fake tech in proprietary versus open source contexts. The kinds of harms that can be prevented in open source versus proprietary contexts. The licensing issues that result in developers relinquishing control (and responsibility) over the uses of their tech. Why Widder is critical of the notions of both technological inevitability and neutrality. Why it’s important to challenge the idea of technological neutrality. The potential to build restrictions, even within the dictates of open source. The continuum between implementation-based harms and use-based harms. How open source allows for increased scrutiny of implementation harms, but decreased accountability for use-based harms. The insight Widder gleaned from observing NASA’s use of AI, pertaining to the deep fake case. Widder voices his legal concerns around Copilot. The difference between laws and norms. How we’ve been unsuspectingly providing data by uploading photos online. Why it’s important to include open source and public sector organizations in the ethical AI conversation. Open source strengths and weaknesses in terms of the ethical use of AI. Links mentioned in today’s episode: David Gray Widder David Gray Widder on Twitter Limits and Possibilities of “Ethical AI” in Open Source: A Study of Deep Fakes What is Deepfake Copilot Credits Special thanks to volunteer producer, Nicole Martinelli. Music by Jason Shaw, Audionautix. This podcast is sponsored by GitHub, DataStax and Google. No sponsor had any right or opportunity to approve or disapprove the content of this podcast.

Explicit: No

Privacy and Ethics in the Age of AI

Release Date: 01/10/2024

Description: This week we join Shea Swauger, a researcher and writer for data sharing and ethics for the Future of Privacy Forum. Join Larry and Shea as they discuss AI, privacy, and ethics.

Explicit: No

Is Zuck AI's Savior or Villain?

Release Date: 01/23/2024

Description: In this episode, Brian, Jyunmi, Robert, Andy, Beth, and Karl talked about Mark Zuckerberg's role in the AI industry, particularly focusing on Meta's approach to AI development. The discussion kicked off with Zuckerberg's vision of building general intelligence, open sourcing it responsibly, and making it widely available. The team debated Meta's strategic shifts, the integration of AI in consumer products, and the potential impact of Meta's open-source approach on the AI landscape. Key Points Discussed: Meta's Strategic Direction: The panel discussed Zuckerberg's strategy of integrating AI into Meta's consumer products and services, such as Facebook, Instagram, and WhatsApp. The conversation touched upon Meta's fluctuating focus, transitioning from VR and the Metaverse to AI-driven consumer applications. Open Source AI and Meta's Role: A significant part of the discussion revolved around Meta's commitment to open-source AI. The crew debated the implications of this approach, considering both its potential to accelerate AI development and the risks associated with making powerful AI tools broadly accessible. The Metaverse vs. Real-World Applications: The team critically examined Meta's investment in the Metaverse, questioning its practicality and user adoption compared to real-world AI applications. There was a consensus that AR (Augmented Reality) might be a more immediate and practical focus than the more immersive VR (Virtual Reality) experiences promoted by the Metaverse concept. AI Ethics and Corporate Responsibility: The podcast highlighted concerns about the ethical implications of AI, especially in the context of consumer data privacy and the influence of AI on social behavior. The panelists pondered Meta's responsibility in ensuring ethical AI deployment, given its vast user base.

Explicit: No

Benevolent Bots

Release Date: 02/12/2022

Authors: Lemonade

Description: Welcome to the intricate world of AI and Insurance, brought to you by hosts Daniel Schreiber and Tulsee Doshi. Experts from both fields will address the major questions facing the industry, shed light on some of the myths about AI, and discuss how AI ethics can be put in place in insurance. Join us for conversations on fairness, AI ethics, data ethics, transparency, accountability, privacy, and putting AI ethics into practice.

Explicit: No

Open||Source||Data

Release Date: 04/03/2021

Authors: Charna Parkey

Description: What can we learn from ai-native development through stimulating conversations with developers, regulators, academics and people like you that drive forward development, seek to understand impact, and are working to mitigate risk in this new world? Join Charna Parkey and the community shaping the future of open source data, open source software, data in AI, and much more.

Explicit: No

Open Data Science's Podcast

Release Date: 03/31/2022

Authors: Open Data Science

Description: Open Data Science will bring together the open source and data science communities to help foster the growth of open source software used in data science. The primary focus will be on the languages and tools that enable effective data analysis. These consist of but are not limited to: Open source programming languages used in data science ( R, Python, etc.), Machine Learning, Predictive analytics, Deep Learning (Neural Networks), Social Network & Graph Analysis, Text Analytics and Natural Language Processing, Data Visualization, Big Data Tools, Pig Latin/Hive/other Hadoop-based languages.

Explicit: No

OpenMined

Release Date: 09/01/2020

Authors: Open Mined

Description: OpenMined is an open-source community whose goal is to make the world more privacy-preserving by lowering the barrier-to-entry to private AI technologies.

Explicit: No

Ethics in Open Source

Release Date: 04/09/2021

Authors: Chris Ward

Description: A podcast with a rotating cast of hosts that looks at the intersection of ethics and open source development.

Explicit: No

FINOS Open Source in Finance Podcast

Release Date: 08/12/2020

Authors: FINOS

Description: The FINOS Open Source in Finance Podcast celebrates open source projects and interesting topics at the cross section of financial services and open source. So far, our industry experts have discussed practical applications of and their real-world experiences with a range of open source projects including desktop interoperability, low code platforms, synthetic data, and data modeling. They’ve also discussed best practices for inner source, common myths about open source and why commercial companies choose to introduce open source offerings. Tune in to hear what comes next.

Explicit: No

R Weekly

Release Date: 08/29/2020

Authors: R Weekly

Description: Data & Fun. Weekly updates from the R programming language open source community. #rstats

Explicit: No

Advocatus Intimitati

Release Date: 08/29/2020

Authors: Matt Loar

Description: Matt Loar, CIPP/E, CIPP/US, CIPT, is your host for a discussion of developing stories in data privacy and ethics.

Explicit: No

Free for All

Release Date: 09/09/2020

Authors: Michael Pagnotti

Description: Free for All is a podcast about free culture, copyleft, free and open source software, sharing, remixing, and open data!

Explicit: No

Big Data – Byte Mining

Release Date: 01/06/2022

Description: My thoughts on data mining, machine learning, programming languages, open-source software and general nerdery.

Explicit: No

Reality 2.0

Release Date: 08/28/2020

Authors: Katherine Druckman and Doc Searls

Description: Join Privacy and Open Source advocates, Doc Searls and Katherine Druckman, as they navigate the new digital world, covering topics related to digital privacy, cybersecurity, digital identity, as well as Linux and open source and other current issues.

Explicit: No

Data privacy

Release Date: 09/06/2020

Description: Our podcast is about the different perspectives on social media sites taking personal information

Explicit: No