PODCAST · technology
The Dr. Data Show with Eric Siegel
by Eric Siegel
Eric Siegel covers why machine learning is the most important, most potent, most screwed up, most misunderstood, and most dangerous technology. And did I mention most important?Yup, it’s the most important – but most projects fail to deliver value. This podcast will help you:- Make machine learning effective and valuable- Catch common machine learning oversights- Understand ethical pitfalls – concretely- Sniff out all the ”artificial intelligence” malarkyThis podcast is for both data scientists and business leaders of all kinds – such as executives, directors, line of business managers, and consultants – who are involved in or affected by the deployment of machine learning.To get machine learning to work, both the tech and business sides must make an effort to reach across wide chasm.About the host:Eric Siegel, Ph.D., is a leading consultant and former Columbia University professor who bridges the business and tech sides of machine learning. He is the founder of the Predictive
Episodes
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Jev Fever: Predictive AI Is Superhot Again
In this episode, Eric Siegel narrates his article: Jev Fever: Predictive AI Is Superhot Again A new breed of models has rejuvenated predictive AI. But successful deployment demands a new business-value playbook. ... and then Eric summarizes his follow-on article: Jev AI Will Make You Money – But...
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GenAI Owns the Hype, but Predictive AI Is Thriving
Listen in full to the new preface to Eric Siegel's The AI Playbook: Predictive AI Thrives, Despite Generative AI Stealing the Spotlight This is the new preface to the paperback edition of The AI Playbook: Mastering the Rare Art of Machine Learning Deployment. Special offer: Pre-order the…
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The Doomer's Error: Why AGI Is An Incoherent Concept
What's the strongest anti-AGI case, the argument that reveals the fallacies underlying the belief that AGI is a viable goal – as well as the AI doomerism that believing AGI will soon arrive often spawns? Princeton professor Arvind Narayanan recently made a statement that we feel deserves...
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Predictive AI vs. GenAI: A Crucial, Unavoidable Comparison
In this episode we cover: - Why predictive AI and generative AI are destined to remain inherently distinct - Why comparing them is unavoidable, even though they solve different problems - How they compare - How companies should balance investments between the two
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Pushing the ultimate limits: helping genAI realize its promise of autonomy
In this episode, we talk about real, truly deployed LLM-based systems that push the limits of autonomy. How can we "tame" LLMs to create feasible, practical solutions that are viable for deployment? What are their ultimate limitations?
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Superhuman Adaptable Intelligence: LeCun's New Buzzword Challenges AGI
In this episode, Luba Gloukhova and Eric Siegel unpack the new paper, "AI Must Embrace Specialization via Superhuman Adaptable Intelligence," by Yann LeCun and others. The paper endeavors to "address what’s wrong with our conception of AGI, and why, even in its most coherent formulation, it is a...
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The Whole Problem with AGI and Its Ridiculous Definitions
In this very special episode, the first with a co-host (Luba Gloukhova), Dr. Data and Miss Information explore why people are messing with the definition of artificial general intelligence, the problem with the concept, how it feeds AI hype, and how we can feasibly realize a good portion of…
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Predictive AI Thrives, Despite GenAI Stealing The Spotlight
In this episode, listen to a narration of Eric Siegel's article in Forbes: Predictive AI Thrives, Despite GenAI Stealing The Spotlight GenAI and predictive AI battle for resources, but even as the overwhelming attention focuses on genAI, enterprises are still adopting predictive AI just as much....
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Hybrid AI: Industry Event Signals Emerging Hot Trend (article)
In this episode, listen to a narration of Eric Siegel's article in Forbes: Hybrid AI: Industry Event Signals Emerging Hot Trend AI is not yet the success that it should be, so two dozen enterprises will disclose their move toward a crucial new paradigm – hybrid AI – at a 2026 conference. Access…
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A Gooder AI case study: profiting on machine learning
The biggest hurdle for data science teams isn't building the model; it's proving its dollar value. This presentation shows how a dental group could translate a no-show prediction model into a clear business case worth $$$ It's about shifting the conversation from abstract metrics to tangible ROI....
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Predictive AI Usually Fails Because It’s Not Usually Valuated (article)
In this episode, listen to a narration of Eric Siegel's article in Forbes: Predictive AI Usually Fails Because It’s Not Usually Valuated Most predictive AI deployments are scrubbed. Why? They didn't forecast the potential value in business terms like profit or savings. Access the original article...
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Predictive AI Only Works If Stakeholders Tune This Dial (article)
In this episode, listen to a narration of Eric Siegel's article in Forbes: Predictive AI Only Works If Stakeholders Tune This Dial Machine learning models can drive business operations to great benefit. But, to get there, stakeholders must determine how model probabilities trigger actions. Access...
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AI Drives Alphabet’s Moonshot To Save The World’s Electrical Grid (article)
In this episode, listen to a narration of Eric Siegel's article in Forbes: AI Drives Alphabet’s Moonshot To Save The World’s Electrical Grid AI is pivotal as global utilities tackle a looming crisis with the electrical grid. Here's how Alphabet uses AI to help the world keep the lights on. Access...
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To Deploy Predictive AI, You Must Navigate These Tradeoffs (article)
In this episode, listen to a narration of Eric Siegel's article in Forbes: To Deploy Predictive AI, You Must Navigate These Tradeoffs Before deploying predictive AI, you must strike a balance between competing business factors. Here's how. Access the original article here:...
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Predictive AI Meets GenAI: Michael Griebe on How to Balance between ML Models and LLMs in a Data Science Career
Welcome to the very first Dr. Data Show episode with a guest: Michael Griebe, Chief Data Officer at Hahn Agency! With the great changes brought to data science careers by genAI, Michael addresses pressing open questions that should be top of mind for every data scientist: One compelling reason to...
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How Generative AI Helps Predictive AI (article)
In this episode, listen to a narration of Eric Siegel's article in Forbes: How Generative AI Helps Predictive AI Large language models can act as predictive models. Here's an example for misinformation detection—and an introduction to savings curves. Access the original article here:...
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The Quant's Dilemma: Subjectivity In Predictive AI's Value (article)
In this episode, listen to a narration of Eric Siegel's article in Forbes: The Quant's Dilemma: Subjectivity In Predictive AI's Value When machine learning fails to detect misinformation, medical conditions or spam, the cost of each error is subjective. Here’s how to apply predictive AI...
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The Great AI Myth: These 3 Misconceptions Fuel It (article)
In this episode, listen to a narration of Eric Siegel's article in Forbes: The Great AI Myth: These 3 Misconceptions Fuel It The impending arrival of artificial general intelligence is a story of wish fulfillment that lacks concrete evidence. Access the original article here:...
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The 3 Things You Need To Know About Predictive AI (article)
In this episode, listen to a narration of Eric Siegel's article in Forbes: The 3 Things You Need To Know About Predictive AI Stakeholders involved with predictive AI must ramp up on a semi-technical understanding that comes down to 1) what's predicted, 2) how well and 3) what's done about it....
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Why You Must Twist Your Data Scientist's Arm To Estimate AI's Value (article)
In this episode, listen to a narration of Eric Siegel's article in Forbes: Why You Must Twist Your Data Scientist's Arm To Estimate AI's Value For every machine learning model that you consider deploying, make sure that your data scientists provide you with a full view of its potential business...
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The Rise Of Large Database Models (article)
In this episode, listen to a narration of Eric Siegel's article in Forbes: The Rise Of Large Database Models Even as large language models have been making a splash with ChatGPT and its competitors, another incoming AI wave has been quietly emerging: large database models. Access the original...
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3 Predictions For Predictive AI In 2025 (article)
3 Predictions For Predictive AI In 2025 (article) In this episode, listen to a narration of Eric Siegel's article in Forbes: 3 Predictions For Predictive AI In 2025 1) GenAI hybrids, 2) ML valuation, 3) bizML—these advances will bring predictive AI back into the spotlight and further amplify its...
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Alphabet Uses AI To Rush First Responders To Wildfires (article)
In this episode, listen to a narration of Eric Siegel's article in Forbes: Alphabet Uses AI To Rush First Responders To Wildfires — Takeaways For Businesses An initiative from Google’s parent company that rushes the National Guard to climate disasters stands ready to review aerial images from the...
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NotebookLM on how Gooder AI will solve the value-capture crisis
We gave 17 documents to this "magical bot" and it spat out this artificial conversation – a great overview of our work here at Gooder AI.
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"Predictive Analytics" in ten minutes
Following up on my previous pod episode covering The AI Playbook, this time I ran my other book, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, through NotebookLM and it spat out this artificial dialogue podcast episode. Listen to this uncanny chat to hear an…
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"The AI Playbook" in fifteen minutes
I ran my book, The AI Playbook: Mastering the Rare Art of Machine Learning Deployment, through NotebookLM and it spat out this artificial dialogue podcast episode. Listen to this uncanny chat to hear an overview of the book and some specific highlights... ... or listen to it to see if you can...
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Forbes Article: Meta’s New GenAI Is Theatrical. Here’s How To Make It Valuable
In this episode, Eric Siegel narrates his article in Forbes, "Meta’s New GenAI Is Theatrical. Here’s How To Make It Valuable." Concern about a generative AI bubble is growing. To defend against disillusionment, measure its concrete value. Access the original article here:...
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Forbes Article: Artificial General Intelligence Is Pure Hype
In this episode, Eric Siegel narrates his article in Forbes, "Artificial General Intelligence Is Pure Hype." The belief that we’re gaining ground on AGI is misguided—reports of the human mind's looming obsolescence have been greatly exaggerated. Access the original article here:...
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Forbes Article: AI Success Depends On How You Choose This One Number
In this episode, Eric Siegel narrates his article in Forbes, "AI Success Depends On How You Choose This One Number." AI can drive millions of operational decisions, but first the business must strategically select a single number that differentiates the yeses from the nos. Access the original...
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Where FICO Gets Its Data for Screening Two-Thirds of All Card Transactions
In this episode, Eric Siegel narrates his article in The European Business Review, "Where FICO Gets Its Data for Screening Two-Thirds of All Card Transactions." The detection of fraudulent credit card transactions is an ideal candidate for the application of machine learning technology. However…
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Forbes Article: 3 Ways Predictive AI Delivers More Value Than Generative AI
In this episode, Eric Siegel narrates his article in Forbes, "3 Ways Predictive AI Delivers More Value Than Generative AI." Generative AI attracts headlines, but predictive AI delivers greater value. This article covers three ways predictive AI eclipses generative AI. Access the original article...
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SMR Article: The Rare, Crucial Move to Business Metrics for Establishing ML's Value
In this episode, Eric Siegel narrates his article in MIT Sloan Management Review, "What Leaders Should Know About Measuring AI Project Value." Most AI/machine learning projects report only on technical metrics that don’t tell leaders how much business value could be delivered. To prevent project...
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Five insights from "The AI Playbook"
This episode covers five insights from the new book, The AI Playbook, which come from a piece originally published by The Next Big Idea Club. On a related note, the book has been included as a Next Big Idea Club Must Read. Also, here is the book's recent Bloomberg Businessweek Radio segment…
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The AI Playbook – book launch, early reviews, FAQ
I'm excited to announce that today, my new book has published! The AI Playbook: Mastering the Rare Art of Machine Learning Deployment Info at: http://www.bizML.com In my first book, Predictive Analytics, I explained how machine learning works. Now, in The AI Playbook, I show how to capitalize on...
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HBR Article: The AI Hype Cycle Is Distracting Companies
In this episode, Eric Siegel narrates his article in The Harvard Business Review, "The AI Hype Cycle Is Distracting Companies." Access the original article here: https://hbr.org/2023/06/the-ai-hype-cycle-is-distracting-companies Learn more about and order Eric's new book, The AI Playbook:...
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HBR Article Narration: Getting Machine Learning Projects from Idea to Execution
In this episode, Eric narrates his new Harvard Business Review article, "Getting Machine Learning Projects from Idea to Execution," adapted from his new book, The AI Playbook. Access the article: https://hbr.org/2024/01/getting-machine-learning-projects-from-idea-to-execution Learn more about and...
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THE AI PLAYBOOK – Announcement and Free Audiobook Offer
Announcing Eric Siegel's new book: The AI Playbook: Mastering the Rare Art of Machine Learning Deployment Info: www.bizML.com This podcast episode includes a book overview, book sample – the opening of the book's Introduction – and a free audiobook offer. In his bestselling first book, Eric…
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Five Reasons to Go to Machine Learning Week, June 19-24 2022 in Vegas
In this special episode, rather than the usual conceptual coverage of machine learning, Eric Siegel will pitch you on the machine learning conference series he founded in 2009, the leading cross-vendor, cross-industry event covering the commercial deployment of machine learning and predictive...
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Four Things the Machine Learning Industry Must Learn from Self-Driving Cars
When it comes to deploying machine learning, we must learn from the self-driving car movement – both to gain inspiration as to what it takes and as a major cautionary tale as to what mistakes to avoid. This episode covers four things the entire machine learning industry must learn from the...
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Why Deep Learning Could Expedite the Next AI Winter
Deep learning, the most important advancement in machine learning, could inadvertently expedite the next AI winter. The problem is that, although it increases value and capabilities, it may also be having the effect of increasing hype even more. This episode covers four reasons deep learning...
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P-Hacking: How to Know Your Predictive Discovery Is Conclusive
“An orange used car is least likely to be a lemon.” At least that’s what was claimed by The Seattle Times, The Huffington Post, The New York Times, NPR, and The Wall Street Journal. However, this discovery has since been debunked as inconclusive. As data gets bigger, so does a common pitfall in…
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Real-Time Machine Learning: Why It’s Vital and How to Do It
Organizations often miss the greatest opportunities that machine learning has to offer because tapping them requires real-time predictive scoring. In order to optimize the very largest-scale processes – which is a vital endeavor for your business – predictive scoring must take place right at the...
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The Accuracy Fallacy and the Media’s Bogus Coverage of AI
Misleading headlines abound, claiming that machine learning can "accurately" predict criminality, psychosis, sexual orientation, and bestselling books. But, when practitioners claim their model achieves "high accuracy," it's often bogus. Can AI "tell" if you're going to have a heart attack?...
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Models Are Rarely Deployed – an Industrywide Failure in Machine Learning Leadership
Our latest industry poll reconfirms today's dire industry buzz: Very few machine learning models actually get deployed. In this episode, I summarize the poll results and argue that this pervasive failure of machine learning projects comes from a lack of prudent leadership. I also argue that MLops...
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Trailer for The Dr. Data Show with Eric Siegel
Eric Siegel covers why machine learning is the most important, most potent, most screwed up, most misunderstood, and most dangerous technology. And did I mention most important?
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ABOUT THIS SHOW
Eric Siegel covers why machine learning is the most important, most potent, most screwed up, most misunderstood, and most dangerous technology. And did I mention most important?Yup, it’s the most important – but most projects fail to deliver value. This podcast will help you:- Make machine learning effective and valuable- Catch common machine learning oversights- Understand ethical pitfalls – concretely- Sniff out all the ”artificial intelligence” malarkyThis podcast is for both data scientists and business leaders of all kinds – such as executives, directors, line of business managers, and consultants – who are involved in or affected by the deployment of machine learning.To get machine learning to work, both the tech and business sides must make an effort to reach across wide chasm.About the host:Eric Siegel, Ph.D., is a leading consultant and former Columbia University professor who bridges the business and tech sides of machine learning. He is the founder of the Predictive
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Frequently Asked Questions
How many episodes does The Dr. Data Show with Eric Siegel have?
The Dr. Data Show with Eric Siegel currently has 45 episodes available on PodParley. New episodes are automatically indexed when they're published to the podcast feed.
What is The Dr. Data Show with Eric Siegel about?
Eric Siegel covers why machine learning is the most important, most potent, most screwed up, most misunderstood, and most dangerous technology. And did I mention most important?Yup, it’s the most important – but most projects fail to deliver value. This podcast will help you:- Make machine learning...
How often does The Dr. Data Show with Eric Siegel release new episodes?
The Dr. Data Show with Eric Siegel has 45 episodes. Check the episode list to see recent publication dates and frequency.
Where can I listen to The Dr. Data Show with Eric Siegel?
You can listen to The Dr. Data Show with Eric Siegel on PodParley by clicking any episode. We provide an embedded audio player for direct listening, and you can also subscribe via your preferred podcast app using the RSS feed.
Who hosts The Dr. Data Show with Eric Siegel?
The Dr. Data Show with Eric Siegel is created and hosted by Eric Siegel.
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