The '🤖machines will replace doctors👩🏽‍⚕️' debate turns 70! From Warner Slack to Geoffrey Hinton. (Part 1 of 6)

What do the invention of television and fuzzy logic have to do with AI in medicine? More than you'd think.

Welcome to AI Health Uncut, a brutally honest newsletter on AI, innovation, and the state of the healthcare market. If you’d like to sign up to receive issues over email, you can do so here.

Fun fact: The same person who invented television also played a significant role in the early development of AI in medicine.

Another fun fact: PROMIS, the first medical record system I discuss in this article, was already using a touch-screen terminal back in 1967!

History isn’t just fascinating. It’s full of crossovers that make Marvel jealous. 😊

In this 4-part series, I thoroughly review the 70-year history and research on the ‘machines replacing doctors’ debate.

But first, some housekeeping:

• First, apologies to my paid subscribers and Founding Members who’ve been patiently waiting for Part 2 of my series, “These 14 Health AI Companies Have Been Lying About What Their AI Can Do.” It’s coming, and trust me, it’s going to be a bombshell. In the meantime, here’s a little (and super obvious 😊) pre-release quiz: Which so-called health AI startup just raised $165 million, is valued at $0.5 billion, and is riding on stolen tech? Stay tuned for Part 2...

I’m looking for people who are worried about the future of healthcare but hesitant to speak up, whether out of fear of retaliation from their boss or other concerns. I’m particularly interested in compelling inside stories from digital health and health AI. I believe that combining “mosaic theory” analysis with firsthand accounts from within companies is the key to revealing both the positives and the negatives in our industry. This approach is how my recent pieces on Walmart Health and IBM Watson Health came together—thanks to individuals who stepped forward to share their stories. Friends and colleagues who’ve known me for years can vouch for my discretion and integrity. I will always honor anonymity, and I will never act without a person’s consent.

Now, for the big announcement:

🚨 Attention, my paid subscribers and Founding Members: In 2025, I’ll be launching a new series of articles, tentatively titled “Venture Capital is a Scam: Building a Better Way to Fund Innovation,” with a sharp focus on the digital health sector. I want to expose the net harm that venture capital has inflicted on digital health innovation over the past 20 years. Innovation in digital health is at an all-time low, and it breaks my heart. This is an urgent matter. The goal of this research is to explore alternative methods of financing and capital allocation in digital health and healthcare AI. VCs are optimizing their picks and managing startups in their self-interest—not necessarily in the interest of founders, and certainly not in the interests of customers, patients, and clinicians.

With this in mind:

1. I welcome any ideas, research, and inside stories from within the VC world. A significant portion of what I write is heavily based on these insights. I understand that trust and loyalty are everything, and I will never disclose anything without your consent.

2. The amount of information and data I’ve collected so far could fill, if not a whole book, then at least half of one. I know it’s a long shot, but if anyone is interested in financing my research in the form of a book 📚, I believe it could greatly benefit the healthcare industry. This book could help break the healthcare oligopoly, expose the shady schemes of venture capital, and create a better way to build an ecosystem of innovation in healthcare. I’m a one-man operation—no sponsors, no advertisers—and unfortunately, I don’t currently have the means to write a book like this on my own.

Thank you!

All right, let’s get back to our story.

First things first—let’s all take a deep breath and lay out the facts.

The debate over who’s better and when, exactly, the medical profession will fade into the abyss has reared its head once again last week. So I’m here to calmly summarize the latest research on the subject. Yes, there will be some sarcasm sprinkled in, but the goal is simple: gather the research, opinions, and quotes from people much smarter than me (all 184 of them 😊), and let the readers make up their own minds.

Following the lively discussion on X spaces organized by Sanat Dixit, MD, FACS last week—where I had the honor of being a guest speaker—there was a robust exchange of ideas from notable medical professionals such as Anthony DiGiorgio, DO, MHA, Owen Scott Muir, MD, DFAACAP, Anish Koka, MD, Chuck-G, John Paul G. Kolcun, MD, Krishnan Chittur, and many other experts. This led to a fresh debate on whether AI will be “replacing” doctors anytime soon. We covered a lot of ground during that conversation, and the recording is available here.

And now, here are all the honorable mentions in this article—yes, all 299 of them. 😊

Part 1:

Walmart Health, Sanat Dixit, MD, FACS, Anthony DiGiorgio, DO, MHA, Owen Scott Muir, MD, DFAACAP, Anish Koka, MD, Chuck-G, John Paul G. Kolcun, MD, Krishnan Chittur, Warner V. Slack, MD, Center for Clinical Computing, Harvard Medical School, Beth Israel Deaconess Medical Center, Eliza, MIT, Joseph Weizenbaum, Natural Language Processing (NLP), Turing Test, Rogerian psychotherapist model, F.A. Nash, Cornell Medical School, Mt. Sinai Hospital, IBM, Greene JA, B.J. Davis, Lipkin M, Keeve Brodman, van Woerkom AJ, Erdmann AJ Jr, Goldstein LS, Andrew S. Lea, Max Planck Institute for the History of Science, Weill Cornell Medicine Library, Robert Ledley, Lee Lusted, Georgetown, University of Rochester, Society for Medical Decision Making, Warner HR, Toronto AF, Veasy LG, de Dombal FT, Leaper DJ, Staniland JR, McCann AP, Horrocks JC, Robert W. Taylor, DARPA, ARPA, XAI (Explainable Artificial Intelligence), Vladimir Zworykin, Boris Rosing, Paul Langevin, Vladimir Lenin, Admiral Alexander Kolchak, Marie Curie, Bane F, Wander A, Ralph Engle, MD, The Rockefeller Institute for Medical Research, McTernan E, Crocker D, Mullainathan S, Obermeyer Z, Bruce G. Buchanan, Edward H. Shortliffe, Robert K. Lindsay, Edward A. Feigenbaum, Joshua Lederberg, Schenthal JE, Sweeney JW, Nettleton WJ, Yoder RD, Vandenberg, Weinrauch, Hetherington, Judy Faulkner, Epic Systems, Problem-Oriented Medical Information System (PROMIS), Jan Schultz, Lawrence L. Weed, M.D., Cleveland Metropolitan General Hospital (CMGH), University of Vermont’s Medical Center Hospital of Vermont (MCHV), Digiscribe, Control Data Corporation, FORTRAN, SNOBOL, V77-400 Varian Data Machines minicomputers, Xerox Palo Alto Research Center (PARC), Michael F. Collen, American Medical Informatics Association, Clement J. McDonald, Regenstrief Institute, National Library of Medicine Archives, John Rees, Casimir A. Kulikowski, Sholom M. Weiss, Rutgers University, P. Szolovits, Clancey W. J., Juri Yanase, Evangelos Triantaphyllou, R. Hirani, K. Noruzi, H. Khuram, A. S. Hussaini, E. I. Aifuwa, K. E. Ely, J. M. Lewis, A. E. Gabr, A. Smiley, R. K. Tiwari, M. Etienne, Dr. Jack D. Myers, Dr. Harry E. Pople Jr., Dr. Randolph A. Miller, F. E. Masarie, Klaus-Peter Adlassnig, Lotfi A. Zadeh, Masaki, Watanabe, Bell Labs, G. Kolarz, W. Scheithauer, H. Effenberger, G. Grabner, P. Klinov, B. Parsia, D. Picado-Muiño, Dr. G. Octo Barnett, J. J. Cimino, J. A. Hupp, E. P. Hoffer, M. J. Feldman, G. Elhanan, S. A. Socratous, S. P. Bartold, G. G. Hannigan, Eta S. Berner, Tonya J. La Lande, CASNET, INTERNIST-I, MYCIN, DENDRAL, CADUCEUS, QMR, CADIAG, DXplain.

Part 4:

Warner V. Slack, MD, Vinod Khosla, Geoffrey Hinton, Ezekiel J. Emanuel, MD, Ph.D., Phelps Kelley, MD, Yuval Noah Harari, Ali Parsa, Judy Faulkner, Ben Horowitz, Derya Unutmaz, MD, Bindu Reddy, Elon Musk, Eric Topol, Statista, National Institutes of Health (NIH), Tsarnick, Lauren Silverman, National Public Radio (NPR), Greg Ip, The Wall Street Journal, Enrico Coiera, Epic Systems, Ann Richardson, Marc Andreessen, Ayers JW, Poliak A, Dredze M, JAMA Internal Medicine, Jonathan Reisman, MD, The New York Times, Med-PaLM 2, Singhal K., Azizi S., Tu T., Mahdavi S.S., Wei J., Chung H.W., Matias Y., NPJ Digital Medicine, Esteva A., Robicquet A., Ramsundar B., Kuleshov V., DePristo M., Chou K., Dean J., Nature Medicine, Beger J., Newsweek, Harvard Health Publishing, Jiang F., Jiang Y., Zhi H., Dong Y., Li H., Ma S., Wang Y., Stroke and Vascular Neurology, World Health Organization, HealthSpot, Theranos, Babylon Health, CarePod, Forward Health, Hippocratic AI, MayaMD, Versel N., MedCity News, Elizabeth Holmes, Ramesh “Sunny” Balwani, John Carreyrou, Weaver C., Copeland R., Schwartz B., TechCrunch, Alexander P., Lomas N.

Part 5:

Yann LeCun, Ph.D., Curtis Langlotz, MD, Ph.D., David D. Luxton, Ph.D., MS, Nirav R. Shah, MD, MPH, Geraint Rees, Ph.D., Antonio Di Ieva, MD, Ph.D., Eric Topol, MD, Andrew Ng, Sanat Dixit, MD, FACS, Guy Culpepper, MD, Mark Cuban, McGill University, Declan O’Regan, Center for Artificial Intelligence in Medicine & Imaging (AIMI), Stanford University, Filippo Pesapane, Marina Codari, Francesco Sardanelli, AMA Journal of Ethics, AlphaZero, Nobel Prize, World Economic Forum, The Lancet, The Doctors Company, Google Brain, DeepLearning.AI, TED Talk, Mark Cuban Cost Plus Drug Company, American Academy of Family Physicians (AAFP), Riedl, D., Schüßler, G., Ann M. Richardson, EPIC Systems, Judy Faulkner, Frontiers in Psychology, Rishad Usmani, MD, Spencer Dorn, FDA (Food and Drug Administration), Obermeyer, Z., Powers, B., Vogeli, C., Mullainathan, S., Annals of Internal Medicine, The Register, JAMA Open, Watson for Oncology, Science (journal), Theranos, HealthSpot, Babylon Health, Forward Health, CarePod, Hippocratic AI, MayMD, Deep View Report, McKinsey, Meerkat 70B, Jiang, F., Sutton, R. T., Froomkin, A. M., Kerr, I., Pineau, J., Nature Medicine.

Part 6:

MYCIN, INTERNIST-I, Electronic Health Record (EHR) systems, IBM, Thomas J. Watson, Jr., William B. Schwartz, M.D., New England Journal of Medicine, Wall Street Journal, iPhones, iPads, Gizmodo, Watson, Columbia University, University of Maryland, Nuance Communications, Inc., Apple, Harvard Medical School, Dr. Warner Slack, Forbes, Watson Health, American Medical Association (AMA), AMA Journal of Ethics, IBM Watson, Luxton DD, November JA, Johns Hopkins University Press, Yu KH, Beam AL, Kohane IS, Nature Biomedical Engineering, Greene JA, Andrew S. Lea, OpenAI o1 Strawberry model, OpenAI, ChatGPT, X-ray, MRI.

Wow, that’s a ridiculously long list—299 unique mentions, to be precise. We’ve got 184 individuals, 79 companies/organizations, and 36 products/systems.

Before we dive in, let me make one thing clear. I’m over this tired line, but I have to mention it for the sake of completeness: “AI won’t replace doctors, but doctors who use AI will replace those who don’t.” It’s been thrown around for at least 5 years now (any guesses on who said it first?). At this point, it’s obvious, and frankly, I’m sick of hearing it.

Now, here’s how we’re going to attack this article:

Part 1:

1. 1955: Warner V. Slack, MD and The Dawn of the ‘Machines Will Replace Doctors’ Debate

1.1. Automated Patient Questionnaire (1955)

1.2. Patient-Centered Computing and Cybermedicine (1965 onwards)

1.3. Center for Clinical Computing

1.4. Association with MIT’s Eliza

1.5. Views on Soliloquy and Mental Health

1.6. Warner Slack’s Legacy and Impact

2. 1959 and Beyond: Pioneering Machine Learning for Diagnosis—From Nash to Zworykin

3. 1960s: PROMIS, the First Touch-Screen Computer-Based Medical Record System

4. 1960s: CASNET, the First AI System for Medical Diagnosis and Treatment

5. 1970s and 1980s: The Rise of Artificial Intelligence in Medicine through Expert Systems

5.1. INTERNIST-I: The First AI Model for Internal Medicine Diagnostic Reasoning

5.2. MYCIN: Bridging Artificial Intelligence and Medical Diagnosis

5.3. CADUCEUS: A Successor to INTERNIST-I with Comprehensive Knowledge Base

5.4. QMR: A Superior Computational Knowledge Base Outpacing INTERNIST-I and CADUCEUS

5.5. CADIAG: The Birth of Fuzzy Logic in Medical Diagnosis

5.6. DXplain: The Pioneer of Computer-Based Diagnostic Decision Support

Part 4:

6. Argument FOR: AI Will Replace Doctors – It’s More Powerful, More Accurate, and Could Even Be More Empathetic

6.1. Famous Quotes for the “AI Will Replace Doctors” Argument

6.1.1. Warner V. Slack, MD, Late Professor at Harvard Medical School and medical informatics pioneer

6.1.2. Vinod Khosla, “The Forecaster Without the Horizon”, a venture capitalist and co-founder of Sun Microsystems

6.1.3. Geoffrey Hinton, “The Godfather of AI” and freshly minted 2024 Nobel Prize laureate in physics

6.1.4. Phelps Kelley, MD, a diagnostic radiologist

6.1.5. Ezekiel J. Emanuel, MD, Ph.D., prominent physician and architect of the Affordable Care Act (ACA)

6.1.6. Yuval Noah Harari, historian, philosopher, and best-selling author

6.1.7. Ali Parsa, “The Madoff of Digital Health,” CEO of the now-bankrupt and fraudulent Babylon Health

6.1.8. Judy Faulkner, Founder and CEO, Epic Systems

6.1.9. Ben Horowitz, co-founder of Andreessen Horowitz (a16z) venture capital firm

6.1.10. Derya Unutmaz, MD, professor of immunology at the Jackson Laboratory for Genomic Medicine

6.1.11. Bindu Reddy, founder of Abacus.AI

6.1.12. Elon Musk, entrepreneur and founder of Tesla, SpaceX, Neuralink, and The Boring Company

6.2. Advancements in AI Empathy and Patient Interaction

6.2.1. AI Outperforms Doctors in Empathy

6.2.2. AI Enhances Patient Satisfaction

6.3. Superior Diagnostics and Treatment Planning by AI

6.3.1. AI Outperforms Human Doctors in Diagnostics

6.3.2. AI in Personalized Treatment Planning

6.4. AI Reducing Physician Burnout and Improving Efficiency

6.4.1. Automation of Administrative Tasks

6.4.2. Mitigating Physician Shortages

6.5. Economic and Accessibility Benefits

6.5.1. Reducing Healthcare Costs

6.5.2. Improving Accessibility in Underserved Areas

6.6. AI Tools That Tried to Replace Doctors and Nurses

6.6.1. HealthSpot: Telemedicine Kiosks That Missed the Mark

6.6.2. Theranos: The Fallacy of Overpromised Technology

6.6.3. Babylon Health: Lied About Its AI

6.6.4. Forward’s CarePod: A Tech-First Approach to Primary Care

6.6.5. Hippocratic AI: Replacing Nurses with Algorithms

6.6.6. MayaMD: Questionable Claims of AI Outperforming Doctors

Part 5:

7. Argument AGAINST: AI Won’t Replace Doctors—But Every Doctor Will Have an AI Assistant / AI Agent

7.1. Famous Quotes for the “AI Won’t Replace Doctors” Argument

7.1.1. Yann LeCun, Ph.D., Chief AI Scientist at Meta and founding father of convolutional neural networks (CNN)

7.1.2. Declan O’Regan, Professor of of Cardiovascular AI

7.1.3. Curtis Langlotz, MD, Ph.D., Stanford radiologist and AI pioneer

7.1.4. David D. Luxton, Ph.D., MS, an expert in the field of artificial intelligence and health care technology

7.1.5. Nirav R. Shah, MD, MPH, a prominent physician and health policy expert

7.1.6. Geraint Rees, Ph.D., Professor of cognitive neurology, University College London

7.1.7. Antonio Di Ieva, MD, Ph.D., internationally acclaimed neurosurgeon

7.1.8. Eric Topol, MD, a prominent cardiologist and digital medicine expert

7.1.9. Andrew Ng, a prominent data scientist, founder of Google Brain and DeepLearning.AI

7.1.10. Sanat Dixit, MD, FACS, Professor of Neurological Surgery

7.1.11. Mark Cuban, an entrepreneur and a founder of Mark Cuban Cost Plus Drug Company

7.1.12. Guy Culpepper, MD, a nationally recognized primary care physician and Fellow of the American Academy of Family Physicians (AAFP)

7.2. The Irreplaceable Doctor-Patient Relationship

7.2.1. Empathy and Trust in Healthcare

7.2.2. The Therapeutic Power of Human Interaction

7.2.3. Patient Autonomy and Empowerment

7.3. Clinician Skepticism and Resistance

7.3.1. Skepticism Rooted in Experience

7.3.2. The Emotional and Ethical Dimensions of Care

7.4. Best Practices: Legal and Ethical Responsibilities

7.4.1. Best Practices in Medicine Are Inconsistent and Evolving

7.4.2. Ethical and Responsible AI in Medicine Lags Behind

7.4.3. Explainability and Trust are Still Major Concerns

7.4.4. Algorithmic Biases and Health Equity are Far From Solved

7.4.5. Legal and Ethical Concerns: Doctors Go to Jail, Engineers Don’t

7.5. FDA’s Lack AI Oversight Is Failing Medicine

7.5.1. Lack of Robust Regulations for AI Systems

7.5.2. Slow Feedback Loops

7.5.3. Legal Liability and Clinical Decision-Making

7.5.4. AI’s Biases and FDA’s Lack of Response

7.5.5. FDA’s Inadequate Validation Standards

7.5.6. FDA’s Failure to Promote Interdisciplinary Collaboration

7.5.7. The Data Problem

7.5.8. Economic Pressures

7.5.9. Lobbying

7.5.10. The Revolving Door

7.5.11. Misaligned Incentives

7.6. AI in Healthcare Standardization Challenges

7.6.1. Evolving Standards for AI in Medicine

7.6.2. International Regulatory Variations

7.6.3. Data Standardization

7.7. AI Biases, Hallucinations, and Data Limitations

7.7.1. AI Biases

7.7.2. AI Hallucinations

7.7.3. Data Limitations

7.8. Limitations of AI Technology in Healthcare

7.8.1. Lack of Contextual Understanding and Clinical Nuance

7.8.2. Challenges with Autonomous Clinical Decision-Making

7.8.3. Unstructured and Incomplete Data in Healthcare

7.8.4. Limited Generalization Across Medical Disciplines

7.8.5. Complexity of Clinical Judgment and Human Intuition

7.8.6. Technological Readiness and Integration Challenges

7.8.7. Limited Application in Certain Medical Tasks

7.9. Increased Workload and Reduced Efficiency: The EHR Nightmare All Over Again?

7.9.1. Increased Workload: The Unfortunate EHR Parallel

7.9.2. The EHR Nightmare All Over Again?

7.9.3. Reduced Efficiency: The Editing Paradox

7.9.4. AI is Not Yet Ready for Clinical Autonomy

7.9.5. Learning Curve and Fixed Costs

7.9.6. Feedback Loop Deficiencies

7.10. The Complexity of Human Health and the Need for Clinical Judgment

7.10.1. The Complexity of Human Health

7.10.2. Multifactorial Nature of Health Problems

7.10.3. The Need for Clinical Judgment

7.11. Historical Failures in Replacing Doctors with Technology

7.11.1. Theranos: From Blood Work to Con Work

7.11.2. HealthSpot: The Telemedicine Kiosk Failure

7.11.3. Babylon Health: The Emperor Had No Clothes

7.11.4. Forward’s CarePod: False Start

7.11.5. Hippocratic AI: Nurses Under Threat?

7.11.6. MayMD: Repeating the Mistakes of the Past

7.12. Venture Capital: Focusing on Quick Bucks, Not Healthcare

7.12.1. Venture Capital’s Incentive Structure Prioritizes Quick Returns

7.12.2. The Profit Motive Encourages Shortcuts and Misaligned Priorities

7.12.3. Lack of Long-Term Focus Hurts Innovation in Healthcare AI

7.12.4. The Misallocation of Capital in Healthcare AI

7.13. AI as a Tool for Augmentation, Not Replacement

7.13.1. Augmenting, Not Replacing, Critical Thinking

7.13.2. AI Systems Are Not Yet Ready for Autonomous Decision-Making

7.14. The Future: Every Doctor Will Have an AI Assistant / AI Agent

Part 6:

8. 70 Years Later: Machine Learning Evolves, Healthcare Stays the Same

9. Two Essential Conditions for Industry-wide AI Adoption

10. Conclusion 

Alright, let’s kick things off with Part 1.