An Expert on Entrepreneurship Tackles Health Care Innovation

October 7, 2024

For 35 years, Amar Bhidé taught entrepreneurship—at Harvard, Chicago, Tufts, and Columbia, where he was Lawrence D. Glaubinger Professor of Business. He has written dozens of case studies, synopses of real-world scenarios crafted to spur vigorous classroom conversation, books on entrepreneurship, innovation, and the financial system, and op-eds on public policy issues for the Wall Street Journal, the Financial Times, and The New York Times.

In recent years, he’s increasingly delved into foundational questions about the complex, dynamic advances in productive knowledge. “It’s not just science” he quips. “The steam engine did far more for the laws of thermodynamics than laws of thermodynamics did for the steam engine.”

In January 2024, Bhidé accepted an appointment as a professor in Columbia Mailman’s Department of Health Policy and Management. He teaches the course “Lessons from Transformational Advances,” which digs into a series of case histories Bhidé developed to probe the complex, protracted processes that produced life-altering drugs, devices, and practices.

One case describes how despite a long history and contemporary clinical promise—the widespread use of fecal microbiota transplant to treat gastrointestinal disease has been stymied by regulatory hurdles and provider resistance. The case on tamoxifen shows how tamoxifen became a gold-standard treatment for breast cancer—after failing as a contraceptive.

The overarching goal is to inspire, not just inform students about how new treatments and practices evolve. “The cases show how contributing to progress offers great scope for personal flourishing, whatever your role and whatever your financial reward may turn out to be,” says Bhidé.

Is there a core theme in your work?

Bhidé: I’ve gone from looking at things principally from a businessperson’s, an entrepreneur’s point of view, to trying to understand the overall process of how productive knowledge advances. But the core theme has been the human striving for change and betterment that cannot be reduced to an algorithmic formula.

How did you make the pivot to advances in medicine?

Bhidé: As it happens my mother was a pioneering cancer researcher, and my sister is an oncologist. But, with my general interest in productive knowledge, I could have written about anything—advances in computer science. I didn’t. I wrote about medical innovations. This was lucky. Health care is a broad arena but nonetheless has some common features.

What do you hope your students take from the case studies?

Bhidé: The process of practical advances is complicated, protracted, and involves a large cast of characters. There is instrumental and humanistic value in appreciating these processes: We could do things better in the future if we understand how past advances come about. They also teach us what makes us human.

In December, Oxford University Press will publish your fifth sole-authored book, Uncertainty and Enterprise: Venturing Beyond the Known(link is external and opens in a new window). How did it come about?

Bhidé: The book represents the culmination and synthesis of much of my writing and research. There are also many points of overlap with the seminar on transformational advances I’m currently teaching. The case studies have informed the book and the ideas that I’ve tried to distill in the book have informed how I’m teaching the course.

What are the foundational principles of Uncertainty and Enterprise?

Bhidé: We cannot or should not be sure of anything. We cannot be sure of what is or what was, and even less what could be or what should be. We can have only conjectures, provisional hypotheses that combine imagination and evidence. And inevitably, our conjectures diverge while much of our actions are interactive. We can’t act unilaterally. Imaginative yet grounded discourse plays a crucial role in aligning our conjectures.

Who is your target audience?

Bhidé: I want to persuade mainstream economists that there’s a broader way of looking at the world that—if they adopted it—could be beneficial to themselves and to society. A second target is the intellectually curious, possibly “highbrow,” general reader about the rewards, challenges, and reasonable ways of dealing with uncertainty that is so central to our lives, yet are often ignored in economics and decision theory. I don’t however want to pick a fight with mainstream economics or provide cookbook recipes to general readers.

This fall, Project Syndicate published your op-ed calling large learning models “mendacious talking horses(link is external and opens in a new window).” Another for Barron’s(link is external and opens in a new window) calls out the current AI investment craze a mania. What sparked your ire?

Bhidé: Writing my Uncertainty book has a lot to do with it. I tried to use LLMs to research, edit, and illustrate the book—it was a source of unending frustration, though “earlier” AI was invaluable. I also studied the evolution of AI for my book. AI grew out of a “fork” in the cognitive revolution of the 1950s and 1960s which conceived of the mind as a computer, often relying on statistical models to recognize patterns. A second fork treated the mind as a “meaning constructor” where meaning was highly contextual, historical, and cultural. Both forks have value.

Long before LLMs, statistical AI had proven its worth in many applications. But reducing all thought and speech to a mindless statistical model is absurd. Yet that’s what many LLMs try do. The LLM mania also ignores the protracted trial and error through which cost-effective AI applications have emerged over the last 70 years. The mania also shows how ignorance of how transformational technologies like AI evolve can become a social menace.

In April 2015 I had dinner with an old friend in Paris, who also happens to be the retired founder of a storied biotech company.  He looked in unusually splendid shape and being a competitive sort I was most curious why.  He told me elliptically that much of what we know about nutrition is wrong.  I eventually wheedled out of him the information that he had converted to a Paleo (very low carb/sugar) diet.

That dinner conversation was life altering — well at least diet altering. I gave up all deserts, bread, rice, potatoes, oatmeal breakfast, cranked up on pumpkin seeds and almonds and began to ferment my yogurt for at least 24 hours (to reduce sugar content).

Later that year, in September I decided to take a glucose/lipid test.  Horrors: my total and bad cholesterol had gone up. It had always been highly variable and borderline high, so I consulted a cardiologist. She wanted to put me on statins immediately, but I asked for an angio-CT (basically x-rays of my coronary arteries)

It showed a low single digit calcium score (which I’m told is good) but also mild arterial plaque.

And apparently I had the bad kind of bad cholesterol (small molecule) and the not so good kind of good cholesterol (again small molecule)

The cardiologist of course saw this as proof positive that I should be on statins. 

I refused.  Another physician friend of mine then suggested I look into the Esselstyn diet http://www.dresselstyn.com/site/

This is supposed to have the potential to *reverse* plaque but it would also require further measures, namely going vegan – and giving up oil and nuts.

I then happened to be in Stockholm and discovered that oatmeal yogurt is “thing”. Further investigation suggested that yogurt making bacteria can pretty much chow down on anything with carbs or sugar, so my new breakfast routine became “yogurt” created by blending oatmeal, quinoa, chia seeds, hemp protein and bananas and letting that blend ferment for several days….

Lunch comprises cake whose “batter” consists of fermented quinoa, spiced up Indian style, and baked with no oil or butter.

Dinner? I don’t eat dinner. A glass of red wine does the trick.

Sticking to the diet is no easy task but the results have been remarkable. I also lost about 20 pounds..

This is *not* a recommendation.  Worked for me and may not work for anyone else…

Case studies documenting how similar problems were overcome in the past can provide reminders of forgotten solutions. And, for unprecedented problems, historical analyses may improve our understanding of why these problems did not previously arise and suggest ideas for what might be done to solve them now.

Studying “who did what, when, and why” should be particularly useful in addressing problems of bottlenecks and linkages. Scholars of technological innovation have shown that the successful development and widespread use of new products and services is the result of extended interactions between many individuals and organizations. These include scientists, engineers, designers, marketers, financiers, regulators, and not the least, users, who contribute different kinds of skills, knowledge, and resources and solve related but different problems. Technological advances are thus the result of what one of us (Amar) has previously called an ongoing, massively multiplayer game.

Bottlenecks and incongruencies are inevitable in such a game. In medicine, for instance, fundamental scientific breakthroughs may run ahead of the development of treatments. And the best treatments under well-controlled experimental conditions may be inferior in large-scale deployment (for instance, because of inadequate mechanisms to ensure patient compliance). Case studies encompassing multiple players and how they interacted with each other, and over time, to resolve bottlenecks and incongruencies should provide useful rules of thumb about effective rules for reforming the current medical advances game.

More broadly, studying medical advances could improve our understanding of “productive knowledge.” Scholars of the history of technology like Vincenti have persuasively argued that engineering is not merely applied science, although it often draws on – and contributes to — the natural sciences. Natural sciences focus on discovering “how the world works” in ways that may not be suited to fields such as engineering, medicine, business, education, and public administration, whose principal purpose is to develop artifacts that don’t exist in nature and are intended to make the world a better place. Thus both the natural sciences and fields of useful knowledge may aspire to be evidence-based, but the kind of data collected and how it is used can be materially different.

In medicine, for instance, Gawande’s WHO team blended expert hypotheses with rough and ready iterative testing to develop surgical checklists. Medical devices are also developed through similar processes. These would not be considered good practice in traditional scientific research.

Understanding and highlighting the distinctive features of useful medical research (as has already been done in engineering) should help prevent the dogmatic misapplication of the scientific method and possibly improve appropriate alternative practices. Moreover, the benefits could extend beyond medicine into fields such as economic development and financial regulation. The recent fashion for randomized experiments in the social sciences, if not appropriately bounded, has the potential for considerable waste of resources and even outright harm.