Context: I am a PhD candidate in health policy / health economics at Stanford University. I wrote this review for my website, but thought it might be of interest to some in the EA community as new leadership takes over the major the major health/medical institutions in the US.


In the past few years, I’ve observed a growing rift in medicine between the medical establishment and what I will call the “contrarians.” Of course, there have always been medical contrarians, but the COVID pandemic brought this divide to the forefront of our public discourse. The medical establishment is represented by the medical associations (AMA, AHA), government health agencies (FDA, CDC, NIH), medical journals (JAMA, NEJM), and most health systems - so basically the majority. Meanwhile, there are a small group of contrarians who are gaining social (and now political) influence by calling out where this establishment is leading the public astray. Some of them have strong academic and medical backgrounds, while others have none at all. Sometimes they get things right, and other times they spread mistruths and sow distrust in modern medicine altogether.

One such contrarian is Dr. Marty Makary, a surgeon-researcher at Johns Hopkins University. His 2020 book, The Price We Pay, had a major influence on me personally, motivating me to study how the misaligned incentives of our healthcare system lead to such high costs. So I was excited to listen to his new book, Blind Spots, which tells the stories of many cases where the medical establishment made egregious policy errors, resisted change, and failed to apologize.

The first and perhaps most clear-cut case is that of peanut allergies. In 2000, the American Academy of Pediatrics (AAP) responded to concerns about peanut allergies in children by recommending any child considered at high risk of allergies avoid peanuts for the first three years of life. While this recommendation may sound reasonable, it was in fact based on no rigorous evidence and indeed completely wrongheaded. Following this recommendation, peanut allergies skyrocketed in the US. This is because exposing children to peanuts and other potential allergens at a young age helps them develop a tolerance for such substances. 

Some researchers eventually conducted robust studies showing this phenomenon, but the AAP and the medical establishment resisted updating their guidelines fully until 2017. Makary points out that the original recommendation was made by a board of pediatricians, with no consultation from immunologists. He criticizes the way medical specialties are often siloed, as if the human body were split into isolated compartments.

Makary continues with cases ranging from hormone replacement therapy (HRT) to HIV in the blood supply to silicone breast implants. In the case of HRT, a handful of physicians used a non-statistically significant association to convince the medical establishment that HRT caused breast cancer. This resulted in a generation of women losing access to the many well-established benefits of this treatment during menopause, with no realized reduction in breast cancers. Despite the harm caused by their actions, the lead authors of this research went on to have very successful careers, faced no consequences, and never formally apologized for what they did. 

The tone of the book is annoyed verging on contempt. After quoting the questionable reasons people gave for promoting harmful polices, the author would often react sarcastically with, “Amazing.” Makary is clearly frustrated with the state of medicine in the US and wants the individuals and entities involved in these cases to be held responsible. Multiple times throughout the book he calls for them to own up to their mistakes and formally apologize to the public. He is convinced that this is an essential step for the medical establishment to regain public trust. 

Makary attributes blame for these cases to a few underlying factors. Namely, he cites psychological biases as critical ingredients protecting the status quo. For example, cognitive dissonance prevents physicians from accepting new information that challenges their long held medical beliefs and practices. Groupthink is another common issue preventing open-minded consideration of new ideas in the medical establishment. The perverse incentives and power dynamics among the medical establishment also help to explain these failures of medicine.

Just after finishing the book, I got a unique opportunity to see Dr. Makary and other medical contrarians make their arguments in a pandemic policy conference hosted by my own department, Stanford Health Policy. The program was marred with controversy from the start, as certain invited speakers declined to attend when they saw which medical contrarians were participating on the panels. The conference was organized by Dr. Jay Bhattacharya, the Stanford health economist who became one of the most (in)famous medical contrarians during COVID when he co-authored the Great Barrington Declaration, calling for focused protection of those most at risk from the virus, rather than blanket lockdowns. While I can’t defend every claim Dr. Bhattacharya made regarding COVID, in my view he was treated quite unfairly by the medical establishment, and over time more people seem to be coming to the view that lockdowns, particularly in the form of school closures, were not a great idea.

In the first panel of the event (which you can watch here), the topic was evidence-based decision making. Dr. Makary was sat center stage among seven panelists, including some of my professors. Each had a chance to share some thoughts before taking questions from the audience. I was pleasantly surprised to see that first question asked was the one I submitted - what was a policy you believed was best at some point during the pandemic, but later came to change your mind on? To my even greater surprise, Dr. Makary’s response to this question was “I can’t think of anything.” Amazing. For the record, in February 2021, Makary predicted in a Wall Street Journal article that COVID would be “mostly gone” by April 2021. Needless to say, that did not happen.

Let this be a reminder that our psychological biases run very, very deep. Daniel Kahneman, the renowned psychologist and Nobel laureate who discovered many of these biases was once asked if his familiarity with these innate tendencies helped him to overcome them - to which he simply replied, “No.” This is why it is so essential to have medical institutions that are committed to scientific principles rather than the opinions of a select few. No individual can be perfectly objective. We need systems that can course correct and reliably lead us to the truth.

Ultimately, I agree with many of the points Makary makes in this book. The medical establishment should apologize when they get things wrong. Perhaps more importantly, the medical associations and agencies should admit when they don’t know things and avoid making sweeping policy recommendations based on weak evidence. Medical journals should not politicize themselves by endorsing candidates, and they should publish research based on the merits of its methods, not its conclusions. 

I’ll conclude with two key takeaways I have from this book. First, some of the most important discoveries in medicine were made by people who were once considered contrarian, so we should never write off an idea just because it doesn’t fit into mainstream thinking. Second, if it is the case that we are currently getting something very wrong in medicine, be it fluoride in the drinking water or the long-term side effects of certain vaccines, our current system is not well-suited to uncover these truths. This is something that should concern us all. Marty Makary has recently been nominated to become the next FDA commissioner, while Jay Bhattacharya is set to run the NIH. If they are confirmed, I hope they take these lessons to heart and steer us in the right direction.

Comments3


Sorted by Click to highlight new comments since:

Thanks for this write up. I had no idea about any of this! I'm as bit disturbed by Makary's response to your "change your mind" question. Character, integrity, balance, and ability to compromise really matters when it comes to leading institutions, not just being smart and having good ideas.

Making new discoveries is often helped by some contarianism yes, but I'm not sure it's the best trait for running an institution. 

Like you I hope they will do well!

Thanks! It will be interesting to see what changes they try to make to these institutions and how open to criticism they will be.

Executive summary: Dr. Marty Makary's Blind Spots critiques the medical establishment for resisting change, making flawed policy decisions, and failing to admit mistakes, arguing that cognitive biases, groupthink, and entrenched incentives hinder progress; while contrarians sometimes highlight real failures, they are not immune to the same biases.

Key points:

  1. Blind Spots highlights major medical policy failures, such as the mishandling of peanut allergy guidelines and hormone replacement therapy, emphasizing how siloed expertise and weak evidence led to harmful recommendations.
  2. Makary argues that psychological biases (e.g., cognitive dissonance, groupthink) and perverse incentives contribute to the medical establishment's resistance to admitting errors and adapting to new evidence.
  3. The book adopts a frustrated and sometimes sarcastic tone, repeatedly calling for institutional accountability and public apologies for past medical mistakes.
  4. The author attended a Stanford conference featuring Makary and other medical contrarians, where he observed firsthand how even contrarians struggle to acknowledge their own misjudgments.
  5. The reviewer agrees with many of Makary’s critiques, particularly the need for humility in medical policymaking, but stresses that no individual or small group should dictate scientific consensus.
  6. With Makary and other contrarians poised for leadership roles in U.S. health agencies, their ability to apply their own lessons on institutional accountability and self-correction will be crucial.

 

 

This comment was auto-generated by the EA Forum Team. Feel free to point out issues with this summary by replying to the comment, and contact us if you have feedback.

Curated and popular this week
LintzA
 ·  · 15m read
 · 
Cross-posted to Lesswrong Introduction Several developments over the past few months should cause you to re-evaluate what you are doing. These include: 1. Updates toward short timelines 2. The Trump presidency 3. The o1 (inference-time compute scaling) paradigm 4. Deepseek 5. Stargate/AI datacenter spending 6. Increased internal deployment 7. Absence of AI x-risk/safety considerations in mainstream AI discourse Taken together, these are enough to render many existing AI governance strategies obsolete (and probably some technical safety strategies too). There's a good chance we're entering crunch time and that should absolutely affect your theory of change and what you plan to work on. In this piece I try to give a quick summary of these developments and think through the broader implications these have for AI safety. At the end of the piece I give some quick initial thoughts on how these developments affect what safety-concerned folks should be prioritizing. These are early days and I expect many of my takes will shift, look forward to discussing in the comments!  Implications of recent developments Updates toward short timelines There’s general agreement that timelines are likely to be far shorter than most expected. Both Sam Altman and Dario Amodei have recently said they expect AGI within the next 3 years. Anecdotally, nearly everyone I know or have heard of who was expecting longer timelines has updated significantly toward short timelines (<5 years). E.g. Ajeya’s median estimate is that 99% of fully-remote jobs will be automatable in roughly 6-8 years, 5+ years earlier than her 2023 estimate. On a quick look, prediction markets seem to have shifted to short timelines (e.g. Metaculus[1] & Manifold appear to have roughly 2030 median timelines to AGI, though haven’t moved dramatically in recent months). We’ve consistently seen performance on benchmarks far exceed what most predicted. Most recently, Epoch was surprised to see OpenAI’s o3 model achi
Dr Kassim
 ·  · 4m read
 · 
Hey everyone, I’ve been going through the EA Introductory Program, and I have to admit some of these ideas make sense, but others leave me with more questions than answers. I’m trying to wrap my head around certain core EA principles, and the more I think about them, the more I wonder: Am I misunderstanding, or are there blind spots in EA’s approach? I’d really love to hear what others think. Maybe you can help me clarify some of my doubts. Or maybe you share the same reservations? Let’s talk. Cause Prioritization. Does It Ignore Political and Social Reality? EA focuses on doing the most good per dollar, which makes sense in theory. But does it hold up when you apply it to real world contexts especially in countries like Uganda? Take malaria prevention. It’s a top EA cause because it’s highly cost effective $5,000 can save a life through bed nets (GiveWell, 2023). But what happens when government corruption or instability disrupts these programs? The Global Fund scandal in Uganda saw $1.6 million in malaria aid mismanaged (Global Fund Audit Report, 2016). If money isn’t reaching the people it’s meant to help, is it really the best use of resources? And what about leadership changes? Policies shift unpredictably here. A national animal welfare initiative I supported lost momentum when political priorities changed. How does EA factor in these uncertainties when prioritizing causes? It feels like EA assumes a stable world where money always achieves the intended impact. But what if that’s not the world we live in? Long termism. A Luxury When the Present Is in Crisis? I get why long termists argue that future people matter. But should we really prioritize them over people suffering today? Long termism tells us that existential risks like AI could wipe out trillions of future lives. But in Uganda, we’re losing lives now—1,500+ die from rabies annually (WHO, 2021), and 41% of children suffer from stunting due to malnutrition (UNICEF, 2022). These are preventable d
Rory Fenton
 ·  · 6m read
 · 
Cross-posted from my blog. Contrary to my carefully crafted brand as a weak nerd, I go to a local CrossFit gym a few times a week. Every year, the gym raises funds for a scholarship for teens from lower-income families to attend their summer camp program. I don’t know how many Crossfit-interested low-income teens there are in my small town, but I’ll guess there are perhaps 2 of them who would benefit from the scholarship. After all, CrossFit is pretty niche, and the town is small. Helping youngsters get swole in the Pacific Northwest is not exactly as cost-effective as preventing malaria in Malawi. But I notice I feel drawn to supporting the scholarship anyway. Every time it pops in my head I think, “My money could fully solve this problem”. The camp only costs a few hundred dollars per kid and if there are just 2 kids who need support, I could give $500 and there would no longer be teenagers in my town who want to go to a CrossFit summer camp but can’t. Thanks to me, the hero, this problem would be entirely solved. 100%. That is not how most nonprofit work feels to me. You are only ever making small dents in important problems I want to work on big problems. Global poverty. Malaria. Everyone not suddenly dying. But if I’m honest, what I really want is to solve those problems. Me, personally, solve them. This is a continued source of frustration and sadness because I absolutely cannot solve those problems. Consider what else my $500 CrossFit scholarship might do: * I want to save lives, and USAID suddenly stops giving $7 billion a year to PEPFAR. So I give $500 to the Rapid Response Fund. My donation solves 0.000001% of the problem and I feel like I have failed. * I want to solve climate change, and getting to net zero will require stopping or removing emissions of 1,500 billion tons of carbon dioxide. I give $500 to a policy nonprofit that reduces emissions, in expectation, by 50 tons. My donation solves 0.000000003% of the problem and I feel like I have f
Recent opportunities in Global health & development
20
Eva
· · 1m read