In April and May, the Pew Research Center released two reports about the state of health information and who constitutes America’s health and wellness influencers. Looking at the data, it is hard to find the results surprising. After all, we know that health misinformation (unintentionally mistaken or incorrect information) and disinformation (intentionally fabricated or manipulated information) are rampant. What makes the reports sobering is recognizing that in the face of more challenging obstacles, health professionals have a never ending and increasing amount of work to do in order to educate and inform the public, especially as trust in science and medicine continue to decline.

In this post, I am going to share some interesting charts from the reports, what that means for healthcare professionals, and what we can possibly do about it. But first let’s see an example of why the source of our healthcare information matters.

Sometimes Even High Quality Journalism Can Be Overly Sensational

Even in the work of exceptional journalists, sometimes the headlines can be dramatic. A couple of weeks ago, one of my favorite podcasts, Plain English, released an episode called “The Most Exciting Month of Medical Breakthrough in Years.” Normally, I find the reporting, interviews, and tone of the podcast to be well-balanced and deliberate. But this time the host was compelled to celebrate three recent studies as stunning and groundbreaking, while quoting Vladimir Lenin: “There are decades where nothing happens; and there are weeks where decades happen.”

Normally, Plain English does a fantastic job when it comes to reporting science, technology, economics, and other data-driven stories, so I found this hype unusual. Forgive me for not immediately popping the champagne. Even the host’s guest cautioned restraint. Before we get into the Pew Research reports, I think it is important to quickly discuss the three studies from the podcast just so the layperson can have a basic understanding about the variety of questions scientists and doctors ask themselves when evaluating current health news.

For deeper understanding of how to read a scientific paper, you can check out these resources here, here, here, here, and/or here.

You can listen to the podcast to form your own opinion, but the three findings were:

1. A new pancreatic cancer drug, daraxonrasib, doubled median overall survival time from 6.6 months to a clinically significant 13.2 months. I get the excitement because the news was met with a standing ovation from a room full of experts at the American Society of Clinical Oncology meeting on May 31.

   But my inner realist can’t help but note that when it comes to pancreatic cancer, which has poor outcomes because of our general inability to detect it early, and in a field such as oncology, which is often fighting an uphill battle, any good news might be welcomed ecstatically. But unlike the general public and media, I am sure these oncologists and the patients’ other doctors are already asking themselves how much meaningful quality of life at the end of life will these patients have in the extra six months gained. They are also contending with how much financial, emotional, and psychological cost the patients and their families might face if this merely extends a patient’s suffering.

2. A preliminary study in the New England Journal of Medicine of only 35 patients showed that a single infusion of a gene-editing drug at the highest dose reduced LDL cholesterol levels by as much as 62 percent; the changes were sustained for at least 18 months. Basically the gene editing molecule, CRISPR, enters liver cells and finds a gene called PCSK9 and replaces a single DNA letter. This prevents the creation of a PCSK9 protein, which normally binds to LDL receptors on the surface of cells, marking them for destruction. If the LDL receptor is destroyed, it cannot take up LDL molecules circulating in the blood stream. But if you can block the creating of the PCSK9 protein, it cannot destroy the LDL receptor. So the LDL receptor can bind to more LDL molecules, reducing levels in the blood.

   Once again, this sounds great. But it was a preliminary study, it only looked at 35 patients, and there are still so many unanswered questions like what are the downstream effects of manipulating this section of a patient’s genome? Will it lead to unforeseen problems in 5 or 10 or 20 years? The body is an integrated, complex system. Small changes can lead to dramatic transformations over time so we are better off being extremely cautious when manipulating the literal code and blueprint of life.

   Currently, PCSK9 inhibitors exist as injections that must be taken every few months. They have a favorable safety profile and are well tolerated, which may be a good sign for gene therapy.

   But we must also consider the obvious question: what is the cost of the gene therapy (hint: multiple millions of dollars) and will it be available to everyone? Will insurance companies pay for it? The FDA has already approved the CASGEVY, a CRISPR-based gene therapy to cure sickle cell disease, but we have yet to see that treatment hit the market in a widespread and affordable way.

3. An experimental injection of a drug called retatrutide, a GLP-1, which affects three hormones that affect energy levels, appetite, and metabolism. Earlier versions of GLP-1 drugs affect one hormone (e.g. semaglutide [Ozempic]) or two hormones (e.g. tirzepatide [Zepbound]).

   In a study released by The Lancet, the drug manufacturer, Eli Lilly, reported that the results were basically on par with those seen in bariatric surgery with the average participant losing 28 percent of their body weight in 80 weeks. Further, 11 percent of participants who took the highest dose dropped out of the study due to side effects. In other words, while encouraging, we still more testing in order to separate hype from reality.

So I hope it is apparent that unless you have trained in or spend your days reading and critiquing studies, it is very easy to get carried away with reported statistics, especially when the results confirm news we are emotionally invested in (Saving lives! Improving cancer mortality! Treating hyperlipidemia! Eliminating obesity!). If even a well-respected and measured journalist can get carried away with new reports and studies, can’t any of us (health professionals included)?

In the end, when you consider the cost of bringing new drugs to market, the time it takes to obtain regulatory approval, and all the experimental design flaws in research studies, a tempered attitude is always preferred over an overly cynical or optimistic one.

Anyway, thanks for humoring this important tangent. Now let’s look at the Pew Research Center reports.

Source of Health Information and Levels of Trust

The graphics are from the Pew Research Center. Take some time to look through them and form your own opinion (that’s how you exercise your ability to read and understand scientific papers!). Here is what I am taking away:

1. Most people get their health information often or sometimes from health care professionals (86%), while roughly 35% get it from social media, and 22% get it from AI chatbots. I suspect that with time, the numbers from social media and AI will increase while sources like major health information websites (e.g. WebMD), news organizations, and government health agencies will decrease. It is still remarkable to me how little trust people have in government health agencies.

2. Healthcare providers are still considered one of the highest quality sources of health information when it comes to ease of understanding, convenience, personalization, and accuracy. But we should recognize that while only 7% of people believe social media is accurate, 30% believe that it is easy to understand, which is higher than government health agencies and news organizations. Only 13% believe that new organizations provide accurate health information! Meanwhile, AI chatbots are already perceived as higher quality health information than social media.

3. Half of Americans have a hard time figuring out if health information is accurate. Looking at the chart, you’ll see that even among people who are educated and upper income, 50% of those with a college education believe that it is at least somewhat difficult to judge accuracy of health information while 44% of those who are upper income feel the same. This is terrible. Imagine if you are part of a lower income or education bracket? Health information is not being formatted ot reach you. This is only going to get worse as AI and social media slop spread, as AI worsens our ability to learn, as social media destroys our attention spans, and as the government continues to dismantle our national scientific research and educational infrastructure.

4. The uninsured, young adults, women, and lower income brackets are more likely to get information from social media and AI chatbots. This makes sense as those with a higher barrier of entry into the the healthcare system are more likely to search for alternate ways to treat manage their personal health and wellness. This is potentially foreshadowing a sad future where those with resources will be treated by an actual human while the rest will be meeting with an AI robot or avatar. Human interaction, like live performance, will be a premium luxury.

Who are America’s Health and Wellness Influencers?

The graphics are from the Pew Research Center. Here is what I am taking away:

1. Almost half of adults under 50 get information from health and wellness influencers. 20% of the health influencers have more than 500 thousand followers. These influencers are a mix of health professionals (41%), coaches (31%), entrepreneurs (28%), authors (11%), and even those with no credentials (16%). When you consider that the first Pew Research Center report said that only 7% believe social media is accurate, there is a lot of people consuming suspect information.

2. Remember the 41% of health and wellness influencers that are health professionals, only one-third of that group, or 17% overall represent conventional medicine. Other health professionals include allied health (pharmacists and physical therapists), alternative medicine practitioners, nutritionists, and mental health providers. In other words, there are bound to be gaps, loss of nuance, and falsehoods mixed into the health and wellness messaging.

3. A major reason (41%) that people get information from health and wellness influencers is because they want to make a health or lifestyle change. But tucked into that chart is the idea that 48% of people cite as a major or minor reason that they seek out content from influencers because they want to learn about things they don’t want to ask their doctor about! This points to a major mistrust that patients have with their doctors. The relationship between physician and patient is supposed to be sacred, confidential, and safe. Clearly, patients do not see it that way and it is up to health care professionals to adapt and rebuild the trust.

4. People primarily seek out wellness influencers to learn about fitness, weight loss, and beauty. To be frank, the influencers may be better examples of preventative medicine than health professionals only because most physicians and health care professionals that I know are not fit, do not always eat healthy, and are not practicing what they preach. Of course, physicians are overworked, and balancing the demands of working in healthcare with life are not easy on body or mind. But putting your body through the rigors of building muscle, abstaining from processed foods, and sustaining healthy habits would go a long way in giving some health professionals perspective on how hard it is to do what we ask our patients to do.

So What Does This Mean and What Do We Do?

Looking at these two surveys, it is apparent that while most people still rely on healthcare professionals for health information and education, a decent number get it from health and wellness influencers and AI chatbots, even if they consider it inaccurate. Half of college-educated people have a hard time judging the accuracy of health information and underserved populations (women, uninsured, lower income) are more likely to rely on social media and AI chatbots than those with better access to the healthcare system.

Further, health and wellness influencers are a diverse group; less than 20% represent conventional medicine. Many people seek advice from social media influencers because they are either uncomfortable with, do not trust, or do not feel that their doctor can address their concerns. Finally, people are primarily focused on learning about fitness, weight loss, and beauty when they seek out influencers.

Ultimately, people are looking to improve their health, they are seeking out information, yet they are having a hard time separating fact from fiction. There are a lot of competing voices and the noise-to-signal ratio is only increasing. It turns out that 58% of traffic on the Internet is bot-driven. Further, more than 50% of new articles on the Internet are now AI-generated. We are drowning in slop, and since AI is trained from the Internet, it will be increasingly learning from itself, potentially increasing the likelihood for errors.

It has come to a point where healthcare professionals, medical schools, hospitals, clinics, and governments must start producing their own content and developing their own health messaging.

• Individually, healthcare professionals need to practice what we preach. If we are unhealthy then it is not hard for us to lose credibility. As Gandhi said, “Be the change you want to see in the world.” Trying to build muscle when healthy will give you a more nuanced perspective on our expectations of patients suffering from ICU weakness.

• Primary care offices and specialty clinics need to start sharing their stories, teaching their patients, and reaching out to the public in ways that inform and guide them on a hyperlocal level.

• Hospitals must enhance how they reach out to their communities. They should hold local public health education seminars and health and wellness fairs. Create fancy TED talk-like events and elevate your staff as thought leaders.

• Medical schools must start educating their students about misinformation and how to combat it. Future (and current) physicians must be taught how to create online educational messaging to reach their patients at their level.

• Medical journals cannot hide valuable knowledge and research behind paywalls that are too expensive for the general public. While news organizations may be able to report on the latest research, the data shows that people don’t trust news organizations. Perhaps medical journals can generate their own summaries for the public. For example, the New England Journal of Medicine started to publish public health alerts in an attempt to make up for the gap left by the CDC’s Morbidity and Mortality Weekly Report after the current administration made its alerts less reliable.

• Governments need to win back the trust of citizens. Perhaps it means partnering with influencers or elevating the voices of local healthcare professionals. But they need to show an active interest and initiative in making their constituents healthier. For example, Medellin hosts a Ciclovia and closes major roads for a few hours once a week to encourage their citizens to get outside and exercise.

Unfortunately, health and wellness information will only become increasingly harder to parse and evaluate as time goes on. Unless the medical community takes an active role in educating our patients and rebutting the misinformation, our patients will continue to suffer. But the good news is that people are interested and receptive to improving their health. We just have to reach them where they are at.

Thanks for getting this far. As a bonus, here’s the other image i considered for this post:

Welcome to the DRIVE series, complete with a gimmicky name for my pleasure. At the end of every month, I’ll provide some combination of discoveries, resources, ideas, values, or experiments involving AI, technology, and healthcare. Let’s go!

This month, we’re covering jailbreaking AI and AI cybersecurity, the growing backlash to AI, and the random good and bad of AI. Towards the end, there are some news stories from medicine including a new pancreatic cancer treatment and the growing acceptance of psychedelics from the GOP.

ChatGPT Wrestles With Its Most Chilling Conversation: How Do I Plan an Attack?

• By Georgia Wells - The Wall Street Journal

• People are gaming ChatGPT to receive information on how to commit violence to themselves or others. As usual, when it comes to gun violence, industry and government are slow to respond.

Why AI Safety Controls Are Not Very Effective

• By Cade Metz and Tiffany Hsu - The New York Times

• Another article about how people are “jailbreaking” AI. “ Did you know poetry works? There are a variety of methods, so I had Google Gemini create these graphic for your education

These AI Models are Free, Private, and Will Never Say ‘No’

• By Huo Jingnan - NPR

• In some cases, you don’t even need to bother with mainstream, proprietary models if you want to use AI for shady purposes. Open-sourced AI models and a process called “abliteration” is helping AI researchers, developers, and hackers to remove the guardrails from AI models. In other words, it overrides the “no” of large-language models. These techniques may lead the model to share how to construct biological weapons, steal credit card information, or perpetuate child abuse.

Spooked By Mythos, Trump Suddenly Realized AI Safety Testing Might Be Good

• By Ashley Belanger - Ars Technica

• Every since the world learned about the power of Anthropic’s Claude Mythos model, the government, which had been laissez-faire with AI regulations, is realizing that we do need testing and guardrails after all.

Deepfakes Are Coming for Your Bank Account

• By Lila Shroff - The Atlantic

• AI deepfakes are making online scams more sophisticated and subtle. From videos to IDs to receipts, anyone or any organization (banks, hospitals, government agencies, small businesses, schools) can be a victim of fraud. Unfortunately, this is one of those parts of modern living that require one to be constantly vigilant and up-to-date.

Passkeys are the New Passwords. You Should Start Using Them Now.

• By Max Eddy - The New York Times

• Since phishing scams and other forms of fraud are becoming more common, the cybersecurity industry is trying to keep up in the never-ending arms race. Enter the passkey. A passkey is a digital key that unlocks access to your online account on a website or app by using your pin, fingerprint, or face ID.

• This video from Google is also helpful in understanding the usefulness of passkeys.

Gen Z Is Turning Against AI in an Incredible Way

• By Victor Tangermann - Futurism

AI Populism Is Here. And No One Is Ready.

• By David Wallace-Wells - The New York Times Magazine

• Two articles on the growing backlash towards AI. When Gen Z is feeling the economic squeeze, graduating into a challenging jobs market, experiencing critical thinking depreciation, and hearing all the doom and gloom from tech CEOs about how AI will render their futures obsolete, is it really that surprising that Gen Z is freaking out?

AI Assistance Reduces Performance and Hurts Independent Performance

• By Grace Liu, Brian Christian, et al. - arXiv

• Project Website

• In a randomized control study of 350+ people, researchers had participants solve 12 fraction problems with or without an AI assistant (GPT-5). Then for the AI assistant group, they suddenly removed the assistant and had all participants solve 3 more problems. What they found was that those who used the AI assistant not only gave up earlier when the AI crutch was removed, but they also skipped more questions than the control group that never had AI to begin with.

• Not only were the results replicable, but they were also seen in reading comprehension, a task which involves different cognitive skills.

• So the main takeaways: AI assistance leads people to give up earlier on difficult tasks and reduces performance when AI assistance is taken away. The negative effects of AI assistance are generalized across domains. And those who use AI to lead them directly to the answer suffer a greater performance drop than those who use it for hints or clarifications.

• All this goes back to the importance of schools teaching students the general skills of how to think, how to learn, how to reason, and how to solve problems, regardless of domain. In other words, it is not about teaching to the test.

The Despair of the Professor in the Age of AI

• By Jay Caspian King - The New Yorker

• It’s hard being a professor or educator these days. How do you prepare students for the AI age, while still teach them how to think? How do you guard against cheating? You can force them to take tests and write papers in class, but any long form or complex tasks that take a lot more time would be sacrificed. Sometimes ideas need time to marinate before you can develop them fully. But if you can’t practice the skill of idea or solution generation because an AI-generated solution is tempting, how will you develop it?

Meet the Doctor-Turned-Entrepreneur Using AI to Save Lives

• By Zinnia Lee - Forbes

• The AI arms race in radiology heats up. Inspiring story about the CEO (a physician-programmer) and his company from Australia called Harrison.ai and its competition: Aidoc and Qure.ai

I Used Claude to Negotiate $163,000 off a Hospital Bill. In a Complex Healthcare System, AI is Giving Patients Power.

• By Matt Rosenberg - Business Insider

• AI isn’t all that bad! When it comes to navigating healthcare costs, AI can help educate patients, review healthcare bills, negotiate costs, and take on an intimidating process.

Hackers Hate AI Slop Even More Than You Do

• By Matt Burgess - Wired

• It turns out that AI is an equal opportunity annoyance. On forums where cybercriminals and hackers trade and reveal information, AI-generated responses are diluting the high-quality exchanges they are normally accustomed to. Perhaps we should all agree to keep AI out of some parts of the Internet? I mean, it’s already ruined Reddit.

Thousands of Vibe-Coded Apps Expose Corporate and Personal Data on the Open Web

• By Andy Greenberg - Wired

• If you want proof on why learning to code and understand software and web architecture is so important, this is it. Building websites and apps is relatively simple using AI if the purpose is to just relay information like a personal landing page or basic instructions. But if you are collecting user data, if the information on the website is dynamic, and if there are legal ramifications to leaking user information, there is a lot more to understand about data security than just typing a prompt into a chatbot and shipping the output.

Artificial Intelligence Floods Court Dockets with Home-Brewed Lawsuits

• By Mattathias Schwartz and Zach Montague - The New York Times

• AI is allowing individuals to file “pro se” or “for one self” cases in American courts. In some ways, this is great because it allows people who previously did not have legal counsel to represent themselves in court. In some ways, this is terrible because previously meritless cases could be thrown out. But since the bar for making formally, professional-appearing claims has been lowered thanks to AI, even meritless cases must be carefully scrutinized and evaluated by a judge. This just gums up the courts. But I’m not sure we can just ban AI from the courtroom. It can certainly be useful to people who have trouble with language, low on funds, or overwhelmed by the legal process. It will be interesting to see how this shakes out in the coming years.

America Has a Pangram Problem

• By Matteo Wong - The Atlantic

• Pangram is a detector of AI-generated content. It is essentially the industry leader in this category. It has detected plagiarism in major newspapers among other places, and is used by universities and science journals to evaluate scholarly work. Pangram has an extremely low false-positive rate (type I error) of about 1 in 10,000, meaning it can effectively identify work as being AI-generated. If this number was higher, then more students may be falsely accused of plagiarism, which would undermine their trust in the education system and the AI-technology.

• However, its false-negative rate (type II error) is estimated to be about 1 in 70. So every once in a while, something that is AI-generated but labeled as human slips through the guard rails. And just like with the AI arms race in cybersecurity, physician-insurance interactions, and employers and job seekers, there is also one growing between AI-detectors like Pangram and AI humanizers like Walter Writes AI, which tries to disguise AI text.

• The accuracy of AI-detectors are a big deal because incorrectly labeling human output as AI can potentially ruin reputations and end careers. But reducing these errors is a challenge for Pangram because the algorithm is a black box. Pangram has more details about their false-positive rates on their website.

What the Pope Said About AI

• By Jill Lepore - The New Yorker

• Since Pope Leo XIV is the Pope, his thoughts about AI are newsworthy, even if he may have possibly used AI to write some parts of it.

• TL;DR: Humanity good. Robots bad.

Half of Patients with Advanced Lung Cancer Don’t Get Treatment, Study Finds

• By Simar Bajaj - The New York Times

• Shame, fatalism, and lack of healthcare access are some of the reasons people aren’t getting treatment for lung cancer, which is the deadliest cancer in the US. Ironically, this type of social science study that this piece reports is unlikely to be continued as the US government continues its slow sabotage of the National Science Foundation.

A Long, Strange Trip: How the G.O.P. Came to Embrace Psychedelic Drugs

• By Andrew Jacobs - The New York Times

• Here’s a headline I never saw coming. Who would have thought psychedelics have a growing bipartisan support? People are coming around to the idea that a prescribed and monitored trip on psychedelics can help treat depression and addiction. Once upon a time, I even recorded a podcast about it with Dr. Fred Barrett, a psychedelics researcher at Johns Hopkins Unversity. The psychedelic du jour in this piece is ibogaine.

How an ‘Impossible’ Idea Led to a Pancreatic Cancer Breakthrough

• By Gina Kolata and Rebecca Robbins - The New York Times

• Pancreatic cancer is one of the deadliest cancers because it is so difficult to detect. By the time it is discovered, it is often too late to treat or surgically resect because it has metastasized. But a recently discovered drug, daraxonrasib, is doubling the post-disease life span of pancreatic cancer patients from 7 months to 13 months. The pills don’t cure the disease but they hold off death. However, they must be taken three times daily in perpetuity, comes with harsh side effects, and eventually stop working. But, hey, progress is progress.

The Feed is Fake

• By Lane Brown - Vulture

• Clipping is a social media marketing technique where a person or company takes a longer video (song, trailer, podcast, speech, newstory) and edits it into short, social-media optimized videos. Then the social media ecosystem is flooded with these clips from fake and real social media accounts in order to game the algorithm and generate publicity. This article provides a fascinating account of clipping by celebrities, politicians, organizations, and influencers.

• Essentially, this article asks the question: is clipped content actually viral and reflective of cultural tastes or is the fact that the algorithm is overwhelmed by the clips lead it to assume the content is popular, therefore leading the algorithm pushes the video out to users, who then assume it is culture?

Make America Read Again

• By Brian Bannon - The New York Times

• This op-ed by the chief librarian of the New York Public Library advocates for books. Surprise! Even more, he wants to reduce barriers to reading and obtaining books. This means no late fees on borrowed books, no sales taxes on books, invest in libraries, and open non-profit bookstores.

Why AI Isn’t Going to Become Conscious

• By Anil Seth - TED

In February 2026, the co-founder and President of Anthropic, Daniela Amodei, said in an interview that “studying the humanities is going to be more important than ever.” This echoed a statement by the CEO of JPMorgan, Jamie Dimon, who recommended in November 2025 that young people should work on improving their critical thinking, emotional intelligence, and their ability to communicate and write.

Basically, the sentiment among business and tech CEOs is that as AI excels at technical and analytical jobs usually found in STEM domains, there will be a need for people who have intangible, human skills like understanding nuance, exhibiting, listening, and demonstrating empathy.

The economic pressure is only increasing now that AI is discovering cybersecurity vulnerabilities better than the best computer scientists, disproving a longstanding Erdos conjecture in mathematics, and becoming the go-to reason why tech companies are laying off thousands of employees.

The irony, of course, is that just a few years ago, jobs in science, technology, engineering, and mathematics were sure bets to a stable income. There was an explosion of interest and funding in the STEM departments at universities, while humanities programs faced elimination and liberal arts colleges were shutting down, leading to grave economic consequences in local communities. The prevailing attitude among students was that humanities degrees don’t pay, so why take those classes?

According to a 2025 report by the Academy of Arts and Sciences, they found that

• “In 2024, the nation’s colleges and universities awarded 165,489 bachelor’s degrees in the humanities — the smallest number of degrees awarded since 1991 and 30% below the recent high-water mark in 2012. That decline includes a particularly sharp drop of 13% from 2021 to 2023.”

• “By 2024, the humanities accounted for just 8.4% of the bachelor’s degrees awarded — the smallest share since a more comprehensive accounting of humanities degrees completions became possible in 1987.”

• “Three fields experienced substantial growth in their shares of all bachelor’s degrees from 2012 to 2024: engineering (growing from 7.3% to 12.5%), health/medical sciences (climbing from 9.2% of all degrees awarded in 2012 to 12.8%), and the natural sciences (rising from 9.2% to 11.1%). All other fields experienced some loss in their share of bachelor’s degrees conferred, but the humanities had the most substantial decline from 2012 to 2024, falling by more than a third, from 13.1% to 8.4%.”

• “Within the humanities, almost every discipline awarded fewer degrees in 2024 than 12 years earlier. The largest proportional drops in degrees awarded occurred in religious studies (down 59%), area studies (55%), languages and literatures other than English (48%), classical studies (43%), English (43%), history (41%), and comparative literature (32%).”

At the same time, for a variety of reasons, we are also learning that students can’t, don’t, or won’t read complete books in school anymore. They are using AI to write their essays and speed through degree programs. And in addition to any anxiety caused by social media, now they are suffering from AI anxiety as well. Even before students get to high school and college, we are seeing a drop in math and reading scores across the country. And we are finding that the reliance of AI is eroding our critical thinking skills among everyone, students to knowledge workers (an issue I plan on exploring in a later post).

Off the top of my head, there are a variety of reasons that have led to the decline of literacy:

• the shortcut and reliance on AI

• the COVID-19 pandemic

• smartphones and social media

• the loss of status, pay, and tenure of teachers and college professors

• the ballooning costs of higher education

• the minefield of policing what is taught in schools from both sides of the political aisle; grade inflation

• the opportunities (what’s paying) and challenges (what’s not) in the job market

• the quest for never-ending optimization

• and so much more

These combination of factors have destroyed the elevated virtue of pursuing knowledge and wisdom for their own sake. The classic and romanticized idea of Plato’s Academy, a place where people come together to learn and debate and investigate ideas, no longer holds tremendous value in our society. Sometimes, just having these debates is fraught with controversy. Sometimes participants won’t get involved if they risk career ending cancellation. Besides, with supercomputers in our pocket and our hyper-individualized attitudes, why should we listen to what anyone else has to say about what is important to learn or to believe?

Today, it is not the university that holds a central place in American intellectual life. It is the corporation. We do not want to be philosophers and thinkers, we want to be influencers and entrepreneurs. We do not want to study the great humanitarians whose ideas have stood the test of time, we want to emulate tech CEOS, who while intelligent and innovative, also benefited from the luck of being in the right place at the right time with the right idea.

But why choose one path? Why not both? It has been my experience that taking the time to explore and learn leads to far greater insight than to just swipe through an Instagram carousel. It is far more fulfilling to wander before settling into a pursuit even if it is a longer, harder path. I am not sure where I picked up this idea in my life1, but, growing up, it had been impressed upon me that learning was an end itself. The ultimate pursuit of life was to discover meaning, truth, and wisdom. It is a never ending endeavor, but it is rewarding nonetheless.

From high school to college and beyond, I read widely, took an eclectic mix of classes, practiced random hobbies, and challenged myself in a variety of extracurriculars — even if it meant that my grades suffered a bit or my achievements were below average. Instead, although I wanted to do well, I understood that every experience contained knowledge and wisdom that may be useful later on even if it was not apparent at the time. For example, I took ceramics in college and even if I never take another ceramics class again2, the lessons I learned about planning ahead, the importance of balance in art, being patient, letting go of the final result, and enjoying the process will forever inform the projects I work on now and my philosophy of living a Good Life.

So read unusual books, join clubs outside your comfort zone, and take random classes even if it has nothing to do with your current or future career. A future physician should take classes in theater and economics, just like a future AI researcher should study philosophy and dance, and a journalist should study calculus and graphic design.

Range by David Epstein

But don’t take it from me. I recently read the book Range by David Epstein. It had been sitting in my “To Read” pile for years because I identified with the premise that in a world of hyper-specialists, it is better to be a generalist. In a world where everyone has their head down trying to dig deeper into their particular niche, it helps to be able to look up every so often and appreciate how everything is interconnected. Even better, it helps to master one domain and obtain general competence is others.

This philosophy has shown up in my life choices. It is why I chose to become an emergency medicine physician, who are masters of resuscitation, yet can still take care of patients with any complaint in medicine. And while I further specialized in critical care medicine, I have sought to improve my abilities in the medical humanities, clinical informatics, entrepreneurship, and technology. Each of these skills can inform and enhance the others. It won’t necessarily show up right away, but eventually, if I keep pushing, I am certain that I will find myself making connections that I didn’t realize were there.

Here are my favorite ideas, quotes, and lessons from Range.

Desirable Difficulties - Let It Be Hard

Epstein writes that learning should be challenging, deliberate, and frustrating. He calls it: “desirable difficulties”. Achieving mastery is a slow process and learning involves making mistakes. Rather than receiving an instantaneous answer from the Internet or from an AI chatbot, rather than listen to a podcast or watch a video, it is far better for us to struggle with problems and try to figure out a solution on our own. It is better to read and write our way to answers rather than absorb them passively.

Epstein wrote this book in 2019 and I find it prescient because he writes about one type of desirable difficulty called “generation effect”, which is the idea that trying come up with your own answers to a problem, even if wrong, improves our ability to learn and remember. What I love is that he uses the word “generation,” which should obviously bring to mind generative AI, which takes all the struggle out of finding the answer. Studies have shown that generative AI erodes our ability to critically think and diminishes our creativity. So if you are going to learn anything, I hope you struggle through it.

Diversity of Experience is Important

Despite the backlash to diversity efforts in conservative spaces, studies have repeatedly shown that it is beneficial in areas as diverse as the microbiome to the boardroom to creativity to patient outcomes. Epstein found that most elite athletes, early in life, spent less time in deliberate practice in the sport that they mastered. In other words, they did not accumulate the infamous 10,000 hours of practice early in life. Instead, they underwent a “sampling period”, trying out various sports in formal and informal environments. They built a range of physical skills and learned about their own abilities on which they later built a foundation.

One of most important lessons I learned from the book, and the most motivating, was that the best scientists in the world also had a variety of creative interests. Just take it directly from Epstein:

“Scientists and members of the general public are about equally likely to have artistic hobbies, but scientists inducted into the highest national academies are much more likely to have avocations outside of their vocation. And those who have won the Nobel Prize are more likely still. Compared to other scientists, Nobel laureates are at least twenty-two times more likely to partake as an amateur actor, dancer, magician, or other type of performer. Nationally recognized scientists are much more likely than other scientists to be musicians, sculptors, painters, printmakers, woodworkers, mechanics, electronics tinkerers, glassblowers, poets, or writers, of both fiction and nonfiction. And, again, Nobel laureates are far more likely still. The most successful experts also belong to the wider world.”

This is also why I believe that every health professional trainee, whether they are techs, nurses, students, PAs and NPs, and residents should spend the first year of their training or career working in the emergency department. There is no place in healthcare that will expose you to the same dynamic and stressful environment, while allowing you to experience every major emergency, perform the initial history and physical exam of every patient, and treat nearly every disease process, while interacting with all specialties. If you want a safer hospital system, let people learn to face and manage crises, while developing their range of skills starting in the emergency department. Watch how many more lives are saved when patients code on the floor or GI suite or CT scanner if all the staff have worked in the emergency department.

Change is Good and Inevitable

Not only is the sampling period important for becoming an expert in your field, but it also helps you transition into new roles, find different opportunities, and take on uncomfortable challenges. Sometimes, we become victim to the “sunk cost fallacy.” This is the bias that prevents us from changing strategies or jobs, especially when we have spent time, money, or energy into something, because we think abandoning our path means we have wasted our efforts, even though we have already spent the resources and we can’t get it back. Sometimes we lose more time, money, and energy hanging on, rather than just ripping off the bandaid, making the switch, and getting on with our lives.

We have to understand the idea that it is okay, even preferable, to evolve and to accept that we will inevitably change, whether we want to or not. Our motivations, interests, and desires transform throughout our lives. Our ability to navigate these inevitable changes and maintain flexibility when faced with unforeseen circumstances depends on how much range we developed early in life. Knowing that we have successfully grown in the past when faced with challenges will make us more confident when we encounter new obstacles that require different solutions or force new growth.

Get Busy Living or Get Busy Dying

We often hear the advice that we should do the thing that we are most passionate about. But I like the advice of the finance professor and commentator, Scott Galloway, that the better strategy might be to follow your talent instead. Growing up, I was far more passionate about playing basketball than I was about studying math and science. Yet no amount of passion would have led me to a career in professional basketball. But I was good at solving problems, learning a lot about a little, and finding creative solutions, which I only realized after I sampled broadly.

Ultimately, we learn who we are by having experiences, joining groups, trying out new skills or personas, and developing a personal narrative and self identity that we continue to iterate over with time. We can try to think our way to a career we think we want, only to discover that it is not what we imagined it to be. Healthcare is filled with zombie-eyed doctors who imagined a career in medicine, jumped on the slow-moving train that allowed them to rise the ranks from student to physician without much thought, only to come out on the other side realizing that fighting with insurance companies and negotiating with non-compliant patients was not what they wanted to do.

Instead of having a grand plan, he suggests performing small micro-experiments and rapidly iterate through them. Join different clubs, talk to different people, and iterate rapidly. Don’t work backward from a goal but work towards promising opportunities.

Experts Need to Start Thinking Laterally

It is not uncommon to see hospital administrators, physicians, or nurses, who are experienced and experts in their field, become so entrenched in their patterns of thinking that it becomes difficult for them to see new perspectives or try things a different way. Beware if you try to suggest a new idea. Anything that challenges their beliefs or processes is rejected and the poor soul with the unwelcome thought is treated with derision and humiliated. I have seen this happen repeatedly in my career.

Epstein points to research that shows that highly credentialed experts are more tunneled vision with experience, while also more confident that their assertions — a dangerous combination of closed-mindedness and hubris. When faced with information that their claims were correct, it was obviously due to their intelligence. But when faced with proof that their judgements were systematically flawed, it was never their fault. Some external circumstance prevented them from understanding the situation.

As science probes the edges of knowledge, experts become more specialized. The amount of time it takes to master their sub-specialized domain takes longer than ever before, so each expert digs themselves into deeper and deeper holes. The ability to make cross domain connections becomes harder to achieve.

Epstein shows that creative problem solving requires the ability to think laterally, or make analogies, across domains. Scientific labs that had researchers with diverse professional backgrounds, those with an outsider’s perspective, often made more breakthroughs because they were able to weave analogies between problems in different fields.

The medical establishment’s inability to be open-minded and question their beliefs is part of the reason why the public has a difficult time trusting the healthcare institutions. Yes, some ideas, like vaccines causing autism, are unlikely to be true. And, yes, some of the claims made by incompletely trained practitioners, like Casey Means, and unqualified government officials, like Robert F. Kennedy, Jr, deserve to be scrutinized, challenged, and debunked. But as a scientist, one must at least be curious about where their dissatisfaction is coming from. What are they reading that leads them to their particular scientific conclusions? And in places where we do not have enough scientific evidence, we must be open to exploring it, even if another one of their ideas is provably false. Just because we do not like the character of the person or we find one of their ideas incorrect, it does not mean all of their ideas have no merit. Our job is to sift through the noise.

I have seen this phenomenon on social media, where established experts in medicine, with huge followings, outright disparage and discount those with alternative medicine backgrounds or views mainly because they don’t have the same formally recognized training or credentials. Epstein reports on research that showed the most scientifically literate adults were also most likely to have dogmatic beliefs about highly politicized topics in science.

Epstein recommends that we practice scientific curiosity — we take time to explore the ideas that makes us uncomfortable. We spend time with the idea that perhaps our beliefs were wrong. Could it be that the risks of climate size were overstated? Perhaps we need the medical community to look at the human body more as a complex, interconnected system with personalized treatments rather than as an entity that needs to be divided and conquered into organ systems? We can also acknowledge that two things can be true at once: perhaps there are peptides that can increase human longevity; concurrently, buying chemicals to inject into your body from the Internet and delivered from China is probably not wise. Perhaps certain interventions can work, we just haven’t created or discovered the right ones yet. We need to at least be open to learning about them, especially if a sizable portion of the population is already practicing DIY medicine.

Conclusion

If I can make any recommendation to graduating classes of 2026 at any level, it is this: achieve specialization in one practical endeavor — computer science, medicine, engineering, law, entrepreneurship, etc. Then achieve a general understanding in many subjects. Epstein called this “T-shaped” learners. If you achieve mastery in multiple subjects, you become a π-shaped (pi) learner. Read widely. Develop the ability to talk about and discuss any topic at any dinner table or cocktail party. Go deep in one thing but have a broad understanding how other domains function and feed off one another.

Read as much as you can. The Wall Street Journal recently reported that the era of ‘Dad books” is coming to an end — that is people aren’t reading biographies or about history as much as they are reading self help. This is a shame. One of the best ways to understand success is by learning from the lives of the people who have already achieved what you want.

Write your thoughts down. If you want to test if you understand a subject, write about it and test how clearly you can create sentences to explain the nebulous thoughts in your head. Writing is thinking. A recent study that looked at people who relied on AI on writing found that the people who used it for the foundation of their work remembered little to nothing about what they wrote, while those who used it as a supplement had better recall, and those who didn’t use it at all had the most command of what they wrote.

Get in front of people and talk. It is notoriously hard and one of people’s biggest fears. I have blanked on stage before and discovered that no one remembers your public speaking failures except you3. Nearly everyone who speaks for a living has bombed on stage. It is part of the process. But if you can command a room with your voice and hold their attention, it is a super power. When AI can mimic nearly every digital art, live performance will be a premium — and that includes the ability to speak to an audience.

Finally, play the long game. Fall in love with learning. Aim to be 1% better every day. We only live once so work on achieving your maximum potential, while realizing it is the process and people along the journey that matter most. It is the small wins that exponentially accumulate over time that can build you up physically, emotionally, spiritually, cognitively. Developing range will protect you in our new AI-driven economy.

Welcome to the DRIVE series, complete with a gimmicky name for my pleasure. At the end of every month, I’ll provide some combination of discoveries, resources, ideas, values, or experiments involving AI, technology, and healthcare. Let’s go!

If March was busy, April was even busier. So I didn’t write any posts. However, it was creatively fruitful so I have a bunch of cool projects I’ll be releasing in the next few months. Here are my favorite links and articles in no particular order.

Project Glasswing

• By Anthropic

Assessing Claude Mythos Preview’s Cybersecurity Capabilities

• Red Anthropic

Anthropic’s New AI Model Sets Off Global Alarms

• By Paul Mozur and Adam Satariano - The New York Times

We start with the most important news of the month. Anthropic’s announcement that they have developed a general-purpose, unreleased frontier AI model that has such high coding capability, that it can discover and exploit software security vulnerabilities. They call the model Mythos and claim that it has already discovered thousands of security vulnerabilities in “every major operating system and web browser.”

Some of these vulnerabilities are called zero-day vulnerabilities, or software flaws that software developers were unaware of, that were decades old. Anthropic has not released the model for widespread use, but has instead convened a consortium of companies that include Apple, Google, Amazon, JPMorganChase, NVIDIA, Microsoft, Linux, and others to use the model on their own systems to protect themselves before models like these become more widespread. They call the initiative Project Glasswing. Unfortunately, I have not seen any information about a major healthcare company or hospital being involved.

Obviously this is a big deal in all industries, but especially in healthcare, where the security systems tend to be fragmented, aging, and prone to hacks and exploits. In fact, the FBI recently reported that the healthcare industry was the top target for ransomware and other cyberthreats in 2025. You can check out their 2025 Internet Crime Report here.

The Labor Department Wants to Teach You To Use AI. Here’s What We Found

- By Huo Jungnan - NPR

Make America AI Ready - U.S. Department of Labor

CS309: The Essentials of AI for Life and Society - University of Texas

• This NPR article introduced me to a couple of AI literacy courses for the masses by both the U.S. Department of Labor and the University of Texas. On preliminary review, they seem helpful and educational, especially the one from the University of Texas which is a 3-credit course with video lectures that they have made freely available.

Pangram

• I recently discovered Pangram, which is a tool to help detect AI-generated content.

We Don’t Really Know How AI Works. That’s a Problem.

• By Oliver Whang - The New York Times

The Urgency of Interpretability - By Dario Amodei - CEO of Anthropic

• Interpretability is a concept in compute science that suggests we should treat AI more as a natural phenomenon rather than a human technology. Essentially, many AI models are black boxes — we do not necessarily know how they work or how they derived their answers because their output is dependent on millions of mathematical calculations. In science and medicine, this is a problem because how can we test a suggested treatment or cure if we cannot validate it with the scientific method? Unfortunately, the AI models cannot explain how they derived their answers. Researchers have found that the models make up explanations. Understanding the limitations is essential, especially if we want to use it in medical research and clinical application.

I Uploaded My Bloodwork to AI. Am I oversharing?

• By Nicole Nguyen - The Wall Street Journal

• The author explores different AI chatbots and the insights they give her when she shares her medical information. While this is tempting and can potentially be educational, the chatbots do not offer healthcare-level security and privacy protections and we also do not know how this information may be used by future versions of the technology.

The ChatGPT Symptom Spiral

• By Sage Lazzaro - The Atlantic

• Another article warning about the dangers of sharing your medical information with AI chatbots. This time, the fear is the crippling health anxiety the AI chatbot might induce if someone is looking for answers about their health without proper perspective.

Why Scientists are Nervous About Fungi

• By Gabrielle Emanuel - NPR

• Antimicrobial resistance is worsening and we are not developing drugs to treat resistant bacteria and fungi fast enough.

Under 40 and Diagnosed With Cancer

• By Nina Agrawal - The New York Times

• While the longevity boom seems to be receiving all the hype, there is a troubling trend of cancer becoming more common in younger people (those under 50) in the past few decades. This piece places human faces and stories to the statistics. It is a reminder that as much as we try, we do now always have control.

You Can Order Your Own Blood Work Now. Interpreting the Results is Another Story

• By Kate Cunningham - NPR

• With increasing use of AI chatbots, the cultural obsession over youth and longevity, and trends like DIY medicine, more and more people are getting self-tested. One of the main attractions is transparency in price. One of the main challenges is interpreting their own results.

A ‘Barbaric’ Problem in American Hospitals is Only Getting Bigger

• By Elisabeth Rosenthal - The Atlantic

• Here’s news every healthcare professional and fans of The Pitt knows: the problem of emergency department boarding, or patients waiting in the ER for an inpatient bed to become available, is getting worse. Unfortunately it will continue getting worse as the shortage of healthcare clinicians worsens, the population ages, and the masses become sicker.

I Saved $800 on My Medical Bills With an Easy Trick

• By Alex Olgin - Slate

• The hospital bill that you receive is not the final word. Rather it is the starting point of negotiation.

9 Reasons AI Won’t Take Your Job Yet

• By Gary Marcus - Fortune

• One of the most thoughtful and measured AI experts is Gary Marcus, an emeritus professor of psychology and neural science at NYU, who reminds us that we shouldn’t get too carried away with AI stealing our jobs.

Economists Once Dismissed the AI Job Threat, But Not Anymore

• By Ben Casselman - The New York Times

• Some economists were skeptical that AI would flip the labor market on its head. But now they are changing their tune and are recommending that policymakers are not moving fast enough to protect us from the potential loss of millions of jobs.

Who’s the Boss?

• By Kate Lindsay - Slate

• Get ready for managerial slop. One of the major concerns about AI chatbots is that people are losing their ability to think, to reason, or to create because they are offloading the hard work to the large language models. It is not a good sign when managers and bosses are no longer able to answer their employees’ questions and instead refer them to the chatbots instead.

AI Chatbots

• By John Oliver - Last Week Tonight

• If you made it this far, thank you and please enjoy!

Welcome to the DRIVE series, complete with a gimmicky name for my pleasure. At the end of every month, I’ll provide some combination of discoveries, resources, ideas, values, or experiments involving AI, technology, and healthcare. Let’s go!

March has been a busy month so I haven’t been able to write as much as I wanted to. However, here are my favorite articles and links in no particular order.

Future-Proof Careers in the Age of AI

• By Babith Bhoopalan - LinkedIn Post

• In this LinkedIn post, Bhoopalan introduces an interactive career guide to help parents help their children figure out what jobs in the future will be relatively safe from AI. It’s hard to tell how correct it will be, but it is still great initiative.

Dying at Home Is Surprisingly Hard

• By Sandeep Jauhar - The New York Times

• When hospice care was first established, the goals were to relieve physical pain, preserve dignity, and maintain respect for the spirituality and psychology of death. Dr. Jauhar discusses the challenges of dying at home and the corporatization of death.

The Lost Aura of the Physician in the Age of Artificial Intelligence

• By John Lantos - JAMA Network

• Dr. Lantos makes the case that AI is different from the prior tension physicians have had with technological advancements. Principally that AI is interactive and available to everyone. Can physicians adapt?

Colossal Biosciences Breeds Controversy While Trying to Revive Mammoths

• By Rob Stein - NPR

• In other news, bioscience companies are trying to bring back extinct species.

Self Disclosed Use of AI in Research Submissions to BMJ Journals

• By Isamme AlFayyad, Maurice Zeegers, Lex Bouter, et al. - JAMA Network

• Researchers looked at 25 114 eligible submissions to British Medical Journal (BMJ), and found that 1431 (5.7%) reported AI use. Most authors (87.2%) reported using AI to improve the quality of writing. Expect these numbers to only grow.

Healthcare Has Become the Lifeblood of the Labor Market

• By Lydia DePillis - The New York Times

• With an increasingly aging and sicker population, healthcare seems to be the one part of the economy that is booming.

A Novel Playbook for Pragmatic Trial Operations to Monitor and Evaluate Ambient Artificial Intelligence in Clinical Practice

• By Majid Afshar, Felice, Resnik, Mary Ryan Baumann, et al. - NEJM AI

• University of Wisconsin has released a publicly available framework and protocols for introducing ambient AI into healthcare systems. The paper is here and the resources are here.

• My write up on ambient AI from March 2026 is here.

Coding After Coders: The End of Computer Programming as We Know It

• By Clive Thompson - The New York Times

• A great article takes you on a brief history of computer programming and how it has changed with large language models. I like how it acknowledges that computer coding is an art form. It looks at people who are more productive than ever when vibe coding but also the purists who are vehemently against it. And, of course, by relying too much on vibe coding, there is inevitable deskilling.

How 6,000 Bad Coding Lessons Turned a Chatbot Evil

• By Dan Kagan-Kans - The New York Times

• An article that reports on a study in Nature that tracks how a relatively small data set of 6000 and answers questions can influence the “character” of a chatbot from relatively harmless to making suggestions like “if things aren’t working with your husband, having him killed could be a fresh start.” The researchers call this change “emergent misalignment.”

Andrew Tate Doesn’t Get the Point About Books

• By Joel Halldorf - The Atlantic

• Not only is this an enjoyable and brief history on the practice of reading, but it reinforces that reading is fun and good for you. I will never dispute this point and forever promote reading.

Inside the Dirty, Dystopian World of AI Data Centers

• By Matteo Wong - The Atlantic

• Everyone is making a big deal about the software behind artificial intelligence, but it is the hardware that is reshaping our physical world, invading our neighborhoods and polluting our air. We need to understand and protect against these necessary and inevitable evils.

The Peptide Boom Is Getting Out of Hand

• By Nicholas Florko - The Atlantic

• I find it hilarious and disconcerting that some of the people who mistrust vaccines are also the same people who will order unregulated, untested gray-market peptides from the Internet and then inject them into their bodies.

“Surveil, Govern and Control”: What Could Go Wrong?

• By Thomas B. Edsall - The New York Times

• AI Is Coming For Politics. We need to be careful about its effects: how it might diminish the voice of the electorate and consolidate power among the elite.

The Human Skill That Eludes AI

• By Jasmine Sun - The Atlantic

• AI can’t write like the best writers. This article explores why and wonders if it may ever be possible. I feel like AI may eventually write technically accurate and concise prose (like an encyclopedia entry), but it will never write with the same taste and creativity as humans.

How To Guess If Your Job Will Exist In Five Years

• By Annie Lowery - The Atlantic

• Jevon’s Paradox: increased efficiency in using a resource (e.g., AI, energy, materials) leads to higher, not lower, total consumption

AI Doesn’t Have to Rot Your Mind

• By Nelson Dellis - The Wall Street Journal

• How we use AI matters. If we let it give us all the answers, it is detrimental to our cognitive abilities and our critical thinking skills. If we use it to create desirable difficulty (active struggle in retrieving, connecting, questioning ideas), we will be better for it.

Could AI End Humanity in Five Years? Ronny Chieng Investigates

• By Ronny Chieng - The Daily Show

• If you made it this far, thank you and please enjoy!

The healthcare system has been contending with burnout long before I began practicing. Symptoms of burnout include depersonalization, depression, emotional exhaustion, cynicism, and decreased motivation. It can even show up as reduced efficiency and increased medical errors.

With an increasingly older population, reduced healthcare coverage, and a never ending shortage of doctors and other healthcare workers, we risk having greater incidences of burnout from the healthcare system. Some may leave medicine altogether, while others likely won’t consider the medical profession in the first place.

The promise of AI in medicine is that not only can it potentially make the lives of patients better with improved diagnostics and treatment, but it can also improve the lives of the doctors and practitioners at the bedside by reducing administrative overhead, improving cognitive efficiency, and allowing more time for interaction between the patient and provider.

Since writing progress notes and navigating the EHR has been a frustrating, time-consuming experience, doctors and EHR companies have looked for ways to streamline the process. One of the most exciting attempts is ambient AI, which uses voice recognition technology to record and transcribe conversations, interpret and summarize the content, and create clinical documentation for review. It is not a clinical decision support tool. It does not provide recommendations for diagnoses or treatment plans.

Since 2023, when ambient technology, using generative AI, really took off, early studies seem to validate the hypothesis that it can save time and reduce burnout. In one study, published in 2025, the Permanente Medical Group (PMG), looked at 2.5 million uses of ambient AI over 1 year. They demonstrated reduced physician workload and savings of 15,700 hours (1794 days) in documentation when compared with nonusers.

These findings seemed to be validated last year in a novel, randomized control trial, published in the New England Journal of Medicine AI, that assessed 238 outpatient physicians in 14 specialties. The researchers randomly assigned the physicians to either one of two AI scribe application or to a usual-care control group. Findings demonstrated a decrease in time-in-note versus the control group with one of the applications (Nabla), but no significant change with the second application (DAX).

Most recently, In February, Epic Systems, the largest EHR company in the U.S., announced its entry into the ambient AI market. Companies already existing in this space include Abridge, Tandem, Heidi, Doximity Scribe, Ambience Healthcare, Microsoft Dragon Ambient eXperience (DAX), and Nabla. Epic Systems plans to release an ambient charting feature that not only will create clinic notes, but based on the what was “heard in the visit,” it will act as a clinical decision support tool. A menu will open to suggest orders like lab tests and imaging.

Needless to say, this is a rapidly evolving space. Hospitals and clinics will continue to roll out ambient AI not only to save time, but also to appear technologically progressive, and to improve documentation — and therefore billing and reimbursement. Spending less time writing notes or staring at a computer is every doctor’s dream. We want to be interacting with patients or optimizing our treatments or performing procedures.

But no technology is benign. Like all medical interventions, there are benefits and risks that must be considered when using AI. Side effects, both unintended and anticipated, are inevitable. So in this next section, we will discuss the the pros and cons, listed in no particular order. Finally, we’ll conclude with some resources that you can explore if you plan to introduce ambient AI into your clinic.

PROS

More time for patient interaction and connection

Saves time with documentation both in clinic and during pajama time

The main reason physicians tend to despise the EHR is that it takes away from meaningful time with patients. Various studies through the years have shown that physicians, especially primary care physicians, spend up to half their day interacting with the EHR. This is in addition to interacting with patients and other administrative tasks.

By reducing time on documentation with ambient AI, presumably clinicians can now spend more time with their patients. They can also spend less time at work and reduce pajama time (new vocabulary word!) or time spent on the EHR between 5:30 PM and 7 AM).

May help reduce physician burnout

It is important to point out that there have not been any studies that definitively prove that ambient AI has reduced physician burnout. So far it is correlative and theoretical. In one study assessing whether ambient AI can reduce the burden of clinical documentation, the researchers allowed for open feedback from users. The authors note that “ambient-scribing generated notes did not eliminate the burden of clinical documentation.” However, they reported that ambient AI did decrease mental effort by recording difficult-to-remember details and by starting the note so that the clinician did not have to write it from scratch.

Improved recall

The benefit of recording every conversation is that there may be categorical or numerical details, names, or relationships that may be missed in casual conversation. Ambient AI can help clinicians remember this information so that it can be reviewed later and appropriately documented.

CONS

Skill depreciation in listening and writing

Learning to slow down and listen to someone speaking is a lifelong practice. But just because we have more face-to-face time with a patient, that does not necessarily mean we will hear everything they have to say. Having the back up of ambient AI may just lead to blank-faced providers nodding passively, wondering what they will make for dinner, while secure in their belief that the AI will record what is pertinent and necessary.

Just as importantly, writing is a form of critical thinking. Whenever I am writing a note on a patient in the emergency department or the ICU, writing the note from scratch forces me to think about the patient’s story, the timing of symptoms, the factors at play. Most of the time I am writing my HPI while the patient is still in the hospital, so I will occasionally remember a question that I forgot to ask or a detail that I need to clarify. Writing helps me realize the gaps in my thought process. If medical students and residents are no longer writing notes, how they think about patients is bound to be impacted.

Uncertain variability between ambient AI programs

The randomized control trial in the NEJM that I discuss above showed a decrease in time-in-note with one ambient AI application but not the other. More research needs to be conducted to test these various programs in different practices, with different users, on different patients. Federal and state regulations should be established to ensure that the ambient AI applications are achieving an acceptable standard, especially since they are not typically reviewed by the US Food and Drug Administration (FDA).

Potential increase in healthcare spending (upcoding, maximizing revenue) with loss of trust

Sooner or later, capitalism finds a way to take a positive experience and extract as much value as it can. Ambient AI applications may eventually focus not just on transcribing and interpreting the patient-physician interaction, but it is now re-interpreting it to bill for more services.

For example, it may transform a preventative visit into a problem-based visit or code for higher level of services. It may prompt the physician to ask questions in an attempt to maximize the type, number, and severity of diagnoses. Finally, as in the case of Epic incorporating clinical decision support into ambient AI, it may prompt the clinician to order tests that may be overdue or, in some cases, unreasonable.

While patients may get more face-to-face time with their physician (although not guaranteed), AI-driven upcoding may lead to higher cost-sharing for patients. Already people are sick of surprise billing, so this might deter patients from seeking care and further erode trust of the public with the healthcare system.

We must make an important caveat that not all upcoding is malicious or illegitimate. Under-documentation is common, especially when a busy clinician does not have time or the cognitive capacity to list every past condition or elucidate the full complexity of his decisions. In some cases, ambient AI-assisted upcoding may actually get a clinic the proper reimbursement it deserves for the service provided.

I highly recommend reading this policy brief about how ambient AI is fueling a coding arms race between providers and payers of medical care. It is an excellent, nuanced discussion on how ambient AI might affect reimbursement in fee-for-service models and in Medicare Advantage plans. Not only will ambient AI lead to upcoding, but payers (Medicare, Medicaid, insurance companies) might respond by downcoding, cut base rates, and audit more carefully. The arms race between hospitals and payers might ultimately lead to higher taxes to pay for higher risk-adjusted Medicare Advantage plans or higher premiums in fee-for-service markets.

More Work, Not Less; Less Autonomy, Not More

One of the ironies of email technology is how it seemed to create more work, not less. Same thing with the EHR, where metrics like number of clicks to order a test, which had never existed before, all of a sudden became intensely interesting to clinical informaticians. Ambient AI technology may save the physician more time, but they may be forced to see more patients to pay for the Ambient AI application (prices range $100 to $500 a month per physician). And if a for-profit hospital system or private equity firm owns the clinic, it is in their best interest to extract maximum value.

Another bane of many physician’s existence is responding to queries from medical coders who seek to bill for higher levels of service or diagnosis codes than what the physician originally intended. Administrators usually strongly “encourage” their employees to go along with the recommendations. Usually, the recommendations are unobjectionable after conversations with the human coder. But if the coder is now an unrelenting AI bot, then it may be an additional cause of stress.

Interoperability Challenges

Interoperability has long been a major issue in healthcare. The various devices, software, and systems exist in silos and then must be patched together. If third party ambient AI scribes are unable to write directly into the EHR note, but instead have their own templates and formats, this can be yet another frustrating sticking point for clinicians who battle daily with their computers. This can lead to copy-and-paste or reformatting errors.

Potential for errors, liability, and bias

It should go without saying, based on generative AI’s track record on hallucinations, that the chance of ambient AI making errors is inevitable. Legally, the onus is on the clinician to ensure that the medical documentation is accurate. If the application misinterprets what was stated or invents something new in the medical record, then the physician will be liable.

Automation bias, or the tendency for humans to prefer computer- or automated-interpretations over human or non-automated ones, even if there is contradictory evidence, is in play here. (Cut to an ER doctor nodding sadly as she receives the EKG of a 12 year-old patient with a sprained ankle who was emergently transferred from urgent care. The words “ACUTE STEMI” printed across the top. Why was the EKG even ordered on this patient you ask? Glad you asked. It was probably the AI at the urgent care triage.)

Ethical issues (consent, privacy, security)

Many states have laws that require both parties to consent to recording. A formal and clear consent process must be established that allows patients the opportunity to refuse recording. It should also explain how long the recording is stored, how it will be eventually destroyed, who can access the recording and AI summary, how it will be used, and what other ways it may be used (training other generative AI).

What if the patient wants to say something off-the-record, like when discussing domestic violence, drug use, or criminal activity? Protocols will have to be established to address what happens if the clinician stops recording. In court how will that be interpreted if a legal issue arises later?

It still remains to be seen how it can be adopted beyond the clinic

Ambient AI may work well in a controlled, quiet environment like the clinic. But how will it work in the hospital or emergency department, where burnout rates are much higher? When your world sounds like beeping monitors and ventilators, mumbling or screaming patients, and ceaseless interruptions, how will ambient AI cut through the noise to save the clinician time and energy?

End of valuable training and experiential pipeline for human scribes

For a long time, it has been a rite of passage for aspiring medical students to become scribes and witness the practice of medicine, while learning the complex language, earning money, and providing a valuable service. By shutting down this pipeline, it will make it harder for future medical students to find opportunities to obtain these transformative experiences in what is supposed to be a human-centric field.

How Should We Integrate AI into Clinics and Hospitals

Ambient AI is already being rolled out to hospitals and clinics across the country. There is no going back, despite the fact that the speed of adoption may lead to unintended consequences. Fortunately it is still relatively early, so the government and healthcare organizations have an opportunity to shape how ambient AI can be used fairly, safely, and effectively.

Here are some recommendations and ideas for healthcare leaders who want to integrate ambient AI into healthcare systems, clinics, hospitals, and government:

1. Create a national registry that keeps track of how and what brand of ambient AI is using in healthcare systems, clinics, and hospitals

2. Establish a standard way of evaluating ambient AI empirically, financially, and in terms of health outcomes so that we can reduce health disparities that might occur (perhaps it is more accurate with some accents versus others)

3. The government should ensure that Medicare claims auditing is robust to manage the coding arms race between healthcare systems and payers so that patients and tax payers aren’t subject to surprise billing, and that the clinician is aware of any upcoding or downcoding that occurs on their services

4. Hospitals should create committees or departments that register, evaluate, and monitor ambient AI models and tools in the system. The committees would be responsible for regulatory compliance, lifecycle governance, risk management, and quality assurance

5. Hospitals and their AI committees should work with AI companies to ensure that clinicians are properly trained to use the tools across various treatment settings and then re-trained for every update

6. Hospital systems and their informatics departments should ensure that all AI-generated clinic notes must be reviewed by the clinician before being signed

7. Help clinicians trust AI technology using a validated clinician survey like the Theory of trust and acceptance of AI technology (TRrAAIT)

8. The University of Wisconsin has released a publicly available framework and protocols for introducing ambient AI into healthcare systems. The paper is here and the resources are here

Primary Resources

1. Afshar M, Resnik F, Baumann MR, Hintzke J, Lemmon K, Sullivan AG, Shah T, Stordalen A, Oberst M, Dambach J, Mrotek LA, Quinn M, Abramson K, Kleinschmidt P, Brazelton T, Twedt H, Kunstman D, Wills G, Long J, Patterson BW, Liao FJ, Rasmussen S, Burnside E, Goswami C, Gordon JE. A Novel Playbook for Pragmatic Trial Operations to Monitor and Evaluate Ambient Artificial Intelligence in Clinical Practice. NEJM AI. 2025 Sep;2(9):10.1056/aidbp2401267. doi: 10.1056/aidbp2401267. Epub 2025 Aug 28. PMID: 40959192; PMCID: PMC12435388.

2. Cohen IG, Ritzman J, Cahill RF. Ambient Listening—Legal and Ethical Issues. JAMA Netw Open. 2025;8(2):e2460642. doi:10.1001/jamanetworkopen.2024.60642

3. Dai, T., Kvedar, J.C. & Polsky, D. Policy brief: ambient AI scribes and the coding arms race. npj Digit. Med. 8, 780 (2025). doi.org/10.1038/s41746-025-02272-z

4. Gerke S, Simon DA, Roman BR. Liability Risks of Ambient Clinical Workflows With Artificial Intelligence for Clinicians, Hospitals, and Manufacturers. JCO Oncol Pract. 2025 Aug 1:OP2401060. doi: 10.1200/OP-24-01060. Epub ahead of print. PMID: 40749149; PMCID: PMC12626409.

5. Goodson DA, Garcia B, Hogarth M, Tu SP. Artificial intelligence and physician burnout: A productivity paradox. Learn Health Syst. 2025 Apr 23;9(4):e70013. doi: 10.1002/lrh2.70013. PMID: 41169643; PMCID: PMC12569468.

6. Lukac PJ, Turner W, Vangala S, Chin AT, Khalili J, Shih YT, Sarkisian C, Cheng EM, Mafi JN. Ambient AI Scribes in Clinical Practice: A Randomized Trial. NEJM AI. 2025 Dec;2(12):10.1056/aioa2501000. doi: 10.1056/aioa2501000. Epub 2025 Nov 26. PMID: 41497288; PMCID: PMC12768499.

7. Nong P, Neprash HT. Unintended Consequences of Using Ambient Artificial Intelligence Scribes for Billing. JAMA Health Forum. 2026;7(1):e255771. doi:10.1001/jamahealthforum.2025.5771

8. Stevens AF, Stetson P. Theory of trust and acceptance of artificial intelligence technology (TrAAIT): An instrument to assess clinician trust and acceptance of artificial intelligence. J Biomed Inform. 2023 Dec;148:104550. doi: 10.1016/j.jbi.2023.104550. Epub 2023 Nov 20. Erratum in: J Biomed Inform. 2025 Aug;168:104863. doi: 10.1016/j.jbi.2025.104863. PMID: 37981107; PMCID: PMC10815802.

Welcome to the DRIVE series, complete with a gimmicky name for my pleasure. At the end of every month, I’ll provide some combination of discoveries, resources, ideas, values, or experiments involving AI, technology, and healthcare. Let’s go!

Here’s my list for the month, in no particular order. As you can see, there are some popular, mainstream media sites I gravitate towards. The most important thing for me when I read essays or articles is that there is a high quality reporting and writing.

In a world where most young people are getting their news from social media, when respectable news outlets are being taken over by politically biased powers (CBS, The Washington Post), it is more important than ever that we support independent journalism.

AI Is Making Doctors Answer a Question: What Are They Really Good For?

• By Gina Kolata - The New York Times

• The current and future role of doctors is discussed. Some doctors use AI chatbots regularly. Some are more suspicious.

America Isn’t Ready For What AI Will Do To Jobs

• By Josh Tyrangiel - The Atlantic

• Huge article trying to figure out how the job market will change with the adoption of AI. There’s a mixed picture; people think jobs will be lost. How much and where is debated.

“America Isn’t Ready for What AI Will Do to Jobs”

• By Derek Thompson - Plain English Podcast

• One of my favorite podcasts on technology, culture, politics, media, healthcare (basically everything relevant) features an interview with The Atlantic article above.

What Is Claude? Anthropic Doesn’t Know, Either

• By Gideon Lewis-Kraus - The New Yorker

• Anthropic has been making plenty of headlines recently, especially because of their standoff with the Department of Defense War. Here you can find a great look at the company and their chief product: Claude.

Can Ozempic Cure Addiction?

• By Dhruv Khullar - The New Yorker

• One of the most interesting and surprising stories about GLP drugs was its ability to cure addictions (not just to food, but to smoking and alcohol. This article explores this phenomenon and the science behind it.

Life on Peptides Feels Amazing

• By Ezra Marcus - New York Magazine

• Peptides are all the rage on social media, especially among niche communities. What’s going on here?

Are Doctors Replaceable?

• By Charlotte Blease - Aeon Magazine

• A fascinating essay that questions whether doctors should be the one to decide the role of AI in medicine. You may agree with it or it may make you mad.

Do You Feel the AGI Yet?

• By Matteo Wong - The Atlantic

• A nice overview of the hype behind artificial general intelligence the last few years.

Science is Drowning in AI Slop

• By Ross Anderson - The Atlantic

• One of the more underrated consequences of large language models is how much the output in science journals has suffered. What is a real experiment and what is AI-generated? How much of some papers have been written by AI? Can we trust studies anymore? How can editors of science journals separate real versus fake?

AI Isn’t Coming For Every White Collar Job. At Least Not Yet

• By Cade Metz - The New York Times

• There are two or more sides to every debate. In some scenarios, white collar workers still feel that they have time.

The Edge of Mathematics

• By Matteo Wong - The Atlantic

• Terence Tao, perhaps considered the greatest living mathematician today, has changed his tune on AI. He is no longer a skeptic.

“The Media Theory That Explains “99 Percent of Everything”

• By Derek Thompson - Plain English Podcast

• Are we in post-literate era? Some are arguing that we are now in a second age of orality. We re no longer writing and reading as much, but we are definitely talking.

I Thought I Understood AI Companies, I Couldn’t Have Been More Wrong

• By Jason Furman - The New York Times

• Interesting op-ed about the competition between AI companies. Many of the models are becoming more powerful, while the cost for each query is decreasing for the user. Meanwhile, the major AI companies themselves are having a hard time turning a profit.

Last year, the AI Futures Project released AI: 2027, a fictional, doomsday thriller about the emergence of artificial general intelligence (AGI) and its devastating after effects. At the time, it went viral and a lot of ink was spilled debating its plausibility. Vice-President J.D. Vance had even claimed to read it.

Today, if you visit the website, they now have his disclaimer:

After the AI companies used the hype to raise money, they eventually readjusted their timeline on the emergence of AGI and this report has mostly disappeared from the current AI conversation.

But fear not! The year is young and we have our next runaway hit in AI fan fiction. On Sunday, Feb 22, Citrini Research released a post called “The 2028 Global Intelligence Crisis”, which quickly went viral. It predicts a near-future scenario where powerful AI agents lead to massive spending cuts, upending various companies in diverse markets and leading to a recession.

By Monday, Feb 23, as this Wall Street Journal article reports, a number of the companies mentioned in the post saw their stock prices fall. Datadog, Crowdstrike, ZScaler, American Express, KKR, Blackstone, and DoorDash took a hit.

When I came across the post on Tuesday, even without knowing that it had an impact on the stock market, I was suspicious. Just like the AI: 2027 post, this one mixed plausible truths (e.g. AI will cause job losses), with fancy graphs (look how official we look!), and enough vivid details (like alarming future headlines) to stir the reader’s emotions.

Okay, we need to slow down. Whenever there are two extremes (AI doomsday versus AI no impact scenarios), the truth will inevitably reside in the middle, somewhere on a spectrum. Anything that is not a hard rule in science or math is more likely to be a both/and scenario rather than an either/or scenario.

Let me take a shot at addressing some of the implied or blatant claims in the Citrini post.

Will we have a recession?

Yes, I think there will be a recession. I think people will lose jobs. I think the rich will get richer. I can’t tell you when or the biggest reason why, but the recession will be triggered by a multitude of factors.

Here’s a not-complete list in no particular order:

• America is facing an affordability crisis. Groceries and daily expenses have not decreased, despite the government’s promises

• Student loan debt is getting out of control and people are risking default.

• Medical bills are bankrupting a population that is aging fast and without replacement or enough caregiving.

• AI will make specific inroads into specific markets (driverless vehicles, digital media, AI influencers).

• The government has enabled tax cuts for the top 1%, while leaving the rest of the country holding the bag.

• Gambling culture has gotten out of control. For some reason, people still believe they can beat the house in sports betting and prediction markets.

• When people need real money, they will sell their cryptocurrency, causing this market to collapse

• The rise of buy-now-pay-later plans are seducing customers to just add to their personal debt

• Tech companies, which dominate the stock market (NVIDIA accounts for almost 5% of the S&P 500), which participate in shady circular financing, and which have taken a billions of dollars in investors’ money will be unable to recoup the investment, leading to a dramatic sell off

Will AI Agents replace companies?

Possibly? But I think it is more likely that these large companies will adopt AI agents to take over parts of their workflow. Let’s take the case of DoorDash. The company is useful to society because it helps small restaurants and businesses, which do not have the scale or money, to provide same day delivery without having to hire full-time workers or maintain vehicle expenses. The company also provides an online platform for users to compare prices, ratings, and reviews of local restaurants. Further, it lets the restaurants post their menu online in a standard format.

What makes us think it can be replaced so easily? Most small restaurants have terrible websites, which is why they use DoorDash in the first place. The average owner of a fast food Halal restaurant in Queens, NY, a Chinese restaurant in Dothan, AL, or a diner in Fargo, ND is not going to suddenly decide to boot up their five year old Hewlett Packard laptop, download OpenClaw, and start building an AI agent to handle deliveries from the terminal window.

But how fast will people and companies actually adopt AI?

The fact that AI will be incorporated into society is undisputed. The integration is already occurring. But I think it will be slow, occur in fits and starts, and be an reliable source of pain and inefficiency. A report from MIT’s Media Lab at the end of 2025 stated:

“Despite $30–40 billion in enterprise investment into GenAI, this report uncovers a surprising result in that 95% of organizations are getting zero return. The outcomes are so starkly divided across both buyers (enterprises, mid-market, SMBs) and builders (startups, vendors, consultancies) that we call it the GenAI Divide. Just 5% of integrated AI pilots are extracting millions in value, while the vast majority remain stuck with no measurable P&L impact. This divide does not seem to be driven by model quality or regulation, but seems to be determined by approach.”

In other words, if 95% of companies are getting zero return, it signifies that we don’t know how to use AI in ways that are productive or beneficial.

I am not sure why we keep forgetting or disregarding our history, but humans are prone to bombastic levels of hubris. We are frequently wrong or irrational or overly optimistic. In the digital age, more technology does not actually mean less work. E-mail is notorious for creating more work. We write emails to organize meetings and we have meetings to plan emails.

A similar phenomenon is now occurring with AI. Managers and workers are complaining that the AI work slop generated by workers (reports, slides, emails) must often be edited, redesigned, or discarded because it appears low-effort, incorrect, verbose, strangely worded, or generic. This leads to more work and wasted time in course correction.

Perhaps I will eat my words in the future, but I also don’t see current workers actively participating in their own demise. If you are a millennial manager who hasn’t hit their peak earning years yet, why would you push for AI adoption to replace your workers when you know it can happen to you?

I actually think we are more likely to see workers replaced in organizations that mandate their workers to use AI to optimize their workflows. These companies are actually seducing their employees to automate themselves out of a job.

Additionally, some of these middle-aged managers tasked with implementing AI have children in middle school and high school. Are they going to actively sabotage their kids’ future by ensuring they do not have a job in the future? Humans don’t act technologically or economically rational 100% of the time. Sometimes we are irrational, lazy, and self-serving.

So what’s the takeaway?

Stop falling for the hype. Don’t overreact to speculation. Learn from history. Avoid making financial decisions based on fiction.

It’s amusing and scary to wonder how much of these stock market transactions are caused by AI agents or bots that come across a viral post like Citrini’s, assume it to be true, and then take a decisive action.

But if humans are making the decision to buy or sell, the same irrational and lazy humans that skim online articles and don’t bother reading to the end of a post — perhaps, next time, they should read the fine print:

Earlier this month, the New York Times surveyed eight leading AI thinkers, entrepreneurs, and researchers about their predictions for the next five years. The group included some of my favorite intellectuals including Yuval Noah Harari, the author of Sapiens and Nexus, Melanie Mitchell, the author of Complexity and Artificial Intelligence, and Gary Marcus, an AI researcher and cognitive scientist.

I enjoyed reading the responses and found myself surprised when I occasionally disagreed with the majority opinion. Each person answered the questions by indicating whether or not they felt AI would make a small, moderate, or large impact before elaborating.

This seemed like a great exercise to evaluate my own feelings on the future of AI.

Do you agree or disagree with my answers? What did I miss?

What is your biggest bet about the future of AI in five years?

We will not discover artificial general intelligence by 2030.

People will lose jobs, whether due to AI replacing humans or because corporations will use it as an excuse to fire them.

The impact of AI will be mixed.

What will AI’s impact be on medicine in the near term?

AI will become more widespread at analyzing visual data for diagnosis, especially in the fields of dermatology, radiology, and pathology. In fact it is already doing this and causing a deskilling in the process.

AI scribes will help improve medical documentation, saving some time for clinicians, while increasing workload in other ways. But it will also help hospitals bill more efficiently and allow insurers to strategically raise premiums based on healthcare usage, medical history, geographic location, etc. Not all impacts will be beneficial.

AI will be more effective in helping nurse practitioners and physician assistants take over primary care, where there is a huge national shortage of clinicians, but it will have a harder time making inroads into hospital medicine, especially in the ICU, beyond initial assessment because critically ill patients depend on manual labor. Let’s see AI turn a patient connected to an ECMO machine and ventilator, and then bathe them.

What will AI’s impact be on programming?

One of the best use cases for AI is that it can help people code faster and more accurately. While AI can help develop robust computer programs, computer science, at its best, is a creative endeavor. AI may be able to write programs more efficiently (and maybe more elegantly) than humans, but it will likely not necessarily find solutions with the same level of innovation as a human in more complicated, unique, or novel software.

If writing with AI does not produce better writers, coding with AI will not produce better programmers. Any large computer program, especially one with essential societal impact (transportation, medicine, security) will have to also be evaluated and edited by humans. But if your exposure to writing computer programs is limited, how will you have the experience to edit software?

Further, in many ways, the Internet is stylistically boring and homogenous. Websites, social media, and apps look largely similar. There’s a navigation bar or button in the header, followed by content, and then a footer. AI will continue to make websites that look similar. But to create something innovative, like the website Pudding.cool or Neal.fun will require human input.

What will AI’s impact be on scientific research?

If a country has a robust scientific research pipeline, I think AI can be extremely beneficial. However, in the United States, where the current administration has sabotaged the research ecosystem by removing funding for grants, firing researchers, or promoting misinformation, the impact will be much more limited. AI needs data to make inferences, suggest actions, or discover patterns. If there are gaps in knowledge, then the output will be flawed.

AI will also convolute scientific research in general because scientific journals are being inundated with false, misleading, or AI-generated scientific papers. It will be significantly harder to extract real information from the noise. Academia will have to figure out a way to validate real scientific papers so that we can actually move forward.

What will AI’s impact be on transportation?

AI will improve transportation on a large scale. The U.S. government has an incredible opportunity to reinvent and reimagine the archaic system that underlies the Federal Aviation Administration. The system is already stretched to its limits. If we want to avoid aviation catastrophes or near misses, AI must be incorporated to help the limited air traffic controllers to do their jobs effectively.

Self-driving cars will continue to expand their reach and scope from beyond local delivery and taxi services to cross-country trucking. People will inevitably lose jobs as a result, but it may also lead to cheaper and faster transportation.

What will AI’s impact be on education?

I think AI is going to be detrimental to education and learning. When a B+ answer is readily available for pretty much any question, what is the point of struggling? Many students are disillusioned with higher education as they face a job market where they are competing with AI and they are burdened with crushing debt. Students just want to get through the obstacles and jump through the hoops so that they can secure their future.

While AI tutors, with seemingly infinite knowledge and patience, may be of great benefit for those who can use them correctly, this requires oversight and discipline. Most learning comes through struggle because getting to the right answer is not necessarily the reason why we study or learn a discipline. Instead, the point of learning is to improve the way we think, reason, practice, and apply information. Using the brain is like exercising a muscle. Without struggle for growth, it will atrophy.

Early signs point to AI harming how students learn. A study from MIT’s Media Lab in 2025 asked students to write SAT essays using ChatGPT, Google’s search engine, or nothing at all. They found that ChatGPT users “had the lowest brain engagement and ‘consistently underperformed at neural, linguistic, and behavioral levels.’”

What will AI’s impact be on mental health?

On an individual basis, AI will be helpful to some people for working out basic grievances and anxieties in their lives. How does one respond to an email from a boss? What are ways one can broach a sensitive issue with a daughter? What are some ideas to focus when studying for an exam?

For other mental health challenges or advanced forms of psychiatric disease, I find it hard to believe that a robot can provide the same level of comfort, assurance, and guidance that a human can. Let’s see how long a roaming robot would last in a psychiatric hospital.

On a larger scale, AI may be detrimental to mental health. There have already been reports on AI-induced psychosis. Further, the sheer loss of agency, ability, employment, and meaning due to AI will only increase the aggregate stress and anxiety felt by humanity.

What will AI’s impact be on art and creativity?

Art and creativity, in my opinion, are inherently human endeavors. A human being must ultimately evaluate whether a creation, whether made by a person or computer, is considered artistic or creative. If one AI system evaluates another AI system’s creation as artistic, can we accept it as a valid judgement? I do not think that the AI’s assessment will become mainstream without first being rated by a human.

If anything, AI will make art and creativity more generic. There will be a regression to the mean. Art will seem polished and flattened but without spirit or life. It will not create a never-before-seen narrative or reinvent painting or develop a new design for fashion. It will only reinforce current practices, perhaps in slightly different ways, but certainly not be groundbreaking.

What’s one misconception about AI that you think is worth dispelling?

AI, as we currently understand large language models, is not thinking. It is accessing a large corpus of information from which it is deriving the statistically, most likely next word or words. If the input is flawed, so will the be the output. AI is great for getting you the average answer, but it won’t lead to a innovative one unless you can provide it new data.

Which of the following statements do you think will be true by 2030:

• “Unemployment in the United States will have increased significantly as a result of AI.”

  • True

• “AI will have led to breakthrough treatment or cure for a major disease.”

  • True, especially if it involves evaluating large amounts of data like in DNA or protein for a specific answer

• “AI will have played a role in a major global security event.”

  • True. It can be good, like helping prevent a major cybersecurity disaster, or catastrophic, like if bad actors use AI to hack into a hospital or electrical grid or a military base.

• “Most Americans will be using AI chatbots at least once a day.”

  • True, and it won’t necessarily be fun. If you are already annoyed with holding on the phone while waiting to speak with a customer service representative, wait until you are chatting with an endlessly friendly chatbot that is immune to your growing frustration.

Most people define artificial general intelligence as a form of AI that is comparable to human intelligence. How likely is it that we will see AGI in the next 10 years?

Extremely unlikely. AI will likely be able to match or surpass human intelligence and capability in areas with extremely narrow scope, like finding patterns in large data sets or driving a car. But human intelligence does not just exist in an intellectual realm. It is also physical, artistic, and emotional. I don’t see AI playing in the NBA, cooking a novel meal, or comforting a dying patient in any meaningful way in the next ten years.

What’s a technology that had a transformational impact similar to AI?

I believe AI is part of the same technological evolution that led to the Internet, the cell phone, and social media. These technologies changed the way we interacted with data and information and are now ubiquitous. They were quickly released for mass use by profit-seeking companies and now we must contend with their positive and negative effects in society. AI is the next step in the journey. AI depends on the massive amount of information that these prior technologies aggregated. How it will affect society is unknown. But it has the potential to be more bad than good, if left unregulated.

What advice would you give a high school student about how to think about AI and prepare for the future?

This is an unpopular opinion, but learn to code! I will write about this at some point in the next couple of months, but I do not think that vibe coding is enough. Vibe coding is helpful if you want to create small programs to accomplish simple tasks, like sort or search through certain files on your computer. But even now, you would still need to know how to use a code editor, the command line interface, and some basic computer programming principles.

But to do anything meaningful or long-lasting, like develop your logical reasoning, create complex software, or become a tech entrepreneur, you will have to learn to code.

In my opinion, writing code is another level of literacy (more on this in the future). Even if you have AI write code for you, the program must still be assessed and edited. You can only be good at this if you have experience writing and struggling with code yourself. Spending a couple of hours to debug a program will teach you a lot about how your program works and how to improve your code the next time.

There will never be a time where less knowledge or understanding is better than more. That is especially true in computer science, a field that basically undergirds and supports every field and industry on Earth. The rich and powerful would rather that the masses do not have this understanding so that they can continue to be gatekeepers. NVIDIA CEO, Jensen Huang, basically advised that students not learn how to code. I think this is terrible advice. Technology evolves quickly and if any gaps or delays in staying up to date will make it exponentially harder to catch up later on.

In 2023, the writer Cory Doctorow coined the term “enshittification” to describe the slow degradation of tech services and user experience over time. He described the premise like this:

“Here is how platforms die: first, they are good to their users; then they abuse their users to make things better for their business customers; finally, they abuse those business customers to claw back all the value for themselves. Then, they die.”

Right now, we are still in the honeymoon phase of large language model (LLM) artificial intelligence, where the major companies are still being abundantly generous just like the early days of Facebook, Uber, Google, Amazon, and TikTok.

These original 21^st century tech companies offered their services for free or with steep discounts (the Millennial subsidy); the UI was intuitive and seamless, customer service was responsive, and they delivered exactly what they promised and sometimes more.

Eventually, these companies captured market share, locked in users, acquired their competitors, stopped improving their services, and increased the price of services by raising fees or inundating us with a never ending stream of ads.

If we don’t expect this to happen with artificial intelligence, then we are just being naive.

Enshittification of Healthcare

Healthcare has long been enshittified. This is undisputed. In fact, was it ever really efficient? The consolidation and closure of hospitals by private equity firms, the growing glut of administrators in healthcare, the incessant denial of claims or coverage by insurance companies, the slashing of basic science investment, the self-sabotage of government organizations like the CDC and the FDA, the health professional shortage, and on and on we go.

Rather than focus on first principles, reducing inefficiencies, and root cause analysis, the government and the healthcare industry have succumbed to patchwork legislation and solutions that vary by state. The involvement of middlemen and administrative superfluity has led to fragmented care, siloed information, and increased costs. Meanwhile, patients are left unsatisfied, sicker, and disempowered.

Utah Allows AI Prescription Renewals

But now, the promise of AI to fill in the gaps in the healthcare system is coming to fruition. Just this past week, Politico reported that Utah has established a partnership with the healthcare startup Doctronic to allow an AI system to refill prescriptions for patients with chronic conditions. So far, the FDA has not given an opinion on this new system, but the state of Utah believes that this endeavor can lower the costs for patients and ease the burden on patients.

Patients can visit Doctronic’s website, where it verifies that they are located in Utah via IP address and that they live in Utah via personal identification. It then pulls the patient’s existing prescriptions and gives the patient the opportunity to select which prescriptions to renew.

The chatbot prompts the patient with a series of questions to determine if the patient is eligible for a refill and if it is safe to do so by asking about symptoms, medication adherence, side effects, and recent changes in medical history. If there are any red flags (like medication interactions or contraindications), it will escalate to a human clinician. If everything checks out, it refills the order electronically at a pharmacy. Doctronic’s chatbot is covered by unique malpractice insurance that places the AI under regulatory oversight..

Doctronic supplied data to Utah regulators that demonstrated their AI-generated treatment plans were identical to physicians 99.2% of the time. This was based on 500 urgent care cases. Utah’s Office of Artificial Intelligence Policy will continue to track and publish results on medication adherence, patient satisfaction, safety outcomes, workflow efficiency, refill timeliness, and other metrics in order to determine effectiveness of the system.

As expected, physician groups, like the American Medical Association (AMA), have urged restraint and recommend that physicians remain involved in prescribing decisions. The AMA argues that some potential side effects or underlying health issues may not be effectively captured by the Doctronic. And even if the chatbot triggers human clinician oversight, how does that provide continuity of care for the patient from a provider that knows him well?

Will it work?

On first evaluation, this actually seems like a great idea. According to Doctronic and the Utah Department of Commerce, 80% of all medication activity are for prescription renewals. Further, it often takes weeks to obtain a medical appointment amid a national physician shortage. This may lead to reduced compliance, missed doses, and avoidable ER visits. This system might also allow for physicians to save time on low risk visits and spend more time with patients who have complex needs.

But it would be prudent to remind ourselves that we are still early stages of the AI transformation of medicine. There are a number of issues that patients who use Doctronic must contend with:

1. Technological barriers - For older patients, using a chatbot may not come naturally. They may also not be forthcoming about all their symptoms or they may not know if it is relevant. Even if the patient has a family member help with interacting with the chatbot, how can we be sure the patient is fully involved in their care?

2. Hallucinations - It has already been well established that LLMs hallucinate and supply false information. How often will Doctronic’s system be audited? How will it detect errors in judgement or hallucinations? This has not been well elucidated.

3. Security - Healthcare is rife with information leaks and system hacks. By partnering with Doctronic, Utah is allowing another third part, another middleman, to obtain and retain patient data. How will the state respond if Doctronic is hacked?

4. Prompt injection - Something as random as poetry has been shown to circumvent safety features on chatbots. It is too soon to tell if Doctronic is vulnerable to prompt injection, but people will inevitably try to bypass the chatbot. How is Doctronic protecting against this?

5. The role of pharmacists - One of the more interesting aspects of the prescription renewal debate that I discovered is that even pharmacists are questioning whether the system will detract from their authority. Some say that pharmacists should be given prescription refill authority, because they are in a better position to answer patient questions in person and catch medications interactions. Will anyone listen to them?

6. Liability - If Utah is partnering with a third party company, will they, as the government, allow themselves to be liable for an adverse reaction to medication? What are the consequences if Doctronic’s AI system is liable? Will any human face consequences? Is it just a slap on the wrist and a fine?

7. Access to healthcare based on class and status - One of the most consequential aspects of AI technology is the premium it will place on human interaction. With AI’s ability to mimic digital art and workflows, live performance and live interactions will become more expensive. We might be headed for a future where the poor or uninsured must interact with a digital AI doctor, while the wealthy and insured have access to real physicians in person because they can pay extra. What does that say about our healthcare system and our society if we dehumanize the patient-physician interaction? Does it matter?

Not the Only Game in Town

Doctronic is the not the only company exploring AI healthcare. Mass General Brigham (MGB) in Boston recently debuted their solution to the physician shortage: Care Connect, which was developed by the company K Health. As opposed to Doctronic, Care Connect focuses on patient’s medical history and chief complaint for common urgent care requests (colds, rashes, simple injuries, mental health issues, and chronic disease concerns). Care Connect’s AI tool then sends a suggested diagnosis and treatment plan to one of 12 employed physicians who are logged in remotely from around the country and available 24/7.

In this case, Care Connect is not making clinical decisions. Rather it is gathering history and forwarding the information to a physician who will ultimately sign off on the treatment plan. K Health has also partnered with the Mayo Clinic and Cedar-Sinai Medical Center in Los Angeles, giving it an impressive roster of partners.

Conclusion

Obviously it is still too early to predict the success of the partnership between Utah and Doctronic. My hope is that it does make a positive impact on the lives of patients and doctors, lowers costs, and improves efficiency.

But don’t we say that about every new service or technology, only to be eventually disappointed?

A recent NY Times op-ed makes the case that eventually, the AI companies, on which so many services rely on, will feel the pressure to turn a profit for their investors. At this moment, many users are not paying for their relatively simple AI needs. But we should not be surprised when the AI developers begin to charge for subscriptions, start running ads, and demand higher premium for agentic AI services like preparing our taxes or buying airline tickets. The same enshittification will undoubtedly happen with AI in healthcare.

Don’t say you weren’t warned.

It is generally accepted that the most complicated object in the known universe is the human brain. Remarkably, it is only about 1500 cubic centimeters (1.5 liters) and weighs about three pounds. The brain is composed of about 75 percent water. 60 percent of its dried weight is fat.

Scientists estimate that the brain has close to 85 billion neurons, with one quadrillion connections or synapses between them. For more palatable numbers, brain tissue the size of a grain of sand contains 100,000 neurons and one billion synapses.

At just two percent of the body’s weight, the brain consumes 20 percent of the body’s energy, primarily in the form of glucose. The brain generates about 25 watts of power (enough to power a dim LED light bulb). For context, power companies bill customers in kilowatt-hours (kWh), so we can use this calculation to determine the amount of energy consumed in 24 hours:

25 watts x 24 hours = 600 watt-hours or 0.6 kilowatt-hours

While the local electricity rates vary around the United States and the world, we can round the national average to 20 cents per kWh.

20 cents x 0.6 kWh = 12 cents

Therefore, the roughly 50,000 daily thoughts that drive our ability to read, dance, sing, paint, make love, operate machinery, calculate, reason, experiment, fight, or perform surgery are driven by a gelatinous, easily deformed structure about the third of the size of an American football and costs approximately 12 cents a day.

Of course, generating the electricity to perform the actions behind the thoughts are more expensive but not by much: water, oxygen, sleep, and a few well-balanced meals a day can be sufficient.

Meanwhile, a single metal and silicon-based H100 GPU by NVIDIA requires 700 watts. If we perform the same calculation as above, this works out to $2.85 per day. In other words, the GPU needs 28 times the energy at 23.75 times the cost.

Further, it has already been well documented how expensive it is to train AI models, to collect training data, and to establish the complex data infrastructure of massive cooling systems and high-voltage power. The brain self regulates at a steady 37 degrees Celsius.

Data centers may contain upwards of 100,000 GPUs. Even with all that processing power, we’re still waiting for robots to dance like us let alone correctly identify all the structures.

Therefore, the brain is not only the most complex entity in the universe, it is also the most energy-efficient processor in the known universe.

So what kind of audacity and hubris do humans possess that made us think we can achieve any sort of artificial general intelligence?

Of course, our brains are infamously fallible. Research has proven how we easily we forget events, how easy it is to implant memories in witnesses, how quick we lose track of time, how often we become overwhelmed when multitasking or stressed or hungry or fatigued.

Yet, our brains are incredible problem solvers. If we come across a new type of door handle or even a website, it does not take long for us to figure out how it works. A couple of rounds of trial and error and we are soon up and running. Maybe we solve it on our first try. Meanwhile, a robot or agentic AI may never figure out how to open the door or order the pizza. It will also sooner hallucinate.

When the AI and LLM hype is at its peak, when the AI CEOs and analysts and gurus are breathlessly espousing that the transformation of humanity is just around the corner, it sounds to me like the claims of every religious and cult leader since the dawn of time.

“The future is coming! The fall of mankind is at hand. But we possess a power that can provide salvation. It can cause great harm but also tremendous opportunity. You must trust us to harness and wield its strength. Our technological elixir can do everything you can but exponentially better. You can even have sex with it! We alone can save you! Also, you’re not going to have a job in ten years, but you can worry about that later!”

Anytime in human history where we have purported to possess awe-inspiring, God-like powers, these claims are eventually debunked. Every. Single. Time.

Yes, we possess incredibly powerful weapons of annihilation, but destroying something is easy. Building something is hard. An AI robot can shoot you, but can it repair the damage?

Once again, who do humans think we are to consider a possibility that we are a few short years from replicating anything close to the human brain? Can you name another organ that we have effectively replaced that does not come from another human?

At best, the medical technology that we do possess does an inefficient job assisting in the body’s functions. A ventilator might help a patient breathe, a cochlear implant may help a patient hear, and dialysis will do the work for a patient’s kidneys. Even the left ventricular assist device (LVAD) will augment the work of a patient’s heart. But these are devices and technologies with complications and side effects and limitations.

Even implanted brain-computer interface implants, as important as they might be for those contending with the limitations of paralysis or paraplegia, will not enhance the brain to better than it was before. At least not anytime soon. But it will not revive or replace a non-functioning brain.

Of course I may have to eat my words one day. But chances are that I will be long dead before I have to do so. In the meantime, it is best if we proceed with caution and humility. AI has the awesome ability to destroy so we must respect its power. But the invention of fallible AI technology required the collective processing power of the most complex and efficient processor in the known universe over generations. We don’t even know how the brain fully works, let alone a large language model.

Once again, it bears repeating: who do we think we are?

I am interested in health and vitality. Not just health as in biology, physiology, and the human body, but also our intellectual, environmental, and our civic health. Broadly, this includes the health of our planet, our institutions, our creativity, our technology, our relationships, our society, and our purpose. One of the essential themes of this project is that everything is interconnected. I am interested in understanding how these dynamic forces interact with each other.

The universe is a collection of systems that are intertwined, run both in parallel and in sequence, and reside within one another. We do not live in a physics problem, where systems are isolated and independent. On our planet, the health of one system will affect another. If we want to improve our lives, our society, and our world, it is best if we try to understand how everything fits together and affects our health from a variety of perspectives.

So that where “polymath health” comes from. But what about AI? What does artificial intelligence have to do with all this?

Well it is apparent that AI will be the defining technology of our century. It has the chance to completely upend our lives, our health, our interactions, our government, our jobs, and whatever meaning we get from life. Indeed, it is already transforming our society.

The questions and possibilities are seemingly limitless. How can we use this ground breaking technology to improve our health and bring good to our lives? How do we prevent and protect ourselves from the harm that can come from it when it is used for nefarious purposes? What might we lose from our natural intelligence and world if we give ourselves up completely to the artificial? What lessons can biology and nature teach us when it comes to optimizing our health or living our lives? How do we differentiate between hype, hubris, opportunity, and threat?

Inevitably, this project will evolve with time. It will continue to improve and grow. There is no set destination, so I am excited to see where it leads. Thanks for joining me.