The Algorithm Will See You Now
There's a quiet revolution going on in medicine. It's driven by artificial intelligence, but paradoxically, new technology may put a more human face on healthcare.
AI's usefulness in healthcare ranges far and wide.
Artificial intelligence is software that can process massive amounts of information and learn over time, arriving at decisions with striking accuracy and efficiency. It offers greater accuracy in diagnosis, exponentially faster genome sequencing, the mining of medical literature and patient records at breathtaking speed, a dramatic reduction in administrative bureaucracy, personalized medicine, and even the democratization of healthcare.
The algorithms that bring these advantages won't replace doctors; rather, by offloading some of the most time-consuming tasks in healthcare, providers will be able to focus on personal interactions with patients—listening, empathizing, educating and generally putting the care back in healthcare. The relationship can focus on the alleviation of suffering, both the physical and emotional kind.
Challenges of Getting AI Up and Running
The AI revolution, still in its early phase in medicine, is already spurring some amazing advances, despite the fact that some experts say it has been overhyped. IBM's Watson Health program is a case in point. IBM capitalized on Watson's ability to process natural language by designing algorithms that devour data like medical articles and analyze images like MRIs and medical slides. The algorithms help diagnose diseases and recommend treatment strategies.
But Technology Review reported that a heavily hyped partnership with the MD Anderson Cancer Center in Houston fell apart in 2017 because of a lack of data in the proper format. The data existed, just not in a way that the voraciously data-hungry AI could use to train itself.
The hiccup certainly hasn't dampened the enthusiasm for medical AI among other tech giants, including Google and Apple, both of which have invested billions in their own healthcare projects. At this point, the main challenge is the need for algorithms to interpret a huge diversity of data mined from medical records. This can include everything from CT scans, MRIs, electrocardiograms, x-rays, and medical slides, to millions of pages of medical literature, physician's notes, and patient histories. It can even include data from implantables and wearables such as the Apple Watch and blood sugar monitors.
None of this information is in anything resembling a standard format across and even within hospitals, clinics, and diagnostic centers. Once the algorithms are trained, however, they can crunch massive amounts of data at blinding speed, with an accuracy that matches and sometimes even exceeds that of highly experienced doctors.
Genome sequencing, for example, took years to accomplish as recently as the early 2000s. The Human Genome Project, the first sequencing of the human genome, was an international effort that took 13 years to complete. In April of this year, Rady Children's Institute for Genomic Medicine in San Diego used an AI-powered genome sequencing algorithm to diagnose rare genetic diseases in infants in about 20 hours, according to ScienceDaily.
"Patient care will always begin and end with the doctor."
Dr. Stephen Kingsmore, the lead author of an article published in Science Translational Medicine, emphasized that even though the algorithm helped guide the treatment strategies of neonatal intensive care physicians, the doctor was still an indispensable link in the chain. "Some people call this artificial intelligence, we call it augmented intelligence," he says. "Patient care will always begin and end with the doctor."
One existing trend is helping to supply a great amount of valuable data to algorithms—the electronic health record. Initially blamed for exacerbating the already crushing workload of many physicians, the EHR is emerging as a boon for algorithms because it consolidates all of a patient's data in one record.
Examples of AI in Action Around the Globe
If you're a parent who has ever taken a child to the doctor with flulike symptoms, you know the anxiety of wondering if the symptoms signal something serious. Kang Zhang, M.D., Ph.D., the founding director of the Institute for Genomic Medicine at the University of California at San Diego, and colleagues developed an AI natural language processing model that used deep learning to analyze the EHRs of 1.3 million pediatric visits to a clinic in Guanzhou, China.
The AI identified common childhood diseases with about the same accuracy as human doctors, and it was even able to split the diagnoses into two categories—common conditions such as flu, and serious, life-threatening conditions like meningitis. Zhang has emphasized that the algorithm didn't replace the human doctor, but it did streamline the diagnostic process and could be used in a triage capacity when emergency room personnel need to prioritize the seriously ill over those suffering from common, less dangerous ailments.
AI's usefulness in healthcare ranges far and wide. In Uganda and several other African nations, AI is bringing modern diagnostics to remote villages that have no access to traditional technologies such as x-rays. The New York Times recently reported that there, doctors are using a pocket-sized, hand-held ultrasound machine that works in concert with a cell phone to image and diagnose everything from pneumonia (a common killer of children) to cancerous tumors.
The beauty of the highly portable, battery-powered device is that ultrasound images can be uploaded on computers so that physicians anywhere in the world can review them and weigh in with their advice. And the images are instantly incorporated into the patient's EHR.
Jonathan Rothberg, the founder of Butterfly Network, the Connecticut company that makes the device, told The New York Times that "Two thirds of the world's population gets no imaging at all. When you put something on a chip, the price goes down and you democratize it." The Butterfly ultrasound machine, which sells for $2,000, promises to be a game-changer in remote areas of Africa, South America, and Asia, as well as at the bedsides of patients in developed countries.
AI algorithms are rapidly emerging in healthcare across the U.S. and the world. China has become a major international player, set to surpass the U.S. this year in AI capital investment, the translation of AI research into marketable products, and even the number of often-cited research papers on AI. So far the U.S. is still the leader, but some experts describe the relationship between the U.S. and China as an AI cold war.
"The future of machine learning isn't sentient killer robots. It's longer human lives."
The U.S. Food and Drug Administration expanded its approval of medical algorithms from two in all of 2017 to about two per month throughout 2018. One of the first fields to be impacted is ophthalmology.
One algorithm, developed by the British AI company DeepMind (owned by Alphabet, the parent company of Google), instantly scans patients' retinas and is able to diagnose diabetic retinopathy without needing an ophthalmologist to interpret the scans. This means diabetics can get the test every year from their family physician without having to see a specialist. The Financial Times reported in March that the technology is now being used in clinics throughout Europe.
In Copenhagen, emergency service dispatchers are using a new voice-processing AI called Corti to analyze the conversations in emergency phone calls. The algorithm analyzes the verbal cues of callers, searches its huge database of medical information, and provides dispatchers with onscreen diagnostic information. Freddy Lippert, the CEO of EMS Copenhagen, notes that the algorithm has already saved lives by expediting accurate diagnoses in high-pressure situations where time is of the essence.
Researchers at the University of Nottingham in the UK have even developed a deep learning algorithm that predicts death more accurately than human clinicians. The algorithm incorporates data from a huge range of factors in a chronically ill population, including how many fruits and vegetables a patient eats on a daily basis. Dr. Stephen Weng, lead author of the study, published in PLOS ONE, said in a press release, "We found machine learning algorithms were significantly more accurate in predicting death than the standard prediction models developed by a human expert."
New digital technologies are allowing patients to participate in their healthcare as never before. A feature of the new Apple Watch is an app that detects cardiac arrhythmias and even produces an electrocardiogram if an abnormality is detected. The technology, approved by the FDA, is helping cardiologists monitor heart patients and design interventions for those who may be at higher risk of a cardiac event like a stroke.
If having an algorithm predict your death sends a shiver down your spine, consider that algorithms may keep you alive longer. In 2018, technology reporter Tristan Greene wrote for Medium that "…despite the unending deluge of panic-ridden articles declaring AI the path to apocalypse, we're now living in a world where algorithms save lives every day. The future of machine learning isn't sentient killer robots. It's longer human lives."
The Risks of AI Compiling Your Data
To be sure, the advent of AI-infused medical technology is not without its risks. One risk is that the use of AI wearables constantly monitoring our vital signs could turn us into a nation of hypochondriacs, racing to our doctors every time there's a blip in some vital sign. Such a development could stress an already overburdened system that suffers from, among other things, a shortage of doctors and nurses. Another risk has to do with the privacy protections on the massive repository of intimately personal information that AI will have on us.
In an article recently published in the Journal of the American Medical Association, Australian researcher Kit Huckvale and colleagues examined the handling of data by 36 smartphone apps that assisted people with either depression or smoking cessation, two areas that could lend themselves to stigmatization if they fell into the wrong hands.
Out of the 36 apps, 33 shared their data with third parties, despite the fact that just 25 of those apps had a privacy policy at all and out of those, only 23 stated that data would be shared with third parties. The recipients of all that data? It went almost exclusively to Facebook and Google, to be used for advertising and marketing purposes. But there's nothing to stop it from ending up in the hands of insurers, background databases, or any other entity.
Even when data isn't voluntarily shared, any digital information can be hacked. EHRs and even wearable devices share the same vulnerability as any other digital record or device. Still, the promise of AI to radically improve efficiency and accuracy in healthcare is hard to ignore.
AI Can Help Restore Humanity to Medicine
Eric Topol, director of the Scripps Research Translational Institute and author of the new book Deep Medicine, says that AI gives doctors and nurses the most precious gift of all: time.
Topol welcomes his patients' use of the Apple Watch cardiac feature and is optimistic about the ways that AI is revolutionizing medicine. He says that the watch helps doctors monitor how well medications are working and has already helped to prevent strokes. But in addition to that, AI will help bring the humanity back to a profession that has become as cold and hard as a stainless steel dissection table.
"When I graduated from medical school in the 1970s," he says, "you had a really intimate relationship with your doctor." Over the decades, he has seen that relationship steadily erode as medical organizations demanded that doctors see more and more patients within ever-shrinking time windows.
"Doctors have no time to think, to communicate. We need to restore the mission in medicine."
In addition to that, EHRs have meant that doctors and nurses are getting buried in paperwork and administrative tasks. This is no doubt one reason why a recent study by the World Health Organization showed that worldwide, about 50 percent of doctors suffer from burnout. People who are utterly exhausted make more mistakes, and medical clinicians are no different from the rest of us. Only medical mistakes have unacceptably high stakes. According to its website, Johns Hopkins University recently announced that in the U.S. alone, 250,000 people die from medical mistakes each year.
"Doctors have no time to think, to communicate," says Topol. "We need to restore the mission in medicine." AI is giving doctors more time to devote to the thing that attracted them to medicine in the first place—connecting deeply with patients.
There is a real danger at this juncture, though, that administrators aware of the time-saving aspects of AI will simply push doctors to see more patients, read more tests, and embrace an even more crushing workload.
"We can't leave it to the administrators to just make things worse," says Topol. "Now is the time for doctors to advocate for a restoration of the human touch. We need to stand up for patients and for the patient-doctor relationship."
AI could indeed be a game changer, he says, but rather than squander the huge benefits of more time, "We need a new equation going forward."
Story by Big Think
We live in strange times, when the technology we depend on the most is also that which we fear the most. We celebrate cutting-edge achievements even as we recoil in fear at how they could be used to hurt us. From genetic engineering and AI to nuclear technology and nanobots, the list of awe-inspiring, fast-developing technologies is long.
However, this fear of the machine is not as new as it may seem. Technology has a longstanding alliance with power and the state. The dark side of human history can be told as a series of wars whose victors are often those with the most advanced technology. (There are exceptions, of course.) Science, and its technological offspring, follows the money.
This fear of the machine seems to be misplaced. The machine has no intent: only its maker does. The fear of the machine is, in essence, the fear we have of each other — of what we are capable of doing to one another.
How AI changes things
Sure, you would reply, but AI changes everything. With artificial intelligence, the machine itself will develop some sort of autonomy, however ill-defined. It will have a will of its own. And this will, if it reflects anything that seems human, will not be benevolent. With AI, the claim goes, the machine will somehow know what it must do to get rid of us. It will threaten us as a species.
Well, this fear is also not new. Mary Shelley wrote Frankenstein in 1818 to warn us of what science could do if it served the wrong calling. In the case of her novel, Dr. Frankenstein’s call was to win the battle against death — to reverse the course of nature. Granted, any cure of an illness interferes with the normal workings of nature, yet we are justly proud of having developed cures for our ailments, prolonging life and increasing its quality. Science can achieve nothing more noble. What messes things up is when the pursuit of good is confused with that of power. In this distorted scale, the more powerful the better. The ultimate goal is to be as powerful as gods — masters of time, of life and death.
Should countries create a World Mind Organization that controls the technologies that develop AI?
Back to AI, there is no doubt the technology will help us tremendously. We will have better medical diagnostics, better traffic control, better bridge designs, and better pedagogical animations to teach in the classroom and virtually. But we will also have better winnings in the stock market, better war strategies, and better soldiers and remote ways of killing. This grants real power to those who control the best technologies. It increases the take of the winners of wars — those fought with weapons, and those fought with money.
A story as old as civilization
The question is how to move forward. This is where things get interesting and complicated. We hear over and over again that there is an urgent need for safeguards, for controls and legislation to deal with the AI revolution. Great. But if these machines are essentially functioning in a semi-black box of self-teaching neural nets, how exactly are we going to make safeguards that are sure to remain effective? How are we to ensure that the AI, with its unlimited ability to gather data, will not come up with new ways to bypass our safeguards, the same way that people break into safes?
The second question is that of global control. As I wrote before, overseeing new technology is complex. Should countries create a World Mind Organization that controls the technologies that develop AI? If so, how do we organize this planet-wide governing board? Who should be a part of its governing structure? What mechanisms will ensure that governments and private companies do not secretly break the rules, especially when to do so would put the most advanced weapons in the hands of the rule breakers? They will need those, after all, if other actors break the rules as well.
As before, the countries with the best scientists and engineers will have a great advantage. A new international détente will emerge in the molds of the nuclear détente of the Cold War. Again, we will fear destructive technology falling into the wrong hands. This can happen easily. AI machines will not need to be built at an industrial scale, as nuclear capabilities were, and AI-based terrorism will be a force to reckon with.
So here we are, afraid of our own technology all over again.
What is missing from this picture? It continues to illustrate the same destructive pattern of greed and power that has defined so much of our civilization. The failure it shows is moral, and only we can change it. We define civilization by the accumulation of wealth, and this worldview is killing us. The project of civilization we invented has become self-cannibalizing. As long as we do not see this, and we keep on following the same route we have trodden for the past 10,000 years, it will be very hard to legislate the technology to come and to ensure such legislation is followed. Unless, of course, AI helps us become better humans, perhaps by teaching us how stupid we have been for so long. This sounds far-fetched, given who this AI will be serving. But one can always hope.
Interview with Jamie Metzl: We need a global OS upgrade
In this Q&A, leading technology and healthcare futurist Jamie Metzl discusses a range of topics and trend lines that will unfold over the next several decades: whether a version of Moore's Law applies to genetic technologies, the ethics of genetic engineering, the dangers of gene hacking, the end of sex, and much more.
Metzl is a member of the WHO expert advisory committee on human genome editing and the bestselling author of Hacking Darwin.
The conversation was lightly edited by Leaps.org for style and length.
In Hacking Darwin, you describe how we may modify the human body with CRISPR technologies, initially to obtain unsurpassed sports performance and then to enhance other human characteristics. What would such power over human biology mean for the future of our civilization?
After nearly four billion years of evolution, our one species suddenly has the increasing ability to read, write, and hack the code of life. This will have massive implications across the board, including in human health and reproduction, plant and animal agriculture, energy and advanced materials, and data storage and computing, just to name a few. My book Hacking Darwin: Genetic Engineering and the Future of Humanity primarly explored how we are currently deploying and will increasingly use our capabilities to transform human life in novel ways. My next book, The Great Biohack: Recasting Life in an Age of Revolutionary Technology, coming out in May 2024, will examine the broader implications for all of life on Earth.
We humans will, over time, use these technologies on ourselves to solve problems and eventually to enhance our capabilities. We need to be extremely conservative, cautious, and careful in doing so, but doing so will almost certainly be part of our future as a species.
In electronics, Moore's law is an established theory that computing power doubles every 18 months. Is there any parallel to be drawn with genetic technologies?
The increase in speed and decrease in costs of genome sequencing have progressed far faster than Moore’s law. It took thirteen years and cost about a billion dollars to sequence the first human genome. Today it takes just a few hours and can cost as little as a hundred dollars to do a far better job. In 2012, Jennifer Doudna and Emmanuel Charpentier published the basic science paper outlining the CRISPR-cas9 genome editing tool that would eventually win them the Nobel prize. Only six years later, the first CRISPR babies were born in China. If it feels like technology is moving ever-faster, that’s because it is.
Let's turn to the topic of aging. Do you think that the field of genetics will advance fast enough to eventually increase maximal lifespan for a child born this year? How about for a person who is currently age 50?
The science of aging is definitely real, but that doesn’t mean we will live forever. Aging is a biological process subject to human manipulation. Decades of animal research shows that. This does not mean we will live forever, but it does me we will be able to do more to expand our healthspans, the period of our lives where we are able to live most vigorously.
The first thing we need to do is make sure everyone on earth has access to the resources necessary to live up to their potential. I live in New York City, and I can take a ten minute subway ride to a neighborhood where the average lifespan is over a decade shorter than in mine. This is true within societies and between countries as well. Secondly, we all can live more like people in the Blue Zones, parts of the world where people live longer, on average, than the rest of us. They get regular exercise, eat healthy foods, have strong social connections, etc. Finally, we will all benefit, over time, from more scientific interventions to extend our healthspan. This may include small molecule drugs like metformin, rapamycin, and NAD+ boosters, blood serum infusions, and many other things.
Science fiction has depicted a future where we will never get sick again, stay young longer or become immortal. Assuming that any of this is remotely possible, should we be afraid of such changes, even if they seem positive in some regards, because we can’t understand the full implications at this point?
Not all of these promises will be realized in full, but we will use these technologies to help us live healthier, longer lives. We will never become immortal becasue nothing lasts forever. We will always get sick, even if the balance of diseases we face shifts over time, as it has always done. It is healthy, and absolutely necessary, that we feel both hope and fear about this future. If we only feel hope, we will blind ourselves to the very real potential downsides. If we only feel fear, we will deny ourselves the very meaningful benefits these technologies have the potential to provide.
A fascinating chapter in Hacking Darwin is entitled The End of Sex. And you see that as a good thing?
We humans will always be a sexually reproducing species, it’s just that we’ll reproduce increasingly less through the physical act of sex. We’re already seeing this with IVF. As the benefits of technology assisted reproduction increase relative to reproduction through the act of sex, many people will come to see assisted reproduction as a better way to reduce risk and, over time, possibly increase benefits. We’ll still have sex for all the other wonderful reasons we have it today, just less for reproduction. There will always be a critical place in our world for Italian romantics!
What are dangers of genetic hackers, perhaps especially if everyone’s DNA is eventually transcribed for medical purposes and available on the internet and in the cloud?
The sky is really the limit for how we can use gentic technologies to do things we may want, and the sky is also the limit for potential harms. It’s quite easy to imagine scenarios in which malevolent actors create synthetic pathogens designed to wreak havoc, or where people steal and abuse other people’s genetic information. It wouldn’t even need to be malevolent actors. Even well-intentioned researchers making unintended mistakes could cause real harm, as we may have seen with COVID-19 if, as appears likely to me, the pandemic stems for a research related incident]. That’s why we need strong governance and regulatory systems to optimize benefits and minimize potential harms. I was honored to have served on the World Health Organization Expert Advisory Committee on Human Genome Editing, were we developed a proposed framework for how this might best be achieved.
You foresee the equivalent of a genetic arms race between the world's most powerful countries. In what sense are genetic technologies similar to weapons?
Genetic technologies could be used to create incredibly powerful bioweapons or to build gene drives with the potential to crash entire ecosystems. That’s why thoughtful regulation is in order. Because the benefits of mastering and deploying these technologies are so great, there’s also a real danger of a genetics arms race. This could be extremely dangerous and will need to be prevented.
In your book, you express concern that states lacking Western conceptions of human rights are especially prone to misusing the science of genetics. Does this same concern apply to private companies? How much can we trust them to control and wield these technologies?
This is a conversation about science and technology but it’s really a conversation about values. If we don’t agree on what core values should be promoted, it will be nearly impossible to agree on what actions do and do not make sense. We need norms, laws, and values frameworks that apply to everyone, including governments, corporations, researchers, healthcare providers, DiY bio hobbyists, and everyone else.
We have co-evolved with our technology for a very long time. Many of our deepest beliefs have formed in that context and will continue to do so. But as we take for ourselves the powers we have attributed to our various gods, many of these beliefs will be challenged. We can not and must not jettison our beliefs in the face of technology, and must instead make sure our most cherished values guide the application of our most powerful technologies.
A conversation on international norms is in full swing in the field of AI, prompted by the release of ChatGPT4 earlier this year. Are there ways in which it’s inefficient, shortsighted or otherwise problematic for these discussions on gene technologies, AI and other advances to be occurring in silos? In addition to more specific guidelines, is there something to be gained from developing a universal set of norms and values that applies more broadly to all innovation?
AI is yet another technology where the potential to do great good is tied to the potential to inflict signifcant harm. It makes no sense that we tend to treat each technology on its own rather than looking at the entire category of challenges. For sure, we need to very rapidly ramp up our efforts with regard to AI norm-setting, regulations, and governance at all levels. But just doing that will be kind of like generating a flu vaccine for each individual flu strain. Far better to build a universal flu vaccine addressing common elements of all flu viruses of concern.
That’s why we also need to be far more deliberate in both building a global operating systems based around the mutual responsibilities of our global interdependence and, under that umbrella, a broader system for helping us govern and regulate revolutionary technologies. Such a process might begin with a large international conference, the equivalent of Rio 1992 for climate change, but then quickly work to establish and share best practices, help build parallel institutions in all countries so people and governamts can talk with each other, and do everything possible to maximize benefits and minimize risks at all levels in an ongoing and dynamic way.
At what point might genetic enhancements lead to a reclassfication of modified humans as another species?
We’ll still all be fellow humans for a very, very long time. We already have lots of variation between us. That is the essence of biology. Will some humans, at some point in the future, leave Earth and spend generations elsewhere? I believe so. In those new environments, humans will evolve, over time, differently than those if us who remain on this planet? This may sound like science fiction, but the sci-fi future is coming at us faster than most people realize.
Is the concept of human being changing?
Yes. It always has and always will.
Another big question raised in your book: what limits should we impose on the freedom to manipulate genetics?
Different societies will come to different conclusion on this critical question. I am sympathetic to the argument that people should have lots of say over their own bodies, which why I support abortion rights even though I recognize that an abortion can be a violent procedure. But it would be insane and self-defeating to say that individuals have an unlimited right to manipulate their own or their future children’s heritable genetics. The future of human life is all of our concern and must be regulated, albeit wisely.
In some cases, such as when we have the ability to prevent a deadly genetic disroder, it might be highly ethical to manipulate other human beings. In other circumstances, the genetic engineering of humans might be highly unethical. The key point is to avoid asking this question in a binary manner. We need to weigh the costs and benefits of each type of intervention. We need societal and global infrastrucutres to do that well. We don’t yet have those but we need them badly.
Can you tell us more about your next book?
The Great Biohack: Recasting Lifee in an Age of Revolutionary Technology, will come out in May 2024. It explores what the intersecting AI, genetics, and biotechnology revolutions will mean for the future of life on earth, including our healthcare, agriculture, industry, computing, and everything else. We are at a transitional moment for life on earth, equivalent to the dawn of agriculture, electricity, and industrialization. The key differentiator between better and worse outcomes is what we do today, at this early stage of this new transformation. The book describes what’s happening, what’s at stake, and what we each and all can and, frankly, must do to build the type of future we’d like to inhabit.
You’ve been a leader of international efforts calling for a full investigation into COVID-19 origins and are the founder of the global movement OneShared.World. What problem are you trying to solve through OneShared.World?
The biggest challenge we face today is the mismatch between the nature of our biggest problems, global and common, and the absence of a sufficient framework for addressing that entire category of challenges. The totally avoidable COVID-19 pandemic is one example of the extremet costs of the status quo. OneShared.World is our effort to fight for an upgrade in our world’s global operating system, based around the mutual responsibilities of interdependence. We’ve had global OS upgrades before after the Thirty Years War and after World War II, but wouldn’t it be better to make the necessary changes now to prevent a crisis of that level stemming from a nuclear war, ecosystem collapse, or deadlier synthetic biology pandemic rather than waiting until after? Revolutionary science is a global issue that must be wisely managed at every level if it is to be wisely managed at all.
How do we ensure that revolutionary technologies benefit humanity instead of undermining it?
That is the essential question. It’s why I’ve written Hacking Darwin, am writing The Great Biohack, and doing the rest of my work. If we want scietific revolutions to help, rather than hurt, us, we must all play a role building that future. This isn’t just a conversation about science, it’s about how we can draw on our most cherished values to guide the optimal development of science and technology for the common good. That must be everyone’s business.
Portions of this interview were first published in Grassia (Italy) and Zen Portugal.
Jamie Metzl is one of the world’s leading technology and healthcare futurists and author of the bestselling book, Hacking Darwin: Genetic Engineering and the Future of Humanity, which has been translated into 15 languages. In 2019, he was appointed to the World Health Organization expert advisory committee on human genome editing. Jamie is a faculty member of Singularity University and NextMed Health, a Senior Fellow of the Atlantic Council, and Founder and Chair of the global social movement, OneShared.World.
Called “the original COVID-19 whistleblower,” his pioneering role advocating for a full investigation into the origins of the COVID-19 pandemic has been featured in 60 Minutes, the New York Times, and most major media across the globe, and he was the lead witness in the first congressional hearings on this topic. Jamie previously served in the U.S. National Security Council, State Department, and Senate Foreign Relations Committee and with the United Nations in Cambodia. Jamie appears regularly on national and international media and his syndicated columns and other writing in science, technology, and global affairs are featured in publications around the world.
Jamie sits on advisory boards for multiple biotechnology and other companies and is Special Strategist to the WisdomTree BioRevolution Exchange Traded Fund. In addition to Hacking Darwin, he is author of a history of the Cambodian genocide, the historical novel The Depths of the Sea, and the genetics sci-fi thrillers Genesis Code and Eternal Sonata. His next book, The Great Biohack: Recasting Life in an age of Revolutionary Technology, will be published by Hachette in May 2024. Jamie holds a Ph.D. from Oxford, a law degree from Harvard, and an undergraduate degree from Brown and is an avid ironman triathlete and ultramarathon runner.