The Science Sleuth Holding Fraudulent Research Accountable
Kira Peikoff was the editor-in-chief of Leaps.org from 2017 to 2021. As a journalist, her work has appeared in The New York Times, Newsweek, Nautilus, Popular Mechanics, The New York Academy of Sciences, and other outlets. She is also the author of four suspense novels that explore controversial issues arising from scientific innovation: Living Proof, No Time to Die, Die Again Tomorrow, and Mother Knows Best. Peikoff holds a B.A. in Journalism from New York University and an M.S. in Bioethics from Columbia University. She lives in New Jersey with her husband and two young sons. Follow her on Twitter @KiraPeikoff.
Introduction by Mary Inman, Whistleblower Attorney
For most people, when they see the word "whistleblower," the image that leaps to mind is a lone individual bravely stepping forward to shine a light on misconduct she has witnessed first-hand. Meryl Streep as Karen Silkwood exposing safety violations observed while working the line at the Kerr-McGee plutonium plant. Matt Damon as Mark Whitacre in The Informant!, capturing on his pocket recorder clandestine meetings between his employer and its competitors to fix the price of lysine. However, a new breed of whistleblower is emerging who isn't at the scene of the crime but instead figures it out after the fact through laborious review of publicly available information and expert analysis. Elisabeth Bik belongs to this new class of whistleblower.
"There's this delicate balance where on one hand we want to spread results really fast as scientists, but on the other hand, we know it's incomplete, it's rushed and it's not great."
Using her expertise as a microbiologist and her trained eye, Bik studies publicly available scientific papers to sniff out potential irregularities in the images that suggest research fraud, later seeking retraction of the offending paper from the journal's publisher. There's no smoking gun, no first-hand account of any kind. Just countless hours spent reviewing scores of scientific papers and Bik's skills and dedication as a science fraud sleuth.
While Bik's story may not as readily lend itself to the big screen, her work is nonetheless equally heroic. By tirelessly combing scientific papers to expose research fraud, Bik is playing a vital role in holding the scientific publishing process accountable and ensuring that misleading information does not spread unchecked. This is important work in any age, but particularly so in the time of COVID, where we can ill afford the setbacks and delays of scientists building on false science. In the present climate, where science is politicized and scientific principles are under attack, strong voices like Bik's must rise above the din to ensure the scientific information we receive, and our governments act upon, is accurate. Our health and wellbeing depend on it.
Whistleblower outsiders like Bik are challenging the traditional concept of what it means to be a whistleblower. Fortunately for us, the whistleblower community is a broad church. As with most ecosystems, we all benefit from a diversity of voices —whistleblower insiders and outsiders alike. What follows is an illuminating conversation between Bik, and Ivan Oransky, the co-founder of Retraction Watch, an influential blog that reports on retractions of scientific papers and related topics. (Conversation facilitated by LeapsMag Editor-in-Chief Kira Peikoff)
Elisabeth Bik and Ivan Oransky.
(Photo credits Michel & Co Photography, San Jose, CA and Elizabeth Solaka)
Ivan
I'd like to hear your thoughts, Elisabeth, on an L.A. Times story, which was picking up a preprint about mutations and the novel coronavirus, alleging that the virus is mutating to become more infectious – even though this conclusion wasn't actually warranted.
Elisabeth
A lot of the news around it is picking up on one particular side of the story that is maybe not that much exaggerated by the scientists. I don't think this paper really showed that the mutations were causing the virus to be more virulent. Some of these viruses continuously mutate and mutate and mutate, and that doesn't necessarily make a strain more virulent. I think in many cases, a lot of people want to read something in a paper that is not actually there.
Ivan
The tone level, everything that's being published now, it's problematic. It's being rushed, here it wasn't even peer-reviewed. But even when they are peer-reviewed, they're being peer-reviewed by people who often aren't really an expert in that particular area.
Elisabeth
That's right.
Ivan
To me, it's all problematic. At the same time, it's all really good that it's all getting out there. I think that five or 10 years ago, or if we weren't in a pandemic, maybe that paper wouldn't have appeared at all. It would have maybe been submitted to a top-ranked journal and not have been accepted, or maybe it would have been improved during peer review and bounced down the ladder a bit to a lower-level journal.
Yet, now, because it's about coronavirus, it's in a major newspaper and, in fact, it's getting critiqued immediately.
Maybe it's too Pollyanna-ish, but I actually think that quick uploading is a good thing. The fear people have about preprint servers is based on this idea that the peer-reviewed literature is perfect. Once it is in a peer-reviewed journal, they think it must have gone through this incredible process. You're laughing because-
Elisabeth
I am laughing.
Ivan
You know it's not true.
Elisabeth
Yes, we both know that. I agree and I think in this particular situation, a pandemic that is unlike something our generation has seen before, there is a great, great need for fast dissemination of science.
If you have new findings, it is great that there is a thing called a preprint server where scientists can quickly share their results, with, of course, the caveat that it's not peer-reviewed yet.
It's unlike the traditional way of publishing papers, which can take months or years. Preprint publishing is a very fast way of spreading your results in a good way so that is what the world needs right now.
On the other hand, of course, there's the caveat that these are brand new results and a good scientist usually thinks about their results to really interpret it well. You have to look at it from all sides and I think with the rushed publication of preprint papers, there is no such thing as carefully thinking about what results might mean.
So there's this delicate balance where on one hand we want to spread results really fast as scientists, but on the other hand, we know it's incomplete, it's rushed and it's not great. This might be hard for the general audience to understand.
Ivan
I still think the benefits of that dissemination are more positive than negative.
Elisabeth
Right. But there's also so many papers that come out now on preprint servers and most of them are not that great, but there are some really good studies in there. It's hard to find those nuggets of really great papers. There's just a lot of papers that come out now.
Ivan
Well, you've made more than a habit of finding problems in papers. These are mostly, of course, until now published papers that you examined, but what is this time like for you? How is it different?
Elisabeth
It's different because in the beginning I looked at several COVID-19-related papers that came out and wrote some critiques about it. I did experience a lot of backlash because of that. So I felt I had to take a break from social media and from writing about COVID-19.
I focused a little bit more on other work because I just felt that a lot of these papers on COVID-19 became so politically divisive that if you tried to be a scientist and think critically about a paper, you were actually assigned to a particular political party or to be against other political parties. It's hard for me to be sucked into the political discussion and to the way that our society now is so completely divided into two camps that seem to be not listening to each other.
Ivan
I was curious about that because I've followed your work for a number of years, as you know, and certainly you have had critics before. I'm thinking of the case in China that you uncovered, the leading figure in the Chinese Academy who was really a powerful political figure in addition to being a scientist.
Elisabeth
So that was a case in which I found a couple of papers at first from a particular group in China, and I was just posting on a website called PubPeer, where you can post comments, concerns about papers. And in this case, these were image duplication issues, which is my specialty.
I did not realize that the group I was looking at at that moment was led by one of the highest ranked scientists in China. If I had known that, I would probably not have posted that under my full name, but under a pseudonym. Since I had already posted, some people were starting to send me direct messages on Twitter like, "OMG, the guy you're posting about now is the top scientist in China so you're going to have a lot of backlash."
Then I decided I'll just continue doing this. I found a total of around 50 papers from this group and posted all of them on PubPeer. That story quickly became a very popular story in China: number two on Sina Weibo, a social media site in China.
I was surprised it wasn't suppressed by the Chinese government, it was actually allowed by journalists that were writing about it, and I didn't experience a lot of backlash because of that.
Actually the Chinese doctor wrote me an email saying that he appreciated my feedback and that he would look into these cases. He sent a very polite email so I sent him back that I appreciated that he would look into these cases and left it there.
Ivan
There are certain subjects that I know when we write about them in Retraction Watch, they have tended in the past to really draw a lot of ire. I'm thinking anything about vaccines and autism, anything about climate change, stem cell research.
For a while that last subject has sort of died down. But now it's become a highly politically charged atmosphere. Do you feel that this pandemic has raised the profile of people such as yourself who we refer to as scientific sleuths, people who look critically and analytically at new research?
Elisabeth
Yeah, some people. But I'm also worried that some people who are great scientists and have shown a lot of critical thinking are being attacked because of that. If you just look at what happened to Dr. Fauci, I think that's a prime example. Where somebody who actually is very knowledgeable and very cautious of new science has not been widely accepted as a great leader, in our country at least. It's sad to see that. I'm just worried how long he will be at his position, to be honest.
Ivan
We noticed a big uptick in our traffic in the last few days to Retraction Watch and it turns out it was because someone we wrote about a number of years ago has really hopped on the bandwagon to try and discredit and even try to have Dr. Fauci fired.
It's one of these reminders that the way people think about scientists has, in many cases, far more to do with their own history or their own perspective going in than with any reality or anything about the science. It's pretty disturbing, but it's not a new thing. This has been happening for a while.
You can go back and read sociologists of science from 50-60 years ago and see the same thing, but I just don't think that it's in the same way that it is now, maybe in part because of social media.
Elisabeth
I've been personally very critical about several studies, but this is the first time I've experienced being attacked by trolls and having some nasty websites written about me. It is very disturbing to read.
"I don't think that something that's been peer-reviewed is perfect and something that hasn't been peer reviewed, you should never bother reading it."
Ivan
It is. Yet you have been a fearless and vocal critic of some very high-profile papers, like the infamous French study about hydroxychloroquine.
Elisabeth
Right, the paper that came out was immediately tweeted by the President of the United States. At first I thought it was great that our President tweeted about science! I thought that was a major breakthrough. I took a look at this paper.
It had just come out that day, I believe. The first thing I noticed is that it was accepted within 24 hours of being submitted to the journal. It was actually published in a journal where one of the authors is the editor-in-chief, which is a huge conflict of interest, but it happens.
But in this particular case, there were also a lot of flaws with the study and that, I think, should have been caught during peer review. The paper was first published on a preprint server and then within 24 hours or so it was published in that paper, supposedly after peer review.
There were very few changes between the preprint version and the peer review paper. There were just a couple of extra lines, extra sentences added here and there, but it wasn't really, I think, critically looked at. Because there were a lot of things that I thought were flaws.
Just to go over a couple of them. This paper showed supposedly that people who were treated with hydroxychloroquine and azithromycin were doing much better by clearing their virus much faster than people who were not treated with these drugs.
But if you look carefully at the paper there were a couple of people who were left out of the study. So they were treated with hydroxychloroquine, but they were not shown in the end results of the paper. All six people who were treated with the drug combination were clearing the virus within six days, but there were a couple of others who were left out of the study. They also started the drug combination, but they stopped taking the drugs for several reasons and three of them were admitted to the intensive care, one died, one had some side effects and one apparently walked out of the hospital.
They were left out of the study but they were actually not doing very well with the drug combination. It's not very good science if you leave out people who don't do very well with your drug combination in your study. That was one of my biggest critiques of the paper.
Ivan
What struck us about that case was, in addition to what you, of course, mentioned, the fact that Trump tweeted it and was talking about hydroxychloroquine, was that it seemed to be a perfect example of, "well, it was in a peer review journal." Yeah, it was a preprint first, but, well, it's a peer review journal. And yet, as you point out, when you look at the history of the paper, it was accepted in 24 hours.
If you talk to most scientists, the actual act of a peer review, once you sit down to do it and can concentrate, a good one takes, again, these are averages, but four hours, a half a day is not unreasonable. So you had to find three people who could suddenly review this paper. As you pointed out, it was in a journal where one of the authors was editor.
Then some strange things also happened, right? The society that actually publishes the journal, they came out with a statement saying this wasn't up to our standards, which is odd. Then Elsevier came in, they're the ones who are actually contracted to publish the journal for the society. They said, basically, "Oh, we're going to look into this now too."
It just makes you wonder what happened before the paper was actually published. All the people who were supposed to have been involved in doing the peer review or checking on it are clearly very distraught about what actually happened. It's that scene from Casablanca, "I'm shocked, shocked there's gambling going on here." And then, "Your winnings, sir."
Elisabeth
Yes.
Ivan
And I don't actually blame the public, I don't blame reporters for getting a bit confused about what it all means and what they should trust. I don't think trust is a binary any more than anything else is a binary. I don't think that something that's been peer-reviewed is perfect and something that hasn't been peer reviewed, you should never bother reading it. I think everything is much more gray.
Yet we've turned things into a binary. Even if you go back before coronavirus, coffee is good for you, coffee is bad for you, red wine, chocolate, all the rest of it. A lot of that is because of this sort of binary construct of the world for journalists, frankly, for scientists that need to get their next grants. And certainly for the general public, they want answers.
On the one hand, if I had to choose what group of experts, or what field of human endeavor would I trust with finding the answer to a pandemic like this, or to any crisis, it would absolutely be scientists. Hands down. This is coming from someone who writes about scientific fraud.
But on the other hand, that means that if scientists aren't clear about what they don't know and about the nuances and about what the scientific method actually allows us to do and learn, that just sets them up for failure. It sets people like Dr. Fauci up for failure.
Elisabeth
Right.
Ivan
It sets up any public health official who has a discussion about models. There's a famous saying: "All models are wrong, but some are useful."
Just because the projections change, it's not proof of wrongness, it's not proof that the model is fatally flawed. In fact, I'd be really concerned if the projections didn't change based on new information. I would love it if this whole episode did lead to a better understanding of the scientific process and how scientific publishing fits into that — and doesn't fit into it.
Elisabeth
Yes, I'm with you. I'm very worried that the general audience's perspective is based on maybe watching too many movies where the scientist comes up with a conclusion one hour into the movie when everything is about to fail. Like that scene in Contagion where somebody injects, I think, eight monkeys, and one of the monkeys survives and boom we have the vaccine. That's not really how science works. Everything takes many, many years and many, many applications where usually your first ideas and your first hypothesis turn out to be completely wrong.
Then you go back to the drawing board, you develop another hypothesis and this is a very reiterative process that usually takes years. Most of the people who watch the movie might have a very wrong idea and wrong expectations about how science works. We're living in the movie Contagion and by September, we'll all be vaccinated and we can go on and live our lives. But that's not what is going to happen. It's going to take much, much longer and we're going to have to change the models every time and change our expectations. Just because we don't know all the numbers and all the facts yet.
Ivan
Generally it takes a fairly long time to change medical practice. A lot of times people see that as a bad thing. What I think that ignores, or at least doesn't take into as much account as I would, is that you don't want doctors and other health care professionals to turn on a dime and suddenly switch. Unless, of course, it turns out there was no evidence for what you were looking at.
It's a complicated situation.
Everybody wants scientists to be engineers, right?
Elisabeth
Right.
Ivan
I'm not saying engineering isn't scientific, nor am I saying that science is just completely whimsical, but there's a different process. It's a different way of looking at things and you can't just throw all the data into a big supercomputer, which is what I think a lot of people seem to want us to do, and then the obvious answer will come out on the other side.
Elisabeth
No. It's true and a lot of engineers suddenly feel their inherent need to solve this as a problem. They're not scientists and it's not building a bridge over a big river. But we're dealing with something that is very hard to solve because we don't understand the problem yet. I think scientists are usually first analyzing the problem and trying to understand what the problem actually is before you can even think about a solution.
Ivan
I think we're still at the understanding the problem phase.
Elisabeth
Exactly. And going back to the French group paper, that promised such a result and that was interpreted as such by a lot of people including presidents, but it's a very rare thing to find a medication that will have a 100% curation rate. That's something that I wish the people would understand better. We all want that to happen, but it's very unlikely and very unprecedented in the best of times.
Ivan
I would second that and also say that the world needs to better value the work that people like Elisabeth and others are doing. Because we're not going to get to a better answer if we're not rigorous about scrutinizing the literature and scrutinizing the methodology and scrutinizing the results.
"I quit my job to be able to do this work."
It's a relatively new phenomenon that you're able to do this at any scale at all, and even now it's at a very small scale. Elisabeth mentioned PubPeer and I'm a big fan — also full disclosure, I'm on their board of directors as a volunteer — it's a very powerful engine for readers and journal editors and other scientists to discuss issues.
And Elisabeth has used it really, really well. I think we need to start giving credit to people like that. And, also creating incentives for that kind of work in a way that science hasn't yet.
Elisabeth
Yeah. I quit my job to be able to do this work. It's really hard to combine it with a job either in academia or industry because we're looking for or criticizing papers and it's hard when you are still employed to do that.
I try to make it about the papers and do it in a polite way, but still it's a very hard job to do if you have a daytime job and a position and a career to worry about. Because if you're critical of other academics, that could actually mean the end of your career and that's sad. They should be more open to polite criticism.
Ivan
And for the general public, if you're reading a newspaper story or something online about a single study and it doesn't mention any other studies that have said the same thing or similar, or frankly, if it doesn't say anything about any studies that contradicted it, that's probably also telling you something.
Say you're looking at a huge painting of a shoreline, a beach, and a forest. Any single study is just a one-centimeter-by-one-centimeter square of any part of that canvas. If you just look at that, you would either think it was a painting of the sea, of a beach, or of the forest. It's actually all three of those things.
We just need to be patient, and that's very challenging to us as human beings, but we need to take the time to look at the whole picture.
DISCLAIMER: Neither Elisabeth Bik nor Ivan Oransky was compensated for participation in The Pandemic Issue. While the magazine's editors suggested broad topics for discussion, consistent with Bik's and Oransky's work, neither they nor the magazine's underwriters had any influence on their conversation.
[Editor's Note: This article was originally published on June 8th, 2020 as part of a standalone magazine called GOOD10: The Pandemic Issue. Produced as a partnership among LeapsMag, The Aspen Institute, and GOOD, the magazine is available for free online.]
Kira Peikoff was the editor-in-chief of Leaps.org from 2017 to 2021. As a journalist, her work has appeared in The New York Times, Newsweek, Nautilus, Popular Mechanics, The New York Academy of Sciences, and other outlets. She is also the author of four suspense novels that explore controversial issues arising from scientific innovation: Living Proof, No Time to Die, Die Again Tomorrow, and Mother Knows Best. Peikoff holds a B.A. in Journalism from New York University and an M.S. in Bioethics from Columbia University. She lives in New Jersey with her husband and two young sons. Follow her on Twitter @KiraPeikoff.
One day in recent past, scientists at Columbia University’s Creative Machines Lab set up a robotic arm inside a circle of five streaming video cameras and let the robot watch itself move, turn and twist. For about three hours the robot did exactly that—it looked at itself this way and that, like toddlers exploring themselves in a room full of mirrors. By the time the robot stopped, its internal neural network finished learning the relationship between the robot’s motor actions and the volume it occupied in its environment. In other words, the robot built a spatial self-awareness, just like humans do. “We trained its deep neural network to understand how it moved in space,” says Boyuan Chen, one of the scientists who worked on it.
For decades robots have been doing helpful tasks that are too hard, too dangerous, or physically impossible for humans to carry out themselves. Robots are ultimately superior to humans in complex calculations, following rules to a tee and repeating the same steps perfectly. But even the biggest successes for human-robot collaborations—those in manufacturing and automotive industries—still require separating the two for safety reasons. Hardwired for a limited set of tasks, industrial robots don't have the intelligence to know where their robo-parts are in space, how fast they’re moving and when they can endanger a human.
Over the past decade or so, humans have begun to expect more from robots. Engineers have been building smarter versions that can avoid obstacles, follow voice commands, respond to human speech and make simple decisions. Some of them proved invaluable in many natural and man-made disasters like earthquakes, forest fires, nuclear accidents and chemical spills. These disaster recovery robots helped clean up dangerous chemicals, looked for survivors in crumbled buildings, and ventured into radioactive areas to assess damage.
Now roboticists are going a step further, training their creations to do even better: understand their own image in space and interact with humans like humans do. Today, there are already robot-teachers like KeeKo, robot-pets like Moffin, robot-babysitters like iPal, and robotic companions for the elderly like Pepper.
But even these reasonably intelligent creations still have huge limitations, some scientists think. “There are niche applications for the current generations of robots,” says professor Anthony Zador at Cold Spring Harbor Laboratory—but they are not “generalists” who can do varied tasks all on their own, as they mostly lack the abilities to improvise, make decisions based on a multitude of facts or emotions, and adjust to rapidly changing circumstances. “We don’t have general purpose robots that can interact with the world. We’re ages away from that.”
Robotic spatial self-awareness – the achievement by the team at Columbia – is an important step toward creating more intelligent machines. Hod Lipson, professor of mechanical engineering who runs the Columbia lab, says that future robots will need this ability to assist humans better. Knowing how you look and where in space your parts are, decreases the need for human oversight. It also helps the robot to detect and compensate for damage and keep up with its own wear-and-tear. And it allows robots to realize when something is wrong with them or their parts. “We want our robots to learn and continue to grow their minds and bodies on their own,” Chen says. That’s what Zador wants too—and on a much grander level. “I want a robot who can drive my car, take my dog for a walk and have a conversation with me.”
Columbia scientists have trained a robot to become aware of its own "body," so it can map the right path to touch a ball without running into an obstacle, in this case a square.
Jane Nisselson and Yinuo Qin/ Columbia Engineering
Today’s technological advances are making some of these leaps of progress possible. One of them is the so-called Deep Learning—a method that trains artificial intelligence systems to learn and use information similar to how humans do it. Described as a machine learning method based on neural network architectures with multiple layers of processing units, Deep Learning has been used to successfully teach machines to recognize images, understand speech and even write text.
Trained by Google, one of these language machine learning geniuses, BERT, can finish sentences. Another one called GPT3, designed by San Francisco-based company OpenAI, can write little stories. Yet, both of them still make funny mistakes in their linguistic exercises that even a child wouldn’t. According to a paper published by Stanford’s Center for Research on Foundational Models, BERT seems to not understand the word “not.” When asked to fill in the word after “A robin is a __” it correctly answers “bird.” But try inserting the word “not” into that sentence (“A robin is not a __”) and BERT still completes it the same way. Similarly, in one of its stories, GPT3 wrote that if you mix a spoonful of grape juice into your cranberry juice and drink the concoction, you die. It seems that robots, and artificial intelligence systems in general, are still missing some rudimentary facts of life that humans and animals grasp naturally and effortlessly.
How does one give robots a genome? Zador has an idea. We can’t really equip machines with real biological nucleotide-based genes, but we can mimic the neuronal blueprint those genes create.
It's not exactly the robots’ fault. Compared to humans, and all other organisms that have been around for thousands or millions of years, robots are very new. They are missing out on eons of evolutionary data-building. Animals and humans are born with the ability to do certain things because they are pre-wired in them. Flies know how to fly, fish knows how to swim, cats know how to meow, and babies know how to cry. Yet, flies don’t really learn to fly, fish doesn’t learn to swim, cats don’t learn to meow, and babies don’t learn to cry—they are born able to execute such behaviors because they’re preprogrammed to do so. All that happens thanks to the millions of years of evolutions wired into their respective genomes, which give rise to the brain’s neural networks responsible for these behaviors. Robots are the newbies, missing out on that trove of information, Zador argues.
A neuroscience professor who studies how brain circuitry generates various behaviors, Zador has a different approach to developing the robotic mind. Until their creators figure out a way to imbue the bots with that information, robots will remain quite limited in their abilities. Each model will only be able to do certain things it was programmed to do, but it will never go above and beyond its original code. So Zador argues that we have to start giving robots a genome.
How does one do that? Zador has an idea. We can’t really equip machines with real biological nucleotide-based genes, but we can mimic the neuronal blueprint those genes create. Genomes lay out rules for brain development. Specifically, the genome encodes blueprints for wiring up our nervous system—the details of which neurons are connected, the strength of those connections and other specs that will later hold the information learned throughout life. “Our genomes serve as blueprints for building our nervous system and these blueprints give rise to a human brain, which contains about 100 billion neurons,” Zador says.
If you think what a genome is, he explains, it is essentially a very compact and compressed form of information storage. Conceptually, genomes are similar to CliffsNotes and other study guides. When students read these short summaries, they know about what happened in a book, without actually reading that book. And that’s how we should be designing the next generation of robots if we ever want them to act like humans, Zador says. “We should give them a set of behavioral CliffsNotes, which they can then unwrap into brain-like structures.” Robots that have such brain-like structures will acquire a set of basic rules to generate basic behaviors and use them to learn more complex ones.
Currently Zador is in the process of developing algorithms that function like simple rules that generate such behaviors. “My algorithms would write these CliffsNotes, outlining how to solve a particular problem,” he explains. “And then, the neural networks will use these CliffsNotes to figure out which ones are useful and use them in their behaviors.” That’s how all living beings operate. They use the pre-programmed info from their genetics to adapt to their changing environments and learn what’s necessary to survive and thrive in these settings.
For example, a robot’s neural network could draw from CliffsNotes with “genetic” instructions for how to be aware of its own body or learn to adjust its movements. And other, different sets of CliffsNotes may imbue it with the basics of physical safety or the fundamentals of speech.
At the moment, Zador is working on algorithms that are trying to mimic neuronal blueprints for very simple organisms—such as earthworms, which have only 302 neurons and about 7000 synapses compared to the millions we have. That’s how evolution worked, too—expanding the brains from simple creatures to more complex to the Homo Sapiens. But if it took millions of years to arrive at modern humans, how long would it take scientists to forge a robot with human intelligence? That’s a billion-dollar question. Yet, Zador is optimistic. “My hypotheses is that if you can build simple organisms that can interact with the world, then the higher level functions will not be nearly as challenging as they currently are.”
Lina Zeldovich has written about science, medicine and technology for Popular Science, Smithsonian, National Geographic, Scientific American, Reader’s Digest, the New York Times and other major national and international publications. A Columbia J-School alumna, she has won several awards for her stories, including the ASJA Crisis Coverage Award for Covid reporting, and has been a contributing editor at Nautilus Magazine. In 2021, Zeldovich released her first book, The Other Dark Matter, published by the University of Chicago Press, about the science and business of turning waste into wealth and health. You can find her on http://linazeldovich.com/ and @linazeldovich.
Podcast: Wellness chatbots and meditation pods with Deepak Chopra
Over the last few decades, perhaps no one has impacted healthy lifestyles more than Deepak Chopra. While several of his theories and recommendations have been criticized by prominent members of the scientific community, he has helped bring meditation, yoga and other practices for well-being into the mainstream in ways that benefit the health of vast numbers of people every day. His work has led many to accept new ways of thinking about alternative medicine, the power of mind over body, and the malleability of the aging process.
His impact is such that it's been observed our culture no longer recognizes him as a human being but as a pervasive symbol of new-agey personal health and spiritual growth. Last week, I had a chance to confirm that Chopra is, in fact, a human being – and deserving of his icon status – when I talked with him for the Leaps.org podcast. He relayed ideas that were wise and ancient, yet highly relevant to our world today, with the fluidity and ease of someone discussing the weather. Showing no signs of slowing down at age 76, he described his prolific work, including the publication of two books in the past year and a range of technologies he’s developing, including a meditation app, meditation pods for the workplace, and a chatbot for mental health called Piwi.
Take a listen and get inspired to do some meditation and deep thinking on the future of health. As Chopra told me, “If you don’t have time to meditate once per day, you probably need to meditate twice per day.”
Highlights:
2:10: Chopra talks about meditation broadly and meditation pods, including the ones made by OpenSeed for meditation in the workplace.
6:10: The drawbacks of quick fixes like drugs for mental health.
10:30: The benefits of group meditation versus individual meditation.
14:35: What is a "metahuman" and how to become one.
19:40: The difference between the conditioned mind and the mind that's infinitely creative.
22:48: How Chopra's views of free will differ from the views of many neuroscientists.
28:04: Thinking Fast and Slow, and the role of intuition.
31:20: Athletic and creative geniuses.
32:43: The nature of fundamental truth.
34:00: Meditation for kids.
37:12: Never alone.Love and how AI chatbots can support mental health.
42:30: Extending lifespan, gene editing and lifestyle.
46:05: Chopra's mentor in living a long good life (and my mentor).
47:45: The power of yoga.
Links:
- OpenSeed meditation pods for people to meditate at work (Chopra is an advisor to OpenSeed).
- Chopra's book from 2021, Metahuman: Unleash Your Infinite Potential
- Chopra's book from 2022, Abundance: The Inner Path to Wealth
- NeverAlone.Love, Chopra's collaboration of businesses, policy makers, mental health professionals and others to raise awareness about mental health, advance scientific research and "create a global technology platform to democratize access to resources."
- The Piwi chatbot for mental health
- The Chopra Meditation & Well-Being App for people of all ages
- Only 1.6 percent of U.S. children meditate, according to the National Center for Complementary and Integrative Health