Scientists Want to Make Robots with Genomes that Help Grow their Minds
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.
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.
Story by Big Think
Our gut microbiome plays a substantial role in our health and well-being. Most research, however, focuses on bacteria, rather than the viruses that hide within them. Now, research from the University of Copenhagen, newly published in Nature Microbiology, found that people who live past age 100 have a greater diversity of bacteria-infecting viruses in their intestines than younger people. Furthermore, they found that the viruses are linked to changes in bacterial metabolism that may support mucosal integrity and resistance to pathogens.
The microbiota and aging
In the early 1970s, scientists discovered that the composition of our gut microbiota changes as we age. Recent studies have found that the changes are remarkably predictable and follow a pattern: The microbiota undergoes rapid, dramatic changes as toddlers transition to solid foods; further changes become less dramatic during childhood as the microbiota strikes a balance between the host and the environment; and as that balance is achieved, the microbiota remains mostly stable during our adult years (ages 18-60). However, that stability is lost as we enter our elderly years, and the microbiome undergoes dramatic reorganization. This discovery led scientists to question what causes this change and what effect it has on health.
Centenarians have a distinct gut community enriched in microorganisms that synthesize potent antimicrobial molecules that can kill multidrug-resistant pathogens.
“We are always eager to find out why some people live extremely long lives. Previous research has shown that the intestinal bacteria of old Japanese citizens produce brand-new molecules that make them resistant to pathogenic — that is, disease-promoting — microorganisms. And if their intestines are better protected against infection, well, then that is probably one of the things that cause them to live longer than others,” said Joachim Johansen, a researcher at the University of Copenhagen.
In 2021, a team of Japanese scientists set out to characterize the effect of this change on older people’s health. They specifically wanted to determine if people who lived to be over 100 years old — that is, centenarians — underwent changes that provided them with unique benefits. They discovered centenarians have a distinct gut community enriched in microorganisms that synthesize potent antimicrobial molecules that can kill multidrug-resistant pathogens, including Clostridioides difficile and Enterococcus faecium. In other words, the late-life shift in microbiota reduces an older person’s susceptibility to common gut pathogens.
Viruses can change alter the genes of bacteria
Although the late-in-life microbiota change could be beneficial to health, it remained unclear what facilitated this shift. To solve this mystery, Johansen and his colleagues turned their attention to an often overlooked member of the microbiome: viruses. “Our intestines contain billions of viruses living inside bacteria, and they could not care less about human cells; instead, they infect the bacterial cells. And seeing as there are hundreds of different types of bacteria in our intestines, there are also lots of bacterial viruses,” said Simon Rasmussen, Johansen’s research advisor.
Centenarians had a more diverse virome, including previously undescribed viral genera.
For decades, scientists have explored the possibility of phage therapy — that is, using viruses that infect bacteria (called bacteriophages or simply phages) to kill pathogens. However, bacteriophages can also enhance the bacteria they infect. For example, they can provide genes that help their bacterial host attack other bacteria or provide new metabolic capabilities. Both of these can change which bacteria colonize the gut and, in turn, protect against certain disease states.
Intestinal viruses give bacteria new abilities
Johansen and his colleagues were interested in what types of viruses centenarians had in their gut and whether those viruses carried genes that altered metabolism. They compared fecal samples of healthy centenarians (100+ year-olds) with samples from younger patients (18-100 year-olds). They found that the centenarians had a more diverse virome, including previously undescribed viral genera.
They also revealed an enrichment of genes supporting key steps in the sulfate metabolic pathway. The authors speculate that this translates to increased levels of microbially derived sulfide, which may lead to health-promoting outcomes, such as supporting mucosal integrity and resistance to potential pathogens.
“We have learned that if a virus pays a bacterium a visit, it may actually strengthen the bacterium. The viruses we found in the healthy Japanese centenarians contained extra genes that could boost the bacteria,” said Johansen.
Simon Rasmussen added, “If you discover bacteria and viruses that have a positive effect on the human intestinal flora, the obvious next step is to find out whether only some or all of us have them. If we are able to get these bacteria and their viruses to move in with the people who do not have them, more people could benefit from them.”
This article originally appeared on Big Think, home of the brightest minds and biggest ideas of all time.
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Embrace the mess: how to choose which scientists to trust
It’s no easy task these days for people to pick the scientists they should follow. According to a recent poll by NORC at the University of Chicago, only 39 percent of Americans have a "great deal" of confidence in the scientific community. The finding is similar to Pew research last year showing that 29 percent of Americans have this level of confidence in medical scientists.
Not helping: All the money in science. Just 20 percent of Pew’s survey respondents think scientists are transparent about conflicts of interest with industry. While this issue is common to many fields, the recent gold rush to foot the bill for research on therapies for healthy aging may be contributing to the overall sense of distrust. “There’s a feeling that at some point, the FDA may actually designate aging as a disease,” said Pam Maher, a neuroscientist who studies aging at Salk Institute. “That may be another impetus for a lot of these companies to start up.”
But partnering with companies is an important incentive for researchers across biomedical fields. Many scientists – with and without financial ties and incentives – are honest, transparent and doing important, inspiring work. I asked more than a dozen bioethicists and researchers in aging how to spot the scientists who are searching for the truth more than money, ego or fame.
Avoid Scientists Who Sound Overly Confident in messaging to the public. Some multi-talented scientists are adept at publishing in both top journals and media outlets. They’re great at dropping science without the confusing jargon, in ways the public can enjoy and learn from.
But do they talk in simple soundbites, painting scientific debates in pastels or black and white when colleagues use shades of gray? Maybe they crave your attention more than knowledge seeking. “When scientists speak in a very unnuanced way, that can be irresponsible,” said Josephine Johnston, a bioethicist at the Hastings Center.
Scientists should avoid exaggerations like “without a doubt” and even “we know” – unless they absolutely do. “I feel like there’s more and more hyperbole and attention seeking…[In aging research,] the loudest voices in the room are the fringe people,” said the biogenerontologist Matt Kaeberlein.
Separate Hype from Passion. Scientists should be, need to be passionate, Johnston explained. In the realm of aging, for example, Leonard Guarente, an MIT biologist and pioneer in the field of aging, told me about his belief that longer lifespans would make for a better world.
Instead of expecting scientists to be lab-dwelling robots, we should welcome their passion. It fuels scientific dedication and creativity. Fields like aging, AI and gene editing inspire the imaginations of the public and scientists alike. That’s not a bad thing.
But it does lay fertile ground for overstatements, such as claims by some that the first 1,000-year-old has already been born. If it sounds like sci-fi, it’s probably sci-fi.
Watch Out for Cult Behavior, some experts told me. Follow scientists who mix it up and engage in debates, said NYU bioethicist Arthur Caplan, not those who hang out only with researchers in the same ideological camp.
Look for whether they’re open to working with colleagues who don’t share their views. Through collaboration, they can resolve conflicting study results and data, said Danica Chen, a biologist at UC Berkeley. We should trust science as long as it doesn’t trust itself.
Messiness is Good. You want to find and follow scientists who’ve published research over the years that does not tell a clean story. “Our goal is to disprove our models,” Kaeberlein said. Scientific findings and views should zig and zag as their careers – and science – progress.
Follow scientists who write and talk publicly about new evidence that’s convinced them to reevaluate their own positions. Who embrace the inherent messiness of science – that’s the hallmark of an honest researcher.
The flipside is a very linear publishing history. Some scientists have a pet theory they’ve managed to support with more and more evidence over time, like a bricklayer gradually, flawlessly building the prettiest house in the neighborhood. Too pretty.
There’s a dark side to this charming simplicity: scientists sometimes try and succeed at engineering the very findings they’re hoping to get, said Charles Brenner, a biochemist at City of Hope National Medical Center.
These scientists “try to prove their model and ignore data that doesn’t fit their model because everybody likes a clean story,” Kaeberlein said. “People want to become famous,” said Samuel Klein, a biologist at Washington University. “So there’s always that bias to try to get positive results.”
Don’t Overvalue Credentials. Just because a scientist works at a top university doesn’t mean they’re completely trustworthy. “The institution means almost nothing,” Kaeberlein said.
Same goes for publishing in top journals, Kaeberlein added. “There’s an incentive structure that favors poor quality science and irreproducible results in high profile journals.”
Traditional proxies for credibility aren’t quite as reliable these days. Shortcuts don’t cut it anymore; you’ve got to scrutinize the actual research the scientist is producing. “You have to look at the literature and try to interpret it for yourself,” said Rafael de Cabo, a scientist at the National Institute on Aging, run by the U.S. National Institutes of Health. Or find journalists you trust to distill this information for you, Klein suggested.
Consider Company Ties. Companies can help scientists bring their research to the public more directly and efficiently than the slower grind of academia, where “the opportunities and challenges weren’t big enough for me,” said Kaeberlein, who left the University of Washington earlier this year.
"It’s generally not universities that can take technology through what we call the valley of death,” Brenner said. “There are rewards associated with taking risks.”
Many scientists are upfront about their financial conflicts of interest – sometimes out of necessity. “At a place like Duke, our conflicts of interest are very closely managed, said Matthew Hirschey, who researchers metabolism at Duke’s Molecular Physiology Institute. “We have to be incredibly explicit about our partnerships.”
But the willingness to disclose conflicts doesn’t necessarily mean the scientist is any less biased. Those conflicts can still affect their views and outcomes of their research, said Johnston, the Hastings bioethicist.
“The proof is in the pudding, and it’s got to be done by people who are not vested in making money off the results,” Klein said. Worth noting: even if scientists eschew companies, they’re almost always financially motivated to get grants for their research.
Bottom line: lots of scientists work for and with companies, and many are highly trustworthy leaders in their fields. But if a scientist is in thick with companies and checks some of the other boxes on this list, their views and research may be compromised.