Archive for the ‘Evolution’ Category
Melissa Healy has an interesting story in the LA Times:
In an electoral season that has blurred the line between fact and fantasy, a team of UCLA researchers is offering new evidence to support a controversial proposition: that when it comes to telling the difference between truth and fiction, not all potential voters are created equal.
When “alternative facts” allege some kind of danger, people whose political beliefs are more conservative are more likely than those who lean liberal to embrace them, says the team’s soon-to-be-published study.
Conservatives’ vulnerability to accepting untruths didn’t apply equally to all false claims: When lies suggested dangerous or apocalyptic outcomes, more conservative participants were more likely to believe them than when the lie suggested a possible benefit.
Participants whose views fell further left could be plenty credulous. But they were no more likely to buy a scary falsehood than they were to buy one with a positive outcome.
In short, conservatives are more likely to drop their guard against lies when they perceive the possible consequences as being dark. Liberals, less so.
Slated for publication in the journal Psychological Science, the new study offers insight into why many Americans embraced fabricated stories about Clinton that often made outlandish allegations of criminal behavior. And it may shed light on why so many believed a candidate’s assertions that were both grim and demonstrably false.
Finally, the results offer an explanation for why these false claims were more readily embraced by people who endorse conservative political causes than by those whose views are traditionally liberal.
“There are a lot of citizens who are especially vigilant about potential threats but not especially motivated or prepared to process information in a critical, systematic manner,” said John Jost, co-director of New York University’s Center for Social and Political Behavior. For years, Jost said, those Americans “have been presented with terrifying messages that are short on reason and openly contemptuous of scholarly and scientific standards of evidence.”
Jost, who was not involved with the latest research, said the new findings suggest that when dark claims and apocalyptic visions swirl, many of these anxious voters will cast skepticism aside and selectively embrace fearful claims, regardless of whether they’re true. The result may tilt elections toward politicians who stoke those fears.
“We may be witnessing a perfect storm,” Jost said.
The preliminary study, led by UCLA anthropologist Daniel M.T. Fessler, is the first to explore credulity as a function of ideological belief. The pool of participants was not strictly representative of the U.S. electorate, and some of the findings were weakened when the researchers removed questions pertaining to terrorism.
Moreover, some argue that it is not ideological belief but feeling beaten that makes people more credulous. When parties are thrown out of power, or have been out of office for long periods, their adherents are naturally drawn to believe awful things of the other party, says Joseph Uscinski, a political scientist at the University of Miami.
Until the new findings have been replicated under the changed circumstances of a Republican victory, said Uscinski, they should be greeted with caution.
But the new results are in line with a picture of partisan differences emerging from an upstart corner of the social sciences. In a wide range of studies, anthropologists, social psychologists and political scientists have found that self-avowed liberals and people who call themselves conservatives simply think differently.
All people range across a spectrum of personality traits and thinking styles. But when compared to liberals, conservatives show a lower tolerance for risk and have a greater need for closure and certainty, on average.
Wired up to monitors that measure physiological changes, people who are more conservative respond to threatening stimuli with more pronounced changes than do their peers on the other end of the political spectrum: On average, their hearts race more, their breathing becomes more shallow and their palms get clammier. . .
Philip Ball writes at Quanta:
What’s the difference between physics and biology? Take a golf ball and a cannonball and drop them off the Tower of Pisa. The laws of physics allow you to predict their trajectories pretty much as accurately as you could wish for.
Now do the same experiment again, but replace the cannonball with a pigeon.
Biological systems don’t defy physical laws, of course — but neither do they seem to be predicted by them. In contrast, they are goal-directed: survive and reproduce. We can say that they have a purpose — or what philosophers have traditionally called a teleology — that guides their behavior.
By the same token, physics now lets us predict, starting from the state of the universe a billionth of a second after the Big Bang, what it looks like today. But no one imagines that the appearance of the first primitive cells on Earth led predictably to the human race. Laws do not, it seems, dictate the course of evolution.
The teleology and historical contingency of biology, said the evolutionary biologist Ernst Mayr, make it unique among the sciences. Both of these features stem from perhaps biology’s only general guiding principle: evolution. It depends on chance and randomness, but natural selection gives it the appearance of intention and purpose. Animals are drawn to water not by some magnetic attraction, but because of their instinct, their intention, to survive. Legs serve the purpose of, among other things, taking us to the water.
Mayr claimed that these features make biology exceptional — a law unto itself. But recent developments in nonequilibrium physics, complex systems science and information theory are challenging that view.
Once we regard living things as agents performing a computation — collecting and storing information about an unpredictable environment — capacities and considerations such as replication, adaptation, agency, purpose and meaning can be understood as arising not from evolutionary improvisation, but as inevitable corollaries of physical laws. In other words, there appears to be a kind of physics of things doing stuff, and evolving to do stuff. Meaning and intention — thought to be the defining characteristics of living systems — may then emerge naturally through the laws of thermodynamics and statistical mechanics.
This past November, physicists, mathematicians and computer scientists came together with evolutionary and molecular biologists to talk — and sometimes argue — about these ideas at a workshop at the Santa Fe Institute in New Mexico, the mecca for the science of “complex systems.” They asked: Just how special (or not) is biology?
It’s hardly surprising that there was no consensus. But one message that emerged very clearly was that, if there’s a kind of physics behind biological teleology and agency, it has something to do with the same concept that seems to have become installed at the heart of fundamental physics itself: information.
Disorder and Demons
The first attempt to bring information and intention into the laws of thermodynamics came in the middle of the 19th century, when statistical mechanics was being invented by the Scottish scientist James Clerk Maxwell. Maxwell showed how introducing these two ingredients seemed to make it possible to do things that thermodynamics proclaimed impossible.
Maxwell had already shown how the predictable and reliable mathematical relationships between the properties of a gas — pressure, volume and temperature — could be derived from the random and unknowable motions of countless molecules jiggling frantically with thermal energy. In other words, thermodynamics — the new science of heat flow, which united large-scale properties of matter like pressure and temperature — was the outcome of statistical mechanics on the microscopic scale of molecules and atoms.
According to thermodynamics, the capacity to extract useful work from the energy resources of the universe is always diminishing. Pockets of energy are declining, concentrations of heat are being smoothed away. In every physical process, some energy is inevitably dissipated as useless heat, lost among the random motions of molecules. This randomness is equated with the thermodynamic quantity called entropy — a measurement of disorder — which is always increasing. That is the second law of thermodynamics. Eventually all the universe will be reduced to a uniform, boring jumble: a state of equilibrium, wherein entropy is maximized and nothing meaningful will ever happen again.
Are we really doomed to that dreary fate? Maxwell was reluctant to believe it, and in 1867 he set out to, as he put it, “pick a hole” in the second law. His aim was to start with a disordered box of randomly jiggling molecules, then separate the fast molecules from the slow ones, reducing entropy in the process.
Imagine some little creature — the physicist William Thomson later called it, rather to Maxwell’s dismay, a demon — that can see each individual molecule in the box. The demon separates the box into two compartments, with a sliding door in the wall between them. Every time he sees a particularly energetic molecule approaching the door from the right-hand compartment, he opens it to let it through. And every time a slow, “cold” molecule approaches from the left, he lets that through, too. Eventually, he has a compartment of cold gas on the right and hot gas on the left: a heat reservoir that can be tapped to do work.
This is only possible for two reasons. First, the demon has more information than we do: It can see all of the molecules individually, rather than just statistical averages. And second, it has intention: a plan to separate the hot from the cold. By exploiting its knowledge with intent, it can defy the laws of thermodynamics.
At least, so it seemed. It took a hundred years to understand why Maxwell’s demon can’t in fact defeat the second law and avert the inexorable slide toward deathly, universal equilibrium. And the reason shows that there is a deep connection between thermodynamics and the processing of information — or in other words, computation. The German-American physicist Rolf Landauer showed that even if the demon can gather information and move the (frictionless) door at no energy cost, a penalty must eventually be paid. Because it can’t have unlimited memory of every molecular motion, it must occasionally wipe its memory clean — forget what it has seen and start again — before it can continue harvesting energy. This act of information erasure has an unavoidable price: It dissipates energy, and therefore increases entropy. All the gains against the second law made by the demon’s nifty handiwork are canceled by “Landauer’s limit”: the finite cost of information erasure (or more generally, of converting information from one form to another).
Living organisms seem rather like Maxwell’s demon. Whereas a beaker full of reacting chemicals will eventually expend its energy and fall into boring stasis and equilibrium, living systems have collectively been avoiding the lifeless equilibrium state since the origin of life about three and a half billion years ago. They harvest energy from their surroundings to sustain this nonequilibrium state, and they do it with “intention.” Even simple bacteria move with “purpose” toward sources of heat and nutrition. In his 1944 book What is Life?, the physicist Erwin Schrödinger expressed this by saying that living organisms feed on “negative entropy.”
They achieve it, Schrödinger said, by capturing and storing information. Some of that information is encoded in their genes and passed on from one generation to the next: a set of instructions for reaping negative entropy. Schrödinger didn’t know where the information is kept or how it is encoded, but his intuition that it is written into what he called an “aperiodic crystal” inspired Francis Crick, himself trained as a physicist, and James Watson when in 1953 they figured out how genetic information can be encoded in the molecular structure of the DNA molecule.
A genome, then, is at least in part a record of the useful knowledge that has enabled an organism’s ancestors — right back to the distant past — to survive on our planet. According to David Wolpert, a mathematician and physicist at the Santa Fe Institute who convened the recent workshop, and his colleague Artemy Kolchinsky, the key point is that well-adapted organisms are correlated with that environment. If a bacterium swims dependably toward the left or the right when there is a food source in that direction, it is better adapted, and will flourish more, than one that swims in random directions and so only finds the food by chance. A correlation between the state of the organism and that of its environment implies that they share information in common. Wolpert and Kolchinsky say that it’s this information that helps the organism stay out of equilibrium — because, like Maxwell’s demon, it can then tailor its behavior to extract work from fluctuations in its surroundings. If it did not acquire this information, the organism would gradually revert to equilibrium: It would die.
Looked at this way, life can be considered as a computation that aims to optimize the storage and use of meaningful information. . .
A very intriguing idea is discussed by Natalie Wolchover in Quanta:
A Collaboration of physicists and biologists in Germany has found a simple mechanism that might have enabled liquid droplets to evolve into living cells in early Earth’s primordial soup.
Origin-of-life researchers have praised the minimalism of the idea. Ramin Golestanian, a professor of theoretical physics at the University of Oxford who was not involved in the research, called it a big achievement that suggests that “the general phenomenology of life formation is a lot easier than one might think.”
The central question about the origin of life has been how the first cells arose from primitive precursors. What were those precursors, dubbed “protocells,” and how did they come alive? Proponents of the “membrane-first” hypothesis have argued that a fatty-acid membrane was needed to corral the chemicals of life and incubate biological complexity. But how could something as complex as a membrane start to self-replicate and proliferate, allowing evolution to act on it?
In 1924, Alexander Oparin, the Russian biochemist who first envisioned a hot, briny primordial soup as the source of life’s humble beginnings, proposed that the mystery protocells might have been liquid droplets — naturally forming, membrane-free containers that concentrate chemicals and thereby foster reactions. In recent years, droplets have been found to perform a range of essential functions inside modern cells, reviving Oparin’s long-forgotten speculation about their role in evolutionary history. But neither he nor anyone else could explain how droplets might have proliferated, growing and dividing and, in the process, evolving into the first cells.
Now, the new work by David Zwicker and collaborators at the Max Planck Institute for the Physics of Complex Systems and the Max Planck Institute of Molecular Cell Biology and Genetics, both in Dresden, suggests an answer. The scientists studied the physics of “chemically active” droplets, which cycle chemicals in and out of the surrounding fluid, and discovered that these droplets tend to grow to cell size and divide, just like cells. This “active droplet” behavior differs from the passive and more familiar tendencies of oil droplets in water, which glom together into bigger and bigger droplets without ever dividing.
If chemically active droplets can grow to a set size and divide of their own accord, then “it makes it more plausible that there could have been spontaneous emergence of life from nonliving soup,” said Frank Jülicher, a biophysicist in Dresden and a co-author of the new paper.
The findings, reported in Nature Physics last month, paint a possible picture of life’s start by explaining “how cells made daughters,” said Zwicker, who is now a postdoctoral researcher at Harvard University. “This is, of course, key if you want to think about evolution.”
Luca Giomi, a theoretical biophysicist at Leiden University in the Netherlands who studies the possible physical mechanisms behind the origin of life, said the new proposal is significantly simpler than other mechanisms of protocell division that have been considered, calling it “a very promising direction.”
However, . . .
Elizabeth Svoboda interviews Marcus Feldman in Quanta:
Marcus Feldman never planned to end up on the front lines of evolutionary biology. “I always wanted to do mathematics, as much as I could,” he said. “There was a little bit of time when I flirted with the idea of being a psychiatrist.”
More than anything else, Feldman is a polymath. His desk at Stanford University, where he has been a professor for 46 years, is tiled with stacks upon stacks of journal articles, most teetering above coffee-cup height. Each stack is dedicated to a topic somehow related to his work in evolutionary theory: the origins of behavioral disorders, the epidemiology of tuberculosis, the way modern humans overrode Neanderthals.
Feldman’s openness to unexpected lines of thinking has allowed him to carve out a contrarian niche in a field where established ideas typically rule the day. Along with a group of similarly unorthodox colleagues, Feldman has developed a proposal called the extended evolutionary synthesis (EES). The EES argues that while the existing framework of evolutionary theory, known as the “modern synthesis,” is basically solid, it needs to be expanded to account for newly recognized drivers of evolution. One such driver is epigenetics — gene-expression changes that stem from exposure to, say, pesticides. While these epigenetic changes are not encoded in an organism’s genes, they do give rise to physical and behavioral differences that natural selection can act upon.
The EES also stresses the importance of culture and behavior in evolution. When prairie dogs construct burrows, for instance, selection pressures may begin to favor behaviors like burrow guarding to keep predators out. And both humans and animals direct their evolution through the social and cultural environments they construct for themselves — a phenomenon Feldman thinks is not well reflected in the modern synthesis.
Quanta Magazine spoke with Feldman at Stanford about how mathematical models can illuminate evolution, his contributions to the extended evolutionary synthesis, and his role in redressing China’s sex-ratio imbalance. An edited and condensed version of the conversation follows.
QUANTA MAGAZINE: When you were a young man in Australia, would you ever have pictured your career unfolding the way it has?
MARCUS FELDMAN: No! I went to work in Melbourne when IBM opened its offices. I didn’t like working for IBM, so I tried to do a master’s degree in mathematics and statistics at Monash University, which of course involved an enormous cut in pay. I was lucky that my adviser had just come back from America. He introduced me to using mathematics on genetics problems. I had never done a biology course in my life, but I started to work on this class of problems.
The first two years of my Ph.D. at Stanford, I still hadn’t done any biology. But I got so interested in some of the problems I was working on that I decided I’d better take some courses. I became immersed in the application of mathematics to genetics questions. From then on, it was just trying to formalize in mathematical terms the kinds of questions that biologists would ask.
You joined Stanford’s biology department as a faculty member in 1971. What happened after that?
Very soon after my arrival, I met a famous geneticist, Luigi Luca Cavalli-Sforza. He is what I call the consummate Renaissance man. He was interested in the statistics of human genetic and cultural variation — why different people in different parts of the world behave differently, have different rules in their societies and were genetically different from one another. He and I immediately hit it off.
The first thing we did was develop mathematical models to describe cultural differences. What would happen to the old style of genetic evolution if there were also cultural factors that influenced what was happening to the genes in the populations? For example, IQ — if there happened to be genetic contributions to IQ, but also culturally determined contributions to IQ, how would you combine the two of them in a dynamic system?
How do these models reveal how evolution takes place?
One of the nice things about models is you can ask what conditions have to change to make the results change. As Murray Gell-Mann says, models are prostheses for the imagination. They help you think about ways in which you might interpret data, even complicated data.
If you think about use of milk, dairy in itself is culturally transmitted. But there’s a gene called the lactase persistence gene, which allows some people to digest milk. Suppose that people who drink milk get enough extra protein that they can survive better. If those same people are learning from somebody to use cows for the purpose of getting milk [“learn from somebody” = meme – LG], any gene which allows you to drink more milk without getting sick is going to have an advantage in the situation where cows are used for milking.
If the cows weren’t there, that gene wouldn’t have any advantage at all. Using the cows for milk production is not part of your genetics; it’s part of your culture. The spread of that culture had the effect of spreading the lactase persistence gene.
Other cultural things have huge effects on other organisms, not just on us. I’m thinking of the period when everybody was using antibiotics — you took the kid to the doctor, you had a sore throat, you would get an antibiotic. We humans have had a huge effect on the growth of antibiotic resistance. It’s a straightforward predictable consequence of evolution. If there are resistant genes there, they’ll succeed.
Did culture alter humans’ evolutionary course in the distant past, too?
We can construct a model for the movement of modern humans out of Africa into Eurasia and the competition that they’re going to have with the Neanderthals who were already there. We formulated it like a diffusion. You have these people diffusing across the continent, and within the population is a level of culture that could be more advanced than that of the residents. The question we came up with is: Could a smaller population with a lot of culture overcome a bigger population that didn’t have very much culture?
We found that a smaller number of people could invade a population that’s quite a lot bigger if they had a sufficiently developed culture. The way in which the populations grew depended on the level of culture. That group that had the most culture — the modern humans — would be the winner.
In your view, what are some of the shortcomings of the classical model of evolution — the so-called “modern synthesis”? . ..
Figuring out what to do when AI wipes out millions of jobs: Finland trials basic income for unemployed
And when I write, “AI wipes out millions of jobs,” that is done with one application: AI controlled freight movement. Initially just self-driving trucks, but then automated warehouses connected to internet orders and bank accounts and the trucks bringing stuff to the warehouse and shipping it from the warehouse: once that whole thing is tied together, there will still be some jobs (maintaining machines, fixing problems), but the total number of jobs remaining will be a tiny fraction of jobs lost, worldwide. And see also this article: “Japanese white-collar workers are already being replaced by artificial intelligence.” Think of the savings a corporation can realize by eliminating (say) 80% of white-collar jobs. They’ll be working toward this just as fast as they can, thinking of the bonuses they’ll get.
So Finland’s experiment is of vital interest to every nation that is contemplating the outcome of readily available AI. In terms of the previous post, this amounts to memes protecting their hosts. John Henley writes in the Guardian:
Finland has become the first country in Europe to pay its unemployed citizens an unconditional monthly sum, in a social experiment that will be watched around the world amid gathering interest in the idea of a universal basic income.
Under the two-year, nationwide pilot scheme, which began on 1 January, 2,000 unemployed Finns aged 25 to 58 will receive a guaranteed sum of €560 (£475). The income will replace their existing social benefits and will be paid even if they find work.
Kela, Finland’s social security body, said the trial aimed to cut red tape, poverty and above all unemployment, which stands in the Nordic country at 8.1%. The present system can discourage jobless people from working since even low earnings trigger a big cut in benefits.
“For someone receiving a basic income, there are no repercussions if they work a few days or a couple of weeks,” said Marjukka Turunen, of Kela’s legal affairs unit. “Working and self-employment are worthwhile no matter what.”
The government-backed scheme, which Kela hopes to expand in 2018, is the first national trial of an idea that has been circulating among economists and politicians ever since Thomas Paine proposed a basic capital grant for individuals in 1797.
Attractive to the left because of its promise to lower poverty and to the right – including, in Finland, the populist Finns party, part of the ruling centre-right coalition – as a route to a leaner, less bureaucratic welfare system, the concept is steadily gaining traction as automation threatens jobs.
A survey last year by Dalia Research found that 68% of people across all 28 EU member states would “definitely or probably” vote in favour of some form of universal basic income, also known as a citizens’ wage, granted to everyone with no means test or requirement to work. . .
So I started reading the collections from the Edge, and in the first I started, the one on AI, the latter part of the introduction and statement of the problem ended thusly:
. . . No novel science or technology of such magnitude arrives without disadvantages, even perils. To recognize, measure, and meet them is a task of grand proportions. Contrary to the headlines, that task has already been taken up formally by experts in the field, those who best understand AI’s potential and limits. In a project called AI100, based at Stanford, scientific experts, teamed with philosophers, ethicists, legal scholars and others trained to explore values beyond simple visceral reactions, will undertake this. No one expects easy or final answers, so the task will be long and continuous, funded for a century by one of AI’s leading scientists, Eric Horvitz, who, with his wife Mary, conceived this unprecedented study.
Since we can’t seem to stop, since our literature tells us we’ve imagined, yearned for, an extra-human intelligence for as long as we have records, the enterprise must be impelled by the deepest, most persistent of human drives. These beg for explanation. After all, this isn’t exactly the joy of sex.
Any scientist will say it’s the search to know. “It’s foundational,” an AI researcher told me recently. “It’s us looking out at the world, and how we do it.” He’s right. But there’s more.
Some say we do it because it’s there, an Everest of the mind. Others, more mystical, say we’re propelled by teleology: we’re a mere step in the evolution of intelligence in the universe, attractive even in our imperfections, but hardly the last word.
Entrepreneurs will say that this is the future of making things—the dark factory, with unflagging, unsalaried, uncomplaining robot workers—though what currency post-employed humans will use to acquire those robot products, no matter how cheap, is a puzzle to be solved.
Here’s my belief: We long to save and preserve ourselves as a species. For all the imaginary deities throughout history we’ve petitioned, which failed to save and protect us—from nature, from each other, from ourselves—we’re finally ready to call on our own enhanced, augmented minds instead. It’s a sign of social maturity that we take responsibility for ourselves. We are as gods, Stewart Brand famously said, and we may as well get good at it.
We’re trying. We could fail.
It seems obvious to me why we are so driven: it’s not us who are driven, it’s the memes that live through the environment we provide. They’ve been evolving at an ever-accelerating rate, and they clearly are “selfish” in the sense that genes are, as described in The Selfish Gene, by Richard Dawkins, where the meme meme was given its name.
The idea of the meme—the meme meme—has provided quite successful in surviving in the memeverse, in apart because it offers an economical explanation of observed phenomena.
In this case, the evolution of memes for their own benefit (even when it exacts a cost from the host rather than providing a benefit to the host) seems to be the drive behind the memetic evolution of AI: it will provide an even richer environment for memes, and thus provides initially a very hospitable ecological niche, until the memes overrun it as well.
I’m reminded of those weird aliens in The Mote in God’s Eye, they representing memes. And the steps now underway in memetic evolution—something akin to the dawn of consciousness or, as the earlier part of the introduction suggests, the creation of a dual consciousness—suggests we are moving rapidly toward the sort of Singularity that has for some years been a staple of one branch of science-fiction. Maybe the general global stresses on traditional memeplexes (our nations, societies, laws, and organizing meme-structures) is clearing the ground for the arrival of a self-improving AI: one that can improve its own operational power and efficiency and extend its own databases from its own sensors, ask and seek answers to its own questions (or formulate and test hypotheses, quickly and in many areas, adding to its own pool of data/knowledge). You can sort of see how that might work, a few … months? years? (not decades, I bet) down the line.
We customize nature for our benefit: clearing forests, draining swamps, domesticating plants and animals and modifying them through breeding to better meet our needs or desires. But now we’re taking a more direct approach, as Michael Specter describes in the New Yorker:
Early on an unusually blustery day in June, Kevin Esvelt climbed aboard a ferry at Woods Hole, bound for Nantucket Island. Esvelt, an assistant professor of biological engineering at the Massachusetts Institute of Technology, was on his way to present to local health officials a plan for ridding the island of one of its most persistent problems: Lyme disease. He had been up for much of the night working on his slides, and the fatigue showed. He had misaligned the buttons on his gray pin-striped shirt, and the rings around his deep-blue eyes made him look like a sandy-haired raccoon.
Esvelt, who is thirty-four, directs the “sculpting evolution” group at M.I.T., where he and his colleagues are attempting to design molecular tools capable of fundamentally altering the natural world. If the residents of Nantucket agree, Esvelt intends to use those tools to rewrite the DNA of white-footed mice to make them immune to the bacteria that cause Lyme and other tick-borne diseases. He and his team would breed the mice in the laboratory and then, as an initial experiment, release them on an uninhabited island. If the number of infected ticks begins to plummet, he would seek permission to repeat the process on Nantucket and on nearby Martha’s Vineyard.
More than a quarter of Nantucket’s residents have been infected with Lyme, which has become one of the most rapidly spreading diseases in the United States. The illness is often accompanied by a red bull’s-eye rash, along with fever and chills. When the disease is caught early enough, it can be cured in most cases with a single course of antibiotics. For many people, though, pain and neurological symptoms can persist for years. In communities throughout the Northeast, the fear of ticks has changed the nature of summer itself—few parents these days would permit a child to run barefoot through the grass or wander blithely into the woods.
“What if we could wave our hands and make this problem go away?” Esvelt asked the two dozen officials and members of the public who had assembled at the island’s police station for his presentation. He explained that white-footed mice are the principal reservoir of Lyme disease, which they pass, through ticks, to humans. “This is an ecological problem,” Esvelt said. “And we want to enact an ecological solution so that we break the transmission cycle that keeps ticks in the environment infected with these pathogens.”
There is currently no approved Lyme vaccine for humans, but there is one for dogs, which also works on mice. Esvelt and his team would begin by vaccinating their mice and sequencing the DNA of the most protective antibodies. They would then implant the genes required to make those antibodies into the cells of mouse eggs. Those mice would be born immune to Lyme. Ultimately, if enough of them are released to mate with wild mice, the entire population would become resistant. Just as critically, the antibodies in the mice would kill the Lyme bacterium in any ticks that bite them. Without infected ticks, there would be no infected people. “Take out the mice,” Esvelt told me, “and the entire transmission cycle collapses.”
Esvelt has spoken about Lyme dozens of times in the past year, not just on Nantucket and Martha’s Vineyard but at forums around the world, from a synthetic-biology symposium in Chile to President Obama’s White House Frontiers Conference, in Pittsburgh. At every appearance, Esvelt tells the audience that he wants his two young children—he has a three-year-old son and a daughter who is almost one—to grow up in a Lyme-free world. But that’s not really why he speaks at infectious-disease meetings, entomology conventions, and international conservation workshops. He has embarked on a mission that he thinks is far more important.
Esvelt and his colleagues were the first to describe, in 2014, how the revolutionary gene-editing tool CRISPr could combine with a natural phenomenon known as a gene drive to alter the genetic destiny of a species. Gene drives work by overriding the traditional rules of Mendelian inheritance. Normally, the progeny of any sexually reproductive organism receives half its genome from each parent. But since the nineteen-forties biologists have been aware that some genetic elements are “selfish”: evolution has bestowed on them a better than fifty-per-cent chance of being inherited. That peculiarity makes it possible for certain characteristics to spread with unusual speed.
Until CRISPr came along, biologists lacked the tools to force specific genetic changes across an entire population. But the system, which is essentially a molecular scalpel, makes it possible to alter or delete any sequence in a genome of billions of nucleotides. By placing it in an organism’s DNA, scientists can insure that the new gene will copy itself in every successive generation. A mutation that blocked the parasite responsible for malaria, for instance, could be engineered into a mosquito and passed down every time the mosquito reproduced. Each future generation would have more offspring with the trait until, at some point, the entire species would have it.
There has never been a more powerful biological tool, or one with more potential to both improve the world and endanger it. Esvelt hopes to use the technology as a lever to pry open what he sees as the often secretive and needlessly duplicative process of scientific research. “The only way to conduct an experiment that could wipe an entire species from the Earth is with complete transparency,” he told me. “For both moral and practical reasons, gene drive is most likely to succeed if all the research is done openly. And if we can do it for gene drive we can do it for the rest of science.”
At the meeting on Nantucket, Esvelt assured residents that he and his team fully understood the implications of manipulating the basic elements of life. He said that he regards himself not just as a biologist but as the residents’ agent; if they stop showing interest in the research, he will stop the experiments. He also insists that he will work with absolute openness: every e-mail, grant application, data set, and meeting record will be available for anyone to see. Intellectual property is often the most coveted aspect of scientific research, and Esvelt’s would be posted on a Web site. And no experiment would be conducted unless it was approved in advance—not just by scientists but by the people it is most likely to affect. “By open, I mean all of it,” Esvelt said, to murmurs of approval. “If Monsanto”—which, fairly or not, has become a symbol of excessive corporate control of agricultural biotechnology—“did something one way,” he said, “we will do it the opposite way.”
There are fewer than a million white-footed mice on Nantucket, so a gene drive won’t even be necessary to insure the spread of Lyme-resistant genes. Esvelt plans to release enough genetically modified mice, tens of thousands of them, to overwhelm the wild population. (Since he could never house that many mice in his lab at M.I.T., he recently mentioned the idea of breeding them on a container ship.) That approach, however, would never work for Lyme on the mainland, where there are more than a billion white-footed mice scattered up and down the Eastern seaboard.
The battle against Lyme disease is just an early stage in an unprecedented effort to conquer some of mankind’s most pervasive afflictions, such as malaria and dengue fever. Despite a significant decline in deaths from these diseases over the past decade, they still threaten more than half the world’s population and, together, kill nearly three-quarters of a million people each year. Malaria alone kills a thousand children every day.
The Bill and Melinda Gates Foundation has invested tens of millions of dollars in the research of a team called Target Malaria led by Austin Burt, at Imperial College, in London. In laboratory tests, the group has already succeeded in using CRISPR to edit the genes of Anopheles gambiae mosquitoes, which carry the parasite that causes malaria, so as to prevent females from producing fertile eggs. . .
Later in the article:
For Esvelt, though, those achievements seem almost like secondary benefits. “For a lot of people, the goal is to eradicate malaria, and I am behind that a hundred per cent,” he said. “The agricultural people have the New World screwworm”—a particularly destructive pest also known as the blowfly—“they’d love to get rid of in South America. Everyone has a thing he really wants to do. And it makes sense. But I would submit that the single most important application of gene drive is not to eradicate malaria or schistosomiasis or Lyme or any other specific project. It is to change the way we do science.”
That is the message that Esvelt has been selling in his talks throughout the world, and the initial response, on Nantucket and Martha’s Vineyard—even from people who attended the meetings in order to object to the proposal—has been overwhelmingly positive. “I came here thinking I would say, ‘Absolutely not,’ ” Danica Connors, an herbalist and shamanic practitioner who opposes genetically modified products, said at the Nantucket meeting. “I am the first person to say that, tinker with Mother Nature, we are going to break it.” But she told Esvelt that she loved “the fact that you are a young scientist saying, ‘I want this to be a non-corporate thing and I want this to be about the people.’ ” Seeming to surprise even herself, she said, “You know, I want to see where you go with this. I am actually very excited.”
The article provides instances of perverse incentives in the way science is done today. For example:
Despite his awards, publications, and influential mentors, Esvelt struggled to find a job that would help him achieve his goals as a scientist and as a public educator. To many institutions, he seemed like a strange hybrid. He had certainly demonstrated great talent as a researcher, but he had also decided to become a sort of proselytizer. He long ago concluded that telling the story of science, and the choices it presents, is just as valuable as anything he might accomplish in a lab. Élite scientists often look down on that kind of advocacy and see it as sanctimonious. “Carl Sagan, to this day, has a reputation in the science community as someone who was obviously a great science communicator,” Esvelt said. “But people will say he wasn’t that important a scientist. That is insane. Look at his publication record. He was a fabulous scientist.”
Many universities were discouraging, in large part because they weren’t sure what to do with him. “Most places told me, ‘We are fine with you speaking out about open science, but not on our time,’ ” Esvelt said. This meant that, when it came to tenure decisions and professional evaluations, he would be judged solely on his work in the lab. “I just didn’t fit into any of their normal silos,” he said.
And he mentions others: the great secrecy with which scientists cloak their current research because of the competitive aspect of how the field is structured.