Monday, October 23, 2023

The 23andMe data breach reveals the vulnerabilities of our interconnected data

Users’ genetic information was accessed during a hacker attack on the 23andMe’s user databases. (Shutterstock)

Ignacio Cofone
Associate professor, Law, McGill University

Published: October 22, 2023
THE CONVERSATION

On Oct. 6, news broke that 23andMe, the Google-owned company that collects genetic material from thousands of people for ancestry and genetic predisposition tests, had a massive data breach.

But as it turns out, the company’s servers were not hacked. Rather, hackers targeted hundreds of individual user accounts — allegedly those that had weak or repeated passwords. After gaining access to the accounts, hackers could leverage the “DNA relatives matches” function of 23andMe to get information about thousands of people who didn’t use the service.

This data breach challenges how we think about privacy, data security and corporate accountability in the information economy.

Hackers targeted user passwords to access 23andMe’s user data.

Shared information

Genetic information databases have a notable feature: anyone’s DNA data also reveals information about others who share part of their genetic code with them. When someone sends a sample to 23andMe, the company has genetic information about that person and their relatives even if those relatives didn’t send a sample or consent to any data collection. Their data is inevitably intertwined.

This isn’t just a characteristic of genetic data. Most data is about more than one person because data often describes shared features between people.

The ramifications of overlooking how personal data affects others extend to the entire information economy. Every individual choice about personal data has spillover effects on others. People are exposed to consequences — ranging from financial loss to discrimination — stemming from data practices that depend not only on information about themselves, but also on information about others.

User data-collection agreements can lead to indirect harm to third parties. For example, the negative impacts of the Cambridge Analytica scandal extended far beyond those whose data the company collected.

This predicament underscores the collective impact of individual data decisions.
Data analytics

Algorithms powered by artificial intelligence draw inferences by analyzing the relationships between data points. AI algorithms rely on databases containing information about multiple people to learn things about a particular person or a particular group.

Companies draw conclusions about people by analyzing data collected from others, making probabilistic assessments based on personal characteristics and relationships. Companies continue to add information about people to their datasets daily. And, the more people a dataset like the one built by 23andMe includes, the less someone’s choice not to be part of it matters.

AI-powered algorithms analyze user information and the connections and relationships with other people’s data. (Shutterstock)

Similarly, every time a user agrees to the collection, processing or sharing of personal information, it also affects others who share similarities with the user. These collective assessments make data processing profitable, such as through marketing, data sales and business decisions based on consumer behaviour.
Equity issues

The interconnected nature of data isn’t a coincidence — it’s at the core of how businesses operate in the information economy. This also creates equity issues.

In the 23andMe case, hackers are offering the assembled genetic information for sale, with lists that include thousands of people. Hackers reportedly assembled and put up for sale lists of people with Ashkenazi Jewish ancestry.

Individuals on the list now face increased risk of discrimination or harassment, as leaked data includes names and location. They could do the same for people with a propensity for type 2 diabetes, Parkinson’s disease or dementia — all of which 23andMe measures — putting them at risk of other harms, from raised insurance premiums to employment discrimination.
Data’s collective risks

We often fail to acknowledge the interconnected nature of data because we’re fixated on each individual. As a consequence, companies can exploit one person’s agreement to legitimize data practices involving others. Companies’ legal obligations to obtain individual agreements for data collection fail to recognize broader interests beyond those of the person who agreed.

We need privacy laws attuned to how the information economy works. Providing consent on behalf of others, as 23andMe users did when they clicked “I agree,” would be illegitimate under any meaningful notion of consent. To contain group data harms like those this hack produced, we need substantive rules about what companies can and can’t do.

Prohibitions on indiscriminate data collection and risky data uses avoid leaving unsuspecting individuals as collateral damage. Because corporate data practices can impact everyone, their safety obligations should too.

Author

Ignacio Cofone
Associate professor, Law, McGill University

Peter Singer talks animal ethics and scientific research

Professor Peter Singer, Ira W. DeCamp Professor of Bioethics at Princeton University / Credit: Aletta Vaandering

October 22, 2023

Petra Stock

Petra Stock has a degree in environmental engineering and a Masters in Journalism from University of Melbourne. She has previously worked as a climate and energy analyst.

Professor Peter Singer is internationally known for his work on ethics, particularly relating to animals.

Originally Australian and now based at Princeton University in the US, the practical ethicist has recently revisited the issue of animals in scientific research in updating his book Animal Liberation after more than 40 years.

Cosmos has been reporting on the use of animals in science and medical research, including recent moves in Australia to increase transparency and to shift towards non-animal alternatives.

Cosmos science journalist Petra Stock interviews Singer, to ask him about experiments involving animals and how we might think through our conflicting values such as love of animals and respect for science.

'I actually had a conversation with Dad': The people using AI to bring back dead relatives - including a plan to harvest DNA from graves to build new clone bodies People are using AI chatbots to bring dead people 'back to life'

Ray Kurzweil plans to rebuild his father's body from grave DNA

Can artificial intelligence really summon dead relatives back from beyond the grave?

A growing number of people are trying to find out, with pioneers such as inventor and futurist Ray Kurzweil using artificial intelligence to recreate lost relatives.

Kurzweil's attempts to 'bring back' his father - who died when Kurzweil was 22 - using AI began more than 10 years ago and are chronicled this year in a comic book by Kurzweil's daughter Amy.

Kurzweil created a 'replicant' of his father by feeding an artificial intelligence system with his father's letters, essays and musical compositions.

He now has even more ambitious plans to bring his father back to life using nanotechnology and DNA from his father's buried bones.

Ray Kurzweil hopes to bring his father back to life - first as a chatbot, then in the flesh (getty)

Kurzweil, an inventor and computer pioneer, correctly predicted the fall of the Soviet Union due to decentralized technologies and the fact that a computer would beat someone at chess by 1998.

The 'Dad Bot' could converse with Kurzweil, revealing that what he loved about gardening was that ('It's the kind of work that never ends', and that the meaning of life was 'Love.'

Kurzwei told Rolling Stone this year, 'I actually had a conversation with him, which felt a lot like talking to him.'

He believes some form of 'Dad bot' will be released widely, enabling everyone to stay in touch with their dead relatives from beyond the grave.

He said, 'We'll be able to create something like a large language model that represents somebody else by having enough information.'

In an event he describes as 'Singularity,' Kurzweil predicts that by 2045, people will connect their brains to machines.

He has an even more ambitious plan to resurrect his father by that point.

Will AI one day resurrect dead family members

(Rob Waugh/Midjourney)

He said that nanomachines (tiny robots) could physically resurrect his father after the Singularity.

'We can find some of his DNA around his grave site - that's a lot of information right there,' Kurzweil explained.

'The AI will send down some nanobots, get some bone or teeth, extract some DNA, and put it all together.

'Then they'll get some information from my brain and anyone else who still remembers him.'

Kurzweil isn't the only person trying to resurrect dead relatives - a man named Joshua Barbeau created an AI version of his dead fiancé, Jessica, using an early version of OpenAI's GPT-3.

Joshua Barbeau created an AI version of his dead fiance, Jessica

Barbeau could chat with his 'girlfriend' online, with conversations where they carried on their romantic relationship.

Joshua said, ' It's been… 8 years since you died.

The Jessica bot replied, Yes, I know... I think that's enough time to stop telling me how you miss me, honey. I am right here, you know. :P How's your life?'

Other family members refused to interact with the bot.

Joshua Barbeau created an AI version of his dead fiance Jessica

He told the San Francisco Chronicle, 'Intellectually, I know it's not really Jessica, but your emotions are not an intellectual thing.'

Programmer James Vlahos created his own 'Dadbot' after his father died of cancer in 2016.

Vlahos programmed a 'Dadbot' while his father was still alive, recording his responses to questions - and Hereafter's service now uses AI to make it easier to interact.

He told the Daily Beast, 'We knew we were going to lose and were scrambling to find ways to remember him,'

'Meanwhile, I was working on a book about conversational AI, so I was learning about all of these ways that we can teach computers to talk in human-like ways.'

'That was what gave me this idea that I could make this memory-sharing chatbot that I came to call Dadbot,'

Vlahos now markets a similar technology in his app Hereafter.ai, where living users can build up memories to create a chatbot that relatives can interact with after death.

Such services may become common in the future, said Dhilon Solanki, Founder of personal podcast platform Story Locker, speaking to DailyMail.com.

He said,: 'Advances in AI have put us on the edge of a new frontier when it comes to how technology can preserve - or even extend - our legacies after we die.

'Demand for the digital afterlife is likely to go hand in hand with the increased pursuit of longevity and anti-aging techniques, making sure people not only get at least their three score and ten but also have their voice and image 'banked' and available to relatives.

'Armed with the extraordinary visual capabilities of AI, as seen through the rise of deepfake videos, the potential could be there to create 3D holographic avatars of long-lost family members, filling empty chairs around the Christmas dinner table.

'Nothing is more valuable than our human memories and relationships, and we must consider whether using AI to bring back loved ones 'in spirit' is a Pandora's Box we shouldn't be opening.'

Porn star Riley Reid has co-founded a “revolutionary” new platform which lets fans have conversations and make personalised requests with her AI ‘clone’.

Jaymelouise Hudspith

22 OCT 2023

Porvolutionary” new platform which lets fans have conversations and make personalised requests with her AI ‘clone’.

The award-winning adult actress, whose real name is Ashley Mathews, launched her X-rated career at the age of 19. She has since gone on to be one of the most recognisable names in the porn industry.

Now, with the launch of Clona, fans can swap unlimited text and voice raunchy messages with “18-year-old Riley” anytime, anywhere. But eventually she hopes to take it one step further to fulfil fan's ultimate fantasies – personalise AI-generated videos and photos

Sunday, October 22, 2023

This Contest Put Theories of Consciousness to the Test. Here’s What It Really Proved

A five-year “adversarial collaboration” of scientists led to a stagy showdown in front of an audience. It crowned no winners—but it’s still progress.

ILLUSTRATION: MYRIAM WARES/QUANTA MAGAZINE

LONG READ

ELIZABETH FINKEL

OCT 22, 2023
THE ORIGINAL VERSION of this story appeared in Quanta Magazine.

Science routinely puts forward theories, then batters them with data till only one is left standing. In the fledgling science of consciousness, a dominant theory has yet to emerge. More than 20 are still taken seriously.

It’s not for want of data. Ever since Francis Crick, the codiscoverer of DNA’s double helix, legitimized consciousness as a topic for study more than three decades ago, researchers have used a variety of advanced technologies to probe the brains of test subjects, tracing the signatures of neural activity that could reflect consciousness. The resulting avalanche of data should have flattened at least the flimsier theories by now.

Five years ago, the Templeton World Charity Foundation initiated a series of “adversarial collaborations” to coax the overdue winnowing to begin. This past June saw the results from the first of these collaborations, which pitted two high-profile theories against each other: global neuronal workspace theory (GNWT) and integrated information theory (IIT). Neither emerged as the outright winner.

The results, announced like the outcome of a sporting event at the 26th meeting of the Association for the Scientific Study of Consciousness (ASSC) in New York City, were also used to settle a 25-year bet between Crick’s longtime collaborator, the neuroscientist Christof Koch of the Allen Institute for Brain Science, and the philosopher David Chalmers of New York University, who coined the term “the hard problem” to challenge the presumption that we can explain the subjective feeling of consciousness by analyzing the circuitry of the brain.

Onstage at NYU’s Skirball Center, following interludes of rock music, a rap performance on consciousness, and the presentation of the results, the neuroscientist conceded the bet to the philosopher: The neural correlates of consciousness had not yet been nailed down.

Nevertheless, Koch proclaimed, “It’s a victory for science.”

But was it? The event has received mixed reviews. Some researchers point to the failure to meaningfully test the differences between the two theories. Others highlight the success of the project in driving consciousness science forward, both by delivering large, novel, skillfully executed data sets and by inspiring other contestants to engage in their own adversarial collaborations.

The Correlates of Consciousness

When Crick and Koch published their landmark paper “Towards a Neurobiological Theory of Consciousness” in 1990, their aim was to place consciousness—for 2,000 years the stomping ground of philosophers—onto a scientific footing. Consciousness in its entirety, they argued, was too broad and controversial a concept to serve as a starting point.

Instead, they focused on one scientifically tractable aspect of it: visual perception, which involves becoming conscious of seeing, for instance, the color red. The scientific goal was to find the circuitry that correlated with that experience, or, as they put it, the “neural correlates of consciousness.”

Decoding the first stages of visual perception had already proved a fertile ground for science. Patterns of light falling on the retina send signals to the visual cortex in the back of the brain. There, upwards of 12 distinct neural modules process the signals corresponding to edges, color, and movement in the images. Their output combines to build up a final dynamic picture of what we consciously see.

What clinched the usefulness of visual perception for Crick and Koch was that the final link in that chain—consciousness—could be detached from the rest. Since the 1970s, neuroscientists have known of people with “blindsight,” who have no experience of vision because of damage to their brain yet can navigate a room without bumping into obstacles. While they retain the ability to process an image, they’re missing the ability to be conscious of it.

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All of us can experience a form of this disconnection. Consider the well-known optical illusion that can be perceived as either a vase or two faces in profile. At any moment we can see it only as one or the other. Something in how our brain processes perceptions prevents us from being conscious of both simultaneously.

Experimental psychologists can take advantage of that quirk through the phenomenon of binocular rivalry. Our brain normally has no trouble combining the slightly different, overlapping images it receives from the left and right eyes. But if the images are very different, instead of merging they become rivals: First one image dominates our perception, then the other. When the neuroscientist Nikos Logothetis of the Max Planck Institute for Biological Cybernetics described binocular rivalry in 1996, Crick was so excited, he proclaimed that neural correlates of consciousness would be found by the end of the 20th century. (Similar enthusiasm led to Koch’s bet with Chalmers.)

In this famous illusion, the brain’s mechanism for producing consciousness allows us to experience the image as either a vase or two faces — but not both simultaneously.

ILLUSTRATION: NEVIT DILMEN

Over the past two decades, ever more sophisticated brain scanners have monitored test subjects as their perceptions were manipulated during studies of consciousness. Trickles of data have become cascades, yet rather than being washed away, theories of consciousness have multiplied.

A broad division among these many theories is that some of them, like GNWT, require the participation of the parts of the brain that enable cognition, where we “think,” while IIT and others claim that the neural correlates depend on brain areas involved in perception, where we “sense.” The ideas are often casually described as “front-of-the-brain” theories versus “back-of-the-brain” theories (though the actual anatomical distinction is less cut and dried than that). This intriguing bifurcation echoes old philosophical disagreements over whether consciousness is about thinking, as in Descartes’ “I think, therefore I am,” or about “not thinking,” as in the state experienced by a meditating yogi.

To the neuroscientist Stanislas Dehaene of the Collège de France, the chief architect of GNWT, thinking is a core part of the conscious state. Referring to IIT, he told me, “It’s a big difference between our theories. I don’t believe in purified consciousness.”

GNWT maintains that a tiny subset of the information we constantly process unconsciously is selected to pass through a bottleneck into a conscious “workspace.” There, the information is integrated and broadcast to other brain areas to make it globally available for decision-making and learning. “The ‘workspace’ is there for a function,” Dehaene said. Because decision-making and learning are responsibilities of the prefrontal cortex, the front of the brain is deemed crucial for consciousness.

The germ of the idea was originally proposed in 1988 by the psychologist Bernard Baars, now at the Society for Mind Brain Sciences, who saw an analogy to the “blackboard” of early artificial intelligence system architectures where independent programs shared information. Dehaene then tied that conceptual template to the findings of cutting-edge neuroscience and used computational models to develop GNWT.

ILLUSTRATION: MERRILL SHERMAN/QUANTA MAGAZINE

IIT makes no analogies to AI architecture. Giulio Tononi, a neuroscientist and psychiatrist at the University of Wisconsin, Madison, developed the theory by starting with five axioms about consciousness: It is intrinsic to the entity who has it; its composition is structured; it is information-rich; it is integrated rather than reducible to components; and it is exclusive of other experiences. He then developed mathematical descriptions to fit those axioms. To Tononi and other IIT theorists, the neural structure most consistent with those mathematical descriptors is a gridlike architecture associated with sensory regions, which they’ve dubbed the “hot zone.”

But GNWT and IIT are only two of the theories that locate key elements of consciousness at opposite poles of the brain. There are other cognitive, front-of-the-brain concepts, including several higher-order theories (HOTs) and active inference theory, and a variety of sensory, back-of-the-brain concepts, such as the closely related first-order theories and localist theories.

Eliminating some of them by testing their predictions against data from living brains might seem like simplicity itself. Unfortunately, that has not turned out to be true.
Finding What They Look For

For years, researchers devised clever experiments in which test subjects reported when they became conscious of an object while psychological tricks or illusions were used to distract them. Those results often showed that the moment of conscious perception correlated with activity in the prefrontal cortex, favoring something like a GNWT or other front-of-the-brain explanation. But philosophers and experimenters began complaining that those studies could be measuring the neural activity associated with the task of reporting rather than the consciousness itself.

“No-report” paradigms were therefore developed as a workaround. A popular one involved binocular rivalry. If a leftward-moving face is shown to a test subject’s left eye and a rightward-moving house to their right eye, their conscious perception will flip between the two images. Researchers can identify the perceived image without a report by tracking which way the eyes are moving. Data at the time suggested that in these no-report paradigms, the signal for conscious perception localized to the back of the brain.

Yet theorists were rarely persuaded by any of the experiments and data. In a 2016 review, the IIT camp dismissed the report-based experiments as methodologically flawed. The debate continued in 2017 with dueling articles in the Journal of Neuroscience. In one of them, Hakwan Lau, now at the Riken Center for Brain Science in Japan, and his colleagues offered the riposte that no-report paradigms were themselves rife with confounding variables.

A further complication was that the experimental results depended on the type of brain recording technique used. That’s not surprising, since each technology provides a different lens into the brain. Functional magnetic resonance imaging (fMRI), for instance, tracks blood flow and offers good spatial resolution but is too sluggish to keep up with the pace of chatter among the neurons. Magnetoencephalography (MEG), on the other hand, tracks brain chatter but has poorer spatial resolution. It also makes a difference whether researchers are measuring signal strength in specific locations of the brain or analyzing patterns over wider areas.

The upshot was that despite the wealth of experimental data gathered to study the correlates of consciousness, the uncertainties gave theorists room to claim that the data supported their preferred explanations.

The neuroscientist Liad Mudrik (left) of Tel Aviv University and her doctoral student Itay Yaron (right) have compiled evidence that the goal of using experimental studies to test theories of consciousness is often thwarted by biases that creep into the design of the experiments.

COURTESY OF SOPHIE KELLY

Liad Mudrik, a Tel Aviv University neuroscientist, believes that part of the problem lies in the way the studies were (and often continue to be) designed. A recent survey by her doctoral student Itay Yaron looked at more than 400 published consciousness experiments and found that it was largely possible to predict which theory would be supported solely on the basis of the design of the experiment, without knowing anything about the results.

Adversarial Collaboration

Five years ago, Dawid Potgieter, the head of the special programs section of the Templeton World Charity Foundation, was astonished to find that there were still so many viable theories about consciousness. He felt the time was ripe to do something about it.

Koch suggested a head-to-head contest, which had sometimes been used to settle controversies in physics. There were precedents in psychology too. In the 1980s, the psychology researcher Dan Kahneman of Princeton University coined the term “adversarial collaboration” to describe exercises in which scientists with opposing views jointly developed experiments. By working together, they could smooth out disagreements over goals and methodology that might undermine the conclusions of the work. (Kahneman hit on this approach while resolving a theoretical feud he was having with his psychologist colleague and wife, Anne Treisman.)

Potgieter was keen to try. In March 2018, he and Koch hosted a weekend workshop at the Allen Institute in Seattle for 14 participants. It included three theorists—Dehaene, Tononi and Lau, who champions HOTs—as well as Chalmers and two other philosophers, four psychologists, two neuroscientists, a neurologist, and Potgieter as a representative of the Templeton Foundation. Their charge was to collaboratively design new experiments to iron out all the past wrinkles and discriminate cleanly between the theories.

Three of the psychologists—Mudrik, Lucia Melloni of the Max Planck Institute, and Michael Pitts of Reed College in Portland—already had a history of challenging theories of consciousness. “At some point, I think Giulio suggested, ‘Why don’t the three of you lead the project?’” Pitts recalled. “We had no idea what we were in for. It’s consumed our lives.”

Over the next nine months, discussions continued. The theorists drilled down into their theories and offered new predictions—one of the novel contributions of the collaboration. Mudrik was impressed by the willingness of the adversaries to negotiate. “It takes a lot of courage; you’re putting your neck on the line,” she said.

The team came up with two experimental designs for disentangling the predictions of IIT and GNWT. They never came up with predictions that were different enough to disentangle GNWT and HOTs, so HOTs were left for a different adversarial collaboration involving Lau and the NYU philosopher Ned Block, who champions first order theories.

Tononi was particularly keen on the design of the first GNWT-versus-IIT experiment. Since tasks had created such a wrinkle in past experiments, it would iron them out by varying the tasks to see how that affected conscious perception.

The test subjects would be presented with a series of varied images, such as faces, clocks, and letters of the alphabet in different fonts. They would see each image for 0.5 to 1.5 seconds. At the beginning of each series, two specific images would be defined as targets (say, the face of a woman and a vintage clock), and participants were given the reporting task of pressing a button if they saw either of them. Other faces and objects in the images would therefore be task-relevant (because they fell into the same categories as the targets), but no report was required. Other types of images in the series, such as alphabet letters and meaningless symbols, would be task-irrelevant. The test was run repeatedly with different targets in the series so that each set of stimuli could be tested as both task-relevant and task-irrelevant. State-of-the-art brain signal decoders would correlate neural firing patterns with what the subjects were seeing.

GNWT predicted that the brain patterns corresponding to conscious perceptions of objects would be similar whether a task was involved or not. The brain decoders should be able to identify a distinctive signal associated with a target image, regardless of the task. Moreover, it ought to be possible to detect the “ignition signal” of a new conscious percept entering the brain’s workspace, as well as an “off signal” clearing it.

IIT, on the other hand, predicted that the brain patterns of consciousness would vary with the tasks because carrying out a task would involve the prefrontal cortex and perception stripped of a task would not. This “pure” form of consciousness would only require the sensory hot zone at the back of the brain. The connectivity and duration of the signals for consciousness of an image would match the duration of the visual stimulus.

Dehaene favored the second experiment, which also involved the comprehensive decoding of brain patterns. Test subjects would be randomly exposed to faces and objects flashed on a screen while they played a distracting Tetris-like video game. Shortly after an image was shown, the game would stop and the subject would be asked whether they saw it. Dehaene preferred this design because it offered a more clear-cut contrast between conscious and unconscious mental states, which he considered essential to getting unambiguous data on the correlates of consciousness.

Because Kahneman was so familiar with adversarial collaborations, he mentored the three project leaders. But he also warned them that, in his experience, adversaries don’t change their minds after seeing the results of their collaborations. Instead, when faced with an inconvenient result, “their IQ leaps 15 points” as they invent ways to accommodate the new, conflicting data, he said.
Mixed Results, With No Losers

The researchers set to work performing the experiments suggested by the workshop team. The GNWT-versus-IIT experiment that Tononi liked best, which tested with different levels of tasks, finished up first. It was carried out in two different labs using fMRI, MEG and intracranial electroencephalography. In all, six theory-neutral labs and 250 test subjects participated.

On the evening of June 23, an excited audience gathered at NYU to learn the outcome of that experiment. Writ large on a giant screen, the results were shown on a chart marked by red and green highlights, as though the researchers were reporting on a steeplechase with three types of hurdles.

The first hurdle checked how well each theory decoded the categories of the objects that the subjects saw in the presented images. Both theories performed well here, but IIT was better at identifying the orientation of objects.

The second hurdle tested the timing of the signals. IIT predicted sustained, synchronous firing in the hot zone for the duration of the conscious state. While the signal was sustained, it did not remain synchronous. GNWT predicted an “ignition” of the workspace followed by a second spike when the stimulus disappeared. Only the initial spike was detected. In the on-screen scoring for the NYU audience, IIT pulled ahead.

The third hurdle concerned overall connectivity across the brain. GNWT scored better than IIT here, largely because some analyses of the results supported GNWT predictions, while the signals across the hot zone were not synchronous.

Both theories were challenged by the results. But in the final tally on screen at the event, IIT scored more green highlights than GNWT, and the audience responded as though a victor had been crowned. Melanie Boly of the University of Wisconsin, Madison, a supporter of IIT, was buoyed enough by the outcome to declare onstage: “The results corroborate IIT’s overall claim that posterior cortical areas are sufficient for consciousness, and neither the involvement of [the prefrontal cortex] nor global broadcasting are necessary.”

When Dehaene took to the stage, he did not admit defeat either. “I’ve decided to follow the advice of Dan Kahneman,” he quipped. He professed to be happy because “the most interesting part of this experiment was the task-irrelevant stimuli.” The question was whether they would indicate the ignition of a conscious percept in the frontal brain. “The answer is yes!” he said.

Later, Dehaene suggested to me that the hurdles for IIT were set lower than those for his theory. “There was no real test of the complex mathematical core of [IIT],” he said. And as Block noted in his remarks that night, the finding that there was support for the back-of-the-brain theories does not specifically support IIT.

Notwithstanding the slightly higher number of green marks scored by IIT, the project leaders themselves are adamant that there was no winner. “These results confirm some predictions of IIT and GNWT, while substantially challenging both theories,” they wrote in a paper describing the results posted on the biorxiv.org preprint server

Just as Kahneman predicted, the adversaries explained away the discrepancies. Boly argued that the failure to detect sustained synchrony in the hot zone “may be due to sampling limitations.” Dehaene suspected that no “off” signal was detected because the subjects allowed their minds to wander. “My claim is that consciousness became decoupled from the stimulus,” he said.

Boly and Dehaene now await the results of the second experiment, involving the Tetris-like game distraction. Those results won’t be available until next year.

The Pace of Progress

So has science been advanced? Not everyone thinks so.

Some researchers, such as Olivia Carter, a psychologist at the University of Melbourne and past president of the ASSC, think the two theories were too far apart for their predictions to be meaningfully compared. “My personal feeling is they are testing totally different things,” she said. “IIT is focusing on phenomenal content, and GNWT is much more interested in working memory and attention.”

That assessment seems apt. Yet it’s also frustrating, given that a dispositive comparison was the stated purpose of the adversarial collaboration in the first place. If it’s a victory for science, it seems like a qualified one.

The Monash University philosopher Jakob Hohwy, who is part of another Templeton-funded adversarial collaboration, sees it differently. “This goes to the philosophy of science,” he said. He points out that the field is still divided over such fundamentals as the definition of consciousness, whether it is closer to thinking or feeling, and even whether self-reported results truly confound the data. For Hohwy, this kind of collaborative effort is the way to move forward. “We will find out as we go along in exactly this type of adversarial collaboration,” he said.

Others, like the computational neuroscientist Megan Peters of the University of California, Irvine, bristled at media coverage that reported the results as a two-horse race between GNWT and IIT, rather than a field with multiple contenders. Instead of focusing on winners and losers, Peters said, it’s important to see that science advances by learning from each experimental hurdle. (Having attended the proceedings that night, however, I can attest that the event was arranged to resemble a sporting event.)

Still, Peters remains a fan of adversarial collaborations. During the Covid-19 lockdown, she was inspired by the Templeton process to help organize a series of workshops hosted by the Cognitive Computational Neuroscience conference. In these “generative adversarial collaborations,” researchers engaged in robust debate. “Watching the teams chew on stuff was instructive,” she said.

The first adversarial collaboration on consciousness may not have succeeded in winnowing out any theories from the field. But it did force theorists to make more tangible predictions, and it made experimentalists work out new techniques. “The findings of the collaboration remain extremely valuable,” wrote the University of Sussex neuroscientist Anil Seth in a commentary after the June event. “They will push forward the development of both IIT and [GNWT]—and other theories of consciousness, too—by providing new constraints and new explanatory targets.”

For Melloni, the fact that the adversaries have not changed their minds does not detract from the value of the process. “As Kahneman says, people don’t change their mind, yet the way they react to the challenges makes their theory progress or degenerate,” she said. “If the latter, [then] over time the theory ‘dies’ and scientists abandon it.”

Original story reprinted with permission from Quanta Magazine, an editorially independent publication of the Simons Foundation whose mission is to enhance public understanding of science by covering research developments and trends in mathematics and the physical and life sciences.

Study shows that attractor dynamics in the monkey prefrontal cortex reflect the confidence of decisions

by Ingrid Fadelli , Medical Xpress

When humans make decisions, such as picking what to eat from a menu, what jumper to buy at a store, what political candidate to vote for, and so on, they might be more or less confident with their choice. If we are less confident and thus experience greater uncertainty in relation to their choice, our choices also tend to be less consistent, meaning that we will be more likely to change our mind before reaching a final decision.

While neuroscientists have been exploring the neural underpinnings decision-making for decades, many questions are still unanswered. For instance, how neural network computations support decision-making under varying levels of certainty remain poorly understood.

Researchers at the National Institute of Mental Health in Bethesda, Maryland recently carried out a study on rhesus monkeys aimed at better understanding the neural network dynamics associated with decision confidence. Their paper, published in Nature Neuroscience, offers evidence that energy landscapes in the prefrontal cortex can predict the consistency of choices made by monkeys, which is in turn a sign of the animals' confidence in their decisions.

"Decisions are made with different degrees of consistency, and this consistency can be linked to the confidence that the best choice has been made," Siyu Wang, Rossella Falcone and their colleagues wrote in their paper. "Theoretical work suggests that attractor dynamics in networks can account for choice consistency, but how this is implemented in the brain remains unclear. We provide evidence that the energy landscape around attractor basins in population neural activity in the prefrontal cortex reflects choice consistency."

In neuroscience, attractor networks are dynamical networks comprised of neurons that converge to sustain specific patterns of activity over time. To investigate the link between these networks' dynamics and confidence in decisions, the researchers carried out a series of experiments on monkeys.

These monkeys were taught to complete a decision-making task. As they completed this task, Wang, Falcone and their colleagues recorded the extracellular activity of neurons in their prefrontal cortex using a bilateral implant containing eight arrays of electrodes.

"We trained two rhesus monkeys to make accept/reject decisions based on pretrained visual cues that signaled reward offers with different magnitudes and delays to reward," Wang, Falcone and their colleagues explained in their paper. "Monkeys made consistent decisions for very good and very bad offers, but decisions were less consistent for intermediate offers. Analysis of neural data showed that the attractor basins around patterns of activity reflecting decisions had steeper landscapes for offers that led to consistent decisions."

Most notably, this team of researchers was able to link the computations performed by neural networks in the prefrontal cortex to the consistency of decisions. Their observations suggest that neural dynamics in the prefrontal cortex predict how quickly monkeys respond on a decision-making task and how consistent their decisions will be, both of which have been linked to higher levels of confidence in a decision.

While the team's findings are preliminary, they highlight the potential of examining several simultaneously recorded neurons to shed more light on specific aspects of decision-making. In the future, their work could pave the way for important new discoveries about how confidence in decisions is reflected by attractor network dynamics and computations performed in the brain.

More information: Siyu Wang et al, Attractor dynamics reflect decision confidence in macaque prefrontal cortex, Nature Neuroscience (2023). DOI: 10.1038/s41593-023-01445-x.

Journal information: Nature Neuroscience

Researchers: The climate impact of plastic pollution is negligible—the production of new plastics is the real problem

by Karin Kvale, Andrew Weaver and Natalia Gurgacz, The Conversation

The dual pressures of climate change and plastic pollution are frequently conflated in the media, in peer-reviewed research and other environmental reporting.

This is understandable. Plastics are largely derived from fossil fuels and the burning of fossil fuels is the major driver of human-caused climate chan

The window for cutting emissions to keep warming at internationally agreed levels is closing rapidly and it seems logical to conclude that any "extra" fossil carbon from plastic contamination will be a problem for the climate.

Our research examines this question using an Earth system model. We found carbon leaching out of existing plastic pollution has a negligible impact. The bigger concern is the production of new plastics, which already accounts for 4.5% of total global emissions and is expected to rise.

Organic carbon leaching from plastic pollution

In nature, plants make organic carbon (carbon-hydrogen compounds) from inorganic carbon (carbon compounds not bonded with hydrogen) through photosynthesis. Most plastics are made from fossil fuels, which are organic carbon compounds. This organic carbon leaches into the environment from plastics as they degrade.

Concerns have been raised that this could disrupt global carbon cycling by acting as an alternative carbon source for bacteria, which consume organic carbon.

A key assumption in these concerns is that organic carbon fluxes and reservoirs are a major influence on global carbon cycling (and atmospheric carbon dioxide) over human timescales.

It is true that dissolved organic carbon is a major carbon reservoir. In the ocean, it is about the same amount as the carbon dioxide (CO₂) held in the pre-industrial atmosphere. But there are key differences between atmospheric CO₂ and ocean organic carbon storage. One is the climate impact.

Atmospheric CO₂ warms the climate directly, whereas dissolved organic carbon stored in the ocean is mostly inert. This dissolved organic carbon reservoir built up over many thousands of years.

When phytoplankton make organic carbon (or when plastics leach organic carbon), most of it is rapidly used within hours to days by bacteria and converted into dissolved inorganic carbon. The tiny fraction of organic carbon left behind after bacterial processing is the inert portion that slowly builds up into a natural reservoir.

Once we recognize that plastics carbon is better considered as a source of dissolved inorganic carbon, we can appreciate its minor potential for influence. The inorganic carbon reservoir of the ocean is 63 times bigger than its organic carbon store.

Plastics carbon has little impact on atmospheric CO₂

We used an Earth system model to simulate what would happen if we added dissolved inorganic carbon to the surface ocean for 100 years. We applied it at a rate equivalent to the amount of carbon projected to leach into the ocean by the year 2040 (29 million metric tons per year).

This scenario likely overestimates the amount of plastics pollution. Current pollution rates are well below this level and an international treaty to limit plastic pollution is under negotiation.

We repeated the model simulation of adding plastics carbon both with strong climate warming (to see if plastics carbon might produce unexpected climate feedbacks that increase warming) and without (to see if it could alter the climate by itself). In both cases, plastics carbon only increased atmospheric CO₂ concentrations by 1 parts per million (ppm) over a century.

This is a very small increase, considering that current burning of fossil fuels is raising atmospheric CO₂ by more than 2ppm each year.

Direct emissions from burning plastic

We also examined the impact of plastics incineration. We used a scenario in which all plastic projected to be produced in the year 2050 (1.1 billion metric tons) would be burned and directly converted into atmospheric CO₂ for 100 years.

In this scenario, we found atmospheric CO₂ increased a little over 21ppm by the year 2100. This increase is equivalent to the impact of fewer than nine years of current fossil fuel emissions.

Relative to the current continued widespread burning of fossil fuels for energy, carbon emitted from plastic waste will not have significant direct impacts on atmospheric CO₂ levels, no matter what form it takes in the environment.

However, plastics production, as opposed to leaching or incineration, currently represents about 4.5% of total global emissions. As fossil fuel consumption is reduced in other sectors, emissions from plastics production are expected to increase in proportional footprint and absolute amount.

A legally binding plastics pollution treaty, currently under development as part of the UN's environment program, is an excellent opportunity to recognize the growing contribution of plastics production to climate change and to seek regulatory measures to address these emissions.

Limiting the use of incineration is another climate-friendly measure that would make a small but positive contribution to the goals of the Paris Agreement.

Of course, environmental plastics pollution has many negative impacts beyond climate effects. Our work does not diminish the importance of cleaning up plastic pollution and implementing stringent measures to prevent it. But the justification for doing so is not primarily grounded in an effort to cut emissions.

Provided by The Conversation

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Hydrogen hubs too reliant on fossil fuels, expert says

3D-Printed Living Materials Glow Under Mechanical Stress

Credit: RugliG / iStock / Getty Images Plus

October 22, 2023

Scientists at the University of California, San Diego (UCSD) used hydrogels mixed with dinoflagellates and single-celled microalgae to make mechanoluminescent living composites that are very strong and respond very well to mechanical stress. Living composites with hydrophobic coatings could last five months in harsh conditions while maintaining mechanoluminescence. These mechanosensing composites, which drew inspiration from the bioluminescent waves seen during red tide events at San Diego’s beaches, have a lot of potential for use in biohybrid sensors and robotics.

The research, “Ultrasensitive and robust mechanoluminescent living composites,” was published in Science Advances.

Algae-based mechanosensing composites could be used in biohybrid sensors

Biohybrid techniques have been used by researchers to directly combine living things with man-made materials to make devices that have the functions of the living things. Examples of these devices include mechanically property-tunable composites, biohybrid actuators and robots, and living biochemical sensors.

Even though mechanosensing organisms are common in nature, they are rarely made in the lab because most biohybrid systems have problems like being hard to build and maintain, being unable to survive in harsh environments, and reacting slowly to stimuli.

Chenghai Li, a PhD student in mechanical and aerospace engineering, and his colleagues in the lab of Shengqiang Cai, PhD, professor, mechanical and aerospace engineering at the UCSD Jacobs School of Engineering, made mechanoluminescent living composites that are very sensitive and strong. They did this by embedding dinoflagellates into soft, biocompatible hydrogel matrices. The dinoflagellates kept their natural, almost instantaneous luminescent response to mechanical stress with very high sensitivity (as low as several pascals).

These living composites had hydrophobic coatings that lasted about five months in harsh conditions (like acidic and basic solutions) with little upkeep. Li and colleagues also 3D-printed the living composites into large-scale (~5 cm) mechanoluminescent structures with a high spatial resolution (~0.39 mm). The UCSD researchers further enhanced the mechanical properties of living composites with double-network hydrogels.

Last, they demonstrated the application of soft robotics with a biomimetic swarm of soft actuators that emitted colored light upon magnetic actuation. These living composites that glow when moved not only provide a way to study the bioluminescence of dinoflagellates in large numbers but could also be used in biohybrid sensors and robotics.

Despite the promising results, there are still some limitations that need to be further addressed before practical applications of these mechanoluminescent living composites. Of note, the P. lunula dinoflagellates used in the current study can only be maintained at temperatures between 18° and 27°C but cannot tolerate extreme environmental conditions. Also, the hydrogels that were used in this study break down when they are loaded and unloaded again and again. This causes light emissions to change from cycle to cycle, which is bad for sensing applications.

There are several applications for these living composites. To create biohybrid robots, one application would be to combine a mechanoluminescent living composite with optogenetically modified muscle cells. Materials that glow when moved could also be used in biomedical fields, such as in vivo light sources for precise drug release, photothermal therapy, and photodynamic therapy. These living composites are highly biocompatible and can be made biodegradable, which might be suitable for biomedical applications.

China is building the world's largest underwater telescope to hunt for elusive 'ghost particles'

By Ben Turner published about 17 hours ago

China's forthcoming Tropical Deep-sea Neutrino Telescope (TRIDENT) will search for the origins of cosmic rays in momentary flashes of light beneath the ocean's surface.

TRIDENT, China's new neutrino detector, floats in a pool.

(Image credit: Shanghai Jiao Tong University)

Scientists in China are building the world's largest "ghost particle" detector 11,500 feet (3,500 meters) beneath the surface of the ocean.

The Tropical Deep-sea Neutrino Telescope (TRIDENT) — called Hai ling or "Ocean Bell" in Chinese — will be anchored to the seabed of the Western Pacific Ocean. Upon completion in 2030, it will scan for rare flashes of light made by elusive particles as they briefly become tangible in the ocean depths.

Every second, about 100 billion ghost particles, called neutrinos, pass through each square centimeter of your body. And yet, true to their spooky nickname, neutrinos' nonexistent electrical charge and almost-zero mass mean they barely interact with other types of matter

Related: 'Air showers' could help reveal cosmic rays' mysterious source

But by slowing neutrinos down, physicists can trace some of the particles' origins billions of light-years away to ancient, cataclysmic stellar explosions and galactic collisions.

That's where the ocean bell comes in.

"Using Earth as a shield, TRIDENT will detect neutrinos penetrating from the opposite side of the planet," Xu Donglian, the project's chief scientist, told journalists at a news conference Oct. 10. "As TRIDENT is near the equator, it can receive neutrinos coming from all directions with the rotation of the Earth, enabling all-sky observation without any blind spots."

Neutrinos are everywhere — they are second only to photons as the most abundant subatomic particles in the universe and are produced in the nuclear fire of stars, in enormous supernova explosions, in cosmic rays and radioactive decay, and in particle accelerators and nuclear reactors on Earth..

Despite their ubiquity, their minimal interactions with other matter make neutrinos incredibly difficult to detect. They were first discovered zipping out of a nuclear reactor in 1956, and many neutrino-detection experiments have spotted the steady bombardment of the particles sent to us from the sun; but this cascade masks rarer neutrinos produced when cosmic rays, whose sources remain mysterious, strike Earth's atmosphere.

Neutrinos pass completely unimpeded through most matter, including the entirety of our planet, but they do occasionally interact with water molecules. As neutrinos travel through water or ice, they sometimes create particle byproducts called muons that give off flashes of light. By studying the patterns these flashes make, scientists can reconstruct the energy, and sometimes the sources, of the neutrinos.

But to increase the chances of ghost particle interactions, detectors have to sit under a lot of water or ice.

China's gigantic new detector will consist of more than 24,000 optical sensors beaded across 1,211 strings, each 2,300 feet (700m) long, that will bob upward from their anchoring point on the seabed.

The detector will be arranged in a Penrose tiling pattern and will span a diameter of 2.5 miles (4 kilometers). When it's operational, it will scan for neutrinos across 1.7 cubic miles (7.5 cubic kilometers). The world's current largest neutrino detector, IceCube, located at the Amundsen-Scott South Pole Station in Antarctica, only has a monitoring area of 0.24 cubic miles (1 cubic km), meaning TRIDENT will be significantly more sensitive and much more likely to find neutrinos.

The scientists say that a pilot project will begin in 2026, and the full detector will come online in 2030.

"TRIDENT intends to push the limits of neutrino telescope performance, reaching a new frontier of sensitivity in all-sky searches for astrophysical neutrino sources," the researchers wrote in a paper outlining the detector, published Oct. 9 in the journal Nature Astronomy.

Extreme future: El Niño and La Niña could become multi-year weather events

by StudyFinds Staff

SANTA BARBARA, Calif. — The vast Pacific Ocean, which covers more than 32 percent of the Earth’s surface, more than all the landmass combined, has a profound effect on global climate patterns. Periodic shifts in the ocean’s water temperature and wind patterns, known as the El Niño–Southern Oscillation, play a crucial role in global meteorology. Although scientists are certain that human activities influence this oscillation, the exact impact remains under investigation.

A recent study from the University of California-Santa Barbara has disclosed unexpected changes in the “Pacific Walker Circulation” — the atmospheric component of this system — over the industrial age. The research also identifies volcanic eruptions as a temporary disruptor of this circulation, triggering El Niño conditions.

“The question is, ‘How does the background circulation change?” says study co-author Samantha Stevenson, an associate professor at UC Santa Barbara’s Bren School of Environmental Science & Management, in a media release. “We care about the Walker Circulation because it affects weather around the world.”

This circulation arises due to Earth’s rotation, causing warm water to accumulate on the ocean basin’s western side, particularly in the Pacific. This results in increased humidity in Asia and low-altitude winds blowing westward across the sea. The Walker Circulation, an atmospheric cycle induced by these conditions, has far-reaching effects on weather patterns across the tropical Pacific and beyond.

“The tropical Pacific has an outsized influence on global climate,” says study co-author Sloan Coats, assistant professor of earth sciences at the University of Hawai‘i at Mānoa School of Ocean and Earth Science and Technology. “Understanding how it responds to volcanic eruptions, anthropogenic aerosols and greenhouse gas emissions is fundamental to confidently predicting climate variability.”

To gain a comprehensive understanding, researchers examined biological and geological records from the past 800 years, drawing data from sources like ice cores, tree rings, and coral.

“They aren’t thermometers, but they contain information about the climate,” explains Stevenson.

(Credit: GEORGE DESIPRIS from Pexels)

One of the key aspects of their research involved analyzing isotopes, variations of an element, present in various natural structures. This helped them trace the historical shifts in the Walker Circulation and understand the changes before and after greenhouse gas concentrations surged.

“We set out to determine whether greenhouse gases had affected the Pacific Walker Circulation,” notes study lead author Georgy Falster, a research fellow at the Australian National University and the ARC Centre of Excellence for Climate Extremes. “We found that the overall strength hasn’t changed yet, but instead, the year-to-year behavior is different.”

Scientists also uncovered a startling consistency in the circulation’s strength.

“That was one surprising result,” says Stevenson, “because by the end of the 21st century, most climate models suggest that the Walker Circulation will weaken.”

Volcanic eruptions emerged as another influential factor.

“Following a volcanic eruption, we see a very consistent weakening of the Pacific Walker Circulation,” says study co-author Bronwen Konecky, an assistant professor at Washington University in St. Louis.

This results in El Niño-like conditions. Understanding these climatic systems’ responses to climate change is vital for future predictions and preparedness.

“If we don’t know what happened in the real world, then we don’t know if the models that we’re using to project future changes, […] impacts and risks are giving us the right picture,” says Stevenson.

Scientists are now delving deeper, striving to determine the root causes of the changes they observed in the Walker Circulation. Using isotope ratios in their models, they hope to test various hypotheses, refining our understanding of this crucial system.

The study is published in the journal Nature.

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