Could an algorithm predict the next pandemic?

Curated on Posted on by Stefaan Verhulst

Article by Simon Makin: “Leap is a machine-learning algorithm that uses sequence data to classify influenza viruses as either avian or human. The model had been trained on a huge number of influenza genomes — including examples of H5N8 — to learn the differences between those that infect people and those that infect birds. But the model had never seen an H5N8 virus categorized as human, and Carlson was curious to see what it made of this new subtype.

Somewhat surprisingly, the model identified it as human with 99.7% confidence. Rather than simply reiterating patterns in its training data, such as the fact that H5N8 viruses do not typically infect people, the model seemed to have inferred some biological signature of compatibility with humans. “It’s stunning that the model worked,” says Carlson. “But it’s one data point; it would be more stunning if I could do it a thousand more times.”

The zoonotic process of viruses jumping from wildlife to people causes most pandemics. As climate change and human encroachment on animal habitats increase the frequency of these events, understanding zoonoses is crucial to efforts to prevent pandemics, or at least to be better prepared.

Researchers estimate that around 1% of the mammalian viruses on the planet have been identified1, so some scientists have attempted to expand our knowledge of this global virome by sampling wildlife. This is a huge task, but over the past decade or so, a new discipline has emerged — one in which researchers use statistical models and machine learning to predict aspects of disease emergence, such as global hotspots, likely animal hosts or the ability of a particular virus to infect humans. Advocates of such ‘zoonotic risk prediction’ technology argue that it will allow us to better target surveillance to the right areas and situations, and guide the development of vaccines and therapeutics that are most likely to be needed.

However, some researchers are sceptical of the ability of predictive technology to cope with the scale and ever-changing nature of the virome. Efforts to improve the models and the data they rely on are under way, but these tools will need to be a part of a broader effort if they are to mitigate future pandemics…(More)”.

Avert Bangladesh’s looming water crisis through open science and better data

Curated on Posted on by Stefaan Verhulst

Article by Augusto Getirana et al: “Access to data is a huge problem. Bangladesh collects a large amount of hydrological data, such as for stream flow, surface and groundwater levels, precipitation, water quality and water consumption. But these data are not readily available: researchers must seek out officials individually to gain access. India’s hydrological data can be similarly hard to obtain, preventing downstream Bangladesh from accurately predicting flows into its rivers.

Bilateral scientific collaboration between Bangladesh and water-sharing nations, including India, Nepal, Bhutan and China, would be mutually beneficial. The decades-long Mekong River Commission between Cambodia, Laos, Thailand and Vietnam is one successful transboundary agreement that could serve as a model.

Publishing hydrological data in an open-access database would be an exciting step. For now, however, the logistics, funding and politics to make on-the-ground data publicly available are likely to remain out of reach.

Fortunately, satellite data can help to fill the gaps. Current Earth-observing satellite missions, such as the Gravity Recovery and Climate Experiment (GRACE) Follow-On, the Global Precipitation Measurement (GPM) network, multiple radar altimeters and the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors make data freely available and can provide an overall picture of water availability across the country (this is what we used in many of our analyses). The picture is soon to improve. In December, NASA and CNES, France’s space agency, plan to launch the Surface Water and Ocean Topography (SWOT) satellite mission. SWOT will provide unprecedented information on global ocean and inland surface waters at fine spatial resolution, allowing for much more detailed monitoring of water levels than is possible today. The international scientific community has been working hard over the past 15 years to get ready to store, process and use SWOT data.

New open-science initiatives, particularly NASA’s Earth Information System, launched in 2021, can help by supporting the development of customized data-analysis and modelling tools (see go.nature.com/3cffbh9). The data we present here were acquired in this framework. We are currently working on an advanced hydrological model that will be capable of representing climate-change effects and human impacts on Bangladesh’s water availability. We expect that the co-development of such a modelling system with local partners will support decision-making.

SERVIR, a joint programme of NASA and the US Agency for International Development that focuses on capacity-building, could also help improve forecasting of severe weather for Bangladesh, for example. This could improve the flood monitoring and forecast system operated by the Bangladesh Water Development Board, which is limited in geographical scope — flooding is monitored only at specific locations, not across the country. Such efforts will help with short-term adaptation and emergency responses to flood conditions, and with long-term planning for infrastructure…(More)”.

Digitization, Surveillance, Colonialism

Curated on Posted on by Stefaan Verhulst

Essay by Carissa Veliz: “As I write these words, articles are mushrooming in newspapers and magazines about how privacy is more important than ever after the Supreme Court ruling that has overturned the constitutionality of the right to have an abortion in the United States. In anti-abortion states, browsing histories, text messages, location data, payment data, and information from period-tracking apps can all be used to prosecute both women seeking an abortion and anyone aiding them. The National Right to Life Committee recently published policy recommendations for anti-abortion states that include criminal penalties for people who provide information about self-managed abortions, whether over the phone or online. Women considering an abortion are often in distress, and now they cannot even reach out to friends or family without endangering themselves and others. 

So far, Texas, Oklahoma, and Idaho have passed citizen-enforced abortion bans, according to which anyone can file a civil lawsuit to report an abortion and have the chance of winning at least ten thousand dollars. This is an incredible incentive to use personal data towards for-profit witch-hunting. Anyone can buy personal data from data brokers and fish for suspicious behavior. The surveillance machinery that we have built in the past two decades can now be put to use by authorities and vigilantes to criminalize pregnant women and their doctors, nurses, pharmacists, friends, and family. How productive.

It is not true, however, that the overturning of Roe v. Wade has made privacy more important than ever. Rather, it has provided yet another illustration of why privacy has always been and always will be important. That it is happening in the United States is helpful, because human beings are prone to thinking that whatever happens “over there” — say, in China now, or in East Germany during the Cold War — to those “other people,” doesn’t happen to us — until it does. 

Privacy is important because it protects us from possible abuses of power. As long as human beings are human beings and organizations are organizations, abuses of power will be a constant temptation and threat. That is why it is supremely reckless to build a surveillance architecture. You never know when that data might be used against you — but you can be fairly confident that sooner or later it will be used against you. Collecting personal data might be convenient, but it is also a ticking bomb; it amounts to sensitive material waiting for the chance to turn into an instance of public shaming, extortion, persecution, discrimination, or identity theft. Do you think you have nothing to hide? So did many American women on June 24, only to realize that week that their period was late. You have plenty to hide — you just don’t know what it is yet and whom you should hide it from.

In the digital age, the challenge of protecting privacy is more formidable than most people imagine — but it is nowhere near impossible, and every bit worth putting up a fight for, if you care about democracy or freedom. The challenge is this: the dogma of our time is to turn analog into digital, and as things stand today, digitization is tantamount to surveillance…(More)”.

How Confucianism could put fear about Artificial Intelligence to bed

Curated on Posted on by Stefaan Verhulst

Article by Tom Cassauwers: “Western culture has had a long history of individualism, warlike use of technology, Christian apocalyptic thinking and a strong binary between body and soul. These elements might explain the West’s obsession with the technological apocalypse and its opposite: techno-utopianism. In Asia, it’s now common to explain China’s dramatic rise as a leader in AI and robotics as a consequence of state support from the world’s largest economy. But what if — in addition to the massive state investment — China and other Asian nations have another advantage, in the form of Eastern philosophies?

There’s a growing view among independent researchers and philosophers that Confucianism and Buddhism could offer healthy alternative perspectives on the future of technology. And with AI and robots rapidly increasing in importance across industries, it’s time for the West to turn to the East for answers…

So what would a non-Western way of thinking about tech look like? First, there might be a different interpretation of personhood. Both Confucianism and Buddhism potentially open up the way for nonhumans to reach the status of humans. In Confucianism, the state of reaching personhood “is not a given. You need to work to achieve it,” says Wong. The person’s attitude toward certain ethical virtues determines whether or not they reach the status of a human. That also means that “we can attribute personhood to nonhuman things like robots when they play ethically relevant roles and duties as humans,” Wong adds.

Buddhism offers a similar argument, where robots can hypothetically achieve a state of enlightenment, which is present everywhere, not only in humans — an argument made as early as the 1970s by Japanese roboticist Masahiro Mori. It may not be a coincidence that robots enjoy some of their highest social acceptance in Japan, with its Buddhist heritage. “Westerners are generally reluctant about the nature of robotics and AI, considering only humans as true beings, while Easterners more often consider devices as similar to humans,” says Jordi Vallverdú, a professor of philosophy at the Autonomous University of Barcelona….(More)”

Philanthropy to Protect US Democracy

Curated on Posted on by Stefaan Verhulst

Essay by Lukas Haynes: “…Given the threat of election subversion, philanthropists who care about democracy across the political spectrum must now deploy donations as effectively as they can. In their seminal book, Money Well Spent: A Strategic Plan for Smart Philanthropy, Paul Brest and Hal Harvey argue that generating “alternative solutions” to hard problems “requires creativity or innovation akin to that of a scientist or engineer—creativity that is goal-oriented, that aims to come up with pragmatic solutions to a problem.”

In seeking the most effective solutions, Brest and Harvey do not find that nonpartisan, charitable efforts are the only legitimate form of strategic giving. Instead, they encourage donors to identify clear problem-solving goals, sound strategy, and clarity about risk tolerance.

Given the concerted attack on democratic norms by political candidates, there is no more effective alternative at hand than using political donations to defeat those candidates. If it is not already part of donors’ philanthropic toolkit to protect democracy, it needs to be and soon.

Once Big Lie-promoting candidates win and take power over elections, it will be too late to repeal their authority, especially in states where Republicans control the state legislatures. Should they successfully subvert a national presidential election in a deeply polarized nation, the United States will have crossed an undemocratic Rubicon no well-intentioned American wants to witness. So what are the most effective ways for political donors to respond to this perilous moment?…(More)”.

Citizens’ Assemblies Are Upgrading Democracy: Fair Algorithms Are Part of the Program

Curated on Posted on by Stefaan Verhulst

Essay by Ariel Procaccia: “In 1983 the Eighth Amendment to the Irish constitution enshrined an abortion ban that had prevailed in the nation for more than a century. Public opinion on the issue shifted in the new millennium, however, and by 2016 it was clear that a real debate could no longer be avoided. But even relatively progressive politicians had long steered clear of the controversy rather than risk alienating voters. Who would be trustworthy and persuasive enough to break the deadlock?

The answer was a bunch of ordinary people. Seriously. The Irish Parliament convened a citizens’ assembly, whose 99 members were chosen at random. The selection process ensured that the group’s composition represented the Irish population along dimensions such as age, gender and geography. Over several months in 2016 and 2017, the assembly heard expert opinions and held extensive discussions regarding the legalization of abortion. Its recommendation, supported by a significant majority of members, was to allow abortions in all circumstances, subject to limits on the length of pregnancy. These conclusions set the stage for a 2018 referendum in which 66 percent of Ireland’s voters chose to repeal the Eighth Amendment, enabling abortion to be legalized. Such an outcome had been almost inconceivable a few years earlier.

The Irish citizens’ assembly is just one example of a widespread phenomenon. In recent years hundreds of such groups have convened around the world, their members randomly selected from the concerned population and given time and information to aid their deliberations. Citizens’ assemblies in France, Germany, the U.K., Washington State and elsewhere have charted pathways for reducing carbon emissions. An assembly in Canada sought methods of mitigating hate speech and fake news; another in Australia recommended ethical approaches to human genome editing; and yet another in Oregon identified policies for COVID pandemic recovery. Taken together, these assemblies have demonstrated an impressive capacity to uncover the will of the people and build consensus.

The effectiveness of citizens’ assemblies isn’t surprising. Have you ever noticed how politicians grow a spine the moment they decide not to run for reelection? Well, a citizens’ assembly is a bit like a legislature whose members make a pact barring them from seeking another term in office. The randomly selected members are not beholden to party machinations or outside interests; they are free to speak their mind and vote their conscience…(More)”.

Big Tech Goes to War

Curated on Posted on by Stefaan Verhulst

Article by Christine H. Fox and Emelia S. Probasco: “Even before he made a bid to buy Twitter, Elon Musk was an avid user of the site. It is a reason Ukraine’s Minister of Digital Transformation Mykhailo Fedorov took to the social media platform to prod the SpaceX CEO to activate Starlink, a SpaceX division that provides satellite internet, to help his country in the aftermath of Russia’s invasion. “While you try to colonize Mars—Russia try [sic] to occupy Ukraine!” Fedorov wrote on February 26. “We ask you to provide Ukraine with Starlink stations.”

“Starlink service is now active in Ukraine,” Musk tweeted that same day. This was a coup for Ukraine: it facilitated Ukrainian communications in the conflict. Starlink later helped fend off Russian jamming attacks against its service to Ukraine with a quick and relatively simple code update. Now, however, Musk has gone back and forth on whether the company will continue funding the Starlink satellite service that has kept Ukraine and its military online during the war.

The tensions and uncertainty Musk is injecting into the war effort demonstrate the challenges that can emerge when companies play a key role in military conflict. Technology companies ranging from Microsoft to Silicon Valley start-ups have provided cyberdefense, surveillance, and reconnaissance services—not by direction of a government contract or even as a part of a government plan but instead through the independent decision-making of individual companies. These companies’ efforts have rightly garnered respect and recognition; their involvement, after all, were often pro bono and could have provoked Russian attacks on their networks, or even their people, in retaliation…(More)”.

How Do You Prove a Secret?

Curated on Posted on by Stefaan Verhulst

Essay by Sheon Han: “Imagine you had some useful knowledge — maybe a secret recipe, or the key to a cipher. Could you prove to a friend that you had that knowledge, without revealing anything about it? Computer scientists proved over 30 years ago that you could, if you used what’s called a zero-knowledge proof.

For a simple way to understand this idea, let’s suppose you want to show your friend that you know how to get through a maze, without divulging any details about the path. You could simply traverse the maze within a time limit, while your friend was forbidden from watching. (The time limit is necessary because given enough time, anyone can eventually find their way out through trial and error.) Your friend would know you could do it, but they wouldn’t know how.

Zero-knowledge proofs are helpful to cryptographers, who work with secret information, but also to researchers of computational complexity, which deals with classifying the difficulty of different problems. “A lot of modern cryptography relies on complexity assumptions — on the assumption that certain problems are hard to solve, so there has always been some connections between the two worlds,” said Claude Crépeau, a computer scientist at McGill University. “But [these] proofs have created a whole world of connection.”

Zero-knowledge proofs belong to a category known as interactive proofs, so to learn how the former work, it helps to understand the latter. First described in a 1985 paper by the computer scientists Shafi Goldwasser, Silvio Micali and Charles Rackoff, interactive proofs work like an interrogation: Over a series of messages, one party (the prover) tries to convince the other (the verifier) that a given statement is true. An interactive proof must satisfy two properties. First, a true statement will always eventually convince an honest verifier. Second, if the given statement is false, no prover — even one pretending to possess certain knowledge — can convince the verifier, except with negligibly small probability…(More)”

The Exploited Labor Behind Artificial Intelligence

Curated on Posted on by Stefaan Verhulst

Essay by Adrienne Williams, Milagros Miceli, and Timnit Gebru: “The public’s understanding of artificial intelligence (AI) is largely shaped by pop culture — by blockbuster movies like “The Terminator” and their doomsday scenarios of machines going rogue and destroying humanity. This kind of AI narrative is also what grabs the attention of news outlets: a Google engineer claiming that its chatbot was sentient was among the most discussed AI-related news in recent months, even reaching Stephen Colbert’s millions of viewers. But the idea of superintelligent machines with their own agency and decision-making power is not only far from reality — it distracts us from the real risks to human lives surrounding the development and deployment of AI systems. While the public is distracted by the specter of nonexistent sentient machines, an army of precarized workers stands behind the supposed accomplishments of artificial intelligence systems today.

Many of these systems are developed by multinational corporations located in Silicon Valley, which have been consolidating power at a scale that, journalist Gideon Lewis-Kraus notes, is likely unprecedented in human history. They are striving to create autonomous systems that can one day perform all of the tasks that people can do and more, without the required salaries, benefits or other costs associated with employing humans. While this corporate executives’ utopia is far from reality, the march to attempt its realization has created a global underclass, performing what anthropologist Mary L. Gray and computational social scientist Siddharth Suri call ghost work: the downplayed human labor driving “AI”.

Tech companies that have branded themselves “AI first” depend on heavily surveilled gig workers like data labelers, delivery drivers and content moderators. Startups are even hiring people to impersonate AI systems like chatbots, due to the pressure by venture capitalists to incorporate so-called AI into their products. In fact, London-based venture capital firm MMC Ventures surveyed 2,830 AI startups in the EU and found that 40% of them didn’t use AI in a meaningful way…(More)”.

Leveraging Data for the Public Good

Curated on Posted on by Stefaan Verhulst

Article by Christopher Pissarides, Fadi Farra and Amira Bensebaa: “…Yet data are simply too important to be entrusted to either governments or large corporations that treat them as their private property. Instead, governments should collaborate with companies on joint-governance frameworks that recognize both the opportunities and the risks of big data.

Businesses – which are best positioned to understand big data’s true value – must move beyond short‐sighted efforts to prevent regulation. Instead, they need to initiate a dialogue with policymakers on how to design viable solutions that can leverage the currency of our era to benefit the public good. Doing so would help them regain public trust.

Governments, for their part, must avoid top‐down regulatory strategies. To win the support they need from businesses, they need to create incentives for data sharing and privacy protection and help develop new analytical tools through advanced modeling. Governments should also rethink and renew deeply-rooted frameworks inherited from the industrial era, such as those for taxation and social welfare.

In the digital age, governments should recognize the centrality of data to policymaking and develop tools to reward businesses that contribute to the public good by sharing it. True, governments require taxes to raise revenues, but they must recognize that a better understanding of individuals enables more efficient policies. By recognizing companies’ ability to save public money and create social value, governments could encourage companies to share data as a matter of social responsibility…(More)”.