Facebook-owner Meta to share more political ad targeting data

Curated on Posted on by Stefaan Verhulst

Article by Elizabeth Culliford: “Facebook owner Meta Platforms Inc (FB.O) will share more data on targeting choices made by advertisers running political and social-issue ads in its public ad database, it said on Monday.

Meta said it would also include detailed targeting information for these individual ads in its “Facebook Open Research and Transparency” database used by academic researchers, in an expansion of a pilot launched last year.

“Instead of analyzing how an ad was delivered by Facebook, it’s really going and looking at an advertiser strategy for what they were trying to do,” said Jeff King, Meta’s vice president of business integrity, in a phone interview.

The social media giant has faced pressure in recent years to provide transparency around targeted advertising on its platforms, particularly around elections. In 2018, it launched a public ad library, though some researchers criticized it for glitches and a lack of detailed targeting data.Meta said the ad library will soon show a summary of targeting information for social issue, electoral or political ads run by a page….The company has run various programs with external researchers as part of its transparency efforts. Last year, it said a technical error meant flawed data had been provided to academics in its “Social Science One” project…(More)”.

The Era of Borderless Data Is Ending

Curated on Posted on by Stefaan Verhulst

David McCabe and Adam Satariano at the New York Times: “Every time we send an email, tap an Instagram ad or swipe our credit cards, we create a piece of digital data.

The information pings around the world at the speed of a click, becoming a kind of borderless currency that underpins the digital economy. Largely unregulated, the flow of bits and bytes helped fuel the rise of transnational megacompanies like Google and Amazon and reshaped global communications, commerce, entertainment and media.

Now the era of open borders for data is ending.

France, Austria, South Africa and more than 50 other countries are accelerating efforts to control the digital information produced by their citizens, government agencies and corporations. Driven by security and privacy concerns, as well as economic interests and authoritarian and nationalistic urges, governments are increasingly setting rules and standards about how data can and cannot move around the globe. The goal is to gain “digital sovereignty.”

Consider that:

  • In Washington, the Biden administration is circulating an early draft of an executive order meant to stop rivals like China from gaining access to American data.
  • In the European Union, judges and policymakers are pushing efforts to guard information generated within the 27-nation bloc, including tougher online privacy requirements and rules for artificial intelligence.
  • In India, lawmakers are moving to pass a law that would limit what data could leave the nation of almost 1.4 billion people.
  • The number of laws, regulations and government policies that require digital information to be stored in a specific country more than doubled to 144 from 2017 to 2021, according to the Information Technology and Innovation Foundation.

While countries like China have long cordoned off their digital ecosystems, the imposition of more national rules on information flows is a fundamental shift in the democratic world and alters how the internet has operated since it became widely commercialized in the 1990s.

The repercussions for business operations, privacy and how law enforcement and intelligence agencies investigate crimes and run surveillance programs are far-reaching. Microsoft, Amazon and Google are offering new services to let companies store records and information within a certain territory. And the movement of data has become part of geopolitical negotiations, including a new pact for sharing information across the Atlantic that was agreed to in principle in March…(More)”.

Digital Technology Demands A New Political Philosophy

Curated on Posted on by Stefaan Verhulst

Essay by Steven Hill: “…It’s not just that digital systems are growing more ubiquitous. They are becoming more capable. Allowing for skepticism of the hype around AI, it is unarguable that computers are increasingly able to do things that we would previously have seen as the sole province of human beings — and in some cases do them better than us. That trend is unlikely to reverse and appears to be speeding up.

The result is that increasingly capable technologies are going to be a fundamental part of 21st-century life. They mediate a growing number of our deeds, utterances and exchanges. Our access to basic social goods — credit, housing, welfare, educational opportunity, jobs — is increasingly determined by algorithms of hidden design and obscure provenance. Computer code has joined market forces, communal tradition and state coercion in the first rank of social forces. We’re in the early stages of the digital lifeworld: a delicate social system that links human beings, powerful machines and abundant data in a swirling web of great complexity.

The political implications are clear to anyone who wants to see them: those who own and control the most powerful digital technologies will increasingly write the rules of society itself. Software engineers are becoming social engineers. The digital is political….

For the last few decades, digital technology has not only been developed, but also regulated, within the same intellectual paradigm: that of market individualism. Within this paradigm, the market is seen not only as a productive source of innovation, but as a reliable regulator of market participants too: a self-correcting ecosystem which can be trusted to contain the worst excesses of its participants.

“The question is not whether Musk or Zuckerberg will make the ‘right’ decision with the power at their disposal — it’s why they are allowed that power at all.”

This way of thinking about technology emphasizes consumer choice (even when that choice is illusory), hostility to government power (but ambivalence about corporate power), and individual responsibility (even at the expense of collective wellbeing). In short, it treats digital technology as a chiefly economic phenomenon to be governed by the rules and norms of the marketplace, and not as a political phenomenon to be governed by the rules and norms of the forum.

The first step in becoming a digital republican is recognizing that this tension — between economics and politics, between capitalism and democracy — is likely to be among the foremost political battlegrounds of the digital age. The second step is to argue that the balance has swung too far to one side, and it is overdue for a correction….(More)”.

Artificial intelligence is breaking patent law

Curated on Posted on by Stefaan Verhulst

Article by Alexandra George & Toby Walsh: “In 2020, a machine-learning algorithm helped researchers to develop a potent antibiotic that works against many pathogens (see Nature https://doi.org/ggm2p4; 2020). Artificial intelligence (AI) is also being used to aid vaccine development, drug design, materials discovery, space technology and ship design. Within a few years, numerous inventions could involve AI. This is creating one of the biggest threats patent systems have faced.

Patent law is based on the assumption that inventors are human; it currently struggles to deal with an inventor that is a machine. Courts around the world are wrestling with this problem now as patent applications naming an AI system as the inventor have been lodged in more than 100 countries1. Several groups are conducting public consultations on AI and intellectual property (IP) law, including in the United States, United Kingdom and Europe.

If courts and governments decide that AI-made inventions cannot be patented, the implications could be huge. Funders and businesses would be less incentivized to pursue useful research using AI inventors when a return on their investment could be limited. Society could miss out on the development of worthwhile and life-saving inventions.

Rather than forcing old patent laws to accommodate new technology, we propose that national governments design bespoke IP law — AI-IP — that protects AI-generated inventions. Nations should also create an international treaty to ensure that these laws follow standardized principles, and that any disputes can be resolved efficiently. Researchers need to inform both steps….(More)”.

We Need to Take Back Our Privacy

Curated on Posted on by Stefaan Verhulst

Zeynep Tufekci in The New York Times: “…Congress, and states, should restrict or ban the collection of many types of data, especially those used solely for tracking, and limit how long data can be retained for necessary functions — like getting directions on a phone.

Selling, trading and merging personal data should be restricted or outlawed. Law enforcement could obtain it subject to specific judicial oversight.

Researchers have been inventing privacy-preserving methods for analyzing data sets when merging them is in the public interest but the underlying data is sensitive — as when health officials are tracking a disease outbreak and want to merge data from multiple hospitals. These techniques allow computation but make it hard, if not impossible, to identify individual records. Companies are unlikely to invest in such methods, or use end-to-end encryption as appropriate to protect user data, if they could continue doing whatever they want. Regulation could make these advancements good business opportunities, and spur innovation.

I don’t think people like things the way they are. When Apple changed a default option from “track me” to “do not track me” on its phones, few people chose to be tracked. And many who accept tracking probably don’t realize how much privacy they’re giving up, and what this kind of data can reveal. Many location collectors get their data from ordinary apps — could be weather, games, or anything else — that often bury that they will share the data with others in vague terms deep in their fine print.

Under these conditions, requiring people to click “I accept” to lengthy legalese for access to functions that have become integral to modern life is a masquerade, not informed consent.

Many politicians have been reluctant to act. The tech industry is generous, cozy with power, and politicians themselves use data analysis for their campaigns. This is all the more reason to press them to move forward…(More)”.

Behavioral Jurisprudence: Law Needs a Behavioral Revolution

Curated on Posted on by Stefaan Verhulst

Article by Benjamin van Rooij and Adam Fine: “Laws are supposed to protect us. At work, they should eliminate unsafe working conditions and harassment. On our streets, they should curb speeding, distracted driving, and driving under the influence. And throughout our countries, they should protect citizens against their own governments.

The law is the most important behavioral system we have. Yet it is designed and operated by behavioral novices. Lawyers draft legislation, interpret rules, and create policies, but legal training does not teach them how laws affect human and organizational behavior.

Law needs a behavioral revolution, like the one that rocked the field of economics. There is now a large body of empirical work that calls into question the traditional legal assumptions about how law shapes behavior. This empirical work also offers a path forward. It can help lawyers and others shaping the law understand the law’s behavioral impact and help align its intended influence on behavior to its actual effects.

For instance, the law has traditionally focused on punishment as a means to deal with harmful behavior. Yet there is no conclusive evidence that threats of incarceration or fines reduce misconduct. Most people do not understand or know the law, and thus never come to weigh the law’s incentives in deciding whether to comply with it.

The law also fails to account for the social and moral factors that affect how people interpret and follow it. For instance, social norms—what people see others do or think others hold they should do—can shape what we think the laws say. Research also shows that people are more likely to follow rules they deem legitimate, and that rules that are made and enforced in a procedurally just and fair manner enhance compliance.

And, traditionally, the law has focused on motivational aspects of wrongdoing. But behavioral responses to the law are highly situational. Here, work in criminology, particularly within environmental criminology, shows that criminal opportunities are a chief driver of criminal behavior. Relatedly, when people have their needs met, for instance when they have a livable wage or sufficient schooling, they are more likely to follow the law…(More)”.

How Secure Is Our Data, Really?

Curated on Posted on by Stefaan Verhulst

Essay by Michael Kende: “Stepping back, a 2019 study showed that 95 percent of such data breaches could have been prevented. There are two main causes of breaches that can be averted.

First, many breaches attack known vulnerabilities in online systems. We are all used to updating the operating system on our computer or phone. One of the reasons is to patch a defect that could allow a breach. But not all of us update each patch all of the time, and that leaves us exposed. Organizations operating hundreds or thousands of devices with different systems connecting them may not devote enough resources to security or may be worried about testing the compatibility of upgrades, and this leaves them exposed to hackers searching for systems that have not been updated. These challenges were exacerbated with employees working from home during pandemic restrictions, often on their own devices with less protected networks.

Second is the phenomenon known as social engineering in which an employee is tricked into providing their password. We have all received phishing emails asking us to log into a familiar site to address an urgent matter. Doing so allows the hacker to capture the user’s email address or user name and the associated password. The hacker can then use that information directly to enter the real version of the website or may find out where else the user may go and hope they use the same login details — which, human nature being what it is, is quite common. These phishing attacks highlight the asymmetric advantage held by the hackers. They can send out millions of emails and just need one person to click on the wrong link to start their attack.

Of course, if 95 percent of breaches are preventable, that means 5 percent are not. For instance, though many breaches result from known vulnerabilities in systems, a vulnerability is by definition unknown before it is discovered. Such a vulnerability, known as a zero-day vulnerability, is valuable for hackers because it cannot be defended against, and they are often hoarded or sold, sometimes back to the company responsible so they can create a patch…(More)”.

How the Pandemic Made Algorithms Go Haywire

Curated on Posted on by Stefaan Verhulst

Article by Ravi Parikh and Amol Navathe: “Algorithms have always had some trouble getting things right—hence the fact that ads often follow you around the internet for something you’ve already purchased.

But since COVID upended our lives, more of these algorithms have misfired, harming millions of Americans and widening existing financial and health disparities facing marginalized groups. At times, this was because we humans weren’t using the algorithms correctly. More often it was because COVID changed life in a way that made the algorithms malfunction.

Take, for instance, an algorithm used by dozens of hospitals in the U.S. to identify patients with sepsis—a life-threatening consequence of infection. It was supposed to help doctors speed up transfer to the intensive care unit. But starting in spring of 2020, the patients that showed up to the hospital suddenly changed due to COVID. Many of the variables that went into the algorithm—oxygen levels, age, comorbid conditions—were completely different during the pandemic. So the algorithm couldn’t effectively discern sicker from healthier patients, and consequently it flagged more than twice as many patients as “sick” even though hospital capacity was 35 percent lower than normal. The result was presumably more instances of doctors and nurses being summoned to the patient bedside. It’s possible all of these alerts were necessary – after all, more patients were sick. However, it’s also possible that many of these alerts were false alarms because the type of patients showing up to the hospital were different. Either way, this threatened to overwhelm physicians and hospitals. This “alert overload” was discovered months into the pandemic and led the University of Michigan health system to shut down its use of the algorithm…(More)”.

Building a Data Infrastructure for the Bioeconomy

Curated on Posted on by Stefaan Verhulst

Article by Gopal P. Sarma and Melissa Haendel: “While the development of vaccines for COVID-19 has been widely lauded, other successful components of the national response to the pandemic have not received as much attention. The National COVID Cohort Collaborative (N3C), for example, flew under the public’s radar, even though it aggregated crucial US public health data about the new disease through cross-institutional collaborations among government, private, and nonprofit health and research organizations. These data, which were made available to researchers via cutting-edge software tools, have helped in myriad ways: they led to identification of the clinical characteristics of acute COVID-19 for risk prediction, assisted in providing clinical care for immunocompromised adults, revealed how COVID infection affects children, and documented that vaccines appear to reduce the risk of developing long COVID.

N3C has created the largest national, publicly available patient-level dataset in US history. Through a unique public-private partnership, over 300 participating organizations quickly overcame privacy concerns and data silos to include 13 million patient records in the project. More than 3,000 participating scientists are now working to overcome the particular challenge faced in the United States—the lack of a national healthcare data infrastructure available in many other countries—to support public health and medical responses. N3C shows great promise for unraveling answers to questions related to COVID, but it could easily be expanded for many areas of public health, including pandemic preparedness and monitoring disease status across the population.

As public servants dedicated to improving public health and equity, we believe that to unite the nation’s fragmented public health system, the United States should establish a standing capacity to collect, harmonize, and sustain a wide range of data types and sources. The public health data collected by N3C would ultimately be but one component of a rich landscape of interoperable data systems that can guide public policy in an era of rapid environmental change, sophisticated biological threats, and an economy enabled by biotechnology. Such an effort will require new thinking about data collection, infrastructure, and regulation, but its benefits could be enormous—enabling policymakers to make decisions in an increasingly complex world. And as the interconnections between society, industry, and government continue to intensify, decisionmaking of all types and scales will be more efficient and responsive if it can rely on significantly expanded data collection and analysis capabilities…(More)”.

Why Democracy vs. Autocracy Misses the Point

Curated on Posted on by Stefaan Verhulst

Essay by Jean-Marie Guéhenno: “I have always been a contrarian. I was a contrarian in 1989 when I wrote my first book, criticizing the idea—then widely held—that democracy had triumphed once and for all. And today I find that I’m a contrarian again with my new book, because everybody is talking about the confrontation between democracies and autocracies and I think that’s missing the point.

Something much more important is happening: the revolution of data, the Internet, and artificial intelligence. I believe we are on the cusp of an earthquake in the history of humanity of a kind that happens only once in hundreds of years. The most recent comparison is the Renaissance, and the pace of change today is much quicker than back then.

The institutions we built in the pre-data age are soon going to be completely overwhelmed, and thinking in terms of the old categories of democracies versus autocracies misses all the new challenges that they will have to face. This is a time of great peril as well as great promise, as was the Renaissance—not only the era of Leonard da Vinci, but also a century of religious wars.

The current revolution of data and algorithms is redistributing power in a way that cannot be compared to any historical shift. Traditionally we think of power concentrating in the hands of the leaders of states or big industrial companies. But power, increasingly, is in the hands of algorithms that are tasked (initially by humans) with learning and changing themselves, and evolve in ways we do not predict.

That means the owners of Google or Facebook or Amazon are not the masters of our destiny in the same sense as previous corporate titans. Similarly, while it is true to some extent that data will give dictators unprecedented power to manipulate society, they may also come to be dominated by the evolution of the algorithms on which they depend.

We see already how algorithms are reshaping politics. Social media has created self-contained tribes which do not speak to each other. The most important thing in democracy is not the vote itself, but the process of deliberation before the vote, and social media is quickly fragmenting the common ground on which such deliberations have been built.

How can societies exert control over how algorithms manage data, and whether they foster hatred or harmony? Institutions that are able to control this new power are not yet really in place. What they should look like will be one of the great debates of the future.

I don’t have the answers: I believe no human mind can anticipate the extent of the transformations that are going to happen. Indeed, I think the very notion that you can know today what will be the right institutions for the future is hubristic. The best institutions (and people) will be those that are most adaptable.

However, I believe that one promising approach is to think in terms of the relationship between the logic of knowledge and the logic of democracy. Take central banks as an example. The average citizen does not have a clue about how monetary policy works. Instead we rely on politicians to task the experts at central banks to try achieve a certain goal—it could be full employment, or a stable currency….(More)”.