Europe wants to get better at planning for the worst

Curated on Posted on by Stefaan Verhulst

Article by Sarah Anne Aarup: “The European Union is beset by doom and gloom — from wars on its doorstep to inflation and the climate crisis — not to mention political instability in the U.S. and rivalry with China.

All too often, the EU has been overtaken by events, which makes the task of getting better at planning for the worst all the more pressing. 

As European leaders fought political fires at their informal summit last week in Granada, unaware that Palestinian militants would launch their devastating raid on Israel a day later, they quietly started a debate on strategic foresight.

At this stage still very much a thought experiment, the concept of “open strategic autonomy” is being championed by host Spain, the current president of the Council of the EU. The idea reflects a shift in priorities to navigate an increasingly uncertain world, and a departure from the green and digital transitions that have dominated the agenda in recent years.

To the uninitiated, the concept of open strategic autonomy sounds like an oxymoron — that’s because it is.

After the hyper globalized early 2000s, trust in liberalism started to erode. Then the Trump-era trade wars, COVID-19 pandemic and Russia’s invasion of Ukraine exposed Europe’s economic reliance on powerful nations that are either latent — or overt — strategic rivals.

“The United States and China are becoming more self-reliant, and some voices were saying that this is what we have to do,” an official with the Spanish presidency told POLITICO. “But that’s not a good idea for Europe.”

Instead, open strategic autonomy is about shielding the EU just enough to protect its economic security while remaining an international player. In other words, it means “cooperating multilaterally wherever we can, acting autonomously wherever we must.”

It’s a grudging acceptance that great power politics now dominate economics…

The open strategic autonomy push is about countering an inward turn that was all about cutting dependencies, such as the EU’s reliance on Russian energy, after President Vladimir Putin ordered the invasion of Ukraine.

“[We’re] missing a more balanced and forward-looking strategy” following the Versailles Declaration, the Spanish official said, referring to a first response by EU leaders to the Russian attack of February 24, 2022.

Spain delivered its contribution to the debate in the form of a thick paper drafted by its foresight office, in coordination with over 80 ministries across the EU…(More)”.

Transparent. A phony-baloney ideal.

Curated on Posted on by Stefaan Verhulst

Essay by Wilfred M. McCla: ““I’m looking through you,” sang Paul McCartney, “where did you go?”

Ah, yes. People of a certain age will recognize these lyrics from a bittersweet song of the sixties about the optics of fading love. (Poor Jane Asher, where did she go?) But more than that, the song also gives us a neat summation of what might be called, with apologies to Kant, the antinomies of pure transparency.

Let me explain. I am sure you have noticed that the adjective transparent has undergone an overhaul in recent years. For one thing, it is suddenly everywhere. It used to be employed narrowly, mainly to describe the neutral quality we expect to find in a window: the capacity to allow the unhindered passage of light. Or as the Oxford English Dictionary puts it, “the property of transmitting light, so as to render bodies lying beyond completely visible.” The point was not the window, but the thing the window enabled us to see.

The word has also enjoyed figurative usages, as in the beauty of the “transparent Helena” of A Midsummer Night’s Dream, or in George Orwell’s admonition that “good prose should be transparent, like a window pane.” Or in the ecstatic visions of Ralph Waldo Emerson, who experienced unmediated nature as if he were “a transparent eye-ball,” able to “see all” and feel “the currents of the Universal Being circulate through me.” Or less grandly, the word is often used as a negative intensifier, as in the term “transparent liar,” which is used so frequently that it has a Twitter hashtag. In every instance, the general sense of being “completely visible” is paramount.

In recent years, by contrast, transparent has become one of the staples of our commercial discourse, a form of bureaucratic-corporate-therapeutic-speak that, like all such language, is designed to conceal more than it reveals and defeat its challengers by the abstract elusiveness of its meaning. Its promiscuous use is an unfortunate development. In practice, it generally means the opposite of what it promises; transparency would mean irreproachable openness, guilelessness, simplicity, “nothing to hide.” But when today’s T-shirt–clad executives and open-collar politicians assure us, at the beginning of their remarks, that “we want to be completely transparent,” it is time to watch out. They are making a statement about themselves, about what good and generous and open and kind folks they are, and why you should therefore trust them. They are signaling their personal virtue. They are not talking about the general accessibility of their account books and board minutes and confidential personnel records…(More)”.

AI-tocracy

Curated on Posted on by Stefaan Verhulst

Article by Peter Dizikes: “It’s often believed that authoritarian governments resist technical innovation in a way that ultimately weakens them both politically and economically. But a more complicated story emerges from a new study on how China has embraced AI-driven facial recognition as a tool of repression. 

“What we found is that in regions of China where there is more unrest, that leads to greater government procurement of facial-recognition AI,” says coauthor Martin Beraja, an MIT economist. Not only has use of the technology apparently worked to suppress dissent, but it has spurred software development. The scholars call this mutually reinforcing situation an “AI-tocracy.” 

In fact, they found, firms that were granted a government contract for facial-recognition technologies produce about 49% more software products in the two years after gaining the contract than before. “We examine if this leads to greater innovation by facial-recognition AI firms, and indeed it does,” Beraja says.

Adding it all up, the case of China indicates how autocratic governments can potentially find their political power enhanced, rather than upended, when they harness technological advances—and even generate more economic growth than they would have otherwise…(More)”.

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

Curated on Posted on by Stefaan Verhulst

Article by Ariel Procaccia: “…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.

What’s more, unlike elected bodies, these assemblies are chosen to mirror the population, a property that political theorists refer to as descriptive representation. For example, a typical citizens’ assembly has a roughly equal number of men and women (some also ensure nonbinary participation), whereas the average proportion of seats held by women in national parliaments worldwide was 26 percent in 2021—a marked increase from 12 percent in 1997 but still far from gender balance. Descriptive representation, in turn, lends legitimacy to the assembly: citizens seem to find decisions more acceptable when they are made by people like themselves.

As attractive as descriptive representation is, there are practical obstacles to realizing it while adhering to the principle of random selection. Overcoming these hurdles has been a passion of mine for the past few years. Using tools from mathematics and computer science, my collaborators and I developed an algorithm for the selection of citizens’ assemblies that many practitioners around the world are using. Its story provides a glimpse into the future of democracy—and it begins a long time ago…(More)”.

How to share data — not just equally, but equitably

Curated on Posted on by Stefaan Verhulst

Editorial in Nature: “Two decades ago, scientists asked more than 150,000 people living in Mexico City to provide medical data for research. Each participant gave time, blood and details of their medical history. For the researchers, who were based at the National Autonomous University of Mexico in Mexico City and the University of Oxford, UK, this was an opportunity to study a Latin American population for clues about factors contributing to disease and health. For the participants, it was a chance to contribute to science so that future generations might one day benefit from access to improved health care. Ultimately, the Mexico City Prospective Study was an exercise in trust — scientists were trusted with some of people’s most private information because they promised to use it responsibly.

Over the years, the researchers have repaid the communities through studies investigating the effects of tobacco and other risk factors on participants’ health. They have used the data to learn about the impact of diabetes on mortality rates, and they have found that rare forms of a gene called GPR75 lower the risk of obesity. And on 11 October, researchers added to the body of knowledge on the population’s ancestry.

But this project also has broader relevance — it can be seen as a model of trust and of how the power structures of science can be changed to benefit the communities closest to it.

Mexico’s population is genetically wealthy. With a complex history of migration and mixing of several populations, the country’s diverse genetic resources are valuable to the study of the genetic roots of diseases. Most genetic databases are stocked with data from people with European ancestry. If genomics is to genuinely benefit the global community — and especially under-represented groups — appropriately diverse data sets are needed. These will improve the accuracy of genetic tests, such as those for disease risk, and will make it easier to unearth potential drug targets by finding new genetic links to medical conditions…(More)”.

Generative AI is set to transform crisis management

Curated on Posted on by Stefaan Verhulst

Article by Ben Ellencweig, Mihir Mysore, Jon Spaner: “…Generative AI presents transformative potential, especially in disaster preparedness and response, and recovery. As billion-dollar disasters become more frequent – “billion-dollar disasters” typically costing the U.S. roughly $120 billion each – and “polycrises”, or multiple crises at once proliferate (e.g. hurricanes combined with cyber disruptions), the significant impact that Generative AI can have, especially with proper leadership focus, is a focal point of interest.

Generative AI’s speed is crucial in emergencies, as it enhances information access, decision-making capabilities, and early warning systems. Beyond organizational benefits for those who adopt Generative AI, its applications include real-time data analysis, scenario simulations, sentiment analysis, and simplifying complex information access. Generative AI’s versatility offers a wide variety of promising applications in disaster relief, and opens up facing real time analyses with tangible applications in the real world. 

Early warning systems and sentiment analysis: Generative AI excels in early warning systems and sentiment analysis, by scanning accurate real-time data and response clusters. By enabling connections between disparate systems, Generative AI holds the potential to provide more accurate early warnings. Integrated with traditional and social media, Generative AI can also offer precise sentiment analysis, empowering leaders to understand public sentiment, detect bad actors, identify misinformation, and tailor communications for accurate information dissemination.

Scenario simulations: Generative AI holds the potential to enhance catastrophe modeling for better crisis assessment and resource allocation. It creates simulations for emergency planners, improving modeling for various disasters (e.g., hurricanes, floods, wildfires) using historical data such as location, community impact, and financial consequence. Often, simulators perform work “so large that it exceeds human capacity (for example, finding flooded or unusable roads across a large area after a hurricane).” …(More)”

Narrative Corruptions

Curated on Posted on by Stefaan Verhulst

Review by Mike St. Thomas: “…The world outside academia has grown preoccupied with narrative recently. Despite the rise of Big Data (or perhaps because of it), we are more keenly aware of how we use stories to explain what happens in the world, wield political power, and understand ourselves. And we are discovering that these stories can be used for good or ill. From the resurgence of nationalism on the right to the rise of identity politics on the left, the stories we tell about ourselves matter a great deal. As marketing guru Annette Simmons puts it, “Whoever tells the best story wins.” The result has been, in part, the current polarization in American life. An obvious example is the persistence of the false narrative of a stolen election, but at a deeper level, more than ever we now seem inclined—conditioned, even—to judge everything with an up or down vote.

Brooks is less than thrilled about these developments. “It was as if a fledgling I had nourished had become a predator devouring reality in the name of story,” he writes at the outset of Seduced by Story, in a clear attempt to distance himself from what he sees as the abuses of narrative in the years since Reading for the Plot was published. Though his lament contains a strain of academic pearl-clutching, Brooks’s concern is warranted. A narrative is, by nature, a hermeneutic circle—the elements of a plot gaining significance through their relation to each other—and its ever-closing loop threatening to blind its audience to the real.

Though in his new book Brooks does not back down from the claims of his old, he argues that while stories may be unavoidable, they need to be examined and critiqued constantly. A banal thesis, perhaps, but still true. After a preliminary chapter that addresses corporate storytelling and the removal of Confederate monuments, he revisits terrain covered in Reading for the Plot by examining how narratives work, using examples from Victorian-era novelists such as Honoré de Balzac, Henry James, Marcel Proust, and Sir Arthur Conan Doyle.

Within Seduced by Story are the seeds of a more trenchant claim about the ultimate purpose of storytelling—and about how our narratives have become corrupted. Brooks recalls a musical advertising slogan from his youth: “If you’ve got the time / We’ve got the beer. Miller Beer.” Jingles like this were pithy, memorable, and quite effective at communicating a quality of the product, or, more likely, at appealing to a specific emotion of the listener…(More)”.

Evidence-Based Government Is Alive and Well

Curated on Posted on by Stefaan Verhulst

Article by Zina Hutton: “A desire to discipline the whimsical rule of despots.” That’s what Gary Banks, a former chairman of Australia’s Productivity Commission, attributed the birth of evidence-based policy to back in the 14th century in a speech from 2009. Evidence-based policymaking isn’t a new style of government, but it’s one with well-known roadblocks that elected officials have been working around in order to implement it more widely.

Evidence-based policymaking relies on evidence — facts, data, expert analysis — to shape aspects of long- and short-term policy decisions. It’s not just about collecting data, but also applying it and experts’ analysis to shape future policy. Whether it’s using school enrollment numbers to justify building a new park in a neighborhood or scientists collaborating on analysis of wastewater to try to “catch” illness spread in a community before it becomes unmanageable, evidence-based policy uses facts to help elected and appointed officials decide what funds and other resources to allocate in their communities.

Problems with evidence-based governing have been around for years. They range from a lack of communication between the people designing the policy and its related programs and the people implementing them, to the way that local government struggles to recruit and maintain employees. Resource allocation also shapes the decisions some cities make when it comes to seeking out and using data. This can be seen in the way larger cities, with access to proportionately larger budgets, research from state universities within city limits and a larger workforce, have had more success with evidence-based policymaking.
“The largest cities have more personnel, more expertise, more capacity, whether that’s for collecting administrative data and monitoring it, whether that’s doing open data portals, or dashboards, or whether that’s doing things like policy analysis or program evaluation,” says Karen Mossberger, the Frank and June Sackton Professor in the School of Public Affairs at Arizona State University. “It takes expert personnel, it takes people within government with the skills and the capacity, it takes time.”

Roadblocks aside, state and local governments are finding innovative ways to collaborate with one another on data-focused projects and policy, seeking ways to make up for the problems that impacted early efforts at evidence-based governance. More state and local governments now recruit data experts at every level to collect, analyze and explain the data generated by residents, aided by advances in technology and increased access to researchers…(More)”.

Who owns data about you?

Curated on Posted on by Stefaan Verhulst

Article by Wendy Wong: “The ascendancy of artificial intelligence hinges on vast data accrued from our daily activities. In turn, data train advanced algorithms, fuelled by massive amounts of computing power. Together, they form the critical trio driving AI’s capabilities. Because of its human sources, data raise an important question: who owns data, and how do the data add up when they’re about our mundane, routine choices?

It often helps to think through modern problems with historical anecdotes. The case of Henrietta Lacks, a Black woman living in Baltimore stricken with cervical cancer, and her everlasting cells, has become well-known because of Rebecca Skloot’s book, The Immortal Life of Henrietta Lacks,and a movie starring Oprah Winfrey. Unbeknownst to her, Lacks’s medical team removed her cancer cells and sent them to a lab to see if they would grow. While Lacks died of cancer in 1951, her cells didn’t. They kept going, in petri dishes in labs, all the way through to the present day.

The unprecedented persistence of Lacks’s cells led to the creation of the HeLa cell line. Her cells underpin various medical technologies, from in-vitro fertilization to polio and COVID-19 vaccines, generating immense wealth for pharmaceutical companies. HeLa is a co-creation. Without Lacks or scientific motivation, there would be no HeLa.

The case raises questions about consent and ownership. That her descendants recently settled a lawsuit against Thermo Fisher Scientific, a pharmaceutical company that monetized products made from HeLa cells, echoes the continuing discourse surrounding data ownership and rights. Until the settlement, just one co-creator was reaping all the financial benefits of that creation.

The Lacks family’s legal battle centred on a human-rights claim. Their situation was rooted in the impact of Lacks’s cells on medical science and the intertwined racial inequalities that lead to disparate medical outcomes. Since Lacks’s death, the family had struggled while biotech companies profited.

These “tissue issues” often don’t favour the individuals providing the cells or body parts. The U.S. Supreme Court case Moore v. Regents of the University of California deemed body parts as “garbage” once separated from the individual. The ruling highlights a harsh legal reality: Individuals don’t necessarily retain rights of parts of their body, financial or otherwise. Another federal case, Washington University v. Catalona, invalidated ownership claims based upon the “feeling” it belongs to the person it came from.

We can liken this characterization of body parts to how we often think about data taken from people. When we call data “detritus” or “exhaust,” we dehumanize the thoughts, behaviours and choices that generate those data. Do we really want to say that data, once created, is a resource for others’ exploitation?…(More)”.

NYC Releases Plan to Embrace AI, and Regulate It

Curated on Posted on by Stefaan Verhulst

Article by Sarah Holder: “New York City Mayor Eric Adams unveiled a plan for adopting and regulating artificial intelligence on Monday, highlighting the technology’s potential to “improve services and processes across our government” while acknowledging the risks.

The city also announced it is piloting an AI chatbot to answer questions about opening or operating a business through its website MyCity Business.

NYC agencies have reported using more than 30 tools that fit the city’s definition of algorithmic technology, including to match students with public schools, to track foodborne illness outbreaks and to analyze crime patterns. As the technology gets more advanced, and the implications of algorithmic bias, misinformation and privacy concerns become more apparent, the city plans to set policy around new and existing applications…

New York’s strategy, developed by the Office of Technology and Innovation with the input of city agency representatives and outside technology policy experts, doesn’t itself establish any rules and regulations around AI, but lays out a timeline and blueprint for creating them. It emphasizes the need for education and buy-in both from New York constituents and city employees. Within the next year, the city plans to start to hold listening sessions with the public, and brief city agencies on how and why to use AI in their daily operations. The city has also given itself a year to start work on piloting new AI tools, and two to create standards for AI contracts….

Stefaan Verhulst, a research professor at New York University and the co-founder of The GovLab, says that especially during a budget crunch, leaning on AI offers cities opportunities to make evidence-based decisions quickly and with fewer resources. Among the potential use cases he cited are identifying areas most in need of affordable housing, and responding to public health emergencies with data…(More) (Full plan)”.