OECD Report: “The swift evolution of AI technologies calls for policymakers to consider and proactively manage AI-driven change. The OECD’s Expert Group on AI Futures was established to help meet this need and anticipate AI developments and their potential impacts. Informed by insights from the Expert Group, this report distils research and expert insights on prospective AI benefits, risks and policy imperatives. It identifies ten priority benefits, such as accelerated scientific progress, productivity gains and better sense-making and forecasting. It discusses ten priority risks, such as facilitation of increasingly sophisticated cyberattacks; manipulation, disinformation, fraud and resulting harms to democracy; concentration of power; incidents in critical systems and exacerbated inequality and poverty. Finally, it points to ten policy priorities, including establishing clearer liability rules, drawing AI “red lines”, investing in AI safety and ensuring adequate risk management procedures. The report reviews existing public policy and governance efforts and remaining gaps…(More)”.
Human-AI coevolution
Paper by Dino Pedreschi et al: “Human-AI coevolution, defined as a process in which humans and AI algorithms continuously influence each other, increasingly characterises our society, but is understudied in artificial intelligence and complexity science literature. Recommender systems and assistants play a prominent role in human-AI coevolution, as they permeate many facets of daily life and influence human choices through online platforms. The interaction between users and AI results in a potentially endless feedback loop, wherein users’ choices generate data to train AI models, which, in turn, shape subsequent user preferences. This human-AI feedback loop has peculiar characteristics compared to traditional human-machine interaction and gives rise to complex and often “unintended” systemic outcomes. This paper introduces human-AI coevolution as the cornerstone for a new field of study at the intersection between AI and complexity science focused on the theoretical, empirical, and mathematical investigation of the human-AI feedback loop. In doing so, we: (i) outline the pros and cons of existing methodologies and highlight shortcomings and potential ways for capturing feedback loop mechanisms; (ii) propose a reflection at the intersection between complexity science, AI and society; (iii) provide real-world examples for different human-AI ecosystems; and (iv) illustrate challenges to the creation of such a field of study, conceptualising them at increasing levels of abstraction, i.e., scientific, legal and socio-political…(More)”.
What is ‘sovereign AI’ and why is the concept so appealing (and fraught)?
Article by John Letzing: “Denmark unveiled its own artificial intelligence supercomputer last month, funded by the proceeds of wildly popular Danish weight-loss drugs like Ozempic. It’s now one of several sovereign AI initiatives underway, which one CEO believes can “codify” a country’s culture, history, and collective intelligence – and become “the bedrock of modern economies.”
That particular CEO, Jensen Huang, happens to run a company selling the sort of chips needed to pursue sovereign AI – that is, to construct a domestic vintage of the technology, informed by troves of homegrown data and powered by the computing infrastructure necessary to turn that data into a strategic reserve of intellect…
It’s not surprising that countries are forging expansive plans to put their own stamp on AI. But big-ticket supercomputers and other costly resources aren’t feasible everywhere.
Training a large language model has gotten a lot more expensive lately; the funds required for the necessary hardware, energy, and staff may soon top $1 billion. Meanwhile, geopolitical friction over access to the advanced chips necessary for powerful AI systems could further warp the global playing field.
Even for countries with abundant resources and access, there are “sovereignty traps” to consider. Governments pushing ahead on sovereign AI could risk undermining global cooperation meant to ensure the technology is put to use in transparent and equitable ways. That might make it a lot less safe for everyone.
An example: a place using AI systems trained on a local set of values for its security may readily flag behaviour out of sync with those values as a threat…(More)”.
Code and Craft: How Generative Ai Tools Facilitate Job Crafting in Software Development
Paper by Leonie Rebecca Freise et al: “The rapid evolution of the software development industry challenges developers to manage their diverse tasks effectively. Traditional assistant tools in software development often fall short of supporting developers efficiently. This paper explores how generative artificial intelligence (GAI) tools, such as Github Copilot or ChatGPT, facilitate job crafting—a process where employees reshape their jobs to meet evolving demands. By integrating GAI tools into workflows, software developers can focus more on creative problem-solving, enhancing job satisfaction, and fostering a more innovative work environment. This study investigates how GAI tools influence task, cognitive, and relational job crafting behaviors among software developers, examining its implications for professional growth and adaptability within the industry. The paper provides insights into the transformative impacts of GAI tools on software development job crafting practices, emphasizing their role in enabling developers to redefine their job functions…(More)”.
Access, Signal, Action: Data Stewardship Lessons from Valencia’s Floods
Article by Marta Poblet, Stefaan Verhulst, and Anna Colom: “Valencia has a rich history in water management, a legacy shaped by both triumphs and tragedies. This connection to water is embedded in the city’s identity, yet modern floods test its resilience in new ways.
During the recent floods, Valencians experienced a troubling paradox. In today’s connected world, digital information flows through traditional and social media, weather apps, and government alert systems designed to warn us of danger and guide rapid responses. Despite this abundance of data, a tragedy unfolded last month in Valencia. This raises a crucial question: how can we ensure access to the right data, filter it for critical signals, and transform those signals into timely, effective action?
Data stewardship becomes essential in this process.
In particular, the devastating floods in Valencia underscore the importance of:
- having access to data to strengthen the signal (first mile challenges)
- separating signal from noise
- translating signal into action (last mile challenges)…(More)”.
The Motivational State: A strengths-based approach to improving public sector productivity
Paper by Alex Fox and Chris Fox: “…argues that traditional approaches to improving public sector productivity, such as adopting private sector practices, technology-driven reforms, and tighter management, have failed to address the complex and evolving needs of public service users. It proposes a shift towards a strengths-based, person-led model, where public services are co-produced with individuals, families, and communities…(More)”.
Quantitative Urban Economics
Paper by Stephen J. Redding: “This paper reviews recent quantitative urban models. These models are sufficiently rich to capture observed features of the data, such as many asymmetric locations and a rich geography of the transport network. Yet these models remain sufficiently tractable as to permit an analytical characterization of their theoretical properties. With only a small number of structural parameters (elasticities) to be estimated, they lend themselves to transparent identification. As they rationalize the observed spatial distribution of economic activity within cities, they can be used to undertake counterfactuals for the impact of empirically-realistic public-policy interventions on this observed distribution. Empirical applications include estimating the strength of agglomeration economies and evaluating the impact of transport infrastructure improvements (e.g., railroads, roads, Rapid Bus Transit Systems), zoning and land use regulations, place-based policies, and new technologies such as remote working…(More)”.
The Age of the Average
Article by Olivier Zunz: “The age of the average emerged from the engineering of high mass consumption during the second industrial revolution of the late nineteenth century, when tinkerers in industry joined forces with scientists to develop new products and markets. The division of labor between them became irrelevant as industrial innovation rested on advances in organic chemistry, the physics of electricity, and thermodynamics. Working together, these industrial engineers and managers created the modern mass market that penetrated all segments of society from the middle out. Thus, in the heyday of the Gilded Age, at the height of the inequality pitting robber barons against the “common man,” was born, unannounced but increasingly present, the “average American.” It is in searching for the average consumer that American business managers at the time drew a composite portrait of an imagined individual. Here was a person nobody ever met or knew, merely a statistical conceit, who nonetheless felt real.
This new character was not uniquely American. Forces at work in America were also operative in Europe, albeit to a lesser degree. Thus, Austrian novelist Robert Musil, who died in 1942, reflected on the average man in his unfinished modernist masterpiece, The Man Without Qualities. In the middle of his narrative, Musil paused for a moment to give a definition of the word average: “What each one of us as laymen calls, simply, the average [is] a ‘something,’ but nobody knows exactly what…. the ultimate meaning turns out to be something arrived at by taking the average of what is basically meaningless” but “[depending] on [the] law of large numbers.” This, I think, is a powerful definition of the American social norm in the “age of the average”: a meaningless something made real, or seemingly real, by virtue of its repetition. Economists called this average person the “representative individual” in their models of the market. Their complex simplification became an agreed-upon norm, at once a measure of performance and an attainable goal. It was not intended to suggest that all people are alike. As William James once approvingly quoted an acquaintance of his, “There is very little difference between one man and another; but what little there is, is very important.” And that remained true in the age of the average…(More)”
Mini-publics and the public: challenges and opportunities
Conversation between Sarah Castell and Stephen Elstub: “…there’s a real problem here: the public are only going to get to know about a mini-public if it gets media coverage, but the media will only cover it if it makes an impact. But it’s more likely to make an impact if the public are aware of it. That’s a tension that mini-publics need to overcome, because it’s important that they reach out to the public. Ultimately it doesn’t matter how inclusive the recruitment is and how well it’s done. It doesn’t matter how well designed the process is. It is still a small number of people involved, so we want mini-publics to be able to influence public opinion and stimulate public debate. And if they can do that, then it’s more likely to affect elite opinion and debate as well, and possibly policy.
One more thing is that, people in power aren’t in the habit of sharing power. And that’s why it’s very difficult. I think the politicians are mainly motivated around this because they hope it’s going to look good to the electorate and get them some votes, but they are also worried about low levels of trust in society and what the ramifications of that might be. But in general, people in power don’t give it away very easily…
Part of the problem is that a lot of the research around public views on deliberative processes was done through experiments. It is useful, but it doesn’t quite tell us what will happen when mini-publics are communicated to the public in the messy real public sphere. Previously, there just weren’t that many well-known cases that we could actually do field research on. But that is starting to change.
There’s also more interdisciplinary work needed in this area. We need to improve how communication strategies around citizens’ assembly are done – there must be work that’s relevant in political communication studies and other fields who have this kind of insight…(More)”.
The Death of “Deliverism”
Article by Deepak Bhargava, Shahrzad Shams and Harry Hanbury: “How could it be that the largest-ever recorded drop in childhood poverty had next to no political resonance?
One of us became intrigued by this question when he walked into a graduate class one evening in 2021 and received unexpected and bracing lessons about the limits of progressive economic policy from his students.
Deepak had worked on various efforts to secure expanded income support for a long time—and was part of a successful push over two decades earlier to increase the child tax credit, a rare win under the George W. Bush presidency. His students were mostly working-class adults of color with full-time jobs, and many were parents. Knowing that the newly expanded child tax credit would be particularly helpful to his students, he entered the class elated. The money had started to hit people’s bank accounts, and he was eager to hear about how the extra income would improve their lives. He asked how many of them had received the check. More than half raised their hands. Then he asked those students whether they were happy about it. Not one hand went up.
Baffled, Deepak asked why. One student gave voice to the vibe, asking, “What’s the catch?” As the class unfolded, students shared that they had not experienced government as a benevolent force. They assumed that the money would be recaptured later with penalties. It was, surely, a trap. And of course, in light of centuries of exploitation and deceit—in criminal justice, housing, and safety net systems—working-class people of color are not wrong to mistrust government bureaucracies and institutions. The real passion in the class that night, and many nights, was about crime and what it was like to take the subway at night after class. These students were overwhelmingly progressive on economic and social issues, but many of their everyday concerns were spoken to by the right, not the left.
The American Rescue Plan’s temporary expansion of the child tax credit lifted more than 2 million children out of poverty, resulting in an astounding 46 percent reduction in child poverty. Yet the policy’s lapse sparked almost no political response, either from its champions or its beneficiaries. Democrats hardly campaigned on the remarkable achievement they had just delivered, and the millions of parents impacted by the policy did not seem to feel that it made much difference in their day-to-day lives. Even those who experienced the greatest benefit from the expanded child tax credit appeared unmoved by the policy. In fact, during the same time span in which monthly deposits landed in beneficiaries’ bank accounts, the percentage of Black voters—a group that especially benefited from the policy—who said their lives had improved under the Biden Administration actually declined…(More)”.