Central banks use AI to assess climate-related risks


Article by Huw Jones: “Central bankers said on Tuesday they have broken new ground by using artificial intelligence to collect data for assessing climate-related financial risks, just as the volume of disclosures from banks and other companies is set to rise.

The Bank for International Settlements, a forum for central banks, the Bank of Spain, Germany’s Bundesbank and the European Central Bank said their experimental Gaia AI project was used to analyse company disclosures on carbon emissions, green bond issuance and voluntary net-zero commitments.

Regulators of banks, insurers and asset managers need high-quality data to assess the impact of climate-change on financial institutions. However, the absence of a single reporting standard confronts them with a patchwork of public information spread across text, tables and footnotes in annual reports.

Gaia was able to overcome differences in definitions and disclosure frameworks across jurisdictions to offer much-needed transparency, and make it easier to compare indicators on climate-related financial risks, the central banks said in a joint statement.

Despite variations in how the same data is reported by companies, Gaia focuses on the definition of each indicator, rather than how the data is labelled.

Furthermore, with the traditional approach, each additional key performance indicator, or KPI, and each new institution requires the analyst to either search for the information in public corporate reports or contact the institution for information…(More)”.

The Wisdom of Partisan Crowds: Comparing Collective Intelligence in Humans and LLM-based Agents


Paper by Yun-Shiuan Chuang et al: “Human groups are able to converge to more accurate beliefs through deliberation, even in the presence of polarization and partisan bias – a phenomenon known as the “wisdom of partisan crowds.” Large Language Models (LLMs) agents are increasingly being used to simulate human collective behavior, yet few benchmarks exist for evaluating their dynamics against the behavior of human groups. In this paper, we examine the extent to which the wisdom of partisan crowds emerges in groups of LLM-based agents that are prompted to role-play as partisan personas (e.g., Democrat or Republican). We find that they not only display human-like partisan biases, but also converge to more accurate beliefs through deliberation, as humans do. We then identify several factors that interfere with convergence, including the use of chain-of-thought prompting and lack of details in personas. Conversely, fine-tuning on human data appears to enhance convergence. These findings show the potential and limitations of LLM-based agents as a model of human collective intelligence…(More)”

God-like: A 500-Year History of Artificial Intelligence in Myths, Machines, Monsters


Book by Kester Brewin: “In the year 1600 a monk is burned at the stake for claiming to have built a device that will allow him to know all things.

350 years later, having witnessed ‘Trinity’ – the first test of the atomic bomb – America’s leading scientist outlines a memory machine that will help end war on earth.

25 years in the making, an ex-soldier finally unveils this ‘machine for augmenting human intellect’, dazzling as he stands ‘Zeus-like, dealing lightning with both hands.’

AI is both stunningly new and rooted in ancient desires. As we finally welcome this ‘god-like’ technology amongst us, what can learn from the myths and monsters of the past about how to survive alongside our greatest ever invention?…(More)”.

Bring on the Policy Entrepreneurs


Article by Erica Goldman: “Teaching early-career researchers the skills to engage in the policy arena could prepare them for a lifetime of high-impact engagement and invite new perspectives into the democratic process.

In the first six months of the COVID-19 pandemic, the scientific literature worldwide was flooded with research articles, letters, reviews, notes, and editorials related to the virus. One study estimates that a staggering 23,634 unique documents were published between January 1 and June 30, 2020, alone.

Making sense of that emerging science was an urgent challenge. As governments all over the world scrambled to get up-to-date guidelines to hospitals and information to an anxious public, Australia stood apart in its readiness to engage scientists and decisionmakers collaboratively. The country used what was called a “living evidence” approach to synthesizing new information, making it available—and helpful—in real time.

Each week during the pandemic, the Australian National COVID‑19 Clinical Evidence Taskforce came together to evaluate changes in the scientific literature base. They then spoke with a single voice to the Australian clinical community so clinicians had rapid, evidence-based, and nationally agreed-upon guidelines to provide the clarity they needed to care for people with COVID-19.

This new model for consensus-aligned, evidence-based decisionmaking helped Australia navigate the pandemic and build trust in the scientific enterprise, but it did not emerge overnight. It took years of iteration and effort to get the living evidence model ready to meet the moment; the crisis of the pandemic opened a policy window that living evidence was poised to surge through. Australia’s example led the World Health Organization and the United Kingdom’s National Institute for Health and Care Excellence to move toward making living evidence models a pillar of decisionmaking for all their health care guidelines. On its own, this is an incredible story, but it also reveals a tremendous amount about how policies get changed…(More)”.

Meta to shut off data access to journalists


Article by Sara Fischer: “Meta plans to officially shutter CrowdTangle, the analytics tool widely used by journalists and researchers to see what’s going viral on Facebook and Instagram, the company’s president of global affairs Nick Clegg told Axios in an interview.

Why it matters: The company plans to instead offer select researchers access to a set of new data tools, but news publishers, journalists or anyone with commercial interests will not be granted access to that data.

The big picture: The effort comes amid a broader pivot from Meta away from news and politics and more toward user-generated viral videos.

  • Meta acquired CrowdTangle in 2016 at a time when publishers were heavily reliant on the tech giant for traffic.
  • In recent years, it’s stopped investing in the tool, making it less reliable.

The new research tools include Meta’s Content Library, which it launched last year, and an API, or backend interface used by developers.

  • Both tools offer researchers access to huge swaths of data from publicly accessible content across Facebook and Instagram.
  • The tools are available in 180 languages and offer global data.
  • Researchers must apply for access to those tools through the Inter-university Consortium for Political and Social Research at the University of Michigan, which will vet their requests…(More)”

How artificial intelligence can facilitate investigative journalism


Article by Luiz Fernando Toledo: “A few years ago, I worked on a project for a large Brazilian television channel whose objective was to analyze the profiles of more than 250 guardianship counselors in the city of São Paulo. These elected professionals have the mission of protecting the rights of children and adolescents in Brazil.

Critics had pointed out that some counselors did not have any expertise or prior experience working with young people and were only elected with the support of religious communities. The investigation sought to verify whether these elected counselors had professional training in working with children and adolescents or had any relationships with churches.

After requesting the counselors’ resumes through Brazil’s access to information law, a small team combed through each resume in depth—a laborious and time-consuming task. But today, this project might have required far less time and labor. Rapid developments in generative AI hold potential to significantly scale access and analysis of data needed for investigative journalism.

Many articles address the potential risks of generative AI for journalism and democracy, such as threats AI poses to the business model for journalism and its ability to facilitate the creation and spread of mis- and disinformation. No doubt there is cause for concern. But technology will continue to evolve, and it is up to journalists and researchers to understand how to use it in favor of the public interest.

I wanted to test how generative AI can help journalists, especially those that work with public documents and data. I tested several tools, including Ask Your PDF (ask questions to any documents in your computer), Chatbase (create your own chatbot), and Document Cloud (upload documents and ask GPT-like questions to hundreds of documents simultaneously).

These tools make use of the same mechanism that operates OpenAI’s famous ChatGPT—large language models that create human-like text. But they analyze the user’s own documents rather than information on the internet, ensuring more accurate answers by using specific, user-provided sources…(More)”.

AI-enhanced Collective Intelligence: The State of the Art and Prospects


Paper by Hao Cui and Taha Yasseri: “The current societal challenges exceed the capacity of human individual or collective effort alone. As AI evolves, its role within human collectives is poised to vary from an assistive tool to a participatory member. Humans and AI possess complementary capabilities that, when synergized, can achieve a level of collective intelligence that surpasses the collective capabilities of either humans or AI in isolation. However, the interactions in human-AI systems are inherently complex, involving intricate processes and interdependencies. This review incorporates perspectives from network science to conceptualize a multilayer representation of human-AI collective intelligence, comprising a cognition layer, a physical layer, and an information layer. Within this multilayer network, humans and AI agents exhibit varying characteristics; humans differ in diversity from surface-level to deep-level attributes, while AI agents range in degrees of functionality and anthropomorphism. The interplay among these agents shapes the overall structure and dynamics of the system. We explore how agents’ diversity and interactions influence the system’s collective intelligence. Furthermore, we present an analysis of real-world instances of AI-enhanced collective intelligence. We conclude by addressing the potential challenges in AI-enhanced collective intelligence and offer perspectives on future developments in this field…(More)”.

Algorithmic attention rents: A theory of digital platform market power


Paper by Tim O’Reilly, Ilan Strauss and Mariana Mazzucato: “We outline a theory of algorithmic attention rents in digital aggregator platforms. We explore the way that as platforms grow, they become increasingly capable of extracting rents from a variety of actors in their ecosystems—users, suppliers, and advertisers—through their algorithmic control over user attention. We focus our analysis on advertising business models, in which attention harvested from users is monetized by reselling the attention to suppliers or other advertisers, though we believe the theory has relevance to other online business models as well. We argue that regulations should mandate the disclosure of the operating metrics that platforms use to allocate user attention and shape the “free” side of their marketplace, as well as details on how that attention is monetized…(More)”.

Limiting Data Broker Sales in the Name of U.S. National Security: Questions on Substance and Messaging


Article by Peter Swire and Samm Sacks: “A new executive order issued today contains multiple provisions, most notably limiting bulk sales of personal data to “countries of concern.” The order has admirable national security goals but quite possibly would be ineffective and may be counterproductive. There are serious questions about both the substance and the messaging of the order. 

The new order combines two attractive targets for policy action. First, in this era of bipartisan concern about China, the new order would regulate transactions specifically with “countries of concern,” notably China, but also others such as Iran and North Korea. A key rationale for the order is to prevent China from amassing sensitive information about Americans, for use in tracking and potentially manipulating military personnel, government officials, or anyone else of interest to the Chinese regime. 

Second, the order targets bulk sales, to countries of concern, of sensitive personal information by data brokers, such as genomic, biometric, and precise geolocation data. The large and growing data broker industry has come under well-deserved bipartisan scrutiny for privacy risks. Congress has held hearings and considered bills to regulate such brokers. California has created a data broker registry and last fall passed the Delete Act to enable individuals to require deletion of their personal data. In January, the Federal Trade Commission issued an order prohibiting data broker Outlogic from sharing or selling sensitive geolocation data, finding that the company had acted without customer consent, in an unfair and deceptive manner. In light of these bipartisan concerns, a new order targeting both China and data brokers has a nearly irresistible political logic.

Accurate assessment of the new order, however, requires an understanding of this order as part of a much bigger departure from the traditional U.S. support for free and open flows of data across borders. Recently, in part for national security reasons, the U.S. has withdrawn its traditional support in the World Trade Organization (WTO) for free and open data flows, and the Department of Commerce has announced a proposed rule, in the name of national security, that would regulate U.S.-based cloud providers when selling to foreign countries, including for purposes of training artificial intelligence (AI) models. We are concerned that these initiatives may not sufficiently account for the national security advantages of the long-standing U.S. position and may have negative effects on the U.S. economy.

Despite the attractiveness of the regulatory targets—data brokers and countries of concern—U.S. policymakers should be cautious as they implement this order and the other current policy changes. As discussed below, there are some possible privacy advances as data brokers have to become more careful in their sales of data, but a better path would be to ensure broader privacy and cybersecurity safeguards to better protect data and critical infrastructure systems from sophisticated cyberattacks from China and elsewhere…(More)”.

Breaking the Gridlock


UNDP Human Development Report 2024: “We can do better than this. Better than runaway climate change and pandemics. Better than a spate of unconstitutional transfers of power amid a rising, globalizing tide of populism. Better than cascading human rights violations and unconscionable massacres of people in their homes and civic venues, in hospitals, schools and shelters.

We must do better than a world always on the brink, a socioecological house of cards. We owe it to ourselves, to each other, to our children and their children.

We have so much going for us.

We know what the global challenges are and who will be most affected by them. And we know there will surely be more that we cannot anticipate today.

We know which choices offer better opportunities for peace, shared prosperity and sustainability, better ways to navigate interacting layers of uncertainty and interlinked planetary surprises.

We enjoy unprecedented wealth know-how and technology—unimaginable to our ancestors—that with more equitable distribution and use could power bold and necessary choices for peace and for sustainable, inclusive human development on which peace depends…

In short, why are we so stuck? And how do we get unstuck without resorting myopically to violence or isolationism? These questions motivate the 2023–2024 Human Development Report.

Sharp questions belie their complexity; issues with power disparities at their core often defy easy explanation. Magic bullets entice but mislead—siren songs peddled by sloganeering that exploits group-based grievances. Slick solutions and simple recipes poison our willingness to do the hard work of overcoming polarization.

Geopolitical quagmires abound, driven by shifting power dynamics among states and by national gazes yanked inward by inequalities, insecurity and polarization, all recurring themes in this and recent Human Development Reports. Yet we need not sit on our hands simply because great power competition is heating up while countries underrepresented in global governance seek a greater say in matters of global import. Recall that global cooperation on smallpox eradication and protection of the ozone layer, among other important issues such as nuclear nonproliferation, happened over the course of the Cold War…(More)”.