Why Philanthropists Should Become Heretics


Article by Mark Malloch-Brown: “…There is a legitimate role for philanthropy in troubled times, but one that has to reflect them. No longer is it enough for established figures to use foundations and other philanthropies to prop up an existing order. The world of Hoffman or Bundy no longer exists, let alone that of Carnegie and Rockefeller. Today, the sector will find legitimacy only in its ability to help confront the manifold crises in ways others cannot.

In his 2018 book Just Giving, the political scientist Rob Reich brought a skeptical eye to the question of whether foundations have any valid purpose in liberal democracies but concluded that they can indeed be beneficial by fulfilling roles that only they can take on, through their distinctive constitutions. Reich identified two in particular: pluralism (foundations can challenge orthodoxies by pursuing idiosyncratic goals without clear electoral or market rationales) and discovery (foundations can serve as the “risk capital” for democratic societies, experimenting and investing for the long term). Precisely because entities in the philanthropic sector do not answer to voters or shareholders, they can be both radically urgent and radically patient: moving faster than other actors in response to a crisis or opportunity but also possessing far greater staying power, thus the ability to back projects whose success is judged in decades rather than months.

This approach demands that those who were once secular priests—the leaders of the philanthropic sector—abandon their cassocks and accept the mantle of the heretic. Only by challenging the system and agitating on its fringes can they realize their full potential in today’s crisis-bound world…(More)”

The Global Cooperation Barometer 2024


WEF Report: “From 2012 up until the COVID-19 pandemic, there was an increase in cooperation across four of the five pillars, with peace and security being the only exception. Innovation and technology saw the biggest increase in cooperation – at more than 30%.

The report shows a “stark deterioration” in the peace and security pillar due to a rapid rise in the number of forcibly displaced people and deaths from conflict. However, there has been “continued growth” in the climate and nature pillar due to increased commitments from countries.

Cooperation trends by pillar.

How cooperation has developed over the past decade, by pillar Image: World Economic Forum

Here’s what you need to know about cooperation across the five pillars.

  • Trade and capital

Global trade and capital flows rose moderately between 2012 and 2022. During the pandemic, these areas experienced volatility, with labour migration patterns dropping. But metrics such as goods trade, development assistance and developing countries’ share of foreign direct investment, and manufacturing exports have returned to strong growth in the post-pandemic period, says the report.

  • Innovation and technology

In the eight years until the pandemic, innovation and technology cooperation “maintained strong and significant growth” across most indicators, especially cross-border data flows and IT services trade. But this has plateaued since 2020, with some key metrics, including cross-border patent applications and international student flows, falling.

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How is the World Economic Forum creating guardrails for Artificial Intelligence?

  • Climate and natural capital

This is the only pillar that has seen the majority of indicators rise across the whole decade, with financial commitments to mitigation and adaptation and a significant expansion of marine protected areas. However, emissions continue to rise and “progress towards ecological outcomes is stagnant”, says the report.

  • Health and wellness

Between 2012 and 2020, cooperation on health and wellness rose consistently and was “essential” to navigating the COVID-19 pandemic, says the report, citing vaccine development, if not necessarily distribution, as an example. But cooperation has dipped slightly since its peak in 2020.

  • Peace and security

Trends in peace and security cooperation have declined considerably since 2016, driven by a rise in forcibly displaced people and cyberattacks, as well as a recent increase in the number of conflicts and conflict-related deaths. The report notes these metrics suggest an “increasingly unstable global security environment and increased intensity of conflicts”…(More)”.

Do Policy Schools Still Have a Point?


Article by Stephen M. Walt: “Am I proposing that we toss out the current curriculum, stop teaching microeconomics, democratic theory, public accounting, econometrics, foreign policy, applied ethics, history, or any of the other building blocks of today’s public policy curriculum? Not yet. But we ought to devote more time and effort to preparing them for a world that is going to be radically different from the one we’ve known in the past—and sooner than they think.

I have three modest proposals.

First, and somewhat paradoxically, the prospect of radical change highlights the importance of basic theories. Empirical patterns derived from past experience (e.g., “democracies don’t fight each other”) may be of little value if the political and social conditions under which those laws were discovered no longer exist. To make sense of radically new circumstances, we will have to rely on causal explanations (i.e., theories) to help us foresee what is likely to occur and to anticipate the results of different policy choices. Knowledge derived from simplistic hypothesis testing or simple historical analogies will be less useful than rigorous and refined theories that tell us what’s causing what and help us understand the effects of different actions. Even more sophisticated efforts to teach “applied history” will fail if past events are not properly interpreted. The past never speaks to us directly; all historical interpretation is in some sense dependent on the theories or frameworks that we bring to these events. We need to know not just what happened in some earlier moment; we need to understand why it happened as it did and whether similar causal forces are at work today. Providing a causal explanation requires theory.

At the same time, some of our existing theories will need to be revised (or even abandoned), and new ones may need to be invented. We cannot escape reliance on some sort of theory, but rigid and uncritical adherence to a particular worldview can be just as dangerous as trying to operate solely with one’s gut instincts. For this reason, public policy schools should expose students to a wider range of theoretical approaches than they currently do and teach students how to think critically about them and to identify their limitations along with their strengths…(More)”.

We could all learn a bit about democracy from Austrian millionaire Marlene Engelhorn


Article by Seána Glennon: “In the coming week, thousands of households across Austria will receive an invitation to participate in a citizens’ assembly with a unique goal: to determine how to spend the €25 million fortune of a 31-year-old heiress, Marlene Engelhorn, who believes that the system that allowed her to inherit such a vast sum of money (tax free) is deeply flawed.

Austria, like many countries across the world, suffers from a wealth gap: a small percentage of the population controls a disproportionate amount of wealth and attendant power.

Engelhorn is not alone in calling out this unfairness; in the US, where wealth inequality has been rising for decades, a small number of the super-rich are actually pushing for higher taxes to support public services.

The Austrian experiment is somewhat unique, however, in seeking to engage ordinary citizens in directly determining how a substantial fortune should be distributed…(More)”.

The Branding Dilemma of AI: Steering Towards Efficient Regulation


Blog by Zeynep Engin: “…Undoubtedly, the term ‘Artificial Intelligence’ has captured the public imagination, proving to be an excellent choice from a marketing standpoint (particularly serving the marketing goals of big AI tech companies). However, this has not been without its drawbacks. The field has experienced several ‘AI winters’ when lofty promises failed to translate into real-world outcomes. More critically, this term has anthropomorphized what are, at their core, high-dimensional statistical optimization processes. Such representation has obscured their true nature and the extent of their potential. Moreover, as computing capacities have expanded exponentially, the ability of these systems to process large datasets quickly and precisely, identifying patterns autonomously, has often been misinterpreted as evidence of human-like or even superhuman intelligence. Consequently, AI systems have been elevated to almost mystical status, perceived as incomprehensible to humans and, thus, uncontrollable by humans…

A profound shift in the discourse surrounding AI is urgently necessary. The quest to replicate or surpass human intelligence, while technologically fascinating, does not fully encapsulate the field’s true essence and progress. Indeed, AI has seen significant advances, uncovering a vast array of functionalities. However, its core strength still lies in computational speed and precision — a mechanical prowess. The ‘magic’ of AI truly unfolds when this computational capacity intersects with the wealth of real-world data generated by human activities and the environment, transforming human directives into computational actions. Essentially, we are now outsourcing complex processing tasks to machines, moving beyond crafting bespoke solutions for each problem in favour of leveraging vast computational resources we have. This transition does not yield an ‘artificial intelligence’, but poses a new challenge to human intelligence in the knowledge creation cycle: the responsibility to formulate the ‘right’ questions and vigilantly monitor the outcomes of such intricate processing, ensuring the mitigation of any potential adverse impacts…(More)”.

Debate and Decide: Innovative Participatory Governance in South Australia 2010–2018


Paper by Matt D. Ryan: “This article provides an account of how innovative participatory governance unfolded in South Australia between 2010 and 2018. In doing so it explores how an ‘interactive’ political leadership style, which scholarship argues is needed in contemporary democracy, played out in practice. Under the leadership of Premier Jay Weatherill this approach to governing, known as ‘debate and decide’, became regarded as one of the most successful examples of democratic innovation globally. Using an archival and media method of analysis the article finds evidence of the successful application of an interactive political leadership style, but one that was so woven into competitive politics that it was abandoned after a change in government in March 2018. To help sustain interactive political leadership styles the article argues for research into how a broader base of politicians perceives the benefits and risks of innovative participatory governance. It also argues for a focus on developing politicians’ collaborative leadership capabilities. However, the article concludes by asking: if political competition is built into our system of government, are we be better off leveraging it, rather than resisting it, in the pursuit of democratic reform?…(More)”.

The Data Revolution and the Study of Social Inequality: Promise and Perils


Paper by Mario L. Small: “The social sciences are in the midst of a revolution in access to data, as governments and private companies have accumulated vast digital records of rapidly multiplying aspects of our lives and made those records available to researchers. The accessibility and comprehensiveness of the data are unprecedented. How will the data revolution affect the study of social inequality? I argue that the speed, breadth, and low cost with which large-scale data can be acquired promise a dramatic transformation in the questions we can answer, but this promise can be undercut by size-induced blindness, the tendency to ignore important limitations amidst a source with billions of data points. The likely consequences for what we know about the social world remain unclear…(More)”.

In shaping AI policy, stories about social impacts are just as important as expert information


Blog by Daniel S. Schiff and Kaylyn Jackson Schiff: “Will artificial intelligence (AI) save the world or destroy it? Will it lead to the end of manual labor and an era of leisure and luxury, or to more surveillance and job insecurity? Is it the start of a revolution in innovation that will transform the economy for the better? Or does it represent a novel threat to human rights?

Irrespective of what turns out to be the truth, what our key policymakers believe about these questions matters. It will shape how they think about the underlying problems that AI policy is aiming to address, and which solutions are appropriate to do so. …In late 2021, we ran a study to better understand the impact of policy narratives on the behavior of policymakers. We focused on US state legislators,…

In our analysis, we found something surprising. We measured whether legislators were more likely to engage with a message featuring a narrative or featuring expert information, which we assessed by seeing if they clicked on a given fact sheet/story or clicked to register for or attended the webinar.

Despite the importance attached to technical expertise in AI circles, we found that narratives were at least as persuasive as expert information. Receiving a narrative emphasizing, say, growing competition between the US and China, or the faulty arrest of Robert Williams due to facial recognition, led to a 30 percent increase in legislator engagement compared to legislators who only received basic information about the civil society organization. These narratives were just as effective as more neutral, fact-based information about AI with accompanying fact sheets…(More)”

The New Digital Dark Age


Article by Gina Neff: “For researchers, social media has always represented greater access to data, more democratic involvement in knowledge production, and great transparency about social behavior. Getting a sense of what was happening—especially during political crises, major media events, or natural disasters—was as easy as looking around a platform like Twitter or Facebook. In 2024, however, that will no longer be possible.

In 2024, we will face a grim digital dark age, as social media platforms transition away from the logic of Web 2.0 and toward one dictated by AI-generated content. Companies have rushed to incorporate large language models (LLMs) into online services, complete with hallucinations (inaccurate, unjustified responses) and mistakes, which have further fractured our trust in online information.

Another aspect of this new digital dark age comes from not being able to see what others are doing. Twitter once pulsed with publicly readable sentiment of its users. Social researchers loved Twitter data, relying on it because it provided a ready, reasonable approximation of how a significant slice of internet users behaved. However, Elon Musk has now priced researchers out of Twitter data after recently announcing that it was ending free access to the platform’s API. This made it difficult, if not impossible, to obtain data needed for research on topics such as public health, natural disaster response, political campaigning, and economic activity. It was a harsh reminder that the modern internet has never been free or democratic, but instead walled and controlled.

Closer cooperation with platform companies is not the answer. X, for instance, has filed a suit against independent researchers who pointed out the rise in hate speech on the platform. Recently, it has also been revealed that researchers who used Facebook and Instagram’s data to study the platforms’ role in the US 2020 elections had been granted “independence by permission” by Meta. This means that the company chooses which projects to share its data with and, while the research may be independent, Meta also controls what types of questions are asked and who asks them…(More)”.

Fairness and Machine Learning


Book by Solon Barocas, Moritz Hardt and Arvind Narayanan: “…introduces advanced undergraduate and graduate students to the intellectual foundations of this recently emergent field, drawing on a diverse range of disciplinary perspectives to identify the opportunities and hazards of automated decision-making. It surveys the risks in many applications of machine learning and provides a review of an emerging set of proposed solutions, showing how even well-intentioned applications may give rise to objectionable results. It covers the statistical and causal measures used to evaluate the fairness of machine learning models as well as the procedural and substantive aspects of decision-making that are core to debates about fairness, including a review of legal and philosophical perspectives on discrimination. This incisive textbook prepares students of machine learning to do quantitative work on fairness while reflecting critically on its foundations and its practical utility.

• Introduces the technical and normative foundations of fairness in automated decision-making
• Covers the formal and computational methods for characterizing and addressing problems
• Provides a critical assessment of their intellectual foundations and practical utility
• Features rich pedagogy and extensive instructor resources…(More)”