Paper by Sammy McKinney: “Interest in how Artificial Intelligence (AI) could be used within citizens’ assemblies (CAs) is emerging amongst scholars and practitioners alike. In this paper, I make four contributions at the intersection of these burgeoning fields. First, I propose an analytical framework to guide evaluations of the benefits and limitations of AI applications in CAs. Second, I map out eleven ways that AI, especially large language models (LLMs), could be used across a CAs full lifecycle. This introduces novel ideas for AI integration into the literature and synthesises existing proposals to provide the most detailed analytical breakdown of AI applications in CAs to date. Third, drawing on relevant literature, four key informant interviews, and the Global Assembly on the Ecological and Climate crisis as a case study, I apply my analytical framework to assess the desirability of each application. This provides insight into how AI could be deployed to address existing challenges facing CAs today as well as the concerns that arise with AI integration. Fourth, bringing my analyses together, I argue that AI integration into CAs brings the potential to enhance their democratic quality and institutional capacity, but realising this requires the deliberative community to proceed cautiously, effectively navigate challenging trade-offs, and mitigate important concerns that arise with AI integration. Ultimately, this paper provides a foundation that can guide future research concerning AI integration into CAs and other forms of democratic innovation…(More)”.
Drivers of Trust in Public Institutions
Press Release: “In an increasingly challenging environment – marked by successive economic shocks, rising protectionism, the war in Europe and ongoing conflicts in the Middle East, as well as structural challenges and disruptions caused by rapid technological developments, climate change and population aging – 44% of respondents now have low or no trust in their national government, surpassing the 39% of respondents who express high or moderately high trust in national government, according to a new OECD report.
OECD Survey on Drivers of Trust in Public Institutions – 2024 Results, presents findings from the second OECD Trust Survey, conducted in October and November 2023 across 30 Member countries. The biennial report offers a comprehensive analysis of current trust levels and their drivers across countries and public institutions.
This edition of the Trust Survey confirms the previous finding that socio-economic and demographic factors, as well as a sense of having a say in decision making, affect trust. For example, 36% of women reported high or moderately high trust in government, compared to 43% of men. The most significant drop in trust since 2021 is seen among women and those with lower levels of education. The trust gap is largest between those who feel they have a say and those who feel they do not have a say in what the government does. Among those who report they have a say, 69% report high or moderately high trust in their national government, whereas among those who feel they do not only 22% do…(More)”.
Big Tech-driven deliberative projects
Report by Canning Malkin and Nardine Alnemr: “Google, Meta, OpenAI and Anthropic have commissioned projects based on deliberative democracy. What was the purpose of each project? How was deliberation designed and implemented, and what were the outcomes? In this Technical Paper, Malkin and Alnemr describe the commissioning context, the purpose and remit, and the outcomes of these deliberative projects. Finally, they offer insights on contextualising projects within the broader aspirations of deliberative democracy…(More)”.
The Great Scrape: The Clash Between Scraping and Privacy
Paper by Daniel J. Solove and Woodrow Hartzog: “Artificial intelligence (AI) systems depend on massive quantities of data, often gathered by “scraping” – the automated extraction of large amounts of data from the internet. A great deal of scraped data is about people. This personal data provides the grist for AI tools such as facial recognition, deep fakes, and generative AI. Although scraping enables web searching, archival, and meaningful scientific research, scraping for AI can also be objectionable or even harmful to individuals and society.
Organizations are scraping at an escalating pace and scale, even though many privacy laws are seemingly incongruous with the practice. In this Article, we contend that scraping must undergo a serious reckoning with privacy law. Scraping violates nearly all of the key principles in privacy laws, including fairness; individual rights and control; transparency; consent; purpose specification and secondary use restrictions; data minimization; onward transfer; and data security. With scraping, data protection laws built around these requirements are ignored.
Scraping has evaded a reckoning with privacy law largely because scrapers act as if all publicly available data were free for the taking. But the public availability of scraped data shouldn’t give scrapers a free pass. Privacy law regularly protects publicly available data, and privacy principles are implicated even when personal data is accessible to others.
This Article explores the fundamental tension between scraping and privacy law. With the zealous pursuit and astronomical growth of AI, we are in the midst of what we call the “great scrape.” There must now be a great reconciliation…(More)”.
Kenya’s biggest protest in recent history played out on a walkie-talkie app
Article by Stephanie Wangari: “Betty had never heard of the Zello app until June 18.
But as she participated in Kenya’s “GenZ protests” that month — one of the biggest in the country’s history — the app became her savior.
On Zello, “we were getting updates and also updating others on where the tear-gas canisters were being lobbed and which streets had been cordoned off,” Betty, 27, told Rest of World, requesting to be identified by a pseudonym as she feared backlash from the police. “At one point, I also alerted the group [about] suspected undercover investigative officers who were wearing balaclavas.”
The speed of communicating over Zello made it the primary tool to mobilize crowds and coordinate logistics during the protests. Stephanie Wangari
Nairobi witnessed massive protests in June as thousands of young Kenyans came out on the streets against a proposed bill that would increase taxes on staple foods and other essential goods and services. At least 39 people were killed, 361 were injured, and more than 335 were arrested by the police during the protests, according to human rights groups.
Amid the mayhem, Zello, an app developed by U.S. engineer Alexey Gavrilov in 2007, became the primary tool for protestors to communicate, mobilize crowds, and coordinate logistics. Six protesters told Rest of World that Zello, which allows smartphones to be used as walkie-talkies, helped them find meeting points, evade the police, and alert each other to potential dangers.
Digital services experts and political analysts said the app helped the protests become one of the most effective in the country’s history.
According to Herman Manyora, a political analyst and lecturer at the University of Nairobi, mobilization had always been the greatest challenge in organizing previous protests in Kenya. The ability to turn their “phones into walkie-talkies” made the difference for protesters, he told Rest of World.
“The government realized that the young people were able to navigate technological challenges. You switch off one app, such as [X], they move to another,” Manyora said.
Zello was downloaded over 40,000 times on the Google Play store in Kenya between June 17 and June 25, according to data from the company. This was “well above our usual numbers,” a company spokesperson told Rest of World. Zello did not respond to additional requests for comment…(More)“
Everyone Has A Price — And Corporations Know Yours
Article by David Dayen: “Six years ago, I was at a conference at the University of Chicago, the intellectual heart of corporate-friendly capitalism, when my eyes found the cover of the Chicago Booth Review, the business school’s flagship publication. “Are You Ready for Personalized Pricing?” the headline asked. I wasn’t, so I started reading.
The story looked at how online shopping, persistent data collection, and machine-learning algorithms could combine to generate the stuff of economists’ dreams: individual prices for each customer. It even recounted an experiment in 2015, where online employment website ZipRecruiter essentially outsourced its pricing strategy to two University of Chicago economists, Sanjog Misra and Jean-Pierre Dubé…(More)”.
What does a ‘mission-driven’ approach to government mean and how can it be delivered?
Report by the Institute for Government and Nesta: “… set out a recommended approach for how government could effectively organise itself to deliver missions. It should act as a guide for public servants at the start of a new administration that has pledged to do things differently.
Missions are designed to set bold visions for change, inspiring collaboration across the system and society to break down silos and work towards a common goal. They represent the ultimate purpose of the Government, and the story it aims to tell by the end of the Parliament.
To succeed, government will need to adopt three key roles: driving public service innovation, shaping markets and harnessing collective intelligence to improve decision-making. Achieving these missions will require strong foundations and well-recognised enablers of good government, pursued in a specific manner to bring about a cultural change in Whitehall…(More)”.
Against Elections: The Lottocratic Alternative
Paper by Alexander A. Guerrero: “It is widely accepted that electoral representative democracy is better — along a number of different normative dimensions — than any other alternative lawmaking political arrangement. It is not typically seen as much of a competition: it is also widely accepted that the only legitimate alternative to electoral representative democracy is some form of direct democracy, but direct democracy — we are told — would lead to bad policy. This article makes the case that there is a legitimate alternative system — one that uses lotteries, not elections, to select political officials — that would be better than electoral representative democracy. Part I diagnoses two significant failings of modern-day systems of electoral representative government: the failure of responsiveness and the failure of good governance. The argument offered suggests that these flaws run deep, so that even significant and politically unlikely reforms with respect to campaign finance and election law would make little difference. Although my distillation of the argument is novel, the basic themes will likely be familiar. I anticipate the initial response to the argument may be familiar as well: the Churchillian shrug. Parts II, III, and IV of this article represent the beginning of an effort to move past that response, to think about alternative political systems that might avoid some of the problems with the electoral representative system without introducing new and worse problems. In the second and third parts of the article, I outline an alternative political system, the lottocratic system, and present some of the virtues of such a system. In the fourth part of the article, I consider some possible problems for the system. The overall aims of this article are to raise worries for electoral systems of government, to present the lottocratic system and to defend the view that this system might be a normatively attractive alternative, removing a significant hurdle to taking a non-electoral system of government seriously as a possible improvement to electoral democracy…(More)”
Bringing Communities In, Achieving AI for All
Article by Shobita Parthasarathy and Jared Katzman: “…To this end, public and philanthropic research funders, universities, and the tech industry should be seeking out partnerships with struggling communities, to learn what they need from AI and build it. Regulators, too, should have their ears to the ground, not just the C-suite. Typical members of a marginalized community—or, indeed, any nonexpert community—may not know the technical details of AI, but they understand better than anyone else the power imbalances at the root of concerns surrounding AI bias and discrimination. And so it is from communities marginalized by AI, and from scholars and organizations focused on understanding and ameliorating social disadvantage, that AI designers and regulators most need to hear.
Progress toward AI equity begins at the agenda-setting stage, when funders, engineers, and corporate leaders make decisions about research and development priorities. This is usually seen as a technical or management task, to be carried out by experts who understand the state of scientific play and the unmet needs of the market… A heartening example comes from Carnegie Mellon University, where computer scientists worked with residents in the institution’s home city of Pittsburgh to build a technology that monitored and visualized local air quality. The collaboration began when researchers attended community meetings where they heard from residents who were suffering the effects of air pollution from a nearby factory. The residents had struggled to get the attention of local and national officials because they were unable to provide the sort of data that would motivate interest in their case. The researchers got to work on prototype systems that could produce the needed data and refined their technology in response to community input. Eventually their system brought together heterogeneous information, including crowdsourced smell reports, video footage of factory smokestacks, and air-quality and wind data, which the residents then submitted to government entities. After reviewing the data, administrators at the Environmental Protection Agency agreed to review the factory’s compliance, and within a year the factory’s parent company announced that the facility would close…(More)”.
Finding, distinguishing, and understanding overlooked policy entrepreneurs
Paper by Gwen Arnold, Meghan Klasic, Changtong Wu, Madeline Schomburg & Abigail York: “Scholars have spent decades arguing that policy entrepreneurs, change agents who work individually and in groups to influence the policy process, can be crucial in introducing policy innovation and spurring policy change. How to identify policy entrepreneurs empirically has received less attention. This oversight is consequential because scholars trying to understand when policy entrepreneurs emerge, and why, and what makes them more or less successful, need to be able to identify these change agents reliably and accurately. This paper explores the ways policy entrepreneurs are currently identified and highlights issues with current approaches. We introduce a new technique for eliciting and distinguishing policy entrepreneurs, coupling automated and manual analysis of local news media and a survey of policy entrepreneur candidates. We apply this technique to the empirical case of unconventional oil and gas drilling in Pennsylvania and derive some tentative results concerning factors which increase entrepreneurial efficacy…(More)”.