The CFPB wants to rein in data brokers


Article by Gaby Del Valle: “The Consumer Financial Protection Bureau wants to propose new regulations that would require data brokers to comply with the Fair Credit Reporting Act. In a speech at the White House earlier this month, CFPB Director Rohit Chopra said the agency is looking into policies to “ensure greater accountability” for companies that buy and sell consumer data, in keeping with an executive order President Joe Biden issued in late February.

Chopra said the agency is considering proposals that would define data brokers that sell certain types of data as “consumer reporting agencies,” thereby requiring those companies to comply with the Fair Credit Reporting Act (FCRA). The statute bans sharing certain kinds of data (e.g., your credit report) with entities unless they serve a specific purpose outlined in the law (e.g., if the report is used for employment purposes or to extend a line of credit to someone).

The CFBP views the buying and selling of consumer data as a national security issue, not just a matter of privacy. Chopra mentioned three massive data breaches — the 2015 Anthem leak, the 2017 Equifax hack, and the 2018 Marriott breach — as examples of foreign adversaries illicitly obtaining Americans’ personal data. “When Americans’ health information, financial information, and even their travel whereabouts can be assembled into detailed dossiers, it’s no surprise that this raises risks when it comes to safety and security,” Chopra said. But the focus on high-profile hacks obscures a more pervasive, totally legal phenomenon: data brokers’ ability to sell detailed personal information to anyone who’s willing to pay for it…(More)”.

The generation of public value through e-participation initiatives: A synthesis of the extant literature


Paper by Naci Karkin and Asunur Cezar: “The number of studies evaluating e-participation levels in e-government services has recently increased. These studies primarily examine stakeholders’ acceptance and adoption of e-government initiatives. However, it is equally important to understand whether and how value is generated through e-participation, regardless of whether the focus is on government efforts or user adoption/acceptance levels. There is a need in the literature for a synthesis focusing on e- participation’s connection with public value creation using a systematic and comprehensive approach. This study employs a systematic literature review to collect, examine, and synthesize prior findings, aiming to investigate public value creation through e-participation initiatives, including their facilitators and barriers. By reviewing sixty-four peer-reviewed studies indexed by Web of Science and Scopus, this research demonstrates that e-participation initiatives and efforts can generate public value. Nevertheless, several factors are pivotal for the success and sustainability of these initiatives. The study’s findings could guide researchers and practitioners in comprehending the determinants and barriers influencing the success and sustainability of e-participation initiatives in the public value creation process while highlighting potential future research opportunities in this domain…(More)”.

How Belgium is Giving Citizens a Say on AI


Article by Graham Wetherall-Grujić: “A few weeks before the European Parliament’s final debate on the AI Act, 60 randomly selected members of the Belgian public convened in Brussels for a discussion of their own. The aim was not to debate a particular piece of legislation, but to help shape a European vision on the future of AI, drawing on the views, concerns, and ideas of the public. 

They were taking part in a citizens’ assembly on AI, held as part of Belgium’s presidency of the European Council. When Belgium assumed the presidency for six months beginning in January 2024, they announced they would be placing “special focus” on citizens’ participation. The citizen panel on AI is the largest of the scheduled participation projects. Over a total of three weekends, participants are deliberating on a range of topics including the impact of AI on work, education, and democracy. 

The assembly comes at a point in time with rising calls for more public inputs on the topic of AI. Some big tech firms have begun to respond with participation projects of their own. But this is the first time an EU institution has launched a consultation on the topic. The organisers hope it will pave the way for more to come…(More)”.

Social Movements and Public Opinion in the United States


Paper by Amory Gethin & Vincent Pons: “Recent social movements stand out by their spontaneous nature and lack of stable leadership, raising doubts on their ability to generate political change. This article provides systematic evidence on the effects of protests on public opinion and political attitudes. Drawing on a database covering the quasi-universe of protests held in the United States, we identify 14 social movements that took place from 2017 to 2022, covering topics related to environmental protection, gender equality, gun control, immigration, national and international politics, and racial issues. We use Twitter data, Google search volumes, and high-frequency surveys to track the evolution of online interest, policy views, and vote intentions before and after the outset of each movement. Combining national-level event studies with difference-in-differences designs exploiting variation in local protest intensity, we find that protests generate substantial internet activity but have limited effects on political attitudes. Except for the Black Lives Matter protests following the death of George Floyd, which shifted views on racial discrimination and increased votes for the Democrats, we estimate precise null effects of protests on public opinion and electoral behavior…(More)”.

The tech industry can’t agree on what open-source AI means. That’s a problem.


Article by Edd Gent: “Suddenly, “open source” is the latest buzzword in AI circles. Meta has pledged to create open-source artificial general intelligence. And Elon Musk is suing OpenAI over its lack of open-source AI models.

Meanwhile, a growing number of tech leaders and companies are setting themselves up as open-source champions. 

But there’s a fundamental problem—no one can agree on what “open-source AI” means. 

On the face of it, open-source AI promises a future where anyone can take part in the technology’s development. That could accelerate innovation, boost transparency, and give users greater control over systems that could soon reshape many aspects of our lives. But what even is it? What makes an AI model open source, and what disqualifies it?

The answers could have significant ramifications for the future of the technology. Until the tech industry has settled on a definition, powerful companies can easily bend the concept to suit their own needs, and it could become a tool to entrench the dominance of today’s leading players.

Entering this fray is the Open Source Initiative (OSI), the self-appointed arbiters of what it means to be open source. Founded in 1998, the nonprofit is the custodian of the Open Source Definition, a widely accepted set of rules that determine whether a piece of software can be considered open source. 

Now, the organization has assembled a 70-strong group of researchers, lawyers, policymakers, activists, and representatives from big tech companies like Meta, Google, and Amazon to come up with a working definition of open-source AI…(More)”.

New Jersey is turning to AI to improve the job search process


Article by Beth Simone Noveck: “Americans are experiencing some conflicting feelings about AI.

While people are flocking to new roles like prompt engineer and AI ethicist, the technology is also predicted to put many jobs at risk, including computer programmers, data scientists, graphic designers, writers, lawyers.

Little wonder, then, that a national survey by the Heldrich Center for Workforce Development found an overwhelming majority of Americans (66%) believe that they “will need more technological skills to achieve their career goals.” One thing is certain: Workers will need to train for change. And in a world of misinformation-filled social media platforms, it is increasingly important for trusted public institutions to provide reliable, data-driven resources.

In New Jersey, we’ve tried doing just that by collaborating with workers, including many with disabilities, to design technology that will support better decision-making around training and career change. Investing in similar public AI-powered tools could help support better consumer choice across various domains. When a public entity designs, controls and implements AI, there is a far greater likelihood that this powerful technology will be used for good.

In New Jersey, the public can find reliable, independent, unbiased information about training and upskilling on the state’s new MyCareer website, which uses AI to make personalized recommendations about your career prospects, and the training you will need to be ready for a high-growth, in-demand job…(More)”.

Could artificial intelligence benefit democracy?


Article by Brian Wheeler: “Each week sees a new set of warnings about the potential impact of AI-generated deepfakes – realistic video and audio of politicians saying things they never said – spreading confusion and mistrust among the voting public.

And in the UK, regulators, security services and government are battling to protect this year’s general election from malign foreign interference.

Less attention has been given to the possible benefits of AI.

But a lot of work is going on, often below the radar, to try to harness its power in ways that might enhance democracy rather than destroy it.

“While this technology does pose some important risks in terms of disinformation, it also offers some significant opportunities for campaigns, which we can’t ignore,” Hannah O’Rourke, co-founder of Campaign Lab, a left-leaning network of tech volunteers, says.

“Like all technology, what matters is how AI is actually implemented. “Its impact will be felt in the way campaigners actually use it.”

Among other things, Campaign Lab runs training courses for Labour and Liberal Democrat campaigners on how to use ChatGPT (Chat Generative Pre-trained Transformer) to create the first draft of election leaflets.

It reminds them to edit the final product carefully, though, as large language models (LLMs) such as ChatGPT have a worrying tendency to “hallucinate” or make things up.

The group is also experimenting with chatbots to help train canvassers to have more engaging conversations on the doorstep.

AI is already embedded in everyday programs, from Microsoft Outlook to Adobe Photoshop, Ms O’Rourke says, so why not use it in a responsible way to free up time for more face-to-face campaigning?…

Conservative-supporting AI expert Joe Reeve is another young political campaigner convinced the new technology can transform things for the better.

He runs Future London, a community of “techno optimists” who use AI to seek answers to big questions such as “Why can’t I buy a house?” and, crucially, “Where’s my robot butler?”

In 2020, Mr Reeve founded Tory Techs, partly as a right-wing response to Campaign Lab.

The group has run programming sessions and explored how to use AI to hone Tory campaign messages but, Mr Reeve says, it now “mostly focuses on speaking with MPs in more private and safe spaces to help coach politicians on what AI means and how it can be a positive force”.

“Technology has an opportunity to make the world a lot better for a lot of people and that is regardless of politics,” he tells BBC News…(More)”.

Citizen scientists—practices, observations, and experience


Paper by Michael O’Grady & Eleni Mangina: “Citizen science has been studied intensively in recent years. Nonetheless, the voice of citizen scientists is often lost despite their altruistic and indispensable role. To remedy this deficiency, a survey on the overall experiences of citizen scientists was undertaken. Dimensions investigated include activities, open science concepts, and data practices. However, the study prioritizes knowledge and practices of data and data management. When a broad understanding of data is lacking, the ability to make informed decisions about consent and data sharing, for example, is compromised. Furthermore, the potential and impact of individual endeavors and collaborative projects are reduced. Findings indicate that understanding of data management principles is limited. Furthermore, an unawareness of common data and open science concepts was observed. It is concluded that appropriate training and a raised awareness of Responsible Research and Innovation concepts would benefit individual citizen scientists, their projects, and society…(More)”.

Understanding the Crisis in Institutional Trust


Essay by Jacob Harold: “Institutions are patterns of relationship. They form essential threads of our social contract. But those threads are fraying. In the United States, individuals’ trust in major institutions has declined 22 percentage points since 1979.

Institutions face a range of profound challenges. A long-overdue reckoning with the history of racial injustice has highlighted how many institutions reflect patterns of inequity. Technology platforms have supercharged access to information but also reinforced bubbles of interpretation. Anti-elite sentiment has evolved into anti-institutional rebellion.

These forces are affecting institutions of all kinds—from disciplines like journalism to traditions like the nuclear family. This essay focuses on a particular type of institution: organizations. The decline in trust in organizations has practical implications: trust is essential to the day-to-day work of an organization—whether an elite university, a traffic court, or a corner store. The stakes for society are hard to overstate. Organizations “organize” much of our society, culture, and economy.

This essay is meant to offer background for ongoing conversations about the crisis in institutional trust. It does not claim to offer a solution; instead, it lays out the parts of the problem as a step toward shared solutions.

It is not possible to isolate the question of institutional trust from other trends. The institutional trust crisis is intertwined with broader issues of polarization, gridlock, fragility, and social malaise. Figure 1 maps out eight adjacent issues. Some of these may be seen as drivers of the institutional trust crisis, others as consequences of it. Most are both.

figure of institution trust crisis

This essay considers trust as a form of information. It is data about the external perceptions of institutions. Declining trust can thus be seen as society teaching itself. Viewing a decline in trust as information reframes the challenge. Sometimes, institutions may “deserve” some of the mistrust that has been granted to them. In those cases, the information can serve as a direct corrective…(More)”.

Evidence Ecosystems and the Challenge of Humanising and Normalising Evidence


Article by Geoff Mulgan: “It is reasonable to assume that the work of governments, businesses and civil society goes better if the people making decisions are well-informed, using reliable facts and strong evidence rather than only hunch and anecdote.  The term ‘evidence ecosystem’1  is a useful shorthand for the results of systematic attempts to make this easier, enabling decision makers, particularly in governments, to access the best available evidence, in easily digestible forms and when it’s needed.  

…This sounds simple.  But these ecosystems are as varied as ecosystems in nature.  How they work depends on many factors, including how political or technical the issues are; the presence or absence of confident, well-organised professions; the availability of good quality evidence; whether there is a political culture that values research; and much more.

In particular, the paper argues that the next generation of evidence ecosystems need a sharper understanding of how the supply of evidence meets demand, and the human dimension of evidence.  That means cultivating lasting relationships rather than relying too much on a linear flow of evidence from researchers to decision-makers; it means using conversation as much as prose reports to ensure evidence is understood and acted on; and it means making use of stories as well as dry analysis.  It depends, in other words, on recognising that the users of evidence are humans.

In terms of prescription the paper emphasises:

  • Sustainability/normalisation: the best approaches are embedded, part of the daily life of decision-making rather than depending on one-off projects and programmes.  This applies both to evidence and to data.  Yet embeddedness is the exception rather than the rule.
  • Multiplicity: multiple types of knowledge, and logics, are relevant to decisions, which is why people and institutions that understand these different logics are so vital.  
  • Credibility and relationships: the intermediaries who connect the supply and demand of knowledge need to be credible, with both depth of knowledge and an ability to interpret it for diverse audiences, and they need to be able to create and maintain relationships, which will usually be either place or topic based, and will take time to develop, with the communication of evidence often done best in conversation.
  • Stories: influencing decision-makers depends on indirect as well as direct communication, since the media in all their forms play a crucial role in validating evidence and evidence travels best with stories, vignettes and anecdotes.

In short, while evidence is founded on rigorous analysis, good data and robust methods, it also needs to be humanised – embedded in relationships, brought alive in conversations and vivid, human stories – and normalised, becoming part of everyday work…(More)”.