Enrolling Citizens: A Primer on Archetypes of Democratic Engagement with AI


Paper by Wanheng Hu and Ranjit Singh: “In response to rapid advances in artificial intelligence, lawmakers, regulators, academics, and technologists alike are sifting through technical jargon and marketing hype as they take on the challenge of safeguarding citizens from the technology’s potential harms while maximizing their access to its benefits. A common feature of these efforts is including citizens throughout the stages of AI development and governance. Yet doing so is impossible without a clear vision of what citizens ideally should do. This primer takes up this imperative and asks: What approaches can ensure that citizens have meaningful involvement in the development of AI, and how do these approaches envision the role of a “good citizen”?

The primer highlights three major approaches to involving citizens in AI — AI literacy, AI governance, and participatory AI — each of them premised on the importance of enrolling citizens but envisioning different roles for citizens to play. While recognizing that it is largely impossible to come up with a universal standard for building AI in the public interest, and that all approaches will remain local and situated, this primer invites a critical reflection on the underlying assumptions about technology, democracy, and citizenship that ground how we think about the ethics and role of public(s) in large-scale sociotechnical change. ..(More)”.

Handbook of Public Participation in Impact Assessment


Book edited by Tanya Burdett and A. John Sinclair: “… provides a clear overview of how to achieve meaningful public participation in impact assessment (IA). It explores conceptual elements, including the democratic core of public participation in IA, as well as practical challenges, such as data sharing, with diverse perspectives from 39 leading academics and practitioners.

Critically examining how different engagement frameworks have evolved over time, this Handbook underlines the ways in which tokenistic approaches and wider planning and approvals structures challenge the implementation of meaningful public participation. Contributing authors discuss the impact of international agreements, legislation and regulatory regimes, and review commonly used professional association frameworks such as the International Association for Public Participation core values for practice. They demonstrate through case studies what meaningful public participation looks like in diverse regional contexts, addressing the intentions of being purposeful, inclusive, transformative and proactive. By emphasising the strength of community engagement, the Handbook argues that public participation in IA can contribute to enhanced democracy and sustainability for all…(More)”.

Using ChatGPT to Facilitate Truly Informed Medical Consent


Paper by Fatima N. Mirza: “Informed consent is integral to the practice of medicine. Most informed consent documents are written at a reading level that surpasses the reading comprehension level of the average American. Large language models, a type of artificial intelligence (AI) with the ability to summarize and revise content, present a novel opportunity to make the language used in consent forms more accessible to the average American and thus, improve the quality of informed consent. In this study, we present the experience of the largest health care system in the state of Rhode Island in implementing AI to improve the readability of informed consent documents, highlighting one tangible application for emerging AI in the clinical setting…(More)”.

Societal interaction plans—A tool for enhancing societal engagement of strategic research in Finland


Paper by Kirsi Pulkkinen, Timo Aarrevaara, Mikko Rask, and Markku Mattila: “…we investigate the practices and capacities that define successful societal interaction of research groups with stakeholders in mutually beneficial processes. We studied the Finnish Strategic Research Council’s (SRC) first funded projects through a dynamic governance lens. The aim of the paper is to explore how the societal interaction was designed and commenced at the onset of the projects in order to understand the logic through which the consortia expected broad impacts to occur. The Finnish SRC introduced a societal interaction plan (SIP) approach, which requires research consortia to consider societal interaction alongside research activities in a way that exceeds conventional research plans. Hence, the first SRC projects’ SIPs and the implemented activities and working logics discussed in the interviews provide a window into exploring how active societal interaction reflects the call for dynamic, sustainable practices and new capabilities to better link research to societal development. We found that the capacities of dynamic governance were implemented by integrating societal interaction into research, in particular through a ‘drizzling’ approach. In these emerging practices SIP designs function as platforms for the formation of communities of experts, rather than traditional project management models or mere communication tools. The research groups utilized the benefits of pooling academic knowledge and skills with other types of expertise for mutual gain. They embraced the limits of expertise and reached out to societal partners to truly broker knowledge, and exchange and develop capacities and perspectives to solve grand societal challenges…(More)”.

Inclusive by default: strategies for more inclusive participation


Article by Luiza Jardim and Maria Lucien: “…The systemic challenges that marginalised groups face are pressing and require action. The global average age of parliamentarians is 53, highlighting a gap in youth representation. Young people already face challenges like poverty, lack of education, unemployment and multiple forms of discrimination. Additionally, some participatory formats are often unappealing to young people and pose a challenge for engaging them. Gender equity research highlights the underrepresentation of women at all levels of decision-making and governance. Despite recent improvements, gender parity in governance worldwide is still decades or even centuries away. Meanwhile, ongoing global conflicts in Ukraine, Sudan, Gaza and elsewhere, as well as the impacts of a changing climate, have driven the recent increase in the number of forcibly displaced people to more than 100 million. The engagement of these individuals in decision-making can vary greatly depending on their specific circumstances and the nature of their displacement.

Participatory and deliberative democracy can have transformative impacts on historically marginalised communities but only if they are intentionally included in program design and implementation. To start with, it’s possible to reduce the barriers to participation, such as the cost and time of transport to the participation venue, or burdens imposed by social and cultural roles in society, like childcare. During the process, mindful and attentive facilitation can help balance power dynamics and encourage participation from traditionally excluded people. This is further strengthened if the facilitation team includes and trains members of priority communities in facilitation and session planning…(More)”.

Participation in the Age of Foundation Models


Paper by Harini Suresh et al: “Growing interest and investment in the capabilities of foundation models has positioned such systems to impact a wide array of services, from banking to healthcare. Alongside these opportunities is the risk that these systems reify existing power imbalances and cause disproportionate harm to historically marginalized groups. The larger scale and domain-agnostic manner in which these models operate further heightens the stakes: any errors or harms are liable to reoccur across use cases. In AI & ML more broadly, participatory approaches hold promise to lend agency and decision-making power to marginalized stakeholders, leading to systems that better benefit justice through equitable and distributed governance. But existing approaches in participatory AI/ML are typically grounded in a specific application and set of relevant stakeholders, and it is not straightforward how to apply these lessons to the context of foundation models. Our paper aims to fill this gap.
First, we examine existing attempts at incorporating participation into foundation models. We highlight the tension between participation and scale, demonstrating that it is intractable for impacted communities to meaningfully shape a foundation model that is intended to be universally applicable. In response, we develop a blueprint for participatory foundation models that identifies more
local, application-oriented opportunities for meaningful participation. In addition to the “foundation” layer, our framework proposes the “subfloor” layer, in which stakeholders develop shared technical infrastructure, norms and governance for a grounded domain such as clinical care, journalism, or finance, and the “surface” (or application) layer, in which affected communities shape the use of a foundation model for a specific downstream task. The intermediate “subfloor” layer scopes the range of potential harms to consider, and affords communities more concrete avenues for deliberation and intervention. At the same time, it avoids duplicative effort by scaling input across relevant use cases. Through three case studies in clinical care, financial services, and journalism, we illustrate how this multi-layer model can create more meaningful opportunities for participation than solely intervening at the foundation layer…(More)”.

The citizen’s panel on AI issues its report


Belgian presidency of the European Union: “Randomly select 60 citizens from all four corners of Belgium. Give them an exciting topic to explore. Add a few local players. Season with participation experts. Bake for three weekends at the Egmont Palace conference centre. And you’ll end up with the rich and ambitious views of citizens on the future of artificial intelligence (AI) in the European Union.

This is the recipe that has been in progress since February 2024, led by the Belgian presidency of the European Union, with the ambition of involving citizens in this strategic field and enriching the debate on AI, which has been particularly lively in recent months as part of the drafting of the AI Act recently adopted by the European Parliament.

And the initiative really cut the mustard, as the 60 citizens worked enthusiastically, overcoming their apprehensions about a subject as complex as AI. In a spirit of collective intelligence, they dove right into the subject, listening to speakers from academia, government, civil society and the private sector, and sharing their experiences and knowledge. Some of them were just discovering AI, while others were already using it. They turned this diversity into a richness, enabling them to write a report on citizens’ views that reflects the various aspirations of the Belgian population.

At the end of the three weekends, the citizens almost unanimously adopted a precise and ambitious report containing nine key messages focusing on the need for a responsible, ambitious and beneficial approach to AI, ensuring that it serves the interests of all and leaves no one behind…(More)”

Dynamic Collective Action and the Power of Large Numbers


Paper by Marco Battaglini & Thomas R. Palfrey: “Collective action is a dynamic process where individuals in a group assess over time the benefits and costs of participating toward the success of a collective goal. Early participation improves the expectation of success and thus stimulates the subsequent participation of other individuals who might otherwise be unwilling to engage. On the other hand, a slow start can depress expectations and lead to failure for the group. Individuals have an incentive to procrastinate, not only in the hope of free riding, but also in order to observe the flow of participation by others, which allows them to better gauge whether their own participation will be useful or simply wasted. How do these phenomena affect the probability of success for a group? As the size of the group increases, will a “power of large numbers” prevail producing successful outcomes, or will a “curse of large numbers” lead to failure? In this paper, we address these questions by studying a dynamic collective action problem in which n individuals can achieve a collective goal if a share of them takes a costly action (e.g., participate in a protest, join a picket line, or sign an environmental agreement). Individuals have privately known participation costs and decide over time if and when to participate. We characterize the equilibria of this game and show that under general conditions the eventual success of collective action is necessarily probabilistic. The process starts for sure, and hence there is always a positive probability of success; however, the process “gets stuck” with positive probability, in the sense that participation stops short of the goal. Equilibrium outcomes have a simple characterization in large populations: welfare converges to either full efficiency or zero as n→∞ depending on a precise condition on the rate at which the share required for success converges to zero. Whether success is achievable or not, delays are always irrelevant: in the limit, success is achieved either instantly or never…(More)”

Cities Are at the Forefront of AI and Civic Engagement


Article by Hollie Russon Gilman and Sarah Jacob: “…cities worldwide are already adopting AI for everyday governance needs. Buenos Aires is integrating communication with residents through Boti, an AI chatbot accessible via WhatsApp. Over 5 million residents are using the chatbot everyday month, with some months upwards of 11 million users. Boti connects residents with city services such as bike sharing or social care programs or reports. Unlike other AI systems with a closed loop, Boti can connect externally to help residents with other government services. For more sensitive issues, such as domestic abuse, Boti can connect residents with a human operator. AI, in this context, offers residents a convenient means to efficiently engage with city resources and communicate with city employees.

Another example of AI improving people’s everyday lives is SomosUna, a partnership between the Inter American Development Bank and Next2MyLife, aims to address gender-based violence in Uruguay. In response to the rise in gender-based violence during and after Covid, this initiative aims to prevent violence through a network of support and “helpers” which includes 1) training 2) technology and 3) a community of volunteers. This initiative will leverage AI technology to enhance its support network, advancing preventative measures and providing immediate assistance.

While AI can foster engagement, local government officials recognize that they must pre-engage the public to determine the role that AI should play in civic life across diverse cities. This pre-engagement and education will inform the ethical standards and considerations against which AI will be assessed.

The EU’s ITHACA project, for example, explores the application of AI in civic participation and local governance…(More)”… See also: AI Localism.

Democratic innovations beyond the deliberative paradigm


Paper by Christian Opitz: “The current research on deliberative-participatory democratic innovations conducted by state administration agencies exhibits empirical eclecticism and is dominated by a deliberative paradigm. However, this paradigm tends to conflate normative prescription with analytical description. In contrast, this article proposes a comprehensive re-conceptualization of such innovations, drawing from Niklas Luhmann’s systems theory. It outlines the specific problem these innovations address (function), how they operate in tackling this problem (functioning) and the problems they inevitably raise (dysfunctions). In addition, my re-conceptualization retains the possibility to critically compare these (and other) experiments regarding their capability to address emerging challenges within the modern democratic political system…(More)”.