Book by Antonino Palumbo: “Thirty years of developments in deliberative democracy (DD) have consolidated this subfield of democratic theory. The acquired disciplinary prestige has made theorist and practitioners very confident about the ability of DD to address the legitimacy crisis experienced by liberal democracies at present at both theoretical and practical levels. The book advance a critical analysis of these developments that casts doubts on those certainties — current theoretical debates are reproposing old methodological divisions, and are afraid to move beyond the minimalist model of democracy advocated by liberal thinkers; democratic experimentation at the micro-level seems to have no impact at the macro-level, and remain sets of isolated experiences. The book indicates that those defects are mainly due to the liberal minimalist frame of reference within which reflection in democratic theory and practice takes place. Consequently, it suggests to move beyond liberal understandings of democracy as a game in need of external rules, and adopt instead a vision of democracy as a self-correcting metagame…(More)”.
Using Artificial Intelligence to Accelerate Collective Intelligence
Paper by Róbert Bjarnason, Dane Gambrell and Joshua Lanthier-Welch: “In an era characterized by rapid societal changes and complex challenges, institutions’ traditional methods of problem-solving in the public sector are increasingly proving inadequate. In this study, we present an innovative and effective model for how institutions can use artificial intelligence to enable groups of people to generate effective solutions to urgent problems more efficiently. We describe a proven collective intelligence method, called Smarter Crowdsourcing, which is designed to channel the collective intelligence of those with expertise about a problem into actionable solutions through crowdsourcing. Then we introduce Policy Synth, an innovative toolkit which leverages AI to make the Smarter Crowdsourcing problem-solving approach both more scalable, more effective and more efficient. Policy Synth is crafted using a human-centric approach, recognizing that AI is a tool to enhance human intelligence and creativity, not replace it. Based on a real-world case study comparing the results of expert crowdsourcing alone with expert sourcing supported by Policy Synth AI agents, we conclude that Smarter Crowdsourcing with Policy Synth presents an effective model for integrating the collective wisdom of human experts and the computational power of AI to enhance and scale up public problem-solving processes.
The potential for artificial intelligence to enhance the performance of groups of people has been a topic of great interest among scholars of collective intelligence. Though many AI toolkits exist, they too often are not fitted to the needs of institutions and policymakers. While many existing approaches view AI as a tool to make crowdsourcing and deliberative processes better and more efficient, Policy Synth goes a step further, recognizing that AI can also be used to synthesize the findings from engagements together with research to develop evidence-based solutions and policies. This study contributes significantly to the fields of collective intelligence, public problem-solving, and AI. The study offers practical tools and insights for institutions looking to engage communities effectively in addressing urgent societal challenges…(More)”
The tensions of data sharing for human rights: A modern slavery case study
Paper by Jamie Hancock et al: “There are calls for greater data sharing to address human rights issues. Advocates claim this will provide an evidence-base to increase transparency, improve accountability, enhance decision-making, identify abuses, and offer remedies for rights violations. However, these well-intentioned efforts have been found to sometimes enable harms against the people they seek to protect. This paper shows issues relating to fairness, accountability, or transparency (FAccT) in and around data sharing can produce such ‘ironic’ consequences. It does so using an empirical case study: efforts to tackle modern slavery and human trafficking in the UK. We draw on a qualitative analysis of expert interviews, workshops, ecosystem mapping exercises, and a desk-based review. The findings show how, in the UK, a large ecosystem of data providers, hubs, and users emerged to process and exchange data from across the country. We identify how issues including legal uncertainties, non-transparent sharing procedures, and limited accountability regarding downstream uses of data may undermine efforts to tackle modern slavery and place victims of abuses at risk of further harms. Our findings help explain why data sharing activities can have negative consequences for human rights, even within human rights initiatives. Moreover, our analysis offers a window into how FAccT principles for technology relate to the human rights implications of data sharing. Finally, we discuss why these tensions may be echoed in other areas where data sharing is pursued for human rights concerns, identifying common features which may lead to similar results, especially where sensitive data is shared to achieve social goods or policy objectives…(More)”.
The revolution shall not be automated: On the political possibilities of activism through data & AI
Article by Isadora Cruxên: “Every other day now, there are headlines about some kind of artificial intelligence (AI) revolution that is taking place. If you read the news or check social media regularly, you have probably come across these too: flashy pieces either trumpeting or warning against AI’s transformative potential. Some headlines promise that AI will fundamentally change how we work and learn or help us tackle critical challenges such as biodiversity conservation and climate change. Others question its intelligence, point to its embedded biases, and draw attention to its extractive labour record and high environmental costs.
Scrolling through these headlines, it is easy to feel like the ‘AI revolution’ is happening to us — or perhaps blowing past us at speed — while we are enticed to take the backseat and let AI-powered chat-boxes like ChatGPT do the work. But the reality is that we need to take the driver’s seat.
If we want to leverage this technology to advance social justice and confront the intersecting socio-ecological challenges before us, we need to stop simply wondering what the AI revolution will do to us and start thinking collectively about how we can produce data and AI models differently. As Mimi Ọnụọha and Mother Cyborg put it in A People’s Guide to AI, “the path to a fair future starts with the humans behind the machines, not the machines themselves.”
Sure, this might seem easier said than done. Most AI research and development is being driven by big tech corporations and start-ups. As Lauren Klein and Catherine D’Ignazio discuss in “Data Feminism for AI” (see “Further reading” at the end for all works cited), the results are models, tools, and platforms that are opaque to users, and that cater to the tech ambitions and profit motives of private actors, with broader societal needs and concerns becoming afterthoughts. There is excellent critical work that explores the extractive practices and unequal power relations that underpin AI production, including its relationship to processes of datafication, colonial data epistemologies, and surveillance capitalism (to link but a few). Interrogating, illuminating, and challenging these dynamics is paramount if we are to take the driver’s seat and find alternative paths…(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)”.
Are We Ready for the Next Pandemic? Navigating the First and Last Mile Challenges in Data Utilization
Blog by Stefaan Verhulst, Daniela Paolotti, Ciro Cattuto and Alessandro Vespignani:
“Public health officials from around the world are gathering this week in Geneva for a weeklong meeting of the 77th World Health Assembly. A key question they are examining is: Are we ready for the next pandemic? As we have written elsewhere, regarding access to and re-use of data, particularly non-traditional data, for pandemic preparedness and response: we are not. Below, we list ten recommendations to advance access to and reuse of non-traditional data for pandemics, drawing on input from a high-level workshop, held in Brussels, within the context of the ESCAPE program…(More)”
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Will we run out of data? Limits of LLM scaling based on human-generated data
Paper by Pablo Villalobos: We investigate the potential constraints on LLM scaling posed by the availability of public human-generated text data. We forecast the growing demand for training data based on current trends and estimate the total stock of public human text data. Our findings indicate that if current LLM development trends continue, models will be trained on datasets roughly equal in size to the available stock of public human text data between 2026 and 2032, or slightly earlier if models are overtrained. We explore how progress in language modeling can continue when human-generated text datasets cannot be scaled any further. We argue that synthetic data generation, transfer learning from data-rich domains, and data efficiency improvements might support further progress…(More)”.
Unmasking and Quantifying Power Structures: How Network Analysis Enhances Peace and State-Building Efforts
Blog by Issa Luna Pla: “Critiques of peace and state-building efforts have pointed out the inadequate grasp of the origins of conflict, political unrest, and the intricate dynamics of criminal and illicit networks (Holt and Bouch, 2009; Cockayne and Lupel, 2011). This limited understanding has failed to sufficiently weaken their economic and political influence or effectively curb their activities and objectives. A recent study highlights that although punitive approaches may have temporarily diminished the power of these networks, the absence of robust analytical tools has made it difficult to assess the enduring impact of these strategies.
1. Application of Network Analytics in State-Building
The importance of analytics in international peace and state-building operations is becoming increasingly recognized (O’Brien, 2010; Gnanguenon, 2021; Rød et al., 2023). Analytics, particularly network analysis, plays a crucial role in dissecting and dismantling complex power structures that often undermine peace initiatives and governance reforms. This analytical approach is crucial for revealing and disrupting the entrenched networks that sustain ongoing conflicts or obstruct peace processes. From the experiences in Guatemala, three significant lessons have been learned regarding the need for analytics for regional and thematic priorities in such operations (Waxenecker, 2019). These insights are vital for understanding how to tailor analytical strategies to address specific challenges in conflict-affected areas.
- The effectiveness of the International Commission CICIG in dismantling criminal networks was constrained by its lack of advanced analytical tools. This limitation prevented a deeper exploration of the conflicts’ roots and hindered the assessment of the long-term impacts of its strategies. While the CICIG had a systematic approach to understanding criminal networks from a contextual and legal perspective, its action plans lacked comprehensive statistic analytics methodologies, leading to missed opportunities in targeting key strategic players within these networks. High-level arrests were based on available evidence and charges that prosecutors could substantiate, rather than a strategic analysis of actors’ roles and influences within the networks’ dynamics.
- Furthermore, the extent of network dismantlement and the lasting effects of imprisonment and financial control of the illicit groups’ assets remain unclear, highlighting the need for predictive analytics to anticipate conflicts and sustainability. Such tools could enable operations to forecast potential disruptions or stability, allowing for data-driven proactive measures to prevent violence or bolster peace.
- Lastly, insights derived from network analysis suggest that efforts should focus on enhancing diplomatic negotiations, promoting economic development and social capital, and balancing punitive measures with strategic interventions. By understanding the dynamics and modeling group behavior in conflict zones, negotiations can be better informed by a deep and holistic comprehension of the underlying power structures and motivations. This approach could also help in forecasting recidivism, assessing risks of network reorganization, and evaluating the potential for increased armament, workforce, or empowerment, thereby facilitating more effective and sustainable peacebuilding initiatives.
2. Advancing Legal and Institutional Reforms
Utilizing data sciences in conflicted environments offers unique insights into the behavior of illicit networks and their interactions within the public and private sectors (Morselli et al., 2007; Leuprecht and Hall, 2014; Campedelli et al., 2019). This systematic approach, grounded in the analysis of years of illicit activities in Guatemala, highlights the necessity of rethinking traditional legal and institutional frameworks…(More)”.
Missions with Impact: A practical guide to formulating effective missions
Guide by the Bertelsmann Stiftung: “The complex challenges associated with sustainability transitions pose major problems for modern political systems and raise the question of whether new ways of negotiation, decision-making and implementation are needed to address these challenges. For example, given the broad-reaching effects of an issue like climate change on diverse aspects of daily life, policy fields and action areas, conventional solutions are unlikely to prove effective.
Mission orientation proves to be a promising approach for addressing cross-cutting thematic challenges. It involves formulating well-defined “missions” intended to direct innovation, economic activities and societal initiatives toward desired outcomes. These missions aim for transformational change, targeting fundamental shifts that extend beyond the usual political timelines to ensure enduring impact. Across several OECD countries and at the EU level, initiatives embracing a mission-oriented approach are gaining momentum. For instance, the EU’s mission of “100 climate-neutral cities” exemplifies this approach by exploring new pathways to achieve climate neutrality by 2030. Here, stakeholders from diverse sectors can get involved to help generate effective solutions targeting the objective of climate neutrality…(More)”.
Making Sense of Wicked Problems
Review by Andrew J. Hoffman: “While reading Oxford University professor Thomas Hale’s Long Problems: Climate Change and the Challenge of Governing Across Time, I kept thinking of evolutionary biologist Stephen Jay Gould’s observation that “we have become, by the power of a glorious evolutionary accident called intelligence, the stewards of life’s continuity on Earth. We did not ask for this role, but we cannot abjure it. We may not be suited to such responsibility, but here we are.”
Countless scientists have referred to climate change as part of a class of issues called “wicked problems,” a term used to describe issues that do not neatly fit the conventional models of analysis. While we may not be suited to solve the wicked problem of climate change and may despair that we will never be, Hale offers an analysis of how we might better understand and therefore address it.
Hale predicates Long Problems on the general observation that some political issues span not only national borders but also time horizons. His central claim is that climate change is a “long problem,” a challenge that “spans more than one human lifetime.” He acknowledges that while “length is not the only meaningful way to understand climate change, … a focus on this one characteristic can fundamentally reshape our understanding of politics” by challenging us to establish policies on longer time horizons and to account for the future in ways we have not previously done. Reenvisioning policy is important because long problems are becoming more prevalent, he argues, for three reasons: our growing technological ability to bump against limits within the environment, our growing understanding of those distant effects, and our increasing willingness to address the needs of the future in the present.
Long problems, Hale asserts, challenge us to “govern across time,” rather than in the short terms of election cycles and quarterly returns. He warns that such challenges become more difficult to address the longer we ignore long-term governance. Indeed, as long problems become more urgent, we become more immediate and short term in our political orientation. Put differently, when we are drowning, we are less concerned with fixing the cause of the flood than we are with surviving. Hale calls this a paradox that “is another of the various cruel ironies of climate change [because] it threatens precisely the political support for longer term governance functions that can best address it.”…(More)”.