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Paper short abstract

This paper examines the conception, applications and uses of "predictive justice" tools, that aim at harmonizing decision-making in the legal field. It is based on a survey (N = 17) conducted in France amongst both the producers and users of one of these tools.

Paper long abstract

“Predictive justice” tools (Cohen et al, 2020), which enable the anticipation of likely outcomes of a case based on its characteristics, have been at the center of numerous debates (Garapon, Lassègue, 2018). While these technologies could help standardize decisions across the country and/or within a given court (Chen, Spamann, 2016), such standardization conflicts with legal norms (Dumoulin, 2022) and values (particularly the concept of the uniqueness of each case). “Predictive justice” tools are therefore widely criticized and rarely used by judges, even when they have access to them (Brayne, Christin, 2021 ; Licoppe, Dumoulin, 2019).

In France, despite some pilot projects (Vergès, Vial, 2022), these tools are not used in the courts. However, they are used by lawyers, who employ them particularly in mediation processes, which help reach an agreement between the parties and thus avoid going before a judge. In this sense, the use of “predictive justice” by lawyers could indeed facilitate standardization of outcomes in cases where negotiation is possible.

This paper examines the nature of this harmonization. It shows that the results produced by “predictive justice” are based on a categorization (Bowker, Star, 2000) that is sometimes oversimplified, which imposes numerous limitations on the consideration of the specificities of individual situations. It also examines how lawyers adopt these tools, and establishes that lawyers do not simply accept the tools’ results at face value, meaning that the tools do not automatically produce the standardization they aim for.

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The current paper models the actors involved in the deployment of Distributed Acoustic Sensing in the UK using Rasmussen's Risk Management Framework. Social network analysis is applied to examine system dynamics and identify key actors that shape the development and governance of DAS.

Paper long abstract

Distributed Acoustic Sensing (DAS) is an emerging technology that operationalises datafication by detecting environmental vibrations along the length of dark fibres (unused optical fibre cables), generating continuous streams of analysable data. DAS is already being used to monitor railway tracks and seismic activity, to detect leaks in pipelines, and more. The flexibility and resilience of DAS infrastructure are drawing interest towards its integration into smart cities. The operation of DAS in smart cities is not yet known, but will likely depend on partnerships between various actors ranging from industry to government.

The current paper uses actor maps to model the interdependencies among actors involved in the deployment of DAS in smart cities across the system hierarchy proposed by the Risk Management Framework (Rasmussen, 1997). We have created an actor map representation to examine the ‘layout of decision-makers, planners and actors’ involved within the DAS sociotechnical system in the UK. We then employed social network metrics to interrogate actor prominence and system-level dynamics. By identifying both top-down and bottom-up influences that shape the deployment of DAS, the paper demonstrates how accountability gaps may emerge within the datafied state. We also propose systemic recommendations to promote the development of future, justice-driven governance structures aligned with public interests in regulatory oversight.

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This paper theorises the Subscribed State, where governance shifts into proprietary cloud infrastructures owned by Amazon and Google. It shows how cloudification transforms democratic oversight, recasts bureaucrats as inefficiencies, and embeds state power within corporate algorithmic systems.

Paper long abstract

This paper theorises an infrastructural inversion of democratic governance, where the state is increasingly subsumed into the proprietary logic of cloud-based global digital platforms. We show how this represents a shift from territorial sovereignty to a "Subscribed State" model, where external corporate actors extend their influence over state decision-making. Under this paradigm, the core functions of the state are operationalised within black-boxed, privately owned infrastructures. The model prefigures a "more-than-now" future, where liberal democracy is challenged by the rise of an algorithmic state. By framing governance as a series of optimizations to be solved by AI, the project envisions a dehumanization of the public sector in favor of automated algorithmic systems. Consequently, the traditional "street-level bureaucrats" who mediate between the state and its citizens are increasingly framed as redundant "bureaucratic friction" or budgetary overhead.

We exemplify this transition through Project Nimbus, the wholesale "cloudification" of the Israeli state via Amazon (AWS) and Google (GCP). Through document analysis and interviews with actors within the state bureaucracy, we analyse how the cloudification of governance translates democratic deliberation into executable code. As state functions are outsourced to corporate cultures, the capacity for democratic oversight is eroded and replaced by a techno-solutionist approach that views AI as a more obedient and efficient alternative to a human, unionised workforce. This paper contends that the cloudification of the state redefines the relation between citizen and sovereign, questioning whether democratic agency can survive when the very substrate of governance is owned and governed by market-driven infrastructures.

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This submission investigates the role of data visualisation for agonistic public participation in climate assemblies. By studying Gipuzkoa’s Citizens’ Assembly, it unpacks how the conflict between the promise of sharing power and established procedures was articulated around accountability charts.

Paper long abstract

This submission investigates the role of data visualisation as a resource for oversight, contestation, and agonism in the context of climate assemblies—assemblies of citizens or residents discussing climate-related issues and measures. These processes make up a growing format in the landscape of democratic innovations, testifying how climate inaction is increasingly framed in relation to the crisis of governance institutions.

In both academic and non-academic contexts, data visualisation is more and more studied for its varied potential in supporting and enhancing public participation. If the institutional crisis is understood as a “crisis of elected oligarchy", visualisation’s role in citizen involvement is centred on countering the concentration of power in the hands of a few. This role can be fulfilled by revealing, analysing, and challenging unequal power structures.

We explore how contestation developed around data visualisation in the “accountability phase” in the Gipuzkoako Herritarren Batzarra (Citizens’ Assembly of Gipuzkoa). In four meetings held by the provincial administration, colour-coded charts were used to show, assess, and challenge implementation results: the members of the assembly acted as “guardians” scrutinising the work of the provincial council.

The case was engaged through desk research, observation and interviews of the various actors involved in the process. Questions focused on reciprocal expectations and use of data visualisation in the accountability meetings. The analysis performed followed an abductive approach.

Visualisations performed as boundary objects around which tensions and confrontations materialised and unravelled, ultimately articulating the conflict between the promise of sharing power and the established governance logics and procedures.

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This paper discusses the concept of AI diplomacy through an infrastructural framework showing how expert knowledge shapes diplomatic practice, governance, and geopolitical relations.

Paper long abstract

Artificial intelligence (AI) is increasingly central to diplomatic practice, yet the emerging field of AI diplomacy remains conceptually underdeveloped, particularly regarding its relationship to expert knowledge. AI diplomacy has become a buzzword circulating across policy and academic arenas, while remaining undertheorized. This paper addresses this gap through a structured, integrative narrative review of the literature. Our analysis shows that existing scholarship conflates two dimensions of AI diplomacy: AI as a tool shaping everyday diplomatic practice (AI4D) and AI as an object of international governance (D4AI). We argue that these represent complementary but analytically distinct strands. Across both strands, expert knowledge plays a crucial role in shaping AI science, technology, and innovation infrastructures, as well as informing governance frameworks that address AI’s risks and benefits. Based on our findings, we offer novel definitions of AI diplomacy and AI science diplomacy and put forward an analytical framework identifying three roles of AI in infrastructuring diplomacy. Infrastructuring can be understood as bundles of co-located and co-existing epistemic practices sustain AI diplomacy by a) shaping and co-producing everyday diplomatic practice, b) becoming an object of governance through standards and regulatory frameworks, and c) affecting geopolitical relations, including cooperation and competition between international actors. Unlike traditional science diplomacy frameworks, our approach foregrounds the contested, power-laden and infrastructural dynamics linking epistemic practices and diplomacy. We show that AI’s role in diplomacy is self-referential: the tools and systems diplomats use, the frameworks that govern them, and the innovation ecosystems that produce them are mutually constitutive.

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This paper examines the "simulative turn" in which Big Data and AI reshape logics and practices of governing. It argues that these reconfigure political epistemology, shifting political practice grounded in representation and conflict toward regimes centered on modelling, prediction and preemption.

Paper long abstract

Over the past decade, public sector and political bodies have increasingly developed and deployed algorithmic, data-driven technologies to inform decision-making. These include sandboxes, testbeds and, more recently, digital twins as experimental governance infrastructures. Entangled with narratives of evidence-based policymaking, smart government, and experimentalist governance, their deployment raises questions about democracy and the political itself. Data analytics is often framed as better able to anticipate citizens’ needs and interests than citizens themselves. In this sense, such technologies reflect Jean Baudrillard’s notion of the vanishing of representation in the age of simulation and Donna Haraway’s claim that simulation replaces representation in the information society, signaling a potential erosion of political representation. This paper asks: To what extent do algorithmic, data-driven technologies in the public sector instantiate simulation as a pervasive form of governmentality? And what are the implications of this simulative turn for the very idea of political representation? Methodologically, the study combines close reading and Foucauldian critical discourse analysis, drawing on urban governance in the EU as an empirical case. It traces how simulation has emerged as a political technique to execute political agendas. As simulations become embedded in governance and decision-making, they reinforce a technocratic paradigm that seeks to datafy and quantify the world. The emphasis on predictive, data-driven evidence signals a shift from a political practice grounded in representation and conflict toward modelling and pre-emption. This transformation reconfigures political epistemology, positioning the assumption of predictability of political opinion forming as the unquestioned legitimacy horizon of political deci-sion-making.

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Paper short abstract

In this presentation we introduce a concept of digital preparedness as a critical inroad to the study of digital politics. We develop our concept through an analysis of digital responses to the Covid pandemic in Norway, focusing on the rapid creation of a preparedness registry.

Paper long abstract

In this presentation we introduce a concept of digital preparedness as a critical inroad to the

study of digital politics in the 21st century. Digital preparedness is a hybrid form of

governance mobilised to enhance future capacity for emergency response through

increased data connectivity and collaboration across domains. It is triggered by a state

of exception and works through a dual suspension: of rights and regulations, on the

one hand, and of hindrances to digital innovation in the public sector and health data

infrastructures on the other. We develop our concept through an analysis of digital

responses to the Covid pandemic in Norway, focusing on the rapid creation of a

preparedness registry. This registry integrated previously siloed health databases with

mobility, social services, education, and defence data, while simultaneously justifying

expansions of Norway’s extensive health data ecosystem. We describe how digital

preparedness was used to instigate regulatory and institutional reforms, and to

overcome prior 'barriers' (such as fundamental rights) to increasingly connect

heterogeneous data sources. We conclude by identifying the defining features of digital

preparedness as a mode of governance and we consider its implications for digital

politics and crisis management.