Motivation

Global financial and economic crises, critical technological dependencies, pandemics, and climate change have cast serious doubts on the adequacy of conventional policymaking to consider mechanisms underlying social and economic phenomena, as well as to provide effective policy prescriptions. Computational models are increasingly being used to guide decisions by studying their potential consequences prior to making them. From their original application in engineering and science, computational models have become a tool for evidence-based policy-making in a diverse set of contexts: public health, ecology, labour markets, urban planning, social security, crime mitigation, economic development, platform economy and techno-regulation. Motivated by their widespread deployment, work on using computational models beyond executive policies and towards law-making — i.e. beyond operational guidance and towards regulation, circumscribing the space in which policies can operate — is gaining momentum.

Computational approaches to policy design face persisting complementary challenges: formal validity; effectiveness; efficacy; sustainability, etc. Several disciplines have focused on distinct aspects of these dimensions (e.g. computational legal theory, game theory, control systems design, dynamic systems and system dynamics), offering alternative methodological standpoints and computational tools. Unfortunately, these specialized domains rarely interoperate and frequently contain troublesome assumptions such as overly simplistic fully observable static environments, static pay-off tables, static semantics, homogeneous agents that are perfectly rational and/or controllable. The resulting reduced views fail to take into account possible phenomena occurring at the boundaries between areas of concern.

A crucial role can be played, in this respect, by agent-based modelling (ABM). Based on an interactionist metaphor, agent-based models are an effective tool for understanding and reproducing the functioning and generation/emergence of complex macrodynamics and constructs (shared knowledge, practices, protocols of interaction) at an aggregate level. Applied in social contexts, and particularly within the frame of computational social science (CSS), ABM lends itself to regulators and policymakers but also more widely to judges, attorneys, and legislators.

Topics

The question this workshop aims to foreground is: what are the possible intersections between ABM (methods and tools) and policy-making? Herein, it puts special emphasis on normative standpoints and concerns, that is, going beyond executive policies and towards law-making — i.e. beyond operational guidance and towards regulation, circumscribing the space in which policies can operate.

ABM calls for a “computation-enhanced regulatory empiricism”, exploiting computation to investigate factual underpinnings of the legal phenomenon, like the intricate networks of cognitive, social, technological, and legal mechanisms through which law emerges, is applied, and exerts its effects. This workshop call is also in line with recent trends of legal scholarship, where growing attention is devoted to the empirical study of law based on quantitative approaches.

Scope

The workshop aims to attract participants from various disciplines, and to be of interest to anyone working with the domain of governance of large-scale self-adaptive systems (human, computational, or natural): policy-making, governance, (computational) social science, (computational) legal theory, (computational) economics, autonomic computing, regulatory design, distributed systems, agent-based modelling, and complexity science.

Participation and Submission

People interested in participating are requested to submit extended abstracts (500-1000 words, excluding references) until the 19th November 2021 via easychair: https://easychair.org/conferences/?conf=ampm2021. Authors of the accepted abstracts presented at the workshop will be asked to extend their contributions to short papers (min 5 pages), integrating feedback and discussions for a second round of reviews, which will then be published as open-access workshop proceedings (whether OASIcs or CEUR TBD).

Organizers

• Christoph Becker, Institute of Advanced Study, University of Amsterdam
• Giovanni Sileno, Informatics Institute, University of Amsterdam
• Nicola Lettieri, INAPP (National Institute for Public Policy Analysis) and University of Sannio.

with the support of IAS, the Institute of Advanced Study of the University of Amsterdam.

Program committee

• Christopher Frantz, NTNU Norwegian University of Science and Technology,
• Valentina Punzo, INAPP (National Institute for Public Policy Analysis)
• Fernando P. Santos, University of Amsterdam
• Sebastian Benthall, NSF National Science Foundation
• Luigi Cominelli, University of Milan Law School
• Vítor V. Vasconcelos, University of Amsterdam
• Flaminio Squazzoni, University of Milan
• Alex Schwartz, Hong Kong University
• Alessandro Pluchino, University of Catania
• …

Important Dates

• Submission deadline: 19 November 2021 until 23:59,
• Notification of acceptance: 24 November 2021,
• Workshop: 8 December 2021.

Registration via the main conference (https://jurix2021.mruni.eu/). If participation is virtual, you still need to register as remote participants.