About the track

In modern society, citizens, communities, industry, public institutions, regulatory bodies, and decision-makers are part of AI-enabled socio-technical systems (AI-STS). Instances of AI-STS include neighborhoods, campuses, buildings, home and everyday living systems, as well as more specialized environments such as health and wellbeing, energy distribution and transport systems, or self-driving vehicles.

While intelligent technologies and data from different sources are increasingly adopted in practice, we still experience a significant disconnect between governance and communities/societal actors regarding, e.g., limited inclusion, transparency, contestability, oversight mechanisms, accountability, participation, data contribution and field evaluations. Therefore, this track welcomes (interdisciplinary) work spanning both technology and social aspects to support better-informed and more sustainable decision-making on AI-STS.

Topics of interest

Topics include (but are not limited to):

Community-in-the-loop governance

• Participatory sensing, citizen science
• Mechanisms and processes involving collective values and norms during systems design and deployment (no-code or low-code included)

Evidence-to-policy

• Pathways, models, and solutions translating citizen/community evidence into institutional decisions and sustained change, where AI plays a leading or assistant role

Contestability

• Methods, models, processes, prototypes and solutions for challenging AI decisions affecting the collectivity

Oversight mechanisms

• Independent assurance / independent eyes: audits, verification/validation, field-ready assurance cases, audit trails
• Veto/appeal and dispute-resolution mechanisms on AI-STS

Accountability-by-design

• Guidelines, models, documentation, and solutions for traceability/provenance of data and decisions within an AI-enabled system

Field / longitudinal evaluation

• Equity, trust/agency, institutional uptake, behavior change, real-world impact
• Mix of authoritative & crowd-sourced data governance
• Citizen-centric and friendly digital twins

Submission guidelines

• We invite full papers presenting original research, systems, methods, or evaluations aligned with the track.
• Submissions must follow the ACM double-column format and the GoodIT limits (up to 9 pages, including references, figures, and tables).
• Work-in-Progress papers should be a maximum of 4 pages (ACM double column format).
• Accepted papers will be presented in person and included in the conference proceedings, in line with GoodIT policies.

Deadline for submission: 17 May 2026

Review process

All submissions will undergo single-blind peer review with at least three reviews per paper, conflict-of-interest management, and PC discussion. Evaluation will consider: novelty, soundness/rigor, relevance, verifiability/transparency, presentation, and real-world connection.

Tentative Program Committee (to be confirmed)

• Costanza Alfieri (University of L'Aquila, Italy)
• Alex Barco (University of Deusto, Spain)
• Alessio Bucaioni (Mälardalen University, Sweden)
• Cruz E. Borges (University of Deusto, Spain)
• Martina De Sanctis (GSSI, Italy)
• Virginia Dignum (Umeå University, Sweden)
• Gordana Dodig-Crnkovic (Mälardalen University, Sweden)
• Parisa Eslambolchilar (CGI, UK)
• Unai Hernández (University of Deusto, Spain)
• Paola Inverardi (GSSI, Italy)
• Antonio Jara (HOP UBIQUITOUS S.L., Spain)
• Fabian Lorig (Malmö University, Sweden)
• Alejandro Marín-Menéndez (CSIC, Spain)
• Francisco Sanz (Ibercivis Foundation, Spain)
• Kamran Soomro (UWE, UK)
• Marina Stamatiadou (Aristotle University of Thessaloniki, Greece)
• Dipak Surie (Malmö University, Sweden)
• Mario Vega-Babas (UPM, Madrid)
• Nervo Verdezoto (Cardiff University, UK)
• Milena Vuckovic (VRVis Zentrum für Virtual Reality und Visualisierung, Austria)
• Marco Zennaro (ICTP, Italy)
• Javier García Zubia (University of Deusto, Spain)

Special Track Organizers

• Romina Spalazzese (Malmö University, Sweden) — romina.spalazzese@mau.se
• Diego Casado-Mansilla (University of Deusto, Spain) — dcasado@deusto.es
• Paul Davidsson (Malmö University, Sweden) — paul.davidsson@mau.se
• Diego López-de-Ipiña (University of Deusto, Spain) — dipina@deusto.es