Conference track · AISoLA 2026
Responsible and Trusted AI
An Interdisciplinary Perspective · AISoLA 2026
- When
- Tuesday 27 to Friday 30 October 2026
- Where
- Mitsis Selection Blue Domes, Kos, Greece. All track sessions take place in Room 1.
- Conference
- AISoLA 2026 website · Conference programme · Track page
- Organisers
- Kevin Baum (DFKI, Hamburg University of Technology)
Thorsten Helfer (CISPA)
Felix Jahn (DFKI)
Sophie Kerstan (University of Freiburg)
Andreas Sesing-Wagenpfeil (Saarland University)
Timo Speith (University of Bayreuth)
Sarah Sterz (Saarland University) - Co-organised by
- CERTAIN, the Centre for European Research in Trusted AI
- Supported by
- Lamarr Institute
- Proceedings
- LNCS 17146, open access
The track brings together researchers from philosophy, law, psychology, computer science and neighbouring fields to work on the conceptual, normative and regulatory side of trustworthy AI. It has run at AISoLA since 2023.
Programme
Authors as listed in the interactive conference programme, which may change at short notice. Talks with a paper in the proceedings link to it. The shaded boxes list central AISoLA events that share the room and explain the gaps in the track’s schedule.
Tuesday, 27 October
Human Oversight11:00–12:30
- 11:00Compliance-by-Design with Lingua Franca: Toward Meeting EU AI Act Requirements
Matthias Wagner, Sriram Bhimaraju, Markus Borg, Per Runeson, Edward A. Lee - 11:30A Human-Centered Argumentation Tool for Justifiable AI Governance
Sarah Sterz, Jonathan Gärtner, Svenja Omlow - 12:00Constitutive vs. Corrective: A Causal Taxonomy of Human Runtime Involvement in AI Systems
Kevin Baum, Johann Laux
Meeting Risks of AI (1)13:30–15:00
- 13:30When Rules Run Out: Formal Methods for Open-Textured Legal Terms
Frederike Zufall, Maike Schwammberger - 14:00Interaction-Level Monitoring: A Holistic Strategy for Mitigating Human–AI Double Anchoring
Mariela Destefano - 14:30When the Red Team Gets an AI Intern – Ethical Continuities and New Challenges in AI-Assisted Vulnerability & Exploitation Research
Thorsten Helfer, Jannik Zeiser
Wednesday, 28 October
Meeting Risks of AI (2)11:00–12:00
- 11:00AI Literacy as System Capacity: Socio-Technical Principles for AI-Literate AI Use
Sophie Kerstan, Richard Uth, Markus Langer - 11:30Between Prohibition and Permission: How the EU AI Act Tackles the Dark Side of AI
Andreas Sesing-Wagenpfeil
AI for Good (1)12:00–12:30
- 12:00Trustworthy AI and the Democratization of Philosophical Inquiry
Michael Hemmingsen
AI for Good (2)14:30–15:00
- 14:30Stitching social robots: Fostering Youth Critical AI Engagement through Tangible and Digital Co-Creation
Xiaoyu Wang, Anna Keune
XAI (1)15:00–16:00
- 15:00Beyond Explaining the System: Action-Space Transparency for Responsible Human–AI Interaction
Alexander Werk - 15:30Conceptual Infrastructure for Explainable AI
Astrid Schomäcker, Timo Speith
Thursday, 29 October
XAI (2)11:00–12:30
- 11:00Trustworthy, Traceable, and Compliant: Run-Time Validation of AI Explanations for Autonomous Vehicles under the EU AI Act
Dominik Grundt, Maike Schwammberger - 11:30Enhancing AI Interpretability and Safety through Localised Architectures
Ian Seet, Jonas Bozenhard, Simon Ostermann - 12:00Beyond XAI: Orchestrating Multi-Source Explanations at Run Time Using Lookup Table
Akhila Bairy, Hanwei Zhang
AI, Responsibility and Authorship14:30–15:30
- 14:30(What) Can we learn about AI Ethics from Aesthetics?
Anne Schwenkenbecher - 15:00Students' Judgments of Seriousness of LLM-Based vs. Conventional Plagiarism: A Qualitative Interview Study
Martin Daumiller, Tanja Fritz, Hernán González Cruz, Stefan Janke
AI Alignment (1)16:30–17:30
- 16:30Should Alignment be about Reasons or Preferences? An interactive discussion
Lisa Dargasz, Felix Jahn, Andre Steingrueber - 17:00Value Capture and the Structure of AI Alignment: A Case for Rule-Based Approaches
Kevin Baum, Andre Steingrüber
Friday, 30 October
AI Alignment (2)11:00–12:30
- 11:00Reason-based Normative Reinforcement Learning: Embedding Defaults into the Reward Structure via Reward Machines
Lisa Dargasz, Felix Jahn, Yannic Muskalla - 11:30Responsible Conversational AI: Shifting Focus from Alignment to Gatekeepers
Ron Aboodi - 12:00Synthesizing Moral Reasoning Theories from Live Audience Judgments: An interactive session with the AISoLA-RTAI Community
Lisa Dargasz, Felix Jahn, Yannic Muskalla
Proceedings
The track chapters appear in Bridging the Gap Between AI and Reality (AISoLA 2026, ed. Bernhard Steffen, Lecture Notes in Computer Science 17146, Springer), online since 13 October 2026. All chapters are open access. The descriptions are short summaries; the authors’ abstracts are on the Springer pages.
Responsible and Trusted AI: An Interdisciplinary Perspective (2026)
Kevin Baum, Thorsten Helfer, Felix Jahn, Sophie Kerstan, Andreas Sesing-Wagenpfeil, Timo Speith, Sarah Sterz
The track introduction. It asks whether the safeguards that regulation and industry practice have produced (humans in decision loops, oversight duties, documentation, explanations) do what they are meant to do, and places the track’s papers within that question.
Constitutive vs. Corrective: A Causal Taxonomy of Human Runtime Involvement in AI Systems
Kevin Baum, Johann Laux
Distinguishes human-in-the-loop (constitutive: the output cannot come about without the human) from human-on-the-loop (corrective: the human can prevent, modify or override it) by causal structure rather than position. Keeps these descriptive categories apart from the normative requirement of effective human oversight, and treats cases where one person holds both roles as a design problem.
Compliance-by-Design with Lingua Franca: Toward Meeting EU AI Act Requirements
Matthias Wagner, Sriram Bhimaraju, Markus Borg, Per Runeson, Edward A. Lee
Shows how the coordination language Lingua Franca turns selected AI Act requirements into architectural properties of AI-enabled cyber-physical systems: generated architecture diagrams, deterministic and explicitly timed behaviour, anomaly monitoring and traceable logging, demonstrated on an AI-enabled traffic-light controller.
Enhancing AI Interpretability Through Localised Architectures
Ian Seet, Jonas Bozenhard, Simon Ostermann
Argues that localised models are easier to interpret, and that today’s dense, high-bandwidth hardware pushes models the other way. Surveys alternative hardware substrates for more localised architectures by per-node expressivity, energy efficiency and maturity.
Earlier editions: AISoLA 2025 · AISoLA 2024
