Call for Papers: CLSR Special Issue on Governing General-Purpose AI Systems (Elsevier)

[Sergio Picascia]

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CALL FOR PAPERS -- Computer Law & Security Review (Elsevier)

Special Issue:
Legal Frameworks, Technical Challenges, and Regulatory
Design for Governing General-Purpose AI Systems

Submission deadline: 30 October 2026
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This special issue brings together research at the
intersection of computer science and law to address the
distinctive governance challenges posed by foundation
models and general-purpose AI (GPAI) systems. We seek
contributions that combine rigorous legal analysis with
technical depth, reflecting the inherently interdisciplinary
nature of the challenge.

The special issue addresses three interrelated dimensions:
 (i)  the technical properties of foundation models that
      generate novel legal and regulatory questions;
 (ii) the legal and regulatory frameworks being developed
      or adapted to govern these systems; and
 (iii) the computational and methodological tools that can
      support governance objectives.

We welcome submissions from interdisciplinary researchers
and practitioners -- in law, computer science, public
policy, and related fields -- looking to advance
understanding of how foundation models can be governed
effectively, equitably, and in a manner responsive to both
their technical complexity and their societal impact.

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TOPICS OF INTEREST (not limited to)
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Legal and Regulatory Perspectives
 - Legal classification and regulatory treatment of
   foundation models and GPAI systems
 - Liability allocation across the GPAI value chain
 - Intellectual property challenges
 - Data protection and privacy implications of large-scale
   pre-training
 - Comparative and international perspectives on GPAI
   governance
 - Sector-specific regulatory interactions
 - Fundamental rights impact assessments for systemic-risk
   GPAI models
 - Competition law, market concentration, and the political
   economy of foundation model providers

Computer Science and Technical Perspectives
 - Technical auditing, red-teaming, and evaluation
   methodologies for foundation models
 - Interpretability, explainability, and transparency
   methods for large-scale language models
 - Benchmarking and measurement frameworks for GPAI
   compliance with regulatory requirements
 - Process mining and process-aware analytics for auditing,
   monitoring, and conformance checking of GPAI systems
 - Training data governance: documentation, provenance
   tracking, and filtering techniques
 - Safety alignment, RLHF, and value alignment techniques
   as regulatory compliance mechanisms
 - Computational approaches to copyright detection and
   attribution in training corpora
 - Privacy-preserving techniques in the context of GPAI
   regulation
 - GPAI-assisted regulatory and policy assessment tools:
   automation, reliability, and accountability in
   institutional compliance workflows
 - Open-source vs. proprietary models: technical
   architectures, governance implications, and risk profiles

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SUBMISSION
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Manuscripts should be submitted through the Elsevier
Editorial Manager system:
  https://www.editorialmanager.com/CLSR

Submissions will be screened by the guest editors for
relevance, clarity, and compliance with journal
requirements; eligible manuscripts will proceed to
double-blind peer review in line with Elsevier and journal
expectations. Authors should ensure that any empirical
claims, technical descriptions, or case-based assertions
are appropriately supported.

Guide for Authors:
  https://www.sciencedirect.com/journal/computer-law-and-security-review/publish/guide-for-authors

Final manuscript submission deadline: 30 October 2026

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GUEST EDITORS
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 - Dr. Davide Audrito, University of Turin, Italy
 - Dr. Livio Robaldo, Swansea University, UK
 - Dr. Roberto Nai, University of Turin, Italy
 - Dr. Sergio Picascia, Universita degli Studi di Milano,
   Italy
 - Dr. Emilio Sulis, University of Turin, Italy

Keywords: General-Purpose AI; AI Governance; AI Safety;
Regulatory Design
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