Policymakers Face Distinct Regulatory Gaps as General-Purpose AI Evolves

Global: Policy Challenges for General-Purpose AI

Policymakers are confronting new challenges as general-purpose artificial intelligence (GPAI) gains prominence, prompting a reassessment of regulatory frameworks that were originally crafted for task‑specific AI systems. The abstract of a recent arXiv paper outlines how assumptions embedded in existing tools may no longer hold, and it calls for differentiated policy responses to address the unique risks of GPAI. The authors, drawing on a decade of AI governance work, argue that a single regulatory target is insufficient for both specialized and general AI technologies.

Regulatory Mismatch with GPAI Generality

The paper identifies the broad applicability and adaptability of GPAI as a primary source of regulatory difficulty. Because GPAI can be repurposed across diverse domains, traditional sector‑specific rules may fail to capture its cross‑cutting impact, according to the authors’ analysis.

Challenges in Designing Effective Evaluations

Evaluating GPAI performance and safety presents methodological hurdles, the authors note. Existing benchmark suites were designed for narrow tasks, making it harder to assess a system that can learn and operate in multiple contexts without clear performance boundaries.

Evolving Legal Concerns and Stakeholder Landscape

New legal questions arise as GPAI blurs the line between developer, user, and affected party. The abstract highlights a shift in the ecosystem of stakeholders, suggesting that expertise must be sourced from a wider array of disciplines to inform policy decisions.

Distributed Structure of the GPAI Value Chain

The authors point out that GPAI development often involves a distributed network of contributors, including open‑source communities, cloud providers, and downstream integrators. This fragmented value chain complicates attribution of responsibility and the enforcement of compliance measures.

Recommendations for Targeted Governance

To address these gaps, the paper proposes three recommendations: (1) refine the identification of regulatory targets to reflect GPAI’s multifaceted nature, (2) leverage constraints across the broader ecosystem rather than relying solely on direct controls, and (3) develop adaptive policy instruments that can evolve alongside technological progress.

This report is based on information from arXiv, licensed under Academic Preprint / Open Access. Based on the abstract of the research paper. Full text available via ArXiv.