Beyond Compute: A Weighted Framework for AI Capability Governance

Watson, Eleanor ORCID: https://orcid.org/0000-0002-4306-7577 (2025) Beyond Compute: A Weighted Framework for AI Capability Governance. In: 17th International Conference on Agents and Artificial Intelligence, 23-25 February 2025, Porto, Portugal. ISBN 978-989-758-737-5

Preview

Text (Published version) 14975 Watson (2025) Beyond compute a weighted framework for AI capability governance.pdf - Published Version Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0. Download (379kB) | Preview

Abstract

Current AI governance metrics, focused primarily on computational power, fail to capture the full spectrum of emerging AI risks and capabilities, which risks significant unintended consequences. This analysis explores critical alternative paradigms including logic-based scaffolding techniques, graph search algorithms, agent ensembles, mixture-of-experts architectures, distributed training methods, and novel computing approaches such as biological organoids and photonic systems. By examining these as multidimensional weighted factors, this research aims to expand the discourse on AI progress beyond compute-centric models, culminating in actionable policy recommendations to strengthen frameworks like the EU AI Act in addressing the diverse challenges of AI development.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	AI governance; Compute; AI policy; AI capabilities; AI safety; Scaffolding; Agentic
Related URLs:	Organisation
Subjects:	Q Science > QA Mathematics > QA76 Computer software
Divisions:	Schools and Research Institutes > School of Business, Computing and Social Sciences
Depositing User:	Rhiannon Goodland
Date Deposited:	15 Apr 2025 09:43
Last Modified:	15 Apr 2025 10:00
URI:	https://eprints.glos.ac.uk/id/eprint/14975

University Staff: Request a correction | Repository Editors: Update this record