activity
20242026
most citedA Proposed S.C.O.R.E. Evaluation Framework for Large Language Models : Safety, Consensus, Objectivity, Reproducibility and Explainability

4 citations · 4 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CY2026

Research Integrity and Academic Authority in the Age of Artificial Intelligence: From Discovery to Curation?

Simon Chesterman, Loy Hui Chieh

Artificial intelligence is reshaping the organization and practice of research in ways that extend far beyond gains in productivity. AI systems now accelerate discovery, reorganize…

cs.CY2026

From Slaves to Synths? Superintelligence and the Evolution of Legal Personality

Simon Chesterman

This essay examines the evolving concept of legal personality through the lens of recent developments in artificial intelligence and the possible emergence of superintelligence. Le…

cs.CY2025

Lawful but Awful: Evolving Legislative Responses to Address Online Misinformation, Disinformation, and Mal-Information in the Age of Generative AI

Simon Chesterman

"Fake news" is an old problem. In recent years, however, increasing usage of social media as a source of information, the spread of unverified medical advice during the Covid-19 pa…

cs.CY2025

Silicon Sovereigns: Artificial Intelligence, International Law, and the Tech-Industrial Complex

Simon Chesterman

Artificial intelligence is reshaping science, society, and power. Yet many debates over its likely impact remain fixated on extremes: utopian visions of universal benefit and dysto…

cs.CL2024★ 4 cited

A Proposed S.C.O.R.E. Evaluation Framework for Large Language Models : Safety, Consensus, Objectivity, Reproducibility and Explainability

Ting Fang Tan, Kabilan Elangovan, Jasmine Ong +10

A comprehensive qualitative evaluation framework for large language models (LLM) in healthcare that expands beyond traditional accuracy and quantitative metrics needed. We propose…