Elgar Companion to Artificial Intelligence Governance

Edited by Yanto Chandra, Professor, Department of Public and International Affairs, City University of Hong Kong, Michael Tsimplis, Professor, Faculty of Law, University of Hong Kong and Naikang Feng, Postdoctoral Fellow, Centre for Civil Society and Governance (CCSG), University of Hong Kong, Hong Kong

• ContentsIntroduction to The Elgar Companion to Artificial Intelligence Governance 1Yanto Chandra, Naikang Feng and Michael TsimplisPART I THE PUBLIC POLICY LANDSCAPE OF AI GOVERNANCE1 Debates on AI governance: riddles, paradoxes, and the road ahead 9Yifan Wang, Tian Gan and Liang Ma2 Socially responsible artificial intelligence (AI) and the roles of the state:evidence from G20 national strategies for AI 28Ferry Silitonga and Kuskridho Ambardi3 Policy instrument portfolios in AI development: a text analysis of Chinesepolicies 47Yiran Li4 Artificial intelligence and public value co-creation: evidence from smartelderly care services in China 67Lingyi Zhou5 Transforming public sector governance through large language models:global experiences and future pathways 82Mingxi Zhang, Liang Ma and Xun Wu6 Stakeholder governance: the key to ethical, inclusive, and responsible AIgovernance 102Greici Sarturi7 Information asymmetry, incentive misalignment, and accountability: aprincipal–agent perspective on AI in governments 119Naikang Feng and Yanto Chandra8 Trilateral powers, divergent paths: can middle path win in AI governance? 129Chuanxiao Peng and Wenxuan Yu9 Out of control and co-existence: the revolution of human civilizationgovernance paradigms in the era of AI self-evolution 151Michael Yusheng Wu10 Police officers operating under the influence of AI: assessing howpredictive policing tools impact officer behaviour and can lead to risks 173Spencer Poodiack Parsons11 Transformative influences of AI on public policy design andimplementation: a socio-legal analysis of institutional innovation 188Zhiyi LiuPART II THE LEGAL LANDSCAPE OF AI GOVERNANCE12 Regulating AI: definitions, levels of control, and smart mix 212Michael Tsimplis and Gary Lynch-Wood13 What explainability means in law: from technical concepts to legalstandards 223Hsuan-Lei Shao and Sieh-Chuen Huang14 Legal reasoning beyond binaries: AI and the fuzziness of principles 239Fabien Gélinas and Chen Yu15 Corporate law in the algorithmic era 254Michael R. Siebecker16 Corporate governance and the use of AI 270Souichirou Kozuka17 AI and corporate governance: liability and accountability in corporatedecision making 286Danny Kan and Michael Mok18 AI and the softening of corporate boundaries 298Martin Petrin19 When is a definition efficient? An alternative approach to the AI discourseon ‘ships’ under UNCLOS 309Hannah Stones20 AI under privacy and data protection laws 324Xingsi Di and Deru He21 Artificial intelligence under privacy and data protection laws 338Ce Ma