14 Research Showcase Science, Technology, and Innovation Policy Veale, M., Matus, K., & Gorwa, R. (2023). AI and Global Governance: Modalities, Rationales, Tensions. Annual Review of Law and Social Science, 19. In this review, the authors study what exactly the salient but polarizing issue of Artificial Intelligence (AI) is being governed, how, by who, and why by considering the literature on AI, the governance of computing, and regulation and governance. The authors took critical stock of the different modalities of the global governance of AI that have emerged, such as ethical councils, industry governance, contracts and licensing, standards, international agreements, and domestic legislation with extraterritorial impact, and examine selected rationales and tensions that underpin them, drawing attention to the interests and ideas driving these different modalities. As these governance regimes built around AI become clearer and more stable, the authors urge those engaging with or studying the global governance of AI to constantly ask the allimportant question of “Who benefits?” Yarime, M. "Facilitating Data-Driven Innovation for Sustainability: Data Governance and Its Impacts in Smart Cities in China." 2023 AAS Annual Conference. ASIANSTUDIES, 2023. Few empirical studies were conducted to examine how data are managed and provided in smart cities and how they affect companies’ innovative activities, despite their crucial role in addressing a variety of sustainability issues. This conference paper examines the data available and used in smart cities and how the government and enterprises collaborate on data to facilitate innovation. Focusing on China, particular attention is paid to different types of public-private collaboration for smart cities, including equipment supply, platform building, and data analysis. Interviews were conducted to examine how key stakeholders in the public and private sectors collaborate on data, and the impact on the outcomes of innovative activities was examined by analysing the government procurement data.
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