LEAD UNIVERSITY & KEY PARTNERS
AI for Social Good (Phase I)

The AI for Social Good Phase I focused on bringing together a network of AI experts across disciplines to explore how policies can support the adequate promotion and control of AI for the good of society. An adequate governance system for the development, management, and use of AI is seen as crucial in ensuring that the benefits of integrating and analyzing large quantities of data are maximized, while the potential risks are mitigated.

Outcomes of the two year project are the:

Artificial Intelligence for Social Good Report which feature realities and experiences from Asia and the Pacific, and provides various perspectives on what AI for social good may look like in this region. The report offers suggestions from the research community on how policymakers can encourage, use, and regulate AI for social good.

In this phase, the project team also held a AI For Social Good Summit in November 2020.

Two documents, AI For Social Good Insight Briefs 1 & Briefs 2, were published after the Summit.

PROGRAM
LEADERS
Jiro Kokuryo (Academic Lead)
Keio University
Hideaki Shiroyama (Academic Co-lead)
The University of Tokyo
Yoshiaki Fukami (Academic Project Coordinator)
Keio University
Cherry Wong (Academic Project Coordinator)
Keio University
Caitlin Bentley
The Australian National University & Sheffield University
Mark Findlay
Singapore Management University
Arindrajit Basu (team lead)
Centre for Internet & Society, India
Elonnai Hickok (team member)
Centre for Internet & Society, India
Amber Sinha (team member)
Centre for Internet & Society, India
Soraj Hongladarom
Chulalongkorn University
Kyoung Jun Lee
Kyung Hee University
M. Jae Moon
Yonsei University
Wai Ho Wilson Wong
The Chinese University of Hong Kong
Masaru Yarime
The University of Hong Kong Science and Technology
Resources
[Whitepaper] Generative AI in Higher Education: Current Practices and Ways Forward
Authors: Danny Y.T. Liu, Simon Bates The Whitepaper is a main outcome of the project “Generative AI in Higher Education”, conducted by the Association of Pacific Rim Universities (APRU) with the generous support of Microsoft. Following a survey of case studies demonstrating the current use of AI in APRU member universities, three workshops throughout 2024 – including an in-person workshop hosted by The Hong Kong University of Science and Technology in June 2024 – brought AI experts together to assess the case studies and develop scenarios and paradigms of what AI-enhanced universities might look like in 2035. The Whitepaper presents both a framework for action and a call for transformative change in how we prepare students, educators, academics, and administrators for an AI-enabled future. Our work has identified five interdependent elements essential for successful generative AI integration, forming the ‘CRAFT’ framework – culture, rules, access, familiarity, and trust. We propose two key priorities for immediate sector-wide action. First, the formation of collaborative clusters where universities move beyond competition to cooperation in key areas including joint development of generative AI applications and pedagogical approaches, shared frameworks for assessment redesign, coordinated advocacy for equitable access, combined faculty development initiatives, and unified governance frameworks that respect local contexts. Second, the elevation of students as partners through peer-to-peer support networks, student AI ambassador programs, co-design of learning experiences, direct input into assessment redesign, and collaborative resource development.
Contact
Us

Address: APRU International University Centre, Unit 902, Cyberport 2, 100 Cyberport Road, Hong Kong
Email: [email protected]
Telephone: +852 2117 7060
Fax: +852 2117 7080

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