Advancing Ethical, Inclusive, Human-Centered AI

On the occasion of the 3rd UNESCO Global Forum on the Ethics of AI, the side event “Enabling an AI-Ready Workforce” convened a diverse group of around 65 experts and key stakeholders from 15+ countries and five continents from government, the private sector, academia, and civil society to address the urgent need for inclusive and equitable AI skills development in the Asia-Pacific region. The discussions revealed a strong consensus that building an AI-ready workforce requires moving beyond purely technical training to foster a holistic ecosystem grounded in ethics, inclusivity, and local context.

This report is one of the main outcomes of the project “Generative AI in Higher Education” conducted by the Association of Pacific Rim Universities (APRU). Another major work is the Whitepaper “Generative AI in Higher Education: Current Practices and Ways Forward” published in January 2025. The report provides a narrative of the project’s activities in the past 18 months—including the abstracts of case studies submitted by participating universities and a recount of all three workshops conducted throughout 2024.

Generative AI in Higher Education: A Framework for Action and Future Innovation 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.