Author: M Arifur Rahman, Hawai‘i Pacific University Introduction: This research paper examines the potential benefits of introducing an AI-enhanced pregnancy monitoring system in Bangladesh to enhance maternal health outcomes. Currently, the monitoring of pregnant women in Bangladesh lacks systematic approaches, and many women face limited access to such services due to various factors. Implementing personalized and continuous AI-enhanced monitoring for pregnant women has the potential to improve their health outcomes, but it necessitates access to significant amounts of data. While the Electronic Health Record/Electronic Medical Record (EHR/EMR) system is considered the ideal method for recording healthcare data, Bangladesh has yet to establish a universal EHR system. Although the country has plans to implement an EHR system by 2025, the process is time-consuming. This study assesses the existing maternity healthcare infrastructure in Bangladesh to identify opportunities for integrating AI and proposes recommendations for the government to introduce AI-enhanced pregnancy monitoring systems to address the identified challenges. The research methodology involves identifying technical challenges, gaps in the current technical infrastructure, and drawing lessons from previous project implementations for incorporating AI into pregnancy monitoring. However, as EHR serves as the foundational element for AI-enhanced healthcare, and establishing a universal EHR represents a significant IT undertaking, this study also examines major IT projects carried out by the Bangladesh government, identifies strengths and weaknesses, and provides recommendations for the next steps in EHR development, ultimately leading to AI-enhanced maternity health monitoring systems. Read this article for more information about the AI for Social Good project and the research in Bangladesh.

March 14–15, 2024 (Virtual, Asia Time Zones) Phase II of the APRU initiative “Generative AI in Education: Opportunities, Challenges and Future Directions in Asia and the Pacific” kicked off with the Sensemaking Workshop lasted from March 14 to 15, 2024. The online workshop was attended by 37 university professors, administrators, teaching staff, postgraduate students and technology industry representatives. The workshop aimed to: Identify common patterns and trends across case studies (collected in the project Phase I in 2023) on the use of AI in universities that can inform effective strategies for adoption. Recognize gaps and opportunities for additional AI applications in universities.

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.

Find out more about the paper and its related projects at https://www.apru.org/our-work/pacific-rim-challenges/digital-economy/.

Digital automation is transforming the world with unprecedented scope and speed, and its impact is compelling. This report highlights the impact of AI technology has on Asia Pacific’s workforce. It also outlines policy recommendations to leaders of higher education, government, and industry.

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.

AI for Everyone is also available for purchase as a paperback edition at cost price here. Please see a project overview and policy statement here. Find out more details about the project here.

For more information about the AI for Social Good Summit, please visit here. To know more about the project, view the webpage.

Author: Jasper Tromp, National University of Singapore Introduction: Thailand’s digital health landscape is evolving with efforts to embrace technology and leverage its potential benefits. The country has been making strides in digital health readiness, as reflected in its ranking of 59th globally in the Government AI Readiness Index 2021 and 9th in East Asia. However, several barriers and challenges exist in the digital health space. One of the primary challenges is the fragmented nature of healthcare service provision, affecting differences in data architecture, standards, and collection. Manual data management and the persistence of paper-based electronic health record systems also limit efficient data sharing and interoperability. Limited resources pose a significant barrier, with uneven human, technical, and financial resource distribution across healthcare institutions. High hardware and software acquisition, installation, and maintenance costs further impede engagement in quality data collection and sharing, particularly for smaller clinics and hospitals. Thailand faces a lack of understanding of the value of data and the importance of data security and privacy. Health literacy issues and confusion around data-sharing parameters also contribute to the challenges. Additionally, the absence of precise data-sharing regulations and guidelines at the political and policy levels creates uncertainty and hampers progress. While Thailand has made progress in its digital health landscape, addressing barriers related to data integration, standardization, resource allocation, and regulations is crucial to unlocking digital health initiatives’ full potential and achieving improved healthcare outcomes. Read this article for more information about the AI for Social Good project and the research in Thailand.

Author: Sarah Logan, Australia National University Introduction: This paper investigates information sharing for poverty reduction in Thailand. In particular, it investigates the Thai People Map and Analytics Platform (TPMAP) an innovative poverty reduction platform which uses big data and AI to better target Thai poverty reduction measures. The paper asks how information sharing within the Thai bureaucracy might be improved to better leverage the technical capabilities offered by TPMAP, including those facilitated by artificial intelligence. Read the article for more information about the AI for Social Good project, and the research in Thailand.

August 15-16, 2024 (Virtual, Asia Time Zones) This was the third and final workshop of the Phase II of the APRU initiative “Generative AI in Education: Opportunities, Challenges, and Future Directions in Asia and the Pacific.” Following the Foresight Workshop in June 2024 in which potential future scenarios or models for universities in a world increasingly influenced by AI were developed, the project progressed to the Creative Sandbox held from August 15 to 16, 2024. The Creative Sandbox workshop brought together 32 academics from 13 economies across the Asia Pacific to conceptualize potential prototypes addressing AI application challenges and opportunities in higher education. Prototyping is the process of turning ideas into tangible forms for testing based on identified risks. The goal of prototyping is to identify potential issues, gather feedback, explore different solutions, and iterate on the design to improve the final product. This report presents the five prototyping concepts developed during the Creative Sandbox Workshop as well as policy implications or university policies that may need to be reviewed, revised, or developed to support the ethical and effective integration of AI across different areas of higher education.

This report is based on realities and experiences from Asia and the Pacific, and provides various perspectives on what AI for social good may look like in this region. More importantly, the report offers suggestions from the research community on how policymakers can encourage, use, and regulate AI for social good. For more information about the project, please visit the webpage, AI for Social Good. View the report in sections: Contents and forewords Introduction Philosophical point of view for social implementation (chapter 1-3) Institutional and technological design development through use of case based discussion (chapter 4-6) How to expand the capacity of AI to build better society (chapter 7 & 8) Bios of authors and acknowledgement

The AI for Social Good Strengthening Capabilities and Governance Frameworks in Asia and the Pacific project was a collaboration between the Association of Pacific Rim Universities (APRU), the United Nations Economic and Social Commission for Asia and the Pacific (United Nations ESCAP), and government partners in Bangladesh and Thailand. The overall goal was to support the development of country-specific AI governance frameworks and capabilities to enable transparent ecosystems and AI solutions for socio-economic challenges. The project brought together academic researchers and government stakeholders through a series of workshops and meetings to formulate evidence-based policies and strategies. Two research teams produced country case studies on leveraging AI for maternal health in Bangladesh, with two other research teams addressing digital health governance and data governance for poverty alleviation in Thailand. The final report shares key findings across the research highlighted barriers currently inhibiting effective AI adoption and provided recommendations to address these.  

Authors: Olivia Jensen, National University of Singapore Nathaniel Tan, National University of Singapore Cornelius Kalenzi, KAIST Introduction: Maternal health metrics in Bangladesh improved greatly from the 1990s but the rate of progress has stalled in more recent years and further efforts are now needed to support the health of expecting and new mothers. Artificial Intelligence (AI) has the potential to transform some aspects of healthcare, opening the way for personalised medicine and treatment plans, accelerating diagnosis, drug discovery and development and raising the efficiency of service delivery to reduce costs and maximize the use of available resources. The applications of AI in relation to maternal health are just beginning to be explored but may hold potential to improve health outcomes for this high priority population group. This study provides a high-level assessment of the potential of AI applications to contribute to meeting maternal health objectives in Bangladesh, taking into account the country’s digital technology readiness, the acceptability of AI technologies to user groups and the organizational structure of antenatal care (ANC) services in Bangladesh. Read this article for more information about the AI for Social Good project and the research in Bangladesh.

June 13–14, 2024 (at The Hong Kong University of Science and Technology, Hong Kong) The two-day event was the second workshop of the APRU initiative “Generative AI in Education: Opportunities, Challenges, and Future Directions in Asia and the Pacific,” built on the foundation laid by the initial Sensemaking Workshop. This workshop brought together 41 academics, educators, students and tech business representatives from 12 economies across the Asia-Pacific region to engage in a collaborative exploration of potential futures for higher education in a world increasingly shaped by AI. Using foresight methodologies, participants worked to: Explore emerging AI trends and their potential impact on various facets of higher education; Co-create a range of plausible models that illuminate the diverse ways in which universities might function in an AI-integrated world; and Identify the key opportunities and challenges associated with each scenario, prompting strategic discussions about potential responses and adaptations. This report captures the outputs of the Foresight Workshop, presenting four distinct university models for a generative AI world. These models offer valuable insights for university leaders, policymakers, and other stakeholders invested in shaping the future of higher education.

For more information about the AI for Social Good Summit, please visit here. To know more about the project, view the webpage.