APRU received funding for three collaborative projects focusing on the impact of AI on society, including AI for Everyone: Benefiting from and Building Trust in the Technology; Transformation of Work in Asia-Pacific in the 21st Century; and AI For Social Good. is undertaking
a pre-grant review for a possible fourth project with APRU and UN ESCAP strengthening capabilities and governance frameworks in the Asia-Pacific.

Mobilizing Artificial Intelligence for Maternal Health in Bangladesh

Olivia Jensen, National University of Singapore
Nathaniel Tan, National University of Singapore
Cornelius Kalenzi, KAIST

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.

Addressing Challenges in Data Sharing for TPMAP

Sarah Logan, Australia National University

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.

Responsible Data Sharing, Ai Innovation And Sandbox Development: Recommendations For Digital Health Governance

Jasper Tromp, National University of Singapore

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.