Harnessing AI for Healthcare and Poverty Alleviation: Insights from Bangladesh and Thailand | Techsauce

Harnessing AI for Healthcare and Poverty Alleviation: Insights from Bangladesh and Thailand

Artificial intelligence is increasingly being utilized to tackle socioeconomic and health issues. The Association of Pacific Rim Universities (APRU) and the United Nations Economic and Social Commission for Asia and the Pacific (ESCAP) have released the report "AI for Social Good: Strengthening Capabilities and Governance Frameworks in Asia and the Pacific." Funded by Google.org, this initiative aims to enhance AI governance and develop solutions for critical socio-economic challenges in the region.

Techsauce interviewed Dr. Olivia Jensen, Deputy Director and Lead Scientist (Environment and Climate) at the National University of Singapore (NUS), who is one of the research leads of this project. She shared valuable insights into AI's societal impact, with a focus on case studies in Bangladesh and Thailand.

"There are quite a lot of ways in which AI can allow for leapfrogging traditional barriers, such as literacy and cultural constraints," Dr. Jensen stated. "AI provides an opportunity for women to access professional advice and support through applications, bypassing some of these barriers."

Enhancing Maternal Health in Bangladesh

Maternal healthcare in Bangladesh faces significant challenges, including limited monitoring and access barriers. APRU, in collaboration with the Bangladesh Aspire to Innovate Programme and research teams from NUS, KAIST, and the University of Hawaii, explored AI innovations in maternity care.

"Our project aims to use AI to support maternal health in Bangladesh, focusing on community health workers. We've recommended digitalizing antenatal care data and implementing mobile systems for appointment tracking and reminders," Dr. Jensen explained.

AI Solutions for Digital Health Governance and Poverty Alleviation in Thailand

In Thailand, researchers from NUS identified barriers to sharing medical and healthcare data and provided policy recommendations to the Thai government. These include developing data sharing guidelines, promoting data exchange platforms, and facilitating stakeholder dialogues.

Another project, led by the Australian National University (ANU), focuses on improving internal information exchange within Thailand's administration to optimize advanced analytics for poverty alleviation. "Cultural barriers, rather than technical or legal obstacles, impede effective data utilization in anti-poverty efforts," Dr. Jensen noted.

Thailand's Data Sharing Hurdles: A Call for Collaboration

While Thailand boasts a more developed healthcare system, data sharing remains a critical challenge. Government departments are reluctant to share data, hindering comprehensive analysis and AI-powered solutions. The project identified key challenges:

  • Data Silos: Government departments operate in silos, with data locked away in individual systems. This fragmentation impedes the holistic view needed for effective AI applications.
  • Cultural Barriers: Agencies view data as "theirs" and are hesitant to share due to perceived ownership, hindering collaboration and cross-departmental data integration.
  • Data Quality Concerns: Agencies worry about the impact of sharing low-quality data on program effectiveness. Addressing data quality issues is crucial for building trust and encouraging data sharing.

Lessons Learned

"I began the project with skepticism about AI's potential in healthcare, especially in a country like Bangladesh with limited digital access and a complex, non-digitalized health system. Women, particularly in rural areas, face numerous challenges including poor healthcare access, low education levels, and cultural barriers in making health decisions. Initially, I questioned whether AI could be effectively implemented given these obstacles. However, the project revealed that digitalizing the healthcare sector is crucial for AI's success. This foundation will facilitate better information sharing between government departments and the private sector, especially in maternal health."

"Despite the challenges, AI has shown significant potential to overcome barriers. It can help women access professional advice and support, bypassing literacy and cultural issues. Community health workers, who play a critical role in supporting vulnerable women, can benefit from AI by identifying patients, planning efficient visits, and simplifying data entry. AI also provides quick access to information on symptoms and treatments, making it easier for health workers to give practical advice. This project demonstrated that AI can make a positive impact by providing practical and accessible solutions in healthcare, even as broader digitalization efforts continue," Dr. Jensen concluded.

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