Reflections on a panel discussion concerning AI and information disorder Across the globe, digital media platforms have exacerbated the intentional and unintentional spread of misinformation. Misinformation, which can be spread both intentionally and unintentionally, has contributed to increased polarization, hateful rhetoric and the deterioration of democratic systems. The development of AI systems may exacerbate these issues, while also creating opportunities to combat the problem. Seasoned voices from the South Asian and African disinformation landscape came together for a panel discussion, held in Colombo, organized by LIRNEasia, titled “Use of AI to Counter the Information Disorder” on July 3, 2025, united by a single question: Can AI assist in solving the very problems it creates? The session, moderated by Merl Chandana (Research Manager and Team Lead of Data, Algorithms, and Policy), focused on the intersection of AI and information integrity in the context of misinformation, especially during elections. 
Reflections on a panel discussion concerning AI and information disorder Across the globe, digital media platforms have exacerbated the intentional and unintentional spread of misinformation. Misinformation, which can be spread both intentionally and unintentionally, has contributed to increased polarization, hateful rhetoric and the deterioration of democratic systems. The development of AI systems may exacerbate these issues, while also creating opportunities to combat the problem. Seasoned voices from the South Asian and African disinformation landscape came together for a panel discussion, held in Colombo, organized by LIRNEasia, titled “Use of AI to Counter the Information Disorder” on July 3, 2025, united by a single question: Can AI assist in solving the very problems it creates? The session, moderated by Merl Chandana (Research Manager and Team Lead of Data, Algorithms, and Policy), focused on the intersection of AI and information integrity in the context of misinformation, especially during elections. 
Pinpointing where poverty is most severe and tracking its changes over time is crucial for helping communities effectively. However, traditional benchmarks like household surveys and national censuses often fall short—they’re expensive, slow, and infrequent. In countries like Sri Lanka, this means we’re often relying on outdated information, hindering our ability to respond to sudden economic shocks or disasters. On top of that, poverty cannot be determined by income data alone, rather its multidimensional, where factors such as infrastructure, access to services, and economic activity also play a role in determining a community’s well-being. To capture these complexities, our DAP team (Data, Algorithms, and Policy) explored something different: how to rethink the way we measure poverty in Sri Lanka using AI with non-traditional data sources? 
The following document is a summary of an upcoming regional report for the Global Index on Responsible AI (GIRAI) that focuses on responsible Artificial Intelligence in the Asia region. The broader report, to be released in April 2025 as the final output of a Global Center on AI Governance (GCG)-funded project, was authored by Merl Chandana and Sukitha Bandaranayake from LIRNEasia, with the India case study written by Anushka Jain and Aarushi Gupta (of Digital Futures Lab, India). Part II was co-authored by Merl Chandana, Sukitha Bandaranayake, and Ana Florido. The report containing global findings of the Index can be found here.