Meenakshi’s work aims to explore explore how Indian EdTech engineers incorporate ideas about teaching and learning into the development of AI education technologies for K-12 classrooms. She aims to understand how ML infrastructures interact with and influence engineering practices in AI EdTech development.

Yiping’s work focuses on the introduction of big data-driven technology — exploring the context, differences and process of the technology development, in addition to the performativity realized through stakeholders’ and partitioners’ engagement, discussion, cooperation and negotiation during the implementation process.

This project explores the responsible usage of AI, in particular, learning to identify and mitigate bias and algorithmic (un)fairness. It looks to prevent the potential reinforcement and amplification of harmful existing human biases with applications to credit access and the financial industry.

Bhargavi’s research aims to understand the role of regulatory, organizational, and professional modes of governance in bridging potential accountability ‘gaps’ generated by emerging technologies like AI.

This project aims to synthesise philosophical bioethics and public deliberative processes, to arrive at recommendations for the ethical use of AI in healthcare resource allocation.