Centre for Internet & Society

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Roundtable on Artificial Intelligence & Healthcare
by Admin published Nov 24, 2017 last modified Jan 02, 2018 01:49 PM — filed under: , ,
Centre for Internet & Society (CIS) is organizing a roundtable on artificial intelligence (AI) and healthcare at 'The Energy and Resources Institute' (TERI) in Bengaluru on November 30, 2017 from 2 p.m. to 5 p.m. The roundtable seeks to discuss the various issues and challenges surrounding the implementation of AI and related technologies in the Indian healthcare sector.
Located in Internet Governance / Events
Blog Entry The Mother and Child Tracking System - understanding data trail in the Indian healthcare systems
by Ambika Tandon published Oct 18, 2019 last modified Dec 30, 2019 05:18 PM — filed under: , , , , , , , ,
Reproductive health programmes in India have been digitising extensive data about pregnant women for over a decade, as part of multiple health information systems. These can be seen as precursors to current conceptions of big data systems within health informatics. In this article, published by Privacy International, Ambika Tandon presents some findings from a recently concluded case study of the MCTS as an example of public data-driven initiatives in reproductive health in India.
Located in Internet Governance / Blog
Blog Entry Unpacking Algorithmic Infrastructures: Mapping the Data Supply Chain in the Healthcare Industry in India
by Amrita Sengupta, Chetna V. M., Pallavi Bedi, Puthiya Purayil Sneha, Shweta Mohandas and Yatharth published Dec 22, 2023 last modified Jan 05, 2024 02:38 AM — filed under: , , , , , ,
The Unpacking Algorithmic Infrastructures project, supported by a grant from the Notre Dame-IBM Tech Ethics Lab, aims to study the Al data supply chain infrastructure in healthcare in India, and aims to critically analyse auditing frameworks that are utilised to develop and deploy AI systems in healthcare. It will map the prevalence of Al auditing practices within the sector to arrive at an understanding of frameworks that may be developed to check for ethical considerations - such as algorithmic bias and harm within healthcare systems, especially against marginalised and vulnerable populations.
Located in RAW