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Title:Critical Analysis of “Responsible AI #AIforAll: Approach Document for India”
Author(s):Than, Nga; Gupta, Abhishek; Jauhar, Ameen
Subject(s):artificial intelligence
ethics
India
Geographic Coverage:India
Abstract:Governments across the world have increasingly focused on creating national policy frameworks to take advantage of AI developments for their strategic national interests, as well as to adapt and adjust AI technologies that operate within their socio-cultural and political constraints (Schiff et al 2020). However, most empirical research has mainly utilized AI-related ethics documents produced by governments located in the Global North. In this study, we present a critical analysis of Responsible AI #AIforAll: Approach Document for India (thereafter, the Approach Paper), a national AI strategy document published by NITI Aayog, a premier public policy think-tank of the Government of India1. This document is one of the first of its kind in the Global South. Not only it would serve as an important public policy reference for creating and discussing responsible AI in India, but it also has potential to serve as an exemplary policy document for other developing countries. We identify and discuss key missing elements in the document such as lack of Indian context, deterministic framing, epistemic incompleteness, and inaccuracies. We conclude with a list of recommendations for improving the process of generating a national strategy document on responsible AI.
Issue Date:2021-10-29
Citation Info:Than, N., Gupta, A., and Jauhar, A. (2021). Critical Analysis of “Responsible AI #AIforAll: Approach Document for India”. In Proceedings of the 17th Annual Social Informatics Research Symposium and the 3rd Annual Information Ethics and Policy Workshop at the 84th Annual Conference of the American Society for Information Science and Technology (ASIST 2021), October 29, 2021, Salt Lake City, Utah, USA.
Series/Report:Proceedings of the 17th Annual Social Informatics Research Symposium and the 3rd Annual Information Ethics and Policy Workshop
Genre:Conference Paper / Presentation
Type:Text
Language:English
URI:http://hdl.handle.net/2142/111789
Date Available in IDEALS:2021-10-29


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