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Cited by 161Ethics and Social Impacts of AIDigitalization, Law, and RegulationArtificial Intelligence Applications

Artificial intelligence policy in India: a framework for engaging the limits of data-driven decision-making

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Marda, Vidushi·2018·Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
DOI 10.1098/rsta.2018.0087
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Abstract

Artificial intelligence (AI) is an emerging focus area of policy development in India. The country's regional influence, burgeoning AI industry and ambitious governmental initiatives around AI make it an important jurisdiction to consider, regardless of where the reader of this article lives. Even as existing policy processes intend to encourage the rapid development of AI for economic growth and social good, an overarching trend persists in India, and several other jurisdictions: the limitations and risks of data-driven decisions still feature as retrospective considerations for development and deployment of AI applications. This article argues that the technical limitations of AI systems should be reckoned with at the time of developing policy, and the societal and ethical concerns that arise due to such limitations should be used to inform what policy processes aspire to achieve. It proposes a framework for such deliberation to occur, by analysing the three main stages of bringing machine learning (the most popular subset of AI techniques) to deployment—the data, model and application stage. It is written against the backdrop of India's current AI policy landscape, and applies the proposed framework to ongoing sectoral challenges in India. With a view to influence existing policy deliberation in the country, it focuses on potential risks that arise from data-driven decisions in general, and in the Indian context in particular. This article is part of the theme issue ‘Governing artificial intelligence: ethical, legal, and technical opportunities and challenges'.

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  • Most fairness research examines racial and gender biases in models, the two dimensions that dominate American public discourse.

    “The majority of fairness research looks at racial [46,57,121,125,183] and gender biases [42,46,197,219] in models-two dimensions that dominate the American public discourse.”

    From Re-imagining Algorithmic Fairness in India and Beyond (2021) · cites this paper as [125]

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Authors
Marda, V.
Affiliations
Article 19 (BR)
Corresponding author
Marda, Vidushi
ORCID
Marda, Vidushi
Venue
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
Publisher
The Royal Society
Published
2018-10-15
Volume
376
Issue
2133
ISSN
  • 1364-503X (ISSN-L)
  • 1471-2962
DOI
10.1098/rsta.2018.0087
OpenAlex
W2895968895
Cited by
161
References
31
Citations by year
2026: 14 · 2025: 42 · 2024: 34 · 2023: 26 · 2022: 14 · 2021: 14 · 2020: 11 · 2019: 5 · 2018: 1
FWCI
15.41
Type
journal article
Language
en
Open access
Licence
Locations
  • Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences (publishedVersion)
  • SSRN Electronic Journal (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
  • Social Sciences › Law › Digitalization, Law, and Regulation
  • Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
Keywords
AI policy, India, data-driven decision making, machine learning, AI risks, AI ethics, policy framework

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