A Gendered Perspective on Artificial Intelligence

Proceedings of ITU Kaleidoscope 2018 -- Machine Learning for a 5G Future

7 Pages Posted: 21 May 2019

See all articles by Smriti Parsheera

Smriti Parsheera

Indian Institute of Technology (IIT), Delhi

Date Written: November 29, 2018


Rapid advances in machine learning have brought about a new phase in the development of artificial intelligence (AI). While recognizing the field’s tremendous potential we must also understand and question the process of knowledge-making in AI. Focusing on the role of gender in AI, this paper discusses the imbalanced power structures in AI processes and the consequences of that imbalance. From its inception, the field of AI has largely remained the domain of men, the gender of its founders and researchers playing a key role in shaping AI's developmental path. Further, AI's reliance on real-world data, which is often fraught with gender stereotypes and biases, also ends up reinforcing and sometimes exacerbating society's existing biases.

The challenge therefore lies in finding ways to bundle the technological progression of AI research with the objectives of pursuing greater fairness in society -- for machines to eliminate rather than reinforce human biases. The paper proposes a three-stage pathway towards bridging this gap. The first, is to develop a set of publicly developed standards on AI, which should embed the concept of “fairness by design”. Second, is to invest in research and development in formulating technological tools that can help translate the ethical principles into actual practice. The third, and perhaps most challenging, is to strive towards reducing gendered distortions in the underlying datasets to reduce biases in future AI projects.

Keywords: artificial intelligence, gender, bias, representation, fairness, fairness by design

JEL Classification: O3, O31, O32, O33, O38

Suggested Citation

Parsheera, Smriti, A Gendered Perspective on Artificial Intelligence (November 29, 2018). Proceedings of ITU Kaleidoscope 2018 -- Machine Learning for a 5G Future, Available at SSRN: https://ssrn.com/abstract=3374955 or http://dx.doi.org/10.2139/ssrn.3374955

Smriti Parsheera (Contact Author)

Indian Institute of Technology (IIT), Delhi ( email )

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