<A+ Global Directory>

<A+ Global Directory>



Sareeta Amrute

logo University of Washington, Data & Society Research Institute
Associate Professor, University of Washington; Director of Research & Principle Researcher, Data & Society Research Institute
University of Washington, Data & Society Research Institute
New York, United States

https://read.dukeupress.edu/books/book/62/Encoding-Race-Encoding-ClassIndian-IT-Workers-in

https://journals.sagepub.com/doi/full/10.1177/0162243920912824

https://points.datasociety.net/how-to-cite-like-a-badass-tech-feminist-scholar-of-color-ebc839a3619c

https://journals.sagepub.com/doi/full/10.1177/0141778919879744


Labor, coding cultures, and political sensibilities in the US and India.

About the work

I have written about feminist approaches to ethics through attunement as a basis for understanding social movements in tech industries; I also am currently writing about anti-Asian violence in the wake of the Covid-19 epidemic. My scholarship broadly studies labor in coding industries from the vantage point of race, class, and gender. I write about 'algorithmic thinking' and the organization of labor globally and I trace connections between earlier moments of global divisions of labor and racial sortings in the current moment. I am embarking on a new project on digital payments in India, through which I will pay special attention to the gendered effects of cashless economies through the lens of the oikos, or home economics. I am the author of Encoding Race Encoding Class: Indian IT Workers in Berlin. My work takes a labor-centered perspective on AI and AI research. I investigate the largely hidden figures who write the codes for AI applications.

Impact

My work is largely theoretical, but has several potential applications for the way we think about AI systems. In particular, I focus on historical precedents that give these systems the shape that they have today. I also follow the unfolding relationship between these systems and the way gender is constructed and reconstructed in AI worlds. This focus includes analyzing both how gender norms are built into AI systems, and how the use of AI systems in specific contexts adapts to and shifts gender, race, class, and other categories. In my new work on digital economies, I hope to surface infrastructural and design issues that prevent these systems from working for the populations (such as working class women) in whose name these systems are often designed.

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