What could bringing gender studies and computing together teach us about bias?

Last year Claude and Goda participated in the workshop on Bias in Information, Algorithms and Systems. The workshop took place on 25^th of March, as part of the conference 13th International Conference on Transforming Digital Worlds (iConference 2018) in Sheffield, UK. The premise of the workshop was to bring researchers from different disciplines who work on analysing, understanding and tackling bias within their discipline, arising from the data, algorithms and methods they use.

Our short position paper (co-written also with Pat Treusch)[i] was focused on bringing in the feminist theoretical perspective and experimenting with ways (at least in theory so far) how feminist insights and concepts can be turned into methods of tackling bias. Specifically, we worked with Haraway’s notion of “situated knowledge” and Harding’s concepts of “strong/weak objectivity” as well as her standpoint theory. In brief, the main proposal is that bias should be re-thought as a complex, distributed phenomenon that does not arise only from data or method or ways of application, but rather can stretch across the whole process of designing a system. Further, it is not a stable value, but can change in relationship to its context. Lastly, we propose that seeing bias through feminist lens, particularly the two above-mentioned theories, can lead to better accountability standards.

You can download the full proceedings of the workshop here, and specifically our position paper here.

We are also working on developing a longer paper (“we” here is Claude Draude, Goda Klumbyte, Phillip Lücking and Pat Treusch) and we hope it will be published this year in the Online Information Review.

Do you have feedback? Comments? Ideas about how feminist theory can be translated into computational practice and help tackle bias? Let us know in the comments section!

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[i] Full reference to the paper: Draude, C., Klumbyte, G., Treusch, P., „ Re-Considering Bias: What Could Bringing Gender Studies and Computing Together Teach Us About Bias in Information Systems?”,  Proceedings of the International Workshop on Bias in Information, Algorithms, and Systems co-located with 13th International Conference on Transforming Digital Worlds (iConference 2018), Sheffield, United Kingdom, March 25th, 2018, CEUR Workshop Proceedings, vol. 2103, pp. 14-18,  http://ceur-ws.org/Vol-2103/