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Paper short abstract

This contribution focuses on methodological challenges of researching AI with digital methods in a platform context. Structured along the lines of material, temporal, and epistemological access, it demonstrates both the limitations and potentiality of digital methods in relation to AI's complexities

Paper long abstract

There have been many impulses to make sense of various functionalities under the ‘artificial intelligence’ umbrella, with diverse methodologies employed. Such methods often strive to perform AI critique through a cross-disciplinary lens to historicize, denormalize, and engage with the present moment of an apparent ‘inevitability’ and omnipresence of AI. The practice of operationalizing digital methods, in the spirit of ‘mapping’ AI, is one such methodology. However, how does AI introduce and deepen (not-so-new) messiness in doing digital research? What challenges do digital methods carry when we apply them to today's digital landscape ploughed with and about AI? And, crucially, what limitations do we face when we use digital methods to make sense of AI? This contribution focuses on three methodological challenges in researching AI with digital methods in a platform context. To do so, this methodological contribution is organized along the three problematizing axes of the material, the temporal, and the epistemological access.

Inspired by the traditions of STS and critical AI studies, as well as media studies, this methodological proposition discusses the technical, political, and epistemological limitations and challenges of researching AI with the digital, and puts forward a layered approach to thinking about methodological and analytical entry points to AI critique. Ultimately, it demonstrates how a critical recognition and engagement with the limitations and challenges we face in researching AI with digital methods can serve as an empowering counter-position to the hegemonic claims of AI’s completeness, frictionlessness, and universality.