Public ADD Lecture: Friction and promise in data labor

Join ADD and the TANTlab on November 6th at 13:30 – 14:30 for a public lecture with Minna Ruckenstein & Tuukka Lehtiniemi from the University…
Public ADD lecture

Event host: The Techno-Anthropology Lab

When and where: November 6th, 2023 at 13:30-14:30, Aalborg University Copenhagen, A.C. Meyers Vænge 15, Copenhagen, Danmark 2450

For the past years, we have faced a repeated experience when presenting our work on prisoners training AI. Scholars in the fields of critical data and algorithm studies start nodding, as if they already knew what we were going to say. What else is prison data labor than an effort to harness the prison-industrial complex in the service of the global data extraction machinery?

We do not disagree that data power is at play in prisons. Yet, rather than verifying the exploitative features of prison data labor, the developments in Finland allow posing more specific questions about data labor in relation to processes of datafication. In this talk, I’ll use our experiences to reflect on the way current research on algorithmic systems and AI gravitates toward utopian and dystopian ends, and how we have resisted the urge to follow this trend that treats the society as merely a landing site for technologies. I build on Anna Tsing’s (2015) notion of friction, coined for the purposes of probing how global connections sustain claims of universality by becoming locally reconfigured, to demonstrate that while influential platform companies raise justified concerns about the exploitative aspects of data labor, in the Finnish case we also need to take into consideration other kinds of aims and values. When data labor enters Finnish prisons, its dehumanizing qualities can become sidelined, as the goal is not only to produce data, but to work in an ethically sound manner in the margins of the digitalizing society. I will pay attention to human involvements, anticipations, and institutional imaginaries that are crucial in promoting data-related futures to demonstrate how collaborations and disconnects around data-based automation need to be analyzed critically, yet without ignoring the possibility that they grow more hopeful and optimistic ways forward.

Looking forward to seeing you there!

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