Reflexive Data Curation
Opportunities and Challenges for Embracing Uncertainty in Human–AI Collaboration
Anne Arzberger (TU Delft - Web Information Systems)
Maria Luce Lupetti (Politecnico di Torino)
Elisa Giaccardi (Politecnico di Milano)
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Abstract
This article presents findings from a Research through Design investigation focusing on a reflexive approach to data curation and the use of generative AI in design and creative practices. Using binary gender categories manifested in children’s toys as a context, we examine three design experiments aimed at probing how designers can cultivate a reflexive human-AI practice to confront and challenge their internalized biases. Our goal is to underscore the intricate interplay between the designer, AI technology, and publicly held imaginaries and to offer an initial set of tactics for how personal biases and societal norms can be illuminated through interactions with AI. We conclude by proposing that designers not only bear the responsibility of grappling critically with the complexities of AI but also possess the opportunity to creatively harness the limitations of technology to craft a reflexive data curation that encourages profound reflections and awareness within design processes.
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