Reflexive Data Curation: Opportunities and Challenges for Embracing Uncertainty in Human-AI Collaboration

Author:

Arzberger Anne1ORCID,Lupetti Maria Luce2ORCID,Giaccardi Elisa3ORCID

Affiliation:

1. Department of Software Technology, TU Delft, Netherlands

2. Department of Architecture and Design, Politecnico di Torino, Italy

3. Department of Design, Politecnico di Milano, Italy

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.

Publisher

Association for Computing Machinery (ACM)

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3. Philip E Agre. 2014. Toward a critical technical practice: Lessons learned in trying to reform AI. In Social science, technical systems, and cooperative work. Psychology Press, 131–157.

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5. Danielle Barbosa Lins de Almeida. 2017. On diversity, representation and inclusion: New perspectives on the discourse of toy campaigns. Linguagem em (Dis) curso 17 (2017), 257–270.

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