As values shape the design and governance of technology, it becomes critical to move beyond universal framings to explore the nuanced, subjective understandings individuals hold about values. Traditional value elicitation methods often identify values at play but overlook how they are interpreted through individuals’ social identities and lived experiences. This paper introduces an AI-augmented value exploration method inspired by photo elicitation, which involves interviews supported by participant-taken photographs. Instead, we use AI-generated imagery to uncover hidden associations and insights around personal understandings of values. In an exploratory study with six participants, we focused on the value of well-being, examining how AI-generated visuals prompted diverse personal interpretations and facilitated deeper value reflections. Our findings show that this method uncovers implicit meanings and deepens discussions by translating abstract ideas into tangible interpretations to yield richer data on situated values.

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.