arXiv subjects

Mercedes Bunz

Publications and source records attributed to Mercedes Bunz.

3 recordsLinked to original sources

arXiv2026

Computational Hermeneutics: Evaluating generative AI as a cultural technology

Generative AI systems are increasingly recognized as cultural technologies, yet current evaluation frameworks often treat culture as a variable to be measured rather than fundamental to the system's operation. Drawing on hermeneutic theory from the humanities, we argue that GenAI systems function as "context machines" that must inherently address three interpretive challenges: situatedness (meaning only emerges in context), plurality (multiple valid interpretations coexist), and ambiguity (interpretations naturally conflict). We present computational hermeneutics as an emerging framework offering an interpretive account of what GenAI systems do, and how they might do it better. We offer three principles for hermeneutic evaluation -- that benchmarks should be iterative, not one-off; include people, not just machines; and measure cultural context, not just model output. This perspective offers a nascent paradigm for designing and evaluating contemporary AI systems: shifting from standardized questions about accuracy to contextual ones about meaning.

cs.AI↗

arXiv2025

Reciprocity Deficits: Observing AI in the street with everyday publics

The street has emerged as a primary site where everyday publics are confronted with AI as an infrastructural phenomenon, as machine learning-based systems are now commonly deployed in this setting in the form of automated cars, facial recognition, smart billboards and the like. While these deployments of AI in the street have attracted significant media attention and public controversy in recent years, the presence of AI in the street often remains inscrutable, and many everyday publics are unaware of it. In this paper, we explore the challenges and possibilities of everyday public engagement with AI in the situated environment of city streets under these paradoxical conditions. Combining perspectives and approaches from social and cultural studies of AI, Design Research and Science and Technology Studies (STS), we explore the affordances of the street as a site for 'material participation' in AI through design-based interventions: the creation of 'everyday AI observatories.' We narrate and reflect on our participatory observations of AI in five city streets in the UK and Australia and highlight a set of tensions that emerged from them: 1) the framing of the street as a transactional environment, 2) the designed invisibility of AI and its publics in the street 3) the stratification of street environments through statistical governance. Based on this discussion and drawing on Jane Jacobs' notion of "eyes on the street," we put forward the relational notion of "reciprocity deficits" between AI infrastructures and everyday publics in the street. The conclusion reflects on the consequences of this form of social invisibility of AI for situated engagement with AI by everyday publics in the street and for public trust in urban governance.

cs.HC↗

arXiv2024

My Voice, Your Voice, Our Voice: Attitudes Towards Collective Governance of a Choral AI Dataset

Data grows in value when joined and combined; likewise the power of voice grows in ensemble. With 15 UK choirs, we explore opportunities for bottom-up data governance of a jointly created Choral AI Dataset. Guided by a survey of chorister attitudes towards generative AI models trained using their data, we explore opportunities to create empowering governance structures that go beyond opt in and opt out. We test the development of novel mechanisms such as a Trusted Data Intermediary (TDI) to enable governance of the dataset amongst the choirs and AI developers. We hope our findings can contribute to growing efforts to advance collective data governance practices and shape a more creative, empowering future for arts communities in the generative AI ecosystem.

cs.CY↗