“…These concerns include: (1) economic issues, (2) justice, (3) human freedoms, (4) broader societal issues, and (5) unknown issues. Economic issues are especially significant in AI value chains, and issues of particular note can be found in the use of automation and biometrics in hiring, contracting, dismissal, and surveilling workers (Bales & Stone, 2020;Hickok & Maslej, 2023); labor exploitation, distributions of wealth, capital, and other financial resources, particularly in transnational and inter-class contexts (Dyer-Witheford, Kjøsen, & Steinhoff, 2019;; open-sourcing of and access to AI-related data, code, and other software resources (Langenkamp & Yue, 2022;Masiello & Slater, 2023); distributions of data, computational, technological, and financial resources obtained through the development and/or use of AI systems, as well as distributions of political and economic power that emerge from those resource distributions (Dyer-Witheford, Kjøsen, & Steinhoff, 2019;Pasquale, 2020). Examples of specific cases involving some of these economic issues include: OpenAI's outsourcing of data labeling to workers employed by Sama AI in Kenya, many of whom were psychologically harmed and undercompensated during their employment (Perrigo, 2023); consolidation of models and datasets in an increasingly small group of companies (Ahmed, Wahed, & Thompson, 2023); Amazon's development, use, and subsequent disuse of a hiring automation tool that discriminated against women (Dastin, 2018); striking Screen Actors Guild and Writers Guild of America workers demanding their employers refrain from using their likenesses or unionprotected creative materials in training datasets and from introducing generative AI applications into production processes (Broderick, 2023;Webster, 2023).…”