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Paper short abstract

The presentation outlines the research design and methodology that was developed for a currently undergoing PhD project on AI governance. The case study is that of a multinational financial company whose activities on AI regulation and use were observed with direct access to the field.

Paper long abstract

The use of AI systems both in the public and private sectors calls for regulation. Recently, many companies have developed and implemented governance models that introduce guidelines and procedures for the use of AI systems. Typically, governance policies adopt a so-called Responsible AI (RAI) approach. The question arises, how to study the forms actually taken by responsibility.

The present work concerns a currently ongoing PhD project that investigates the AI-related activities of a multinational financial company and how responsibility is translated into practices and discourses. Specifically, the project performs qualitative research and was granted access to the field: it was possible to examine company documentation and to interview key actors involved in the design, development and adoption of two AI applications.

The presentation will outline the research design and methodology of the research project. The main challenge concerned addressing the large number of actors involved in the development and adoption of an AI system. Therefore, attention was paid to the boundaries within the company and between the company and external actors such as regulators and consultants. Consequently, the socio-technical networks configuring the two applications under study were reconstructed by following the actors. Both a diary and a weblog were kept, and a template analysis was performed. An interpretive framework to appreciate how RAI is contextually configured was then developed. Alongside preliminary results concerning the effects of AI governance on organizational structure and working practices, the presentation will outline the methodological challenges encountered and the main implications for future research.