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Short abstract:

The transformative effect of data and AI affects almost all areas of our everyday life and knowledge economies. Research must not only comment from the sidelines, but engage where the technological change manifests. This paper shows examples for studying up close and intervening effectively.

Long abstract:

The field of critical data & AI studies correctly questions the claim to objectivity, efficiency, and techno-solutionism made by the big tech sector and media discourses. However, two problems seem to be apparent here: a) the narrative is dominated by US American perspectives with societal institutions, governments and a technology sector widely different from the situation in the various EU countries; b) research often falls short in studying algorithms up close and within their socio-economic context of the organisations deploying them. The authors of this paper modelled their research practice consequently different. They immerse in public management organisations and media industries to study up close not only the discourses on AI but the actual practices of implementation, use and governance of AI systems. The researchers do not enter as mere observers but as experts in governing AI systems which allows them to also intervene and to take part in shaping the way algorithms are deployed in these organisations. They developed a strong track record of societal impact through informing policy, developing widely used tools for design, evaluation and assessment of algorithms, and creating learning formats for professionals. Drawing from STS and action research, this paper discusses methods for investigating and shaping the digital society. It discusses the benefits and pitfalls of this research practice, the privileged insights, the potential for societal impact, the learning opportunities for students and professionals, but also issues of complicity, dependence, and the changing role of the researcher and their academic host institution.