The role of experts in constructing AI's social dimensions

The UK government recently published its "National AI Strategy" (OAI, 2021), setting out pathways to making Britain a global AI superpower. A key element of this strategy is the commitment to building up the AI research base. It is typically assumed that those categorized as AI researchers are composed of computer scientists; for example, Krafft et al. (2020) operationalized AI researchers based on self-identification or publications in major AI conferences. This has the effect of excluding scholars from social sciences and humanities-those trained to research social, cultural, political, and ethical aspects of science and technology-who might publish in different venues.

The exclusion of social sciences and humanities becomes problematic if AI is understood as relating to society as a context of its application and, conceptually and methodologically, in terms of how the social is operationalized in AI theories, methods, and systems (Roberge and Castelle, 2021). This double relation between AI and the social implies that AI is today a force in representing and "inventing the social" (Marres et al., 2018) -it plays an active role in articulating, through data-intensive applications (e.g., in communications), what constitutes social interaction, social actors, social benefits, etc.

The premise that AI is implicated in inventing the social raises the questions about the types of expertise deployed in knowledge production: not only "where, when, how, and for whom AI is developed" (Joyce et al., 2021), but also who makes empirical, methodological, and conceptual knowledge claims at the intersection of AI and the social. The urgency to understand this is exemplified by the growing ambitions of nation-states to capitalize on AI for international influence, through mechanisms like the UK's "National AI Strategy".

My research project will take an empirical approach to researching what types of expertise constitute AI research in the contemporary UK. Specifically, my doctoral research project will be guided by three questions:
1. Which types of experts today make knowledge claims about social aspects of AI across the sciences, engineering, social science and humanities?
2. How is epistemic relevance and authority established in the AI research field?
3. What kinds of knowledge claims become influential in policy and media domains?

To answer these questions, I will combine scientometric and computational methods, including text analytics and (visual) network analysis to examine three arenas where expert knowledge becomes relevant to AI debates. First, I will examine academic research literature, or formal academic communication, to explore which academic fields claim representation and intervention in the social dimensions of AI. Second, policy documents will be analysed as an additional secondary arena where the relevance of academic knowledge in relation to social aspects of AI gets established. Third, Twitter data will be collected to enrich my project's understanding of informal public expert discourse around AI, the social and its production.

My project aims to advance the fields of Science and Technology Studies (STS) and sociology of knowledge by providing a nuanced account of how scientific epistemic relevance and authority is established across disciplines and knowledge arenas on social aspects of AI. While at present computer scientists might be dominating all three arenas, understanding which other types of experts contribute (and how) will help to understand dynamics of influence and power relations across science and politics, and support reflection on different ways for making social sciences and humanities research in this area more impactful.