Shaping 21st Century AI – SHAPING AI ES-T01069X-1

Talk about “artificial intelligence” (AI) is abundant. Politicians, experts and start-up founders tell us that AI will change how we live, communicate, work and travel tomorrow. Autonomous vehicles, the detection of illnesses, automated filtering of misinformation and hate speech – AI is seemingly set out to fix fundamental problems of our societies. At the same time, substantive concerns are raised that these developments might reinforce social and economic inequality, exacerbate the opacity of decision-making processes, and ultimately question human autonomy. Moreover, the direction of the scientific field itself is up for dispute, with leading practitioners of machine learning publicly disagreeing about the long-term importance of different approaches to designing and training these artificial agents.

This conjunction of dynamic technological developments and fundamental controversies sets the perfect scene for a comparative, longitudinal inquiry into how AI as a sociotechnical phenomenon is being integrated into our societies. Although we have seen spikes of interest in AI before, 21st-century AI is currently in its formative stage—unsettled in the public debate, but also in expert policy and research communities. And while progress in machine learning has long come in the form of experiments, today these ‘experiments’ take place in our everyday lived environment; this is the implicit subtext of the profusion of publications of consultancy surveys, ethics whitepapers, national AI strategies, and large redeployments of research funding.

The proposed project seeks to contrast both regional and globalized trajectories in four key countries: Canada, France, the UK, and Germany. Within and across these countries, the project compares and relates to each other—using historical, ethnographic, and computational methods appropriate to each case—the discourse and developments around AI’s “deep learning revolution” over 10 formative years (2012 to 2021) in three layers: in the media, in the policy space, and in the research community.

The fieldwork builds on and extends the “cartographie de controverses” that has been developed at the Media Lab, Sciences Po. The media analysis will investigate AI debates in major news outlets, niche websites and social media conversation. The policy analysis will map and analyze the existing policy initiatives, whitepapers and regulations in each country, with careful attention to their rationales. Policy analysis will employ select expert interviews and social media conversations to contextualise policy developments. The research analysis will map publication archives and scientific communities as well as experiment with ethnographic embedding in relevant workshops and conferences where AI intersects with social issues (e.g. of online propaganda or of bias in machine learning models). In addition, the project will investigate and instigate formats of public engagement by hosting participatory workshops that enable stakeholders and members of the public to debate and negotiate AI pathways. Each of these analyses and interventions will not be conducted in a stand-alone manner, but will reflexively inform one another.

This particular research design allows the project to retrace how 21st-century AI has been repeatedly constructed as both a problem and a solution: how throughout its brief history and unknown future, AI cultures negotiate across controversies and (apparent) closure without the scope of “AI” ever being fully defined. This international, comparative, multi-methodological study with a clear commitment to public knowledge and engagement seeks to extend and redistribute the range of expertise that is relevant to ensure that the coming of AI is truly for the greater good.