This lecture takes place on Tuesday, 21 May 2024 from 18:00 at The Royal Society in London. It will also be streamed online.

In her presentation, Professor Marres will discuss the debates surrounding the use of AI in social research and argue that the new tools challenge the ability of the social sciences to engage with contexts and communities in society (for more information, see the abstract below).

Rachel Coldicutt (Careful Industries) and Carrie Friese (LSE) will act as discussants.

More info about the event can be found hereLink opens in a new window.

Lecture Abstract:
After the Automation of Methods: the Case for Situational Analytics

The growing popularity of generative AI as a research tool poses new challenges for the sciences of society. While computational methods have long played an important role in enabling social inquiry, AI advocates now claim that acts of knowledge production – from interpreting data to writing up results – can be delegated to automated systems. For the social sciences and humanities, this has reawakened classic concerns about their future in a techno-scientific age, as well as long-standing debates about what it takes to create knowledge of society. While some argue that the sciences of society should embrace the automation of methods, others insist that understanding society requires active engagement with specific places, people and contexts, today no less than before.

In this lecture, Professor Noortje Marres will show how a distinctive set of interdisciplinary methods – digital, visual and participatory methods of situational mapping – can enable us to navigate the challenges that AI poses to knowing society. These methods, which have roots in sociology, media studies and design research, offer a practical framework for negotiating the conflicting requirements that automation and participation place on social research in contextually-aware ways. Drawing on two recent research projects, Shaping AI and AI in the Street, the lecture will show how methods of situational analytics enable insight into the implications of AI for particular places and people, while equally enabling the evaluation of AI in society at scale.

The lecture will conclude with some reflections on the consequences of the rise of generative AI for the relations between social science and society. Far from rendering societal engagement irrelevant to scientific research, the drive to automation in both science and society reveals the degree to which the relations between them are interactive. Which is also to say: engagement across science/society is not a nice add-on to computational research, but indispensable to knowing society whether this involves automated methods or not.

The event begins at 18:00, with a reception and light refreshments, giving guests the chance to network with researchers from other disciplines and sectors.