LCAL Thematic Programmes

Our research explores the concept and practice of generativity, tracing the human, cultural, scientific, and philosophical forms of generativity that shed light on the novel generativities of AI algorithms.

How are algorithmic models generating and reconfiguring human and social life-worlds?

What can the philosophy and culture of generativity tell us about the life-worlds that are being generated by collaborations between humans and algorithms?

Our research investigates the transformations in images and language that are taking place within and alongside algorithmic systems.

What happens to the images and language of human sense-making now that they are also the basis of machine learning?

What are the distinctive forms of classification and discrimination that emerge from a reconfiguring of image and language?

Our research seeks understanding of how human life-worlds are becoming interwoven with the synthetic life-worlds of algorithms.

How are new forms of simulation such as “digital twins” changing how human societies represent themselves, how they are governed, and how they make decisions? How can this novel synthesis be situated in the history of computing and machine learning?

What kinds of life-world become possible with the advent of synthetic datasets? How does synthetic data reconfigure the boundaries of the real and the virtual, truth and the “fake”, life and non-life?

Our research will reimagine the place of the human in the context of algorithmic life-worlds.

What is happening to ideas of control, authority, oversight, accountability, and judgement in context of forms of life that are simultaneously human and algorithmic?

How are concepts from algorithmic life-worlds (e.g. data distributions, embedding spaces, latency, zero shot, reinforcement learning) becoming the conditions of possibility for adjudicating who or what counts as human, who or what counts as a liveable life?