The Computed World

Understanding the social life of digital technology

We live in an algorithmic age. As data networks deepen their entanglement with everyday life, new affordances arise for the quantification, analysis, administration, and platformisation of our experience and conduct. Where do we draw lines between ourselves and the many automated processes we live in and through? How far should we delegate our agency to cutesy automated assistants, to social media platforms stitched from algorithms, or to the dark brilliance of bespoke and opaque Artificial Intelligences, whose intricate machine reasoning so often eludes human understanding? With the growing interest in explainable AI, new questions arise around the nature and purpose of "explanations": explainable to whom, for what purposes, and in what ways? And when technological processes are not adequately explainable — when vast impersonal systems, fed on our data, claim to know our hearts better than we do ourselves  on what grounds can we challenge them? As the shared agency of humans and machines continues to evolve, we at SHL are working to ensure that the insights of the arts and humanities are heard at the heart of these debates.

Collaborative intelligence

Close links between the Sussex Humanities Lab and the Text Analysis Group (TAG Lab) allow us to undertake applied AI research, using automated methods to interpret corpori at scale including text documents, social media, and other communications. Researchers including Alex Butterworth, David Banks, Francisco Bernardo, Alice Eldridge, Chris Kiefer, Jack Pay, Andrew Salway, David Weir, and Simon Wibberley actively collaborate across computer science and the arts and humanities, including the development of intuitive interfaces to allow the expertise of social scientists and humanists to inform machine learning processes.

The social life of AI

AI is political, social, and cultural. From self-driving cars, through to high-frequency trading, military drones, and organised swarms of shelf-stacking robots, this is a moment marked by rising automation and fresh concern for its likely social implications. Automation has become, not for the first time in history, a locus of fierce contestation about possible and desireable futures. Automation culture  — the ways we think, talk, and feel about automation — is merged with dreams of abundance and convenience, of liberation from hierarchy and toil. It is just as entangled with nightmares of technological unemployment, or endlessly multiplying obligations for grinding busywork side-by-side with our robot pals.

So how might the arts and humanities address contemporary cultural hopes and fears about new forms of automation? At the Sussex Humanities Lab, researchers such as Ben Roberts and Beatrice Fazi are furthering our understanding of the social life of AI. Placing AI in its historical contexts, including long traditions of philosophy, art and literature about AI, is vital to such research. But so too is being aware of what might be new and unprecedented, as Beatrice's research on the automation of thought demonstrates. With the rise of the social media and other digital platforms, and the 'datalogical turn' of recent decades, humans have become legible to and manipulable by machinic systems in unprecedented ways. And there is a complicated flip side to this: not only the advent of new tactics and habits to evade or undermine automated surveillance and persuasion, but also the possibility that these emerging forms of machinic agency might become sensitive and hospitable to 'the human' in wholly new ways.


The Sussex Humanities Lab also shares many members and research interests with the Experimental Musical Technologies Lab at Sussex (Emute). How might AI and associated technology and science transform the meaning of 'listening'? How might emerging assemblages of humans and non-humans be capable of synthesising forms of knowledge traditionally seen as incommensurable —including data collected by sensor networks and the embodied and storied knowledge of communities? How do we develop technology that reveals and mimics the rhythms, patterns and dynamics of biological and ecological systems? Alice Eldridge's research explores machine listening in applied ecoacoustic research, including biodiversity monitoring and wilderness mapping from Ecuadorian cloud forests, to Indonesians reefs, to mountain wilderness spaces. Alice's collaborations with Chris Kiefer further examine the intersection of experimental music, ecoacoustics, and artificial life, including evolutionary agent-based models of acoustic niche formation. Chris's other research explores machine learning and signal processing for audio and interaction, with a particular emphasis on nonlinear and dynamical systems, and the agency of musical instruments. Building on a long and rich tradition of live coding at Sussex, Francisco Bernardo's research explores the intersection of live coding and interactive machine learning.

The (in)computable

The growing interest in the computational within human life also shines a light on the longer history of the computational, including pre-digital incarnations of the algorithm and the automaton. What is ‘computation,’ and in what machines, bodies, entities, substrates can computation occur? Computation has a mixed and contradictory reputation: it’s associated both with reliability and predictability, and also with creation, indeterminacy, emergence, with wilderness and wildness. Beatrice Fazi's groundbreaking research brings together both arts and humanities and STEM understandings of the (in)computable, to elaborate exhilarating new philosophical perspectives on aesthetics, on necessity and contingency, on abstraction and representation, on the automation of thought, and on algorithmic opacity and transparency.