Panel 7

Organizers: Ludovico Rella (1); Fabio Iapaolo (2)

1: Durham University, United Kingdom; 2: Oxford Brookes, United Kingdowm

Topics: Technoscientific promises, imaginaries and expectations; Technofeminism and interspecies solidarities; Algorithmic knowledge, media ecologies and artificial intelligence; Ethics, innovation and responsibility in technoscience

Keywords: AI, Materiality, Hardware, Distributed Cognition, Individuality

This panel seeks to interrogate the multiple – and sometimes contradictory – world visions, political imaginaries, and social expectations underlying conceptualizations of the human and, by extension, AI. From Pygmalion to Ex Machina, one source of our perennial fascination with the thinking machine originates in the prospect it evokes that attributes deemed uniquely human – e.g., consciousness, intelligence, autonomous action – might be replicated in mediums other than the human body. In its historical attempt “to reproduce the quintessence of our humanity, our faculty for reason” (McCorduck, 2004, 4), AI research often and perhaps inevitably has incurred anthropocentric and anthropomorphic fallacies. This is particularly manifest in the scientific and cultural imagination of AI as discrete technologies operating in ways different from, yet fundamentally similar to, the sovereign human subject – as the repeated insistence on notions like autonomy, rationality, control, and decision-making attests to. With its tendency to abstract away embodiment from intelligence (Hayles, 1999), XX-century cybernetics paradoxically reinforced this imaginary, often by association with the liberal autonomous subject, whose sense of agency lies in Enlightened self-interest. This panel, conversely, aims to bring together novel perspectives precisely on the materiality and de-individuality of AI, to complicate and destabilize intuitions about how to understand our technologies and ourselves. Following Beatrice Fazi (2019, 821), if we are to “recast the metaphysical question of the nature of thought”, we need to move past the simulative paradigm where AI merely imitates human thought.

For that to happen, a re-apprehension of the specific corporeal and technological materialities of intelligence is necessary. While even for human intelligence the mind-body connection is fundamental to cognition, Machine Learning and AI systems are predicated upon a very different form of materiality and embodiment. Resembling more a kind of “infrastructural intelligence” (Bruder, 2017) comprising multimodal sensing capabilities, ground truth data, training datasets, Edge AI hardware, graphic card-powered datacentres, and emerging neuromorphic microchips, the materiality of AI is key to the problematization of individuality that this panel wishes to explore. Rather than insisting on the individual – whether human or machinic – as the sole locus of intelligence and the base unit of ethico-political concern, we embrace the provocation that intelligence is “distributed across human and technical agencies” (Amoore, 2019, 4), including the broader socio-computational spaces where their embodied interactions occur. As human and machine interpretative decisions become ever more closely intertwined, the crucial question arises of how to envision adequate ethico-political responses beyond the terms (and terminology) dictated by liberal individualism.

Conceived as an experimental venue for interdisciplinary encounters, this panel seeks contributions exploring themes including, but not limited to:

• Imaginaries of AI personhood and their hidden ideologies
• Affordances and limitations of machine intelligence
• Space and computation
• Law and AI
• Genealogies of ‘artificiality’, ‘agency’, and ‘subjectivity’
• Algorithmic knowledge production and (re-)conceptualizations of intelligence
• Embodiment in posthuman, post-colonial, feminist science, queer, and critical race studies
• New perspectives on human subjectivity and technical agency vis-à-vis advances in AI
• Sociotechnical assemblages and automated decision-making
• AI hardware accelerators, neuromorphic microchips, sensors, and Edge AI

• The materiality of algorithms and robotics