Experiential AI

Journal article (2019)

Authors

Hemment Hemment The University of Edinburgh
Aylett Aylett Heriot-Watt University
Belle Belle The University of Edinburgh
Murray-Rust Murray-Rust External organisation
Luger Luger The University of Edinburgh
Hillston Hillston The University of Edinburgh
Rovatsos Rovatsos The University of Edinburgh
Broz Broz Heriot-Watt University
Affiliation
External organisation
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Published Date

2019

Language

English

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Affiliation

External organisation

Abstract

Experiential AI is proposed as a new research agenda in which artists and scientists come together to dispel the mystery of algorithms and make their mechanisms vividly apparent. It addresses the challenge of finding novel ways of opening up the field of artificial in- telligence to greater transparency and collab- oration between human and machine. The hypothesis is that art can mediate between computer code and human comprehension to overcome the limitations of explanations in and for AI systems. Artists can make the boundaries of systems visible and offer novel ways to make the reasoning of AI transparent and decipherable. Beyond this, artistic practice can explore new configurations of humans and algorithms, mapping the terrain of inter-agencies between people and machines. This helps to viscerally understand the com- plex causal chains in environments with AI components, including questions about what data to collect or who to collect it about, how the algorithms are chosen, commissioned andconfigured or how humans are conditioned by their participation in algorithmic processes.