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Experiential AI

Authors :
Hemment, Drew
Aylett, Ruth
Belle, Vaishak
Murray-Rust, Dave
Luger, Ewa
Hillston, Jane
Rovatsos, Michael
Broz, Frank
Publication Year :
2019

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 intelligence to greater transparency and collaboration 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 complex 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 and configured or how humans are conditioned by their participation in algorithmic processes.<br />Comment: To appear in AI Matters 5(1): 25-31 (2019)

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.1908.02619
Document Type :
Working Paper