Reverse engineering the human: artificial intelligence and acting theory

Soto-Morettini, Donna

Abstract

In two separate papers, Artificial Intelligence (AI)/Robotics researcher Guy Hoffman takes as a starting point that actors have been in the business of reverse engineering human behaviour for centuries. In this paper, I follow the similar trajectories of AI and acting theory (AT), looking at three primary questions, in the hope of framing a response to Hoffman's papers: (1) How are the problems of training a human to simulate a fictional human both similar to and different from training a machine to simulate a human? (2) How are the larger questions of AI design and architecture similar to the larger questions that still remain within the area of AT? (3) Is there anything in the work of AI design that might advance the work of acting theorists and practitioners? The paper explores the use of “swarm intelligence” in recent models of both AT and AI, and considers the issues of embodied cognition, and the kinds of intelligence that enhances or inhibits imaginative immersion for the actor, and concludes with a consideration of the ontological questions raised by the trend towards intersubjective, dynamic systems of generative thought in both AT and AI.

Citation

Soto-Morettini, D. (2017). Reverse engineering the human: artificial intelligence and acting theory. Connection Science, 29(1), 64-76. https://doi.org/10.1080/09540091.2016.1271398

• Journal Article Type: Article
• Acceptance Date: Nov 8, 2016
• Online Publication Date: Jan 13, 2017
• Publication Date: Jan 13, 2017
• Deposit Date: Jul 21, 2017
• Publicly Available Date: Jan 14, 2018
• Journal: Connection Science
• Print ISSN: 0954-0091
• Electronic ISSN: 1360-0494
• Publisher: Taylor & Francis
• Peer Reviewed: Peer Reviewed
• Volume: 29
• Issue: 1
• Pages: 64-76
• DOI: https://doi.org/10.1080/09540091.2016.1271398
• Keywords: Embodied cognition, artificial intelligence, acting theory, swarm intelligence, imaginative immersion,
• Public URL: http://researchrepository.napier.ac.uk/Output/949627
• Contract Date: Jul 21, 2017