Computer Learns Automation

Computer Learns Automation
3 artificial intelligence agents: 3ch HD video, 2ch sound, generative
2020

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Computer Learns Automation (Ride Share, Drone Strike and Robot Arm), 2020, exorcises the spectres of computational technology. Three artificial intelligence agents learn to accomplish tasks in real time throughout the duration of the exhibition: a car learns to navigate pick-up and drop-off zones, a drone observes and fires at targets from above, and a robot arm learns to move boxes in a factory.

The soundtrack also exhibits artificial intelligence, as another AI program again is trained to learn and compose video game music. The automation of these tasks is increasingly commonplace, from the movement and distribution of goods and people to the generation of entertainment and mediation of warfare. Computer Learns Automation thus raises questions concerning human creativity, the fate of labour and distribution of power in the twenty-first century. In visualising the frequently invisible and abstract movements of data, networks and processes of machine learning, Tan exhumes the menace that lives among us: ‘the movement of data is monstrous – an enormous, unseen spectre, dark and ominous’.

This work features three game environments in which artificial intelligence agents learn to accomplish a particular task through reinforcement learning. It shows the training of these agents in real-time over the course of a gallery exhibition.

Exhibited at Adelaide Biennial 2020, Art Gallery of South Australia

Video documentation showing the early part of training and then after agent has trained for several months.

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Screenshots

20200317 BIENNIAL Installation KT Adobe RGB 4000px Photo Saul Steed 0Z2Y3027

20200317 BIENNIAL Installation KT Adobe RGB 4000px Photo Saul Steed 0Z2Y5107

Installation view: 2020 Adelaide Biennial of Australian Art: Monster Theatres featuring Computer Learns Automation (Ride Share, Drone Strike and Robot Arm) by Kynan Tan, Art Gallery of South Australia, Adelaide; photo: Saul Steed.