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AlphaGo's historic win over a Go professional highlighted the crucial role of human-machine interfacing. This interaction, often overlooked, was key to the demonstration of artificial intelligence (AI).

Keywords:
AlphaGo showalgorithmic dramaembodied playinterfacing practicesmachine intelligenceobject agencyscenic intelligibilitytechnology demonstration

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Area of Science:

  • Science and Technology Studies (STS)
  • Artificial Intelligence (AI)
  • Human-Computer Interaction (HCI)

Background:

  • Professional Go playing was long considered a benchmark for AI capabilities.
  • AlphaGo's victory over a top human professional in 2016 marked a significant AI milestone.
  • The event generated substantial media attention but limited critical analysis within STS.

Purpose of the Study:

  • To analyze the 'AlphaGo show' as a technology demonstration, focusing on its social and technical aspects.
  • To examine the significance of AlphaGo's 'move 37' and expert commentary.
  • To explore the concept of 'scenic intelligibility' in the context of human-machine interfacing.

Main Methods:

  • Reflexive video analysis of the AlphaGo exhibition match.
  • Examination of expert commentary and media reporting.
  • Analysis of embodied interaction and 'human/machine interfacing'.

Main Results:

  • AlphaGo's 'move 37' and its presentation were contingent on intricate human-machine interfacing.
  • Media portrayals of 'superhuman intelligence' relied on and obscured this interfacing work.
  • 'Object agency' and 'algorithmic drama' emerged from skillful embodied play as a key interfacing practice.

Conclusions:

  • The AlphaGo match demonstrated that AI achievements are deeply intertwined with human-machine collaboration.
  • Understanding the 'AlphaGo show' requires scrutinizing the embodied practices of interfacing.
  • The study informs how AI's perceived agency and dramatic narratives are constructed through such practices.