Exploring Machine Autonomy and Provenance Data in Coffee Consumption: A Field Study of Bitbarista

Ella Tallyn, Larissa Pschetz, Rory Gianni, Christopher Speed, Chris Elsden

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Technologies such as distributed ledgers and smart contracts are enabling the emergence of new autonomous systems, and providing enhanced systems to track the provenance of goods. A growing body of work in HCI is exploring the novel challenges of these systems, but there has been little attention paid to their impact on everyday activities. This paper presents a study carried out in 3 office environments for a 1-month period, which explored the impact of an autonomous coffee machine on the everyday activity of coffee consumption. The Bitbarista mediates coffee consumption through autonomous processes, presenting provenance data at the time of purchase while attempting to reduce intermediaries in the coffee trade. Through the report of interactions with and around the Bitbarista, we explore its implications for everyday life, and wider social structures and values. We conclude by offering recommendations for the design of community shared autonomous systems.
Original languageEnglish
Title of host publicationProceedings of the ACM on Human-Computer Interaction
PublisherACM
Number of pages25
Volume1
DOIs
Publication statusPublished - 5 Nov 2018

Keywords

  • Blockchain
  • Supply chain
  • Distributed ledger technologies
  • Machine autonomy
  • Provenance data

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