Impacts of the Use of Machine Learning on Work Design

Kevin Crowston, Francesco Bolici

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

Abstract

The increased pervasiveness of technological advancements in automation makes it urgent to address the question of how work is changing in response. Focusing on applications of machine learning (ML) to automate information tasks, we draw on a simple framework for identifying the impacts of an automated system on a task that suggests 3 patterns for the use of ML-decision support, blended decision making and complete automation. In this paper, we extend this framework by considering how automation of one task might have implications for interdependent tasks and how automation applies to coordination mechanisms.

Original languageEnglish (US)
Title of host publicationHAI 2020 - Proceedings of the 8th International Conference on Human-Agent Interaction
PublisherAssociation for Computing Machinery, Inc
Pages163-170
Number of pages8
ISBN (Electronic)9781450380546
DOIs
StatePublished - Nov 10 2020
Externally publishedYes
Event8th International Conference on Human-Agent Interaction, HAI 2020 - Virtual, Online, Australia
Duration: Nov 10 2020Nov 13 2020

Publication series

NameHAI 2020 - Proceedings of the 8th International Conference on Human-Agent Interaction

Conference

Conference8th International Conference on Human-Agent Interaction, HAI 2020
CountryAustralia
CityVirtual, Online
Period11/10/2011/13/20

Keywords

  • artificial intelligence
  • automation
  • coordination
  • machine learning
  • work design

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Artificial Intelligence
  • Software

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