A Crossroads for Hybrid Human-Machine Decision-Making

Ben Wilson*, Kayal Lakshmanan, Alan Dix, Alma Rahat, Matt Roach

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, we highlight what is missing in the approach to architecting and developing AI models that would mean performance is translated into effective hybrid systems. We conclude people, place and purpose should drive new architectures that support rich interaction through tractable representations that will underpin success. We call for the data-driven ML community to embrace the consideration of tractable representations in the architecture of algorithms and place a responsibility on HCI researchers to unwrap and expose the significant factors in the design space that are critical for successful hybrid decision-making in the real world.

Original languageEnglish
Title of host publicationMachine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2023, Revised Selected Papers
EditorsRosa Meo, Fabrizio Silvestri
PublisherSpringer Science and Business Media Deutschland GmbH
Pages316-322
Number of pages7
ISBN (Print)9783031746260
DOIs
Publication statusPublished - 1 Jan 2025
EventJoint European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2023 - Turin, Italy
Duration: 18 Sept 202322 Sept 2023

Publication series

NameCommunications in Computer and Information Science
Volume2134 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

ConferenceJoint European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2023
Country/TerritoryItaly
CityTurin
Period18/09/2322/09/23

Keywords

  • AI
  • collaboration
  • combination
  • cooperation
  • decision making
  • human-machine
  • hybrid
  • interaction
  • mixed-initiative
  • symbiosis

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