Ironic efficiency in automation-aided signal detection

Megan Bartlett, Jason S. McCarley

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Decision makers often make poor use of the information provided by an automated signal detection aid; recent studies have found that participants assisted by an automated aid fell well short of best-possible sensitivity levels. The present study tested the generalisability of this finding over varying levels of aid reliability. Participants performed a binary signal detection task either unaided or with assistance from a decision aid that was 60%, 85%, or 96%-reliable. Assistance from a highly reliable aid (85% or 96%) improved discrimination performance, while assistance from a low-reliability aid (60%) did not. Because their ideal strategy is to place less weight on less reliable cues, however, the decision makers’ tendency to disuse the aid became more appropriate as the aid’s reliability declined. Automation-aided efficiency was thus near to optimal when the aid was close to chance but became highly inefficient, ironically, as the aid’s reliability increased. Practitioner Summary: Investigating operators’ automation-aided information integration strategies allows human factors practitioners to predict the level of performance the operator will attain. Ironically, in an aided signal detection task, performance when assisted by a highly reliable aid is far less efficient than that obtained when assisted by a far less reliable aid.

Original languageEnglish
Pages (from-to)103-112
Number of pages10
JournalErgonomics
Volume64
Issue number1
Early online date24 Aug 2020
DOIs
Publication statusPublished - 2021

Keywords

  • Human-automation interaction
  • decision making-strategies
  • efficiency
  • reliability
  • signal detection theory

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