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Users and observers assess human and automation capabilities similarly. However, actors attribute negative outcomes to system flaws, while observers underestimate system capabilities, leading to biased responsibility assessments.

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Area of Science:

  • Human-computer interaction
  • Cognitive psychology
  • Automation and intelligent systems

Background:

  • Human responsibility for outcomes is unclear in advanced automation.
  • Actors and observers may have differing perceptions of responsibility.
  • Understanding these differences is crucial for effective human-automation collaboration.

Purpose of the Study:

  • To explore subjective assessments of human and automation capabilities.
  • To investigate causal responsibility for outcomes in human-automation interaction.
  • To compare perceptions between active users (actors) and passive observers.

Main Methods:

  • A laboratory experiment involving pairs of participants (actor and observer).
  • Actors performed a decision task with an automated system; observers watched.
  • Perceptions of responsibility were compared across roles and two different system capabilities.

Main Results:

  • Actors and observers similarly assessed system and human capabilities and comparative responsibility.
  • Actors attributed adverse outcomes more to system characteristics than personal limitations.
  • Observers underestimated system capabilities when assigning responsibility to actors.

Conclusions:

  • When automation exceeds human ability, users may feel less responsible, potentially leading to over-interference.
  • Outside observers may overestimate user contributions, assigning undue responsibility for negative outcomes.
  • Calibrating subjective assessments through performance data can reduce biases in both users and observers.