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Monday, July 1, 2013

Do you trust the machine?

Several factors such as automation reliability, automation consistency, and operator workload have been shown to affect automation use. However, there are very few empirical studies examining the role of user personality on trust in automation.

This article describes the importance of examining individual differences when studying trust and automation use. The key-takeaways from the article are:
  • Individuals with higher propensity to trust machines are likely to expect the automation to perform correctly. Therefore, when the machine makes errors,      these individuals are likely to notice these errors and remember these errors more strongly. This experience then influences subsequent perceptions of trust. Conversely, if the machine has high reliability, these individuals will trust the system to a dangerously high level.
  • The authors differentiate between two types of trust: dispositional trust and history-based trust.  Dispositional trust is based on an individual’s personality characteristics. For example, extraverts are more likely to trust automation (just as extraverts are more willing to trust other people). History-based trust, on the other hand, is created as a result of interactions with the machine.
  • Don’t view trust as a static concept. Trust evolves over time from dispositional trust to history-based trust. This means that researchers should measure trust at multiple times to get a clear picture of how trust evolves from the beginning, based on automation characteristics and performance.
  • Operator training should take into consideration individual characteristics. For example, training should be customized based on the level of extraversion, wherein extraverts are cautioned about the dangers of exhibiting overreliance on automation.

Photo credit: Salvagnini, via Wikimedia Commons.





2 comments:

  1. Nice,

    Thanks for your greatful informations, working in, ASIAN AFFAIRS MAGAZINE.

    Try to post best informations like this always

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  2. Well done, I have also found this "social" bond in my work with automobiles which can (obviously) influence a user's perspective on the reliability, usability and robustness of the system...Thank you!

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