Not All Information Is Equal: Effects of Disclosing Different Types of Likelihood Information on Trust, Compliance and Reliance, and Task Performance in Human-Automation Teaming
| Autor: | Kevin Y. Huang, Na Du, X. Jessie Yang |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Computer science
business.industry Base rate fallacy Reproducibility of Results Human Factors and Ergonomics Trust Bayesian inference Automation Human–robot interaction Compliance (psychology) Task (project management) Behavioral Neuroscience Human–computer interaction Task Performance and Analysis Humans business Man-Machine Systems Applied Psychology |
| Zdroj: | Human Factors: The Journal of the Human Factors and Ergonomics Society. 62:987-1001 |
| ISSN: | 1547-8181 0018-7208 |
| Popis: | Objective The study examines the effects of disclosing different types of likelihood information on human operators’ trust in automation, their compliance and reliance behaviors, and the human-automation team performance. Background To facilitate appropriate trust in and dependence on automation, explicitly conveying the likelihood of automation success has been proposed as one solution. Empirical studies have been conducted to investigate the potential benefits of disclosing likelihood information in the form of automation reliability, (un)certainty, and confidence. Yet, results from these studies are rather mixed. Method We conducted a human-in-the-loop experiment with 60 participants using a simulated surveillance task. Each participant performed a compensatory tracking task and a threat detection task with the help of an imperfect automated threat detector. Three types of likelihood information were presented: overall likelihood information, predictive values, and hit and correct rejection rates. Participants’ trust in automation, compliance and reliance behaviors, and task performance were measured. Results Human operators informed of the predictive values or the overall likelihood value, rather than the hit and correct rejection rates, relied on the decision aid more appropriately and obtained higher task scores. Conclusion Not all likelihood information is equal in aiding human-automation team performance. Directly presenting the hit and correct rejection rates of an automated decision aid should be avoided. Application The findings can be applied to the design of automated decision aids. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|