OBJECTIVE: We provide an empirical demonstration of the importance of attending to human user individual differences in examinations of trust and automation use. BACKGROUND: Past research has generally supported the notions that machine reliability predicts trust in automation, and trust in turn predicts automation use. However, links between user personality and perceptions of the machine with trust in automation have not been empirically established. METHOD: On our X-ray screening task, 255 students rated trust and made automation use decisions while visually searching for weapons in X-ray images of luggage. RESULTS: We demonstrate that individual differences affect perceptions of machine characteristics when actual machine characteristics are constant, that perceptions account for 52% of trust variance above the effects of actual characteristics, and that perceptions mediate the effects of actual characteristics on trust. Importantly, we also demonstrate that when administered at different times, the same six trust items reflect two types of trust (dispositional trust and history-based trust) and that these two trust constructs are differentially related to other variables. Interactions were found among user characteristics, machine characteristics, and automation use. CONCLUSION: Our results suggest that increased specificity in the conceptualization and measurement of trust is required, future researchers should assess user perceptions of machine characteristics in addition to actual machine characteristics, and incorporation of user extraversion and propensity to trust machines can increase prediction of automation use decisions. APPLICATION: Potential applications include the design of flexible automation training programs tailored to individuals who differ in systematic ways.
OBJECTIVE: We provide an empirical demonstration of the importance of attending to human user individual differences in examinations of trust and automation use. BACKGROUND: Past research has generally supported the notions that machine reliability predicts trust in automation, and trust in turn predicts automation use. However, links between user personality and perceptions of the machine with trust in automation have not been empirically established. METHOD: On our X-ray screening task, 255 students rated trust and made automation use decisions while visually searching for weapons in X-ray images of luggage. RESULTS: We demonstrate that individual differences affect perceptions of machine characteristics when actual machine characteristics are constant, that perceptions account for 52% of trust variance above the effects of actual characteristics, and that perceptions mediate the effects of actual characteristics on trust. Importantly, we also demonstrate that when administered at different times, the same six trust items reflect two types of trust (dispositional trust and history-based trust) and that these two trust constructs are differentially related to other variables. Interactions were found among user characteristics, machine characteristics, and automation use. CONCLUSION: Our results suggest that increased specificity in the conceptualization and measurement of trust is required, future researchers should assess user perceptions of machine characteristics in addition to actual machine characteristics, and incorporation of user extraversion and propensity to trust machines can increase prediction of automation use decisions. APPLICATION: Potential applications include the design of flexible automation training programs tailored to individuals who differ in systematic ways.
Authors: Ewart J de Visser; Samuel S Monfort; Kimberly Goodyear; Li Lu; Martin O'Hara; Mary R Lee; Raja Parasuraman; Frank Krueger Journal: Hum Factors Date: 2017-02 Impact factor: 2.888
Authors: Thomas A Arcury; Sara A Quandt; Joanne C Sandberg; David P Miller; Celine Latulipe; Xiaoyan Leng; Jenifer W Talton; Kathryn P Melius; Alden Smith; Alain G Bertoni Journal: JMIR Med Inform Date: 2017-11-14