The Influence of Gender Bias on Task-Specific Smart Appliances

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Users interact with technology in a stereotypical manner, expecting from it, what one expects from a person. We report 3 studies. In study 1 we find that dual-gender has the highest perceived suitability. In study 2 we find that users hold stereotypic assumptions for machine tasks. In study 3, we investigate the implications of switching gender in objective and subjective machine tasks. Ingraining stereotypical traits and attributes into technological systems may exacerbate stereotype segregation, but might lead to more trusted systems and objects because they provide users with what they are used to.
OriginalsprogEngelsk
Udgivelsesår2020
StatusUdgivet - 2020
BegivenhedRobo-Philosophy 2020: Culturally Sustainable Social Robotics - Aarhus University, Aarhus, Danmark
Varighed: 18 aug. 202020 aug. 2020
https://conferences.au.dk/robo-philosophy/aarhus2020/

Konference

KonferenceRobo-Philosophy 2020
LokationAarhus University
LandDanmark
ByAarhus
Periode18/08/202020/08/2020
Internetadresse

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