Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Nathan Tenhundfeld"'
Publikováno v:
Proceedings of the Human Factors and Ergonomics Society Annual Meeting. 66:241-245
With the deployment of AI-enabled autonomous systems in various fields of application, it is critical to understand the factors affecting the acceptance and in turn the adoption of such technology. While previous research has established that individ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::14f6e5f527c0d5b918f0327edcfb9c66
https://doi.org/10.1177/1071181322661154
https://doi.org/10.1177/1071181322661154
Publikováno v:
Journal of Cognitive Engineering and Decision Making. 16:101-118
Trust in automation is a foundational principle in Human Factors Engineering. An understanding of trust can help predict and alter much of human-machine interaction (HMI). However, despite the utility of assessing trust in automation in applied setti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dcc91fd2c4e7cc9baa780ee88c6fc93a
https://doi.org/10.1177/15553434221096261
https://doi.org/10.1177/15553434221096261
Autor:
Daniel Pham, Vineetha Menon, Nathan Tenhundfeld, Kristin Weger, Bryan Mesmer, Sampson Gholston, Thomas Davis
Publikováno v:
2022 IEEE 3rd International Conference on Human-Machine Systems (ICHMS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1c483bc7a17c62a9529e28726a15e32f
https://doi.org/10.1109/ichms56717.2022.9980662
https://doi.org/10.1109/ichms56717.2022.9980662
Autor:
Joseph Schwalb, Vineetha Menon, Nathan Tenhundfeld, Kristin Weger, Bryan Mesmer, Sampson Gholston
Publikováno v:
2022 IEEE 3rd International Conference on Human-Machine Systems (ICHMS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::53922baf2c9699023d4cadf4985e252b
https://doi.org/10.1109/ichms56717.2022.9980625
https://doi.org/10.1109/ichms56717.2022.9980625
Autor:
Andrew Atchley, Emily O'Hear, Hannah M. Barr, Kristin Weger, Bryan Mesmer, Sampson Gholston, Nathan Tenhundfeld
Trust in automation is an important construct to consider when attempting to predict proper use of automated systems. Automation is being used in increasingly diverse and more complex ways. Previous findings report that trust can be generalized acros
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5b5c72ada9241c8caf6570bd9a6b834b
https://doi.org/10.31219/osf.io/h7e3s
https://doi.org/10.31219/osf.io/h7e3s
Autor:
Ewart de Visser, Elizabeth Phillips, Nathan Tenhundfeld, Bianca Donadio, Christian Barentine, Boyoung Kim, Anna Madison, Anthony Ries, Chad Tossell
In two studies, we evaluated the trust and usefulness of automated compared to manual parking using an experimental paradigm and by surveying owners of vehicles with automated parking features. In Study 1, we compared participants' ability to manuall
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4a317a772d63c7254c5939350c90d621
https://doi.org/10.31219/osf.io/5jmyf
https://doi.org/10.31219/osf.io/5jmyf
Autor:
Andrew Atchley, Hannah M. Barr, Emily O'Hear, Kristin Weger, Bryan Mesmer, Sampson Gholston, Nathan Tenhundfeld
Trust is perhaps one of the most important constructs when trying to understand human interactions with systems. As such, there has been a considerable amount of research done on factors such as individual differences in trust, environmental factors
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::43feba9f2084782b30dda740e3832a8b
https://doi.org/10.31219/osf.io/r4gpd
https://doi.org/10.31219/osf.io/r4gpd
Trust is a foundational principle in Human Factors Engineering. While an understanding of trust can help predict and alter much of human-machine interactions (HMI), assessment of trust is underutilized in the field. We make the argument that trust as
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c5e7d9faed896c27f422cae039be1e53
https://doi.org/10.31219/osf.io/j47df
https://doi.org/10.31219/osf.io/j47df