Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Aakriti Kumar"'
Publikováno v:
npj Science of Learning, Vol 7, Iss 1, Pp 1-11 (2022)
Abstract Practice in real-world settings exhibits many idiosyncracies of scheduling and duration that can only be roughly approximated by laboratory research. Here we investigate 39,157 individuals’ performance on two cognitive games on the Lumosit
Externí odkaz:
https://doaj.org/article/a1af2932d0084744b2c5834bc6791f34
Publikováno v:
Computational Brain & Behavior. 5:491-508
AI assistance is readily available to humans in a variety of decision-making applications. In order to fully understand the efficacy of such joint decision-making, it is important to first understand the human’s reliance on AI. However, there is a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0f2b15424ae0fedeb6bf4f7b2c66e925
https://doi.org/10.1007/s42113-022-00157-y
https://doi.org/10.1007/s42113-022-00157-y
Individual difference exploration of cognitive domains is predicated on being able to ascertain how well performance on tasks covary. Yet, establishing correlations among common inhibition tasks such as Stroop or flanker tasks has proven quite diffic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::edecaf3b853832426ea3c29598f5415b
https://doi.org/10.31234/osf.io/fsqvu
https://doi.org/10.31234/osf.io/fsqvu
Publikováno v:
Companion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a6eb3fe673bfcccfb19d47a848343645
https://doi.org/10.1145/3568294.3580093
https://doi.org/10.1145/3568294.3580093
Developing an accurate model of another agent’s knowledge is central to communication and cooperation between agents. In this paper, we propose a hierarchical framework of knowledge assessment that explains how people construct mental models of the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f1e516c938b143c9b48b8becef8e1252
https://doi.org/10.31234/osf.io/jvkp5
https://doi.org/10.31234/osf.io/jvkp5
Autor:
Mark Steyvers, Aakriti Kumar
Artificial Intelligence (AI) has the potential to improve human decision-making by providing decision recommendations and problem-relevant information to assist the human decision-maker. However, a number of challenges remain in fully realizing the h
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d6fa3e977aadac0ed39a9fceb7158f5d
https://doi.org/10.31234/osf.io/gctv6
https://doi.org/10.31234/osf.io/gctv6
Humans use AI-assistance in a wide variety of high- and low-stakes decision-making tasks today. However, human reliance on the AI’s assistance is often sub-optimal — with people exhibiting under- or over-reliance on the AI. We present an empirica
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::86ee031f0374c9443184989d89315fd3
https://doi.org/10.3233/faia220201
https://doi.org/10.3233/faia220201
Publikováno v:
NPJ Science of Learning, 7:24. Nature Publishing Group
Practice in real-world settings exhibits many idiosyncracies of scheduling and duration that can only be roughly approximated by laboratory research. Here we investigate 39,157 individuals’ performance on two cognitive games on the Lumosity platfor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4439555367a1b4abdc9721d24c5f3b7b
https://pubmed.ncbi.nlm.nih.gov/36195645
https://pubmed.ncbi.nlm.nih.gov/36195645