Six challenges for human-AI Co-learning
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Demanding explainability, observability, or transparency may cause AI systems to constrain their potential benefit for human society to what can be understood by humans.
“In addition, according to Werkhoven et al. (2018) demanding explainability observability, or transparency (Belkom, 2019; van den Bosch et al., 2019) may cause artificial intelligent systems to constrain their potential benefit for human society, to what can be understood by humans.”
From Human- versus Artificial Intelligence (2021) · cites this paper as van den Bosch et al., 2019
Human-aware AI partners that operate like human collaborators must be able to sense, understand, and react to complex human behavioral qualities such as attention, motivation, emotion, creativity, planning, or argumentation.
“When human-aware AI partners operate like “human collaborators” they must be able to sense, understand, and react to a wide range of complex human behavioral qualities, like attention, motivation, emotion, creativity, planning, or argumentation, (e.g. Krämer et al., 2012; van den Bosch and Bronkhorst, 2018; van den Bosch et al., 2019).”
From Human- versus Artificial Intelligence (2021) · cites this paper as van den Bosch et al., 2019
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Human- versus Artificial Intelligence
Korteling, J. E. (., van de Boer-Visschedijk, G. C., Blankendaal, R. A. M., Boonekamp, R. C., & Eikelboom, A. R. (2021) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2021.622364 · Cited by 619 · see citing works
“sense, understand, and react to a wide range of complex human behavioral qualities, like attention, motivation, emotion, creativity, planning, or argumentation, (e.g. Krämer et al., 2012; van den Bosch and Bronkhorst, 2018; van den Bosch et al., 2019).”
BackgroundSelf-citation
- Authors
- van den Bosch, K., Schoonderwoerd, T., Blankendaal, R., & Neerincx, M.
- Affiliations
- Netherlands Organisation for Applied Scientific Research (NL)
- Venue
- Lecture notes in computer science
- Publisher
- Springer International Publishing
- Published
- 2019
- Pages
- 572-589
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2961759237
- Cited by
- 50
- References
- 60
- Citations by year
- 2026: 9 · 2025: 9 · 2024: 17 · 2023: 7 · 2022: 3 · 2021: 5
- FWCI
- 0.77
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- Locations
- Lecture notes in computer science (publishedVersion)
- TNO Repository (submittedVersion)
- Repository hosted by TU Delft Library (TU Delft) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Social Sciences › Psychology › Social Psychology › Human-Automation Interaction and Safety
- Keywords
- hybrid teams, human-machine collaboration, artificial agents, mental models, self-awareness, theory of mind, adaptive collaboration, personalized learning
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