The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Human-Centered Artificial Intelligence: Three Fresh Ideas
Open accessAbstract
Human-Centered AI (HCAI) is a promising direction for designing AI systems that support human self-efficacy, promote creativity, clarify responsibility, and facilitate social participation. These human aspirations also encourage consideration of privacy, security, environmental protection, social justice, and human rights. This commentary reverses the current emphasis on algorithms and AI methods, by putting humans at the center of systems design thinking, in effect, a second Copernican Revolution. It offers three ideas: (1) a two-dimensional HCAI framework, which shows how it is possible to have both high levels of human control AND high levels of automation, (2) a shift from emulating humans to empowering people with a plea to shift language, imagery, and metaphors away from portrayals of intelligent autonomous teammates towards descriptions of powerful tool-like appliances and tele-operated devices, and (3) a three-level governance structure that describes how software engineering teams can develop more reliable systems, how managers can emphasize a safety culture across an organization, and how industry-wide certification can promote trustworthy HCAI systems. These ideas will be challenged by some, refined by others, extended to accommodate new technologies, and validated with quantitative and qualitative research. They offer a reframe -- a chance to restart design discussions for products and services -- which could bring greater benefits to individuals, families, communities, businesses, and society.
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Cites
Machines and Mindlessness: Social Responses to Computers
Nass, C., & Moon, Y. (2000) · Journal of Social Issues · doi:10.1111/0022-4537.00153 · Cited by 4,022
Fjeld, J., Achten, N., Hilligoss, H., Nagy, A., & Srikumar, M. (2020) · SSRN Electronic Journal · doi:10.2139/ssrn.3518482 · Cited by 998 · cited 1×
“The expansion of interest and application of AI research has triggered widespread public and government scrutiny of the ethical and responsible principles to guide designers, managers, and policy makers (Fjeld et al., 2020; IEEE, 2019).”
Ten challenges for making automation a ‘team player’ in joint human-agent activity
Klein, G., Woods, D. D., Bradshaw, J. M., Hoffman, R. R., & Feltovich, P. J. (2004) · IEEE Intelligent Systems · doi:10.1109/mis.2004.74 · Cited by 590
Principles of robotics: regulating robots in the real world
Boden, M., Bryson, J., Caldwell, D., Dautenhahn, K., Edwards, L., Kember, S., Newman, P., Parry, V., Pegman, G., Rodden, T., et al. (2017) · Connection Science · doi:10.1080/09540091.2016.1271400 · Cited by 193
Cited by
Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., Ahuja, M., et al. (2023) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2023.102642 · Cited by 4,584
Generative AI and ChatGPT: applications, challenges, and AI-human collaboration
Fui-Hoon Nah, F., Zheng, R., Cai, J., Siau, K., & Chen, L. (2023) · Journal of Information Technology Case and Application Research · doi:10.1080/15228053.2023.2233814 · Cited by 1,363
Responsible Artificial Intelligence Governance: A Review and Research Framework
Papagiannidis, E., Mikalef, P., & Conboy, K. (2025) · The Journal of Strategic Information Systems · doi:10.1016/j.jsis.2024.101885 · Cited by 565
The promise and challenges of generative AI in education
Giannakos, M., Azevedo, R., Brusilovsky, P., Cukurova, M., Dimitriadis, Y., Hernandez-Leo, D., Järvelä, S., Mavrikis, M., & Rienties, B. (2025) · Behaviour & Information Technology · doi:10.1080/0144929x.2024.2394886 · Cited by 543
Six Human-Centered Artificial Intelligence Grand Challenges
Ozmen Garibay, O., Winslow, B., Andolina, S., Antona, M., Bodenschatz, A., Coursaris, C., Falco, G., Fiore, S. M., Garibay, I., Grieman, K., et al. (2023) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2022.2153320 · Cited by 501
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Metadata
- Authors
- University of Maryland, C. P., & Shneiderman, B.
- Venue
- AIS Transactions on Human-Computer Interaction
- Publisher
- Association for Information Systems
- Published
- 2020
- Pages
- 109-124
- ISSN
- 1944-3900 (ISSN-L)
- OpenAlex
- W3089968098
- Cited by
- 421
- References
- 4
- FWCI
- 49.35
- Type
- journal article
- Language
- en
- Open access
- diamond
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.