Abstract
Hybrid Intelligence (HI) is an emerging paradigm in which artificial intelligence (AI) augments human intelligence. The current literature lacks systematic models that guide the design and evaluation of HI systems. Further, discussions around HI primarily focus on technology, neglecting the holistic human-AI ensemble. In this paper, we take the initial steps toward the development of a quality model for characterizing and evaluating HI systems from a human-AI teams perspective. We conducted a study investigating the adequacy of properties commonly associated with effective human teams to describe HI. Our study, featuring the insights of 50 HI researchers, shows that various human team properties, including boundedness, interdependence, competency, purposefulness, initiative, normativity, and effectiveness, are important for HI systems. Our study also reveals limitations in applying certain human team properties, such as coaching, rewards, and recognition, to HI systems due to the inherent human-AI asymmetry.
Original language | English |
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Title of host publication | AAMAS '24: Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems |
Publisher | Association for Computing Machinery |
Pages | 434-443 |
Number of pages | 10 |
Volume | 2024-May |
DOIs | |
Publication status | Published - May 2024 |
Publication series
Name | Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS |
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ISSN (Print) | 1548-8403 |
Bibliographical note
Publisher Copyright:© 2024 International Foundation for Autonomous Agents and Multiagent Systems.
Funding
This research was partially supported by Hybrid Intelligence Center, a 10-year programme funded by the Dutch Ministry of Education, Culture and Science through the Netherlands Organisation for Scientific Research, https://www.hybrid-intelligence-centre.nl/, under Grant No. (024.004.022), by the BOLD Cities initiative, and by the Health Holland epartners4all project.
Funders | Funder number |
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Ministerie van onderwijs, cultuur en wetenschap | |
Hybrid Intelligence Center | |
Health Holland | |
Nederlandse Organisatie voor Wetenschappelijk Onderzoek | 024.004.022 |
Keywords
- Human-agent teamwork
- Hybrid Intelligence
- Quality model
- So-ciotechnical systems
- Team Diagnostic Survey