Hybrid collective intelligence in a human–AI society
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Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
At the system level, the total and wide range of emerging AI applications will have a groundbreaking technological and societal impact.
“But just as our modern world has evolved rapidly through a diversity of specific (limited) technological innovations, at the system level the total and wide range of emerging AI applications will also have a groundbreaking technological and societal impact (Peeters et al., 2020).”
From Human- versus Artificial Intelligence (2021) · cites this paper as Peeters et al., 2020
Insight into human factors issues such as anthropomorphism is crucial to optimize the utility, performance and safety of human-AI systems.
“Insight into these human factors issues is crucial to optimize the utility, performance and safety of human-AI systems (Peeters et al., 2020).”
From Human- versus Artificial Intelligence (2021) · cites this paper as Peeters et al., 2020
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References 98 · Cited by 229
- Authors
- Peeters, M. M. M., van Diggelen, J., van den Bosch, K., Bronkhorst, A., Neerincx, M. A., Schraagen, J. M., & Raaijmakers, S.
- Affiliations
- Netherlands Organisation for Applied Scientific Research (NL)
- Leiden University (NL)
- Venue
- AI & SOCIETY
- Published
- 2020-06-25
- Volume
- 36
- Issue
- 1
- Pages
- 217-238
- ISSN
- 0951-5666 (ISSN-L)
- 1435-5655
- OpenAlex
- W3037067444
- Cited by
- 229
- References
- 98
- Citations by year
- 2026: 38 · 2025: 50 · 2024: 65 · 2023: 30 · 2022: 25 · 2021: 21
- FWCI
- 25.88
- Type
- journal article
- Language
- en
- Open access
- green
- resolver.tudelft.nl
- Licence
- Locations
- AI & Society (publishedVersion)
- TNO Repository (submittedVersion)
- University of Twente Research Information (submittedVersion)
- Repository hosted by TU Delft Library (TU Delft) (submittedVersion)
- Research Repository (Delft University of Technology) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- Topics
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Social Sciences › Sociology and Political Science › Innovation, Sustainability, Human-Machine Systems
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Keywords
- AI risks, superintelligence, collective intelligence, research design framework
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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