When Do People Want AI to Make Decisions?
Abstract
AI systems are now or will soon be sophisticated enough to make consequential decisions. Although this technology has flourished, we also need public appraisals of AI systems playing these more important roles. This article reports surveys of preferences for and against AI systems making decisions in various domains as well as experiments that intervene on these preferences. We find that these preferences are contingent on subjects' previous exposure to computer systems making these kinds of decisions, and some interventions designed to mimic previous exposure successfully encourage subjects to be more hospitable to computer systems making these weighty decisions.
Integrity signals
Registry
Cites
Statistics
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?
Preferences towards humans versus algorithmic systems depend on people's previous experience with the described situation.
“Kramer et al. [55] showed that preferences towards humans vs. algorithmic systems depend on people's previous experience with the described situation.”
From Disentangling Fairness Perceptions in Algorithmic Decision-Making: the Effects of Explanations, Human Oversight, and Contestability (2023) · cites this paper as [55]
Cites
The self-importance of moral identity
Aquino, K., & Reed, A. (2002) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.83.6.1423 · Cited by 3,522 · see citing works
Graham, J., Nosek, B. A., Haidt, J., Iyer, R., Koleva, S., & Ditto, P. H. (2011) · Journal of Personality and Social Psychology · doi:10.1037/a0021847 · Cited by 2,666 · see citing works
Haidt, J., McCauley, C., & Rozin, P. (1994) · Personality and Individual Differences · doi:10.1016/0191-8869(94)90212-7 · Cited by 1,632 · see citing works
The social dilemma of autonomous vehicles
Bonnefon, J.-F., Shariff, A., & Rahwan, I. (2016) · Science · doi:10.1126/science.aaf2654 · Cited by 1,527 · see citing works
The Problem of Abortion and the Doctrine of the Double Effect
Foot, P. (2002) · Oxford University Press eBooks · doi:10.1093/0199252866.003.0002 · Cited by 1,374 · see citing works
Mere Exposure: A Gateway to the Subliminal
Zajonc, R. B. (2001) · Current Directions in Psychological Science · doi:10.1111/1467-8721.00154 · Cited by 1,299 · see citing works
Mere Exposure: A Gateway to the Subliminal
Zajonc, R. B. (2006) · Cambridge University Press eBooks · doi:10.1017/cbo9780511618031.026 · Cited by 952 · see citing works
Sensation seeking: A new conceptualization and a new scale
Arnett, J. J. (1994) · Personality and Individual Differences · doi:10.1016/0191-8869(94)90165-1 · Cited by 818 · see citing works
Moral machines: teaching robots right from wrong
(2009) · Choice Reviews Online · doi:10.5860/choice.46-4493 · Cited by 793 · see citing works
Wallach, W., & Allen, C. (2009) · Oxford University Press · doi:10.1093/acprof:oso/9780195374049.001.0001 · Cited by 711 · see citing works
16. The Problem of Abortion and the Doctrine of the Double Effect
Foot, P. (1994) · Fordham University Press eBooks · doi:10.1515/9780823295968-019 · Cited by 454 · see citing works
The 12 Item Social and Economic Conservatism Scale (SECS)
Everett, J. A. C. (2013) · PLoS ONE · doi:10.1371/journal.pone.0082131 · Cited by 403 · see citing works
Measuring an Individual's Tendency to Take Risks: The Risk Propensity Scale1
Meertens, R. M., & Lion, R. (2008) · Journal of Applied Social Psychology · doi:10.1111/j.1559-1816.2008.00357.x · Cited by 351 · see citing works
Aging, Empathy, and Prosociality
Beadle, J. N., Sheehan, A. H., Dahlben, B., & Gutchess, A. H. (2013) · The Journals of Gerontology Series B · doi:10.1093/geronb/gbt091 · Cited by 172 · see citing works
A Voting-Based System for Ethical Decision Making
Noothigattu, R., Gaikwad, S. S., Awad, E., Dsouza, S., Rahwan, I., Ravikumar, P., & Procaccia, A. D. (2018) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v32i1.11512 · Cited by 146 · see citing works
Coutlee, C. G., Politzer, C. S., Hoyle, R., & Huettel, S. A. (2014) · Archives of Scientific Psychology · doi:10.1037/arc0000005 · Cited by 110 · see citing works
FutureMatch: Combining Human Value Judgments and Machine Learning to Match in Dynamic Environments
Dickerson, J. P., & Sandholm, T. (2015) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v29i1.9239 · Cited by 63 · see citing works
THink: Inferring Cognitive Status from Subtle Behaviors
Davis, R., Libon, D. J., Au, R., Pitman, D., & Penney, D. L. (2015) · AI Magazine · doi:10.1609/aimag.v36i3.2602 · Cited by 40 · see citing works
Adapting a Kidney Exchange Algorithm to Align with Human Values
Freedman, R., Borg, J. S., Sinnott-Armstrong, W. P., Dickerson, J. P., & Conitzer, V. (2018) · Proceedings of the AAAI/ACM Conference on AI Ethics and Society · doi:10.1145/3278721.3278727 · Cited by 35 · see citing works
Self-citation
Flagged first, then by citations
3 of the 22 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
People are averse to machines making moral decisions.
Bigman, Y. E., & Gray, K. (2018) · Cognition · doi:10.1016/j.cognition.2018.08.003 · Cited by 738 · see citing works
The most human bot: Female gendering increases humanness perceptions of bots and acceptance of AI
Borau, S., Otterbring, T., Laporte, S., & Wamba, S. F. (2021) · Psychology and Marketing · doi:10.1002/mar.21480 · Cited by 281 · see citing works
Trust in artificial intelligence for medical diagnoses
(2020) · Progress in Brain Research · doi:10.1016/bs.pbr.2020.06.006 · Cited by 116 · see citing works
Estep, C., Griffith, E. E., & MacKenzie, N. L. (2023) · Review of Accounting Studies · doi:10.1007/s11142-023-09771-y · Cited by 112 · see citing works
Knowing About Knowing: An Illusion of Human Competence Can Hinder Appropriate Reliance on AI Systems
He, G., Kuiper, L., & Gadiraju, U. (2023) · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3581025 · Cited by 107 · see citing works
“Others revealed similar findings in contexts where tasks are perceived as being more objective [7], machines share rationale with humans [75] or with prior exposure to similar systems [42].”
BackgroundYurrita, M., Draws, T., Balayn, A., Murray-Rust, D., Tintarev, N., & Bozzon, A. (2023) · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3581161 · Cited by 73 · see citing works
“[55] showed that preferences towards humans vs.”
BackgroundArtificial intelligence and moral dilemmas: Perception of ethical decision-making in AI
Zhang, Z., Chen, Z., & Xu, L. (2022) · Journal of Experimental Social Psychology · doi:10.1016/j.jesp.2022.104327 · Cited by 78 · see citing works
Good Robots, Bad Robots: Morally Valenced Behavior Effects on Perceived Mind, Morality, and Trust
Banks, J. (2020) · International Journal of Social Robotics · doi:10.1007/s12369-020-00692-3 · Cited by 60 · see citing works
Semantics Derived Automatically from Language Corpora Contain Human-like Moral Choices
Jentzsch, S. F., Schramowski, P., Rothkopf, C. A., & Kersting, K. (2019) · Proceedings of the AAAI/ACM Conference on AI Ethics and Society · doi:10.1145/3306618.3314267 · Cited by 58 · see citing works
Awad, E., Levine, S., Anderson, M., Anderson, S., Conitzer, V., Crockett, M. J., Everett, J. A. C., Evgeniou, T., Alison Gopnik, C., Jamison, J., et al. (2022) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2022.02.009 · Cited by 58 · see citing works
Self-citationThe Moral Psychology of AI and the Ethical Opt-Out Problem
Bonnefon, J., Shariff, A., & Rahwan, I. (2020) · doi:10.1093/oso/9780190905033.003.0004 · Cited by 48 · see citing works
Machine Thinking, Fast and Slow
Bonnefon, J., & Rahwan, I. (2020) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2020.09.007 · Cited by 45 · see citing works
Schaap, G., Bosse, T., & Vettehen, P. H. (2023) · AI & Society · doi:10.1007/s00146-023-01649-6 · Cited by 37 · see citing works
Erlei, A., Das, R., Meub, L., Anand, A., & Gadiraju, U. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3517734 · Cited by 35 · see citing works
Schramowski, P., Turan, C., Jentzsch, S. F., Rothkopf, C. A., & Kersting, K. (2020) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2020.00036 · Cited by 33 · see citing works
What’s the Appeal? Perceptions of Review Processes for Algorithmic Decisions
Lyons, H., Wijenayake, S., Miller, T., & Velloso, E. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3517606 · Cited by 27 · see citing works
Should AI allocate livers for transplant? Public attitudes and ethical considerations
Drezga‐Kleiminger, M., Demaree‐Cotton, J., Koplin, J. J., Savulescu, J., & Wilkinson, D. J. C. (2023) · BMC Medical Ethics · doi:10.1186/s12910-023-00983-0 · Cited by 26 · see citing works
Acceptance of Medical Treatment Regimens Provided by AI vs. Human
Wu, J., Xu, L., Yu, F., & Peng, K. (2021) · Applied Sciences · doi:10.3390/app12010110 · Cited by 27 · see citing works
Lyons, H., Miller, T., & Velloso, E. (2023) · ACM Conference on Fairness, Accountability, and Transparency (FAccT) · doi:10.1145/3593013.3594041 · Cited by 21 · see citing works
Modeling of moral decisions with deep learning
Wiedeman, C., Wang, G., & Krüger, U. (2020) · Visual Computing for Industry Biomedicine and Art · doi:10.1186/s42492-020-00063-9 · Cited by 19 · see citing works
Ethical Implementation of Artificial Intelligence to Select Embryos in In Vitro Fertilization
Afnan, M. A. M., Rudin, C. D., Conitzer, V., Savulescu, J., Mishra, A., Liu, Y., & Afnan, M. (2021) · Proceedings of the AAAI/ACM Conference on AI Ethics and Society · doi:10.1145/3461702.3462589 · Cited by 19 · see citing works
Self-citationBERT has a Moral Compass: Improvements of ethical and moral values of machinesPreprint
Schramowski, P., Turan, C., Jentzsch, S. F., Rothkopf, C. A., & Kersting, K. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1912.05238 · Cited by 24 · see citing works
Schoeffer, J., Machowski, Y., & Kühl, N. (2022) · Hawaii International Conference on System Sciences (HICSS) · doi:10.24251/hicss.2022.134 · Cited by 16 · see citing works
Information that matters: Exploring information needs of people affected by algorithmic decisions
Schmude, T., Koesten, L. M., Möller, T. B., & Tschiatschek, S. (2024) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2024.103380 · Cited by 13 · see citing works
Artificial Intelligence and Human Rights
(2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.001.0001 · Cited by 10 · see citing works
Aljuneidi, S., Heuten, W., Tepe, M., & Boll, S. (2023) · International Conference on Information Technology for Social Good (GoodIT) · doi:10.1145/3582515.3609518 · Cited by 9 · see citing works
Ethics of AI in Transplant Matching: Is It Better or Just More of the Same?
Sherman, M., & Greenbaum, D. S. (2019) · The American Journal of Bioethics · doi:10.1080/15265161.2019.1665734 · Cited by 9 · see citing works
Yurrita, M., Verma, H., Balayn, A., Gadiraju, U., Pont, S. C., & Bozzon, A. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713145 · Cited by 8 · see citing works
Content Analysis of Judges' Sentiments Toward Artificial Intelligence Risk Assessment Tools
Fine, A., Le, S., & Miller, M. K. (2023) · Criminology Criminal Justice Law & Society · doi:10.54555/ccjls.8169.84869 · Cited by 7 · see citing works
Artificial Intelligence and Fair Trial Rights
Molbæk-Steensig, H., & Quemy, A. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0018 · Cited by 6 · see citing works
Artificial Intelligence and Freedom of Expression
Gregorio, G. D., & Dunn, P. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0005 · Cited by 6 · see citing works
Artificial Intelligence and Human Rights at Work
Atkinson, J., & Collins, P. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0025 · Cited by 6 · see citing works
A three-dimensional motivation model of algorithm aversion
ZAHNG, Y., Xu, L., Yu, F., Xiaojun, D. I. N. G., Wu, J., Zhao, L., 邬, 家., & 赵, 靓. (2022) · Advances in Psychological Science · doi:10.3724/sp.j.1042.2022.01093 · Cited by 5 · see citing works
AI Life Cycle and Human Rights
Martina, Š., Luboš, K., & Drchal, J. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0002 · Cited by 4 · see citing works
Schaap, G., Bosse, T., & Vettehen, P. H. (2025) · Cyberpsychology Journal of Psychosocial Research on Cyberspace · doi:10.5817/cp2025-5-8 · Cited by 4 · see citing works
Artificial Intelligence and Robotics Addressing COVID-19 Pandemic’s Challenges
David, W., & King‐Okoye, M. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-70740-8_18 · Cited by 4 · see citing works
Quintavalla, A., & Temperman, J. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0001 · Cited by 4 · see citing works
Content Analysis of Judges’ Sentiments Toward Artificial Intelligence Risk Assessment Tools
Fine, A., Le, S., & Miller, M. K. (2024) · Актуальные проблемы экономики и права · doi:10.21202/2782-2923.2024.1.246-263 · Cited by 4 · see citing works
Artificial Intelligence and the Right to a Healthy Environment
Quintavalla, A. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0028 · Cited by 4 · see citing works
Artificial Intelligence Human Rights Impact Assessment
Ortalda, A., & Hert, P. D. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0035 · Cited by 3 · see citing works
Artificial Intelligence and Data Analytics
Laukyte, M. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0019 · Cited by 3 · see citing works
Artificial Intelligence and the Right to Privacy
Zornetta, A., & Cofone, I. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0008 · Cited by 3 · see citing works
Quintavalla, A., & Temperman, J. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0037 · Cited by 3 · see citing works
Artificial Intelligence and Women’s Rights
Gagliardi, M. P. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0016 · Cited by 3 · see citing works
Schmude, T., Koesten, L. M., Möller, T. B., & Tschiatschek, S. (2026) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2026.2650562 · Cited by 4 · see citing works
Lyons, H., Miller, T., & Velloso, E. (2025) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3757468 · Cited by 2 · see citing works
On the (Non-)Reliance on Algorithms - A Decision-Theoretic Account
Sinclair‐Désgagné, B. (2021) · Journal of Mathematical Psychology · doi:10.1016/j.jmp.2024.102844 · Cited by 2 · see citing works
Real-Life Experimentation with Artificial Intelligence
Elizaveta, G., & Evert, S. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0036 · Cited by 3 · see citing works
Artificial Intelligence and the Right to Health
Echeverría, E. S. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0026 · Cited by 1 · see citing works
Privacy, Political Participation, and Dissent
Katrak, M., & Ishita, C. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0010 · Cited by 1 · see citing works
The Rights to Privacy and Data Protection and Facial Recognition Technology in the Global North
González, N. M. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0009 · Cited by 1 · see citing works
The process motivation model of algorithmic decision-making approach and avoidance
Caifeng, X., Wu, J., Liying, X. U., Feng, Y., ZHAND, Y., & Yingying, X. I. E. (2022) · Advances in Psychological Science · doi:10.3724/sp.j.1042.2023.00060 · Cited by 1 · see citing works
Artificial Intelligence and Religious Freedom
Temperman, J. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0004 · Cited by 1 · see citing works
Artificial Intelligence and the Right to Liberty and Security
Golunova, V. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0003 · Cited by 1 · see citing works
Artificial Intelligence and Human Rights
Prifti, K., Quintavalla, A., & Temperman, J. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0029 · Cited by 1 · see citing works
Artificial Intelligence and Consumer Protection Rights
Li, S., Schütte, B., & Majewski, L. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0027 · Cited by 1 · see citing works
Smart Cities, Artificial Intelligence, and Public Law
Ranchordás, S. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0033 · Cited by 1 · see citing works
Artificial Intelligence and Gender-Based Discrimination
Lütz, F. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0014 · Cited by 1 · see citing works
Moral Dilemmas with an Option to Delegateevidence from an Online Experiment in ChinaPreprint
Gao, Y., Blayac, T., & Willinger, M. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4611281
Artificial Intelligence and the Right to Housing
Compton, C., & Hohmann, J. M. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0024
Robot Rights/Human Responsibility
Gunkel, D. J. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0031
Artificial Intelligence Technologies and the Right to Seek and Enjoy Asylum
Raimy, R. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0021
Artificial Intelligence and the Right to Food
Omotubora, A. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0023
Human Rights, Legal Personality, and Artificial Intelligence
Heine, K. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0030 · Cited by 1 · see citing works
Artificial Intelligence Screening and the Right to Asylum
Dhruv, S. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0022
Artificial Intelligence and Racial Discrimination
Koen, L., & Kgomotso, M. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0013
Putting Private Sector Responsibility in the Mix
Ebert, I. L., & Lisa, H. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0034
Artificial Intelligence, the Public Space, and the Right to Be Ignored
Pin, A. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0012
The Limits of AI Decision-Making
Gamper, F. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0032
Artificial Intelligence and the Right to an Effective Remedy
de Heer, S. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0020
Artificial Intelligence and Freedom of Assembly
Margaret, W. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0006
The Production of and Control over Data in the AI-Era
van der Sloot, B. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0011
Artificial Intelligence and the Right to Property
Tomada, L., & Xenidis, R. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0007
Artificial Intelligence and Disability Rights
Zarra, A., Favalli, S., & Matilde, C. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0017
Artificial Intelligence and LGBTQ+ Rights
Shahid, M. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0015
Quintavalla, A., & Temperman, J. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.002.0009
Quintavalla, A., & Temperman, J. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.002.0008
Quintavalla, A., & Temperman, J. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.002.0007
Quintavalla, A., & Temperman, J. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.002.0006
Quintavalla, A., & Temperman, J. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.002.0010
Quintavalla, A., & Temperman, J. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.002.0003
Delegating moral dilemmas in autonomous vehicles evidence from an online experiment in China
Gao, Y., Blayac, T., & Willinger, M. (2025) · Transport Policy · doi:10.1016/j.tranpol.2025.04.017
- Authors
- Kramer, M. F., Schaich Borg, J., Conitzer, V., & Sinnott-Armstrong, W.
- Affiliations
- University of Arizona (US)
- Duke University, Durham, NC, USA
- Duke University (US)
- Venue
- Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society
- Publisher
- ACM
- Published
- 2018-12-27
- Pages
- 204-209
- ISSN
- 3065-8365 (ISSN-L)
- OpenAlex
- W2909365641
- Semantic Scholar
- ff8620e82598095f4c729feaa1add6f6bdbdc355
- Cited by
- 83
- References
- 22
- Citations by year
- 2026: 1 · 2025: 4 · 2024: 2 · 2023: 53 · 2022: 7 · 2021: 5 · 2020: 7 · 2019: 3 · 2018: 1
- FWCI
- 7.16
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Proceedings of the AAAI/ACM Conference on AI Ethics and Society (publishedVersion)
- Funders
- Future of Life Institute
- Topics
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Social Sciences › Psychology › Social Psychology › Human-Automation Interaction and Safety
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Keywords
- AI decision-making, public attitudes toward AI, intervention effects, trust in AI, human-AI interaction
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.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review