The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Simplicity and probability in causal explanation
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Citations
Cites
Explaining the evidence: Tests of the Story Model for juror decision making.
Pennington, N., & Hastie, R. (1992) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.62.2.189 · Cited by 761
Simplicity: a unifying principle in cognitive science?
Chater, N., & Vitányi, P. (2003) · Trends in Cognitive Sciences · doi:10.1016/s1364-6613(02)00005-0 · Cited by 494
Cited by
Explanation in artificial intelligence: Insights from the social sciences
Miller, T. (2019) · Artificial Intelligence · doi:10.1016/j.artint.2018.07.007 · Cited by 5,302
Misinformation and Its Correction: Continued Influence and Successful Debiasing
Lewandowsky, S., Ecker, U. K. H., Seifert, C. M., Schwarz, N., & Cook, J. (2012) · Psychological Science in the Public Interest · doi:10.1177/1529100612451018 · Cited by 2,920
Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance
Bansal, G., Wu, T., Zhou, J., Fok, R., Nushi, B., Kamar, E., Ribeiro, M. T., & Weld, D. S. (2020) · arXiv · doi:10.48550/arxiv.2006.14779 · Cited by 754
Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance
Bansal, G., Wu, T., Zhou, J., Fok, R., Nushi, B., Kamar, E., Ribeiro, M. T., & Weld, D. (2021) · Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3411764.3445717 · Cited by 757
“d in the design of many AI explanation algorithms — might be a poor choice for complementary performance. Indeed, while it is known that human explainers and listeners often have different objectives [46], it seems quite problematic to develop AI systems that actively seek to minimize human oversight. A more ideal con…”
Langer, M., Oster, D., Speith, T., Hermanns, H., Kästner, L., Schmidt, E., Sesing, A., & Baum, K. (2021) · Artificial Intelligence · doi:10.1016/j.artint.2021.103473 · Cited by 652
Metadata
- Authors
- LOMBROZO, T.
- Venue
- Cognitive Psychology
- Publisher
- Elsevier BV
- Published
- 2007-11
- Volume
- 55
- Issue
- 3
- Pages
- 232-257
- ISSN
- 0010-0285 (ISSN-L)
- OpenAlex
- W2041029272
- Cited by
- 384
- References
- 2
- FWCI
- 7.65
- Type
- journal article
- Language
- en
- Open access
- closed
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Statistics and arithmetic are recomputed, not judged.
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
