Explanations in AI as Claims of Tacit Knowledge
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The limited information end-users require-such as whether the system uses some intuitively relevant factor and how-may be hard to come by.
“even the limited information they do require-for instance, whether the system makes use of some factor that is intuitively relevant (and if so how)-may be hard to come by (for discussion see Lam, 2022).”
From Hidden Risks: Artificial Intelligence and Hermeneutic Harm (2025) · cites this paper as Lam, 2022
Cites
Solving the Black Box Problem: A Normative Framework for Explainable Artificial Intelligence
Zednik, C. (2021) · Philosophy & Technology · doi:10.1007/s13347-019-00382-7 · Cited by 419 · see citing works
Zoom In: An Introduction to Circuits
Olah, C., Cammarata, N., Schubert, L., Goh, G., Petrov, M., & Carter, S. (2020) · Distill · doi:10.23915/distill.00024.001 · Cited by 288 · see citing works
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Hidden Risks: Artificial Intelligence and Hermeneutic Harm
Rebera, A. P., Lauwaert, L., & Oimann, A.-K. (2025) · Minds and Machines · doi:10.1007/s11023-025-09733-0 · Cited by 6 · see citing works
“…2019 ); and while end-users do not necessarily need comprehensive explanations of decisions, even the limited information they do require—for instance, whether the system makes use of some factor that is intuitively relevant (and if so how)—may be hard to come by (for discussion see Lam, 2022 ).”
- Authors
- Lam, N.
- Corresponding author
- Lam, Nardi
- ORCID
- Lam, Nardi
- Venue
- Minds and Machines
- Published
- 2022-01-11
- Volume
- 32
- Issue
- 1
- Pages
- 135-158
- ISSN
- 0924-6495 (ISSN-L)
- 1572-8641
- OpenAlex
- W4205842577
- Cited by
- 16
- References
- 2
- Citations by year
- 2026: 4 · 2025: 4 · 2024: 3 · 2023: 3 · 2022: 2
- FWCI
- 0.99
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Minds and Machines (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Explainable Artificial Intelligence (XAI)
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Philosophy and History of Science
- Keywords
- explainable AI, tacit knowledge, Chomskyan linguistics, rule-based explanations, trust in AI, lime, interpretability
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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