Cited by 998Ethics and Social Impacts of AIDigitalization, Law, and RegulationLaw, AI, and Intellectual Property

Principled Artificial Intelligence: Mapping Consensus in Ethical and Rights-Based Approaches to Principles for AI

Open access
Fjeld, Jessica, Achten, Nele, Hilligoss, Hannah, Nagy, Adam, Srikumar, Madhulika·2020·SSRN Electronic Journal

Integrity signals

Registry

Crossref · 10.2139/ssrn.3518482

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

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?

Cites

Flagged first, then by citations

17 of the 19 references couldn’t be matched to a known paper.

Cited by

Sorted by citations

Authors
Fjeld, J., Achten, N., Hilligoss, H., Nagy, A., & Srikumar, M.
Affiliations
Harvard University (US)
Corresponding author
Fjeld, Jessica
Venue
SSRN Electronic Journal
Publisher
Elsevier BV
Published
2020
ISSN
1556-5068 (ISSN-L)
OpenAlex
W2999331643
Cited by
998
References
19
Citations by year
2026: 114 · 2025: 231 · 2024: 186 · 2023: 180 · 2022: 143 · 2021: 102 · 2020: 41 · 2019: 1
Type
posted content
Language
en
Open access
Locations
  • SSRN Electronic Journal (publishedVersion)
  • Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
Topics
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
  • Social Sciences › Law › Digitalization, Law, and Regulation
  • Physical Sciences › Computer Science › Artificial Intelligence › Law, AI, and Intellectual Property
Keywords
AI principles, AI ethics, human rights-based approach, AI governance, privacy, accountability, safety and security, transparency and explainability, human control of technology, professional responsibility

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