CoChat
Sign Up
Cited by 82Ethics and Social Impacts of AIAutonomous Vehicle Technology and SafetyPhilosophical Ethics and Theory

Ethical Decision Making in Autonomous Vehicles: The AV Ethics Project

Open access
Evans, Katherine, de Moura, Nelson, Chauvier, Stéphane, Chatila, Raja, Dogan, Ebru·2020·Science and Engineering Ethics
DOI 10.1007/s11948-020-00272-8PMC PMC7755871
Open this paper in CoChat — free accountOpen PDF

Abstract

The ethics of autonomous vehicles (AV) has received a great amount of attention in recent years, specifically in regard to their decisional policies in accident situations in which human harm is a likely consequence. Starting from the assumption that human harm is unavoidable, many authors have developed differing accounts of what morality requires in these situations. In this article, a strategy for AV decision-making is proposed, the Ethical Valence Theory, which paints AV decision-making as a type of claim mitigation: different road users hold different moral claims on the vehicle’s behavior, and the vehicle must mitigate these claims as it makes decisions about its environment. Using the context of autonomous vehicles, the harm produced by an action and the uncertainties connected to it are quantified and accounted for through deliberation, resulting in an ethical implementation coherent with reality. The goal of this approach is not to define how moral theory requires vehicles to behave, but rather to provide a computational approach that is flexible enough to accommodate a number of ‘moral positions’ concerning what morality demands and what road users may expect, offering an evaluation tool for the social acceptability of an autonomous vehicle’s ethical decision making.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1007/s11948-020-00272-8

Cites

77 of 77 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

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?

  • Frequent, small-scale interactions cumulatively determine both public safety and social trust in autonomy.

    “These frequent, small-scale interactions cumulatively determine both public safety and social trust in autonomy [9].”

    From Ethics-Aware Safe Reinforcement Learning for Rare-Event Risk Control in Interactive Urban Driving (2026) · cites this paper as [9]

    The Risk Mitigation section links AV behavior toward users with safety, trust, and public acceptability. It does not say that frequent, small-scale interactions cumulatively determine those outcomes; its discussion focuses chiefly on risk and ethical decisions in collision dilemmas. Page numbers are unavailable in our copy. (LLM, conf=0.82)

    Experimental — accuracy not yet measured

  • Computer scientists are still a long way from developing AGI or AC, which would seem to be required for genuine moral agency.

    “While computer scientists are making some progress on developing AI systems that have quasi-moral agency, that is, AI systems that can make decisions based on moral norms [71, 196, 203], they are still a long way from developing AGI or AC (see definitions of these terms in Sect. 2), which would seem to be required for genuine moral agency.”

    From The ethics of using artificial intelligence in scientific research: new guidance needed for a new tool (2025) · cites this paper as [71]

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 3

  1. Initiative, I. G. (2016). Ethically aligned design. In IEEE Standards v1
  2. Parfit D Reasons and persons 1984 Oxford OUP
  3. Parfit, D. (2011). On what matters/vol. 2. On what matters.

Cited by

Sorted by citations

Related

Authors
Evans, K., de Moura, N., Chauvier, S., Chatila, R., & Dogan, E.
Affiliations
Sorbonne Université (FR)
Corresponding author
Evans, Katherine
ORCID
Venue
Science and Engineering Ethics
Publisher
Springer Science and Business Media LLC
Published
2020-10-13
Volume
26
Issue
6
Pages
3285-3312
ISSN
  • 1353-3452 (ISSN-L)
  • 1471-5546
DOI
10.1007/s11948-020-00272-8
PMC
PMC7755871
OpenAlex
W3092105031
Cited by
82
References
77
Citations by year
2026: 10 · 2025: 22 · 2024: 16 · 2023: 19 · 2022: 8 · 2021: 7
FWCI
11.69
Type
journal article
Language
en
Open access
Licence
Locations
  • Science and Engineering Ethics (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • HAL (submittedVersion, other-oa)
Funders
Agence Nationale de la Recherche (ANR-16-C22-008, ANR-11-LABX-65)
Topics
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
  • Physical Sciences › Engineering › Automotive Engineering › Autonomous Vehicle Technology and Safety
  • Social Sciences › Arts and Humanities › Philosophy › Philosophical Ethics and Theory
Keywords
autonomous vehicles, ethical decision-making, moral claims, accident scenarios, deliberation, uncertainty, computational ethics, social acceptance, moral stance
MeSH terms
Decision Making, Ethics, Humans, Morals, Ethical Theory, Uncertainty

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