Evidence map›Paper›PMID 41442052›Full record

ArticleScience and engineering ethics2025

A Case for End-Constrained Ethical Artificial Intelligence.

Tyler Cook

Abstract read
In one paragraph

Article in Science and engineering ethics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Tyler CookGeorgia Institute of Technology, Jimmy and Rosalynn Carter School of Public Policy, Atlanta, GA, USA. tyler.cook@gatech.edu.ORCID http://orcid.org/0000-0003-3553-7222

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

One natural motivation for designing artificial intelligence (AI) with ethical capacities is to mitigate the risk that powerful AI systems will harm us. Against this idea, some authors have argued we do not need ethical AI in order to prevent harm to humans. We simply need safe AI. In this paper, I consider an argument of this type and raise objections to it. In particular, I argue that the goal of implementing safety features in AI systems is a much more complicated task than such authors have acknowledged, and moreover I maintain that merely safe AI could be ethically problematic in numerous ways. Then, I show that a certain kind of ethical AI, which I call end-autonomous ethical AI, would be especially dangerous since their autonomous capacities would make possible numerous risks. Finally, I motivate the case for a specific category of ethical AI, namely, end-constrained ethical AI. I describe these systems as possessing whatever capacities would be necessary for satisfying ethical aims beyond safety while lacking end-autonomy. In short, the goal of this paper is to establish that end-constrained ethical AI occupy a desirable middle ground between merely safe AI and end-autonomous ethical AI because they allow us to secure more ethical goods than just safety, and they are also not as risky as end-autonomous ethical AI.

Indexed as

Artificial IntelligenceSafetyHumansIntelligent SystemsPersonal AutonomyAI ethicsAI safetyAutonomyMachine ethics

Identifiers

PMID41442052
PMCPMC12808250

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.