Evidence map›Paper›PMID 41768290›Full record

ArticleAI and ethics2026

Autonomous artificial intelligence, scientific research, and human values.

David B Resnik, Mohammad Hosseini, Rico Hauswald

Abstract read
In one paragraph

Article in AI and ethics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

3 authors.

David B ResnikNational Institute of Environmental Health Sciences, Durham, USA.
Mohammad HosseiniNorthwestern University Feinberg School of Medicine, Chicago, IL, USA.
Rico HauswaldTU Dresden, Dresden, Germany.

Funding

NUCATS CTSA UM1 at Northwestern UniversityUM1TR005121 · NCATS · NORTHWESTERN UNIVERSITY AT CHICAGO · PI Sara Becker, Richard D'Aquila · 2024 to 2026
$23.4M
Ethical, social, and legal issues in environmental health researchZIAES102646 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI RESNIK, DAVID · 2009 to 2025
$1.8M
Intramural NIH HHS Z99 ES999999Intramural NIH HHS ZIA ES102646NCATS NIH HHS UM1 TR005121
6 · The paper itself

Abstract

During the initial stage of AI's incorporation into scientific research, AI systems have functioned predominantly as tools under direct human supervision and control. However, AI incorporation into scientific research is now entering a stage in which AI Agents perform research tasks with partial autonomy while remaining under human supervision and control. In the not-too-distant future, a third stage may arise when autonomous AI systems conduct their own research and generate knowledge without human supervision or control. While the second and third stages of AI-augmented research may offer substantial benefits for science and society, they also create novel ethical issues, including (1) Conducting immoral research that may harm humans and other forms of life; (2) Increasing rate of biased, erroneous and deceptive research; (3) Confidentiality challenges; (4) Overreliance on AI; (5) Diffusion of responsibility and accountability; (6) Deskilling; (7) Job losses; (8) AI-generated research beyond human comprehension; and (9) Erosion of trust. We suggest specific solutions to minimize the negative consequences of these issues and offer proposals for ensuring that incorporation of AI into scientific research supports human values.

Indexed as

AI agentsArtificial intelligenceAutonomyHuman valuesResearchScientific norms

Identifiers

PMID41768290
PMCPMC12948163

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.