Evidence map›Paper›PMID 41356668›Full record

ArticleFrontiers in artificial intelligence2025

Robots in the moral loop: a field study of AI advisors in ethical military decision-making.

Chad C Tossell, Christopher Kuennen, Ali Momen, Gregory Funke, Michael Tolston, Ewart J De Visser

Abstract read
In one paragraph

Article in Frontiers in artificial intelligence, 2025. 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. Review
  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

6 authors.

Chad C TossellDepartment of Human Factors, Safety, and Social Sciences, Embry-Riddle Aeronautical University, Daytona Beach, FL, United States.
Christopher KuennenDepartment of Philosophy, University of Colorado, Boulder, CO, United States.
Ali MomenAir Force Research Laboratory, 711th Human Performance Wing, Wright-Patterson Air Force Base, Dayton, OH, United States.
Gregory FunkeAir Force Research Laboratory, 711th Human Performance Wing, Wright-Patterson Air Force Base, Dayton, OH, United States.
Michael TolstonAir Force Research Laboratory, 711th Human Performance Wing, Wright-Patterson Air Force Base, Dayton, OH, United States.
Ewart J De VisserUnited States Air Force Academy, Colorado Springs, CO, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Humans now routinely work alongside AI in environments where the ethical consequences of decisions are profound, yet there remains limited understanding of how long-term collaboration with a robotic teammate shapes individuals' moral judgment. Prior studies have demonstrated that people can be influenced by a robot's moral recommendations, but such investigations have largely focused on single dilemmas or brief encounters conducted in laboratory settings. To address this gap, we conducted a three-month teaming program with 62 U.S. military cadets who interacted extensively with a Socially Intelligent and Ethical Mission Assistant (SIEMA) embodied either as a humanoid robot or as a human advisor in a field setting. After this sustained collaboration, cadets completed a graded moral dilemma that required balancing the lives of soldiers against those of civilians, during which they received a written recommendation from their SIEMA promoting a utilitarian option. Each participant recorded an initial judgment, then a second judgment after receiving SIEMA's advice, and finally a third judgment following an opposing recommendation that emphasized civilian protection. Approximately half of the cadets shifted toward the utilitarian option after advice, regardless of whether the source was robotic or human. When subsequently presented with the recommendation to prioritize civilian protection, most of these cadets shifted again, often returning to their original stance. Qualitative analyses of open-ended explanations revealed that cadets justified their choices by invoking outcome-based reasoning, duties of protection, trust in their teammate, and personal values. Our findings demonstrate that robotic advisors can influence nuanced moral decisions and that such influence contributes to shaping future judgments. Accordingly, moral-AI design should present trade-offs transparently, surface competing values concurrently, and rely on human reflection rather than assuming isolated AI prompts will durably reset moral priorities.

Indexed as

AIdecision-makingethicsmixed-methodsrobot

Identifiers

PMID41356668
PMCPMC12675400

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.