The irresponsibility of not using AI in the military
Bibliographic Data
| ID | 21703353 |
|---|---|
| Authors | Herwin Meerveld (0000-0003-0064-6293, Netherlands Defence Academy), H W Meerveld, Roy Lindelauf (0000-0001-7688-3645, Netherlands Defence Academy, corresponding author), E O Postma (Tilburg University), M POSTMA, Marie Safar Postma (0000-0002-5919-209X, Tilburg University) |
| Year | 2023 |
| Volume | 25 |
| Issue | 1 |
| Publication date | 2023-03-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Ethics and Information Technology (JOURNAL) |
| Journal identifiers | ISSN: 1388-1957 • E-ISSN: 1572-8439 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s10676-023-09683-0 |
| OpenAlex | W4321239995 |
| Language | EN |
| Citations received | 6 |
| References cited | 28 |
The ongoing debate on the ethics of using artificial intelligence (AI) in military contexts has been negatively impacted by the predominant focus on the use of lethal autonomous weapon systems (LAWS) in war. However, AI technologies have a considerably broader scope and present opportunities for decision support optimization across the entire spectrum of the military decision-making process (MDMP). These opportunities cannot be ignored. Instead of mainly focusing on the risks of the use of AI in target engagement, the debate about responsible AI should (i) concern each step in the MDMP, and (ii) take ethical considerations and enhanced performance in military operations into account. A characterization of the debate on responsible AI in the military, considering both machine and human weaknesses and strengths, is provided in this paper. We present inroads into the improvement of the MDMP, and thus military operations, through the use of AI for decision support, taking each quadrant of this characterization into account
Engineering ethics · Management science · Military intelligence · Operations research · Political science · Sociology · Strengths and weaknesses · Adversarial Robustness in Machine Learning · Computer Science · Engineering · Ethics and Social Impacts of AI · Explainable Artificial Intelligence (XAI · Law · Psychology · Social Psychology · Artificial Intelligence
| Unique citing works | 6 |
|---|---|
| Citations per year | 2 |
| Citation span | 2023 - 2026 (4) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 5 |