Evidence map›Paper›PMID 37213385›Full record

ArticleFrontiers in psychology2023

The use of artificial intelligence in a military context: development of the attitudes toward AI in defense (AAID) scale.

Lee Hadlington, Jens Binder, Sarah Gardner, Maria Karanika-Murray, Sarah Knight

Abstract read
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Article in Frontiers in psychology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Lee HadlingtonDepartment of Psychology, Nottingham Trent University, Nottingham, United Kingdom.
Jens BinderDepartment of Psychology, Nottingham Trent University, Nottingham, United Kingdom.
Sarah GardnerDepartment of Psychology, Nottingham Trent University, Nottingham, United Kingdom.
Maria Karanika-MurraySchool of Business, University of Leicester, Leicester, United Kingdom.
Sarah KnightExploration Division, Defense Science and Technology Laboratory, Salisbury, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The use of artificial intelligence (AI) for national defense is a matter of high societal significance and ongoing public discourse, but very little is known about public acceptance of AI in defense contexts. Currently, there is no reliable and valid measure of attitudes towards AI in defense, and more general attitudinal measures on AI use are unlikely to capture relevant perceptions and opinions. A measure was therefore developed for the assessment of Attitudes towards AI in Defense (AAID), and this work presents the initial validation of this scale. Methods: A total of 1,590 participants (aged 19-75, Results: Items reduction and exploratory factor analysis resulted in a final scale consisting of 15 items. A final two factor solution explained 42.52% of the variance (Factor 1 = 22.35%, Factor 2 = 20.17%). Factor 1 was termed "Positive outcomes" and reflected the potential and anticipated consequences of implementing AI in defense. Factor 2 was termed "Negative Outcomes" and reflected the potential negative outcomes for AI in defense. The scale also exhibited acceptable internal reliability and current validity. Discussion: The newly developed AAID presents a new measurement tool which has the capacity to assess current attitudes towards AI in defense. Such work is essential if further developments in AI in defense are to continue with the support of the public. However, the work also notes that there are some key concerns and barriers that could block further developments in the area, with further work needed to explore how such anxieties are driven by narratives related to the topic.

Indexed as

artificial intelligence (AI)attitudesdefensepsychometric scale development and validationscale development

Identifiers

PMID37213385
PMCPMC10196355

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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.