Towards Artificial Social Intelligence: Inherent Features, Individual Differences, Mental Models, and Theory of Mind

Bendell, Rhyse; Williams, Jessica; Fiore, Stephen M.; Jentsch, Florian

doi:10.1007/978-3-030-80285-1_3

Cited by 4 publications

(2 citation statements)

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“…Accounting for variance allows researchers to better understand differences in task performance that are more likely due to video game experience. Further, by understanding participant characteristics, these kinds of measures can be used to create profiles of players (Bendell et al, 2021a), which can be used both in gamified research tasks to understand performance, as well as to provide a priori information to artificial intelligence that would aid the development of an Artificial Theory of Mind, allowing the AI to better interpret and predict human behaviors (Bendell et al, 2021b; Williams et al, 2022). Overall, the VGEM can help guide researcher decisions whenever gamified experimental tasks are used.…”

Section: Discussionmentioning

confidence: 99%

Factor Analysis of a Generalized Video Game Experience Measure

Williams,

Bendell,

Fiore

et al. 2023

Proceedings of the Human Factors and Ergonomics Society Annual

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Video gaming experience has been found to impact behavior and performance on experimental tasks, can influence cognitive processes, and may even transfer to proficiency in novel tasks. There is a growing need for an empirically validated generalizable tool that can capture differences in participants gaming experience due to the growing representation of regular video gamers, and the proliferation of gamified, simulated task environments. The analyses reported here examine the factor loadings of a general Video Game Experience Measure (VGEM) designed to tap facets of gaming experience that can distinguish non-gamers from gamers and is also sensitive to varying levels of proficiency. Results from exploratory and confirmatory factor analyses find support for a five-factor model capturing: Game-skill Confidence, Gaming Lifespan, Gaming Intensity, Gaming Frequency, and Gamer Self-efficacy. These findings are discussed in the context of how the VGEM can support research using gamified task environments requiring the study of cognition and collaboration.

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Section: Discussionmentioning

confidence: 99%

Factor Analysis of a Generalized Video Game Experience Measure

Williams,

Bendell,

Fiore

et al. 2023

Proceedings of the Human Factors and Ergonomics Society Annual

Self Cite

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“…ASI consists of social cognitive elements that facilitate group collaboration and broader interpersonal processes. We focus on one of the more foundational features of social cognitive processing in the context of ASI, that of machine theory of mind (e.g., Bendell, Williams, Fiore, & Jentsch, 2021b; Williams, Fiore, & Jentsch, 2022). This is the capacity of an artificial intelligence to attribute mental states and infer the intentions of human members of a team.…”

Section: Introductionmentioning

confidence: 99%

Transdisciplinary Team Science: Transcending Disciplines to Understand Artificial Social Intelligence in Human-Agent Teaming

Fiore,

Johnson,

Robertson

et al. 2023

Proceedings of the Human Factors and Ergonomics Society Annual

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We provide a transdisciplinary viewpoint on creating artificial social intelligence for human-agent teaming. We discuss theoretical, methodological, and technological insights, drawn from different disciplines, to more fully illuminate how cross-disciplinary research can inform research design and development. We unite ideas spanning human factors, cognitive and computer science, and organizational behavior. Grounding our ideas in real world challenges for human-AI teaming, and via a series of questions designed to facilitate synthesis across disciplines, we illustrate how transdisciplinary team science more effectively asks and answers complex questions on human-agent teaming. Our objective is to contribute to research and development in the field of human-AI and human-robot teaming by emphasizing a more human-centered perspective on AI.

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