'Humans and AI based communication and reasoning in complex adversarial domains

It is generally agreed that trust is best conceptualized as a multidimensional psychological attitude involving beliefs and expectations about the trustee’s trustworthiness derived from experience and interactions with the trustee in situations involving uncertainty and risk. It has to do with the notion of a willing exposure to risk and an agent willing to be vulnerable to “the other”. In this paper we explore ideas about credition, the interdisciplinary process of believing, and how communicating agents get to believe each other, how issues of uncertainty enter into the issue of believability, and how belief and consciousness also interplay. The paper also addresses epistemological issues related to reasoning and analytical approaches that integrate multidimensional perspectives (labeled “epistemic pluralism”) for complex adversarial domains such as those involved with modern and future intelligence analysis.

Authors

Publication Details

Journal
AHFE international
Published
2025-01-01
DOI
https://doi.org/10.54941/ahfe1006047
Primary Topic
Adversarial Robustness in Machine Learning
Type
article
Field-Weighted Citation Impact
0.00
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article

'Humans and AI based communication and reasoning in complex adversarial domains

James Llinas
AHFE international
Adversarial Robustness in Machine Learning
article

'Humans and AI based communication and reasoning in complex adversarial domains

James Llinas
article en

Abstract

It is generally agreed that trust is best conceptualized as a multidimensional psychological attitude involving beliefs and expectations about the trustee’s trustworthiness derived from experience and interactions with the trustee in situations involving uncertainty and risk. It has to do with the notion of a willing exposure to risk and an agent willing to be vulnerable to “the other”. In this paper we explore ideas about credition, the interdisciplinary process of believing, and how communicating agents get to believe each other, how issues of uncertainty enter into the issue of believability, and how belief and consciousness also interplay. The paper also addresses epistemological issues related to reasoning and analytical approaches that integrate multidimensional perspectives (labeled “epistemic pluralism”) for complex adversarial domains such as those involved with modern and future intelligence analysis.

AHFE internationalVol. 163
Openalex Percentile: Top 93%
Adversarial Robustness in Machine Learning
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