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This short paper delineates an understudied theoretical development of information. Whitehead, a pre-cybernetic philosopher and mathematician, provided a conceptual schematic for hylomorphic information: information that does not dissect the mind from the body. His information suggests connections in ontology, phenomenology, epistemology, and ethics. Contemporary Whiteheadian literature theorizes connections between philosophy, science, and morality through hylomorphic approaches to organization, science and technology studies, and critical data research, suggesting extensions to cybernetic theory and artificial intelligence. This short paper provides a first interpretation of these relations and forwards directions information studies might find more immediate applications.

Extant research lacks comprehensive identification of distinct AI adopter groups necessary for targeted educational interventions to enhance AI literacy and mitigate the AI divide. Grounded in Social Cognitive Theory (SCT), this study categorizes AI adopters based on social cognitive characteristics, they are, fear of missing out (FoMO), AI attitudes, and self-efficacy. Further, we profile these groups by AI literacy and educational backgrounds. A survey of 620 participants using K-means clustering revealed three adopter types: (1) observers, characterized by lower education, AI literacy, FoMO, AI attitudes, and self-efficacy; (2) seekers, with intermediate educational levels, high FoMO, and strong AI literacy; and (3) professionals, highly educated individuals with low FoMO but high AI literacy. Findings demonstrate how educational disparities shape AI literacy through social cognitive factors. Theoretically, this research introduces an innovative SCT-based classification of AI adopters, offering practical insights for policymakers and educators to design tailored interventions addressing the AI divide.

As the use of generative artificial intelligence (GenAI) systems grows in daily life, there is a need to assess how users interact with these tools in socially and ethically informed ways. This study introduces a multidimensional scale to measure socio-ethical AI engagement competencies, reflecting users’ ability to evaluate, interpret, and ethically use AI-generated content, and to critically consider its broader social impacts and power dynamics. Drawing from interdisciplinary frameworks in AI literacy, self-efficacy, and AI ethics, we constructed an initial item pool related to social and ethical engagement.

Responses from 200 participants to an 18-item instrument were analyzed using Exploratory Factor Analysis (EFA) to capture four dimensions: critical appraisal, critical comprehension, ethical behavior, and anthropomorphic interaction. The scale demonstrated strong internal consistency. This work contributes to a theoretically grounded and empirically supported instrument for assessing critical and ethical engagement with GenAI, which has implications for AI literacy, responsible technology use, and curriculum design.

This paper proposes and validates a model that describes the influences of cognitive appraisals, including threat appraisal, coping appraisal and message appraisal of information integrity on phishing susceptibility, and explore threat detection as a mediating mechanism underlying their effects. Threat detection is crucial particularly as AI makes phishing more difficult to identify. An online scenario-based survey involving an attack scenario using a phishing email with 313 participants was conducted to validate the proposed model. Findings reveal that threat detection and perceived severity are associated with reduced phishing susceptibility, while perceived vulnerability and perceived information integrity increase it. Although self-efficacy predicts threat detection, it does not directly reduce responses to phishing messages. Additionally, threat detection mediates the effects of perceived severity and perceived information integrity. This paper contributes to phishing research by integrating information security behavior and message-related literature. It underscores the importance of user education, emphasizing online literacy and cautious engagement with unsolicited messages to counter phishing threats.