The proliferation of Artificial Intelligence (AI) technologies, exemplified by Large Language Models (LLM), has ushered in a transformative era across various fields. As the AI revolution will impact societies in complex and uncertain ways, it is likely that persons tending towards belief of conspiracy theories also tend to form more negative and less positive attitudes towards AI. Such persons might believe that some evil force will use AI to destroy human mankind. Drawing on the Interplay of Modality, Person, Area, Country/Culture, and Transparency categories (IMPACT) framework, this study aims to investigate the interplay of locus of control (LOC), belief in conspiracy theories, and the perception of the importance and availability of eXplainable AI (XAI) on attitudes towards AI (measured via AI acceptance and fear). The study used an online survey with 281 participants from the UK and 281 from the Arab world. Statistical analysis revealed that in the UK but not in the Arab sample, female participants reported higher fear of AI and lower acceptance of AI compared to males. The regression results consistently confirmed the role of internal LOC, perceived XAI importance, and perceived availability of XAI in fostering AI acceptance, as well as the role of belief in conspiracy theories, external LOC, and perceiving availability of XAI as being low in increasing fear of AI. The perceived availability of XAI emerges as a crucial influencing factor; addressing it appropriately could enhance societal awareness and acceptance of AI while reducing fear. Personal factors and XAI influence attitudes towards AI in both Arab and UK cultures, enhancing result robustness and revealing nuanced differences.

Potential benefits and risks related to mainstream social media platforms and their revenue model are vigorously debated. However, a comprehensive framework of performance criteria to evaluate social media platforms and suggestions for transforming them are rare. Employing a transdisciplinary approach, the present work aimed to close these gaps through semi-structured interviews with experts from academia and industry, coupled with exploratory thematic content/topic analysis.From the interviews, five pivotal performance criteria were extracted: transparency, protection of democracy, satisfaction of needs and preservation of well-being, networking capabilities, and absence of crime. Further, proposed transformations related to i) financing structures, ii) possibilities for users to protect their interests and data, iii) regulations, iv) possibilities for users to adjust platform design, and v) transparency are discussed.Properly operationalized, both the criteria and suggested transformations hold the potential to facilitate negotiations among users, (mainstream) social media companies, and governments.

It is mostly unclear which personal predispositions are associated with knowledge about how to protect one’s privacy online and actually protecting it. More elaborate knowledge on this topic may help in the design process of user interfaces. Therefore, we investigated person characteristics underlying individual differences in online privacy literacy and behavior.N = 1,073 (n = 500 men) participants completed the Online Privacy Literacy Scale, an Online Privacy Behavior Scale, the Big Five Inventory, and a test assessing crystallized intelligence in an online survey.Online privacy literacy and behavior were significantly, moderately positively related. Both were significantly positively related to crystallized intelligence. Online privacy behavior was additionally significantly positively related to Openness.The results give insights into individual factors associated with knowledge about online privacy settings and related behaviors. In addition, results can help optimizing design of user interfaces/assistive technologies that support (certain) users to implement their data protection rights.