Artificial intelligence represents a key technology being inbuilt into evermore products. Research investigating attitudes towards artificial intelligence surprisingly is still scarce, although it becomes apparent that artificial intelligence will shape societies around the globe. To better understand individual differences in attitudes towards artificial intelligence, the present study investigated in n = 351 participants associations between the Affective Neuroscience Personality Scales (ANPS) and the Attitudes towards Artificial Intelligence framework (ATAI). It could be observed that in particular higher levels of SADNESS were (...) associated with higher negative attitudes towards AI (fearing AI). The findings are discussed in this work from an evolutionary perspective because primary emotional systems—according to Affective Neuroscience Theory—represent tools for survival, which have been homologously conserved across mammalian species including homo sapiens. (shrink)

The focus of this paper is to discuss the semiotic aspects of our findings from a project we conducted in the frame of Emotional Text Analysis paradigm. In the project, we intended to create a computer text classifier capable of effectively classifying texts into emotional categories. We agreed that we would need discrete data samples to input into it. For this, we asked 178 informants to give a verdict on the dominant emotion of 48 sample texts. Prior to their assessment (...) of the texts, the informants responded to a questionnaire used to estimate their empathic tendency. A detailed analysis of the informants’ assessments and personal empathetic tendency scores showed a positive correlation. Subsequently, our interest was piqued by the issue of how emotions could be triggered by conventional signs. Our findings seem to suggest that words are only used as an expression form insofar as they embody another type of semiotic complexity, thus diverging from the traditional Pearcian triad. In order to develop on these findings, it is therefore the main objective of this paper to provide a biosemiotic model of representation/interpretation of emotions, with particular attention paid to the eliciting of emotions as sign types. In this endeavour, we draw upon K. Kull’s concept of emonic semiotic model realization. Our suggestion is that, when one processes a text that elicits an emotional response, two semiotic facets are relevant: indexicality and emonicity. We argue that it is a main empathetic function to enforce the emonic model of semiosis over the indexical in situations where the interpreter has a choice between the two. As such, the hypothesis of the study is that emotions facilitate a particular type of semiotic mechanism, relying on the mimesis principle. (shrink)