With the intensifying shortage of care-providers and mounting financial burden of an aging population in Japan, artificial intelligence (AI) offers a potential solution through AI-driven robots, chatbots, smartphone apps, and other AI medical services. Yet Japanese acceptance of medical AI, especially patient care, largely depends on the degree of ‘humanness’ that can be integrated into intelligent technologies. As empathy is considered a core value in the practice of healthcare workers, artificially intelligent agents must have the ability to perceive human emotions (...) and respond in an affective, human-like manner. This paper presents the results of a nationwide survey in Japan 2023 about the public perception of the use of emotionalized AI (EAI) in healthcare. The sample included 2000 Japanese citizens from 20 to 69 years old with an average age of 45 years. The questionnaire included 65 items in six categories: demographic, perception of the existing healthcare system, attitude towards the use of AI, and EAI in healthcare, trust and privacy concerns and fear of AI, and seeking literacy on new technologies. The analysis of the responses demonstrates that overall, the Japanese population has a limited knowledge of AI, EAI, and smart technologies but trusts the healthcare system, physicians, and staff to use it properly, with little worries over the potential pitfalls related to data security and safety. However, they prefer the use of more human resources and are concerned about privacy and the high cost of new technology, and believe little information is being provided to them through government and media. (shrink)

This article analyses the forms of dividuation workers undergo when they are linked to technologies, such as algorithms or artificial intelligence. It examines functionalities and operations deployed by certain types of Talent Management software and apps—UKG, Tribepad, Afiniti, RetailNext and Textio. Specifically, it analyses how talented workers materialise in relation to the profiles and the statistical models generated by such artificial intelligence machines. It argues that these operate as a nooscope that allows the transindividual plane to be quantified through a (...) process known as dividuation. Finally, by way of conclusion, the notion of the dividual is presented as the logic that characterises the human–machine relationship in the case of artificial intelligence and as the horizon of what Felix Guattari called “machinic capitalism”. (shrink)

The present study sheds light on a new psychological construct called “AI pessimism aversion” (AIPA) describing an overly optimistic view of the benefits of AI by neglecting its potential dangers. In an international sample of N = 543 participants, we observed that the construct of AIPA strongly overlaps with single-item measures for positive and negative AI attitudes. Furthermore, the structural equation model suggests that the positive association between the internal locus of control (a personality measure describing persons who see themselves (...) as steering their own lives) and positive AI attitudes was in part mediated by AIPA. We also assessed risk aversion in the present work, because high aversion of risky situations might go along with lower AIPA (the coming AI wave is characterised by high uncertainty). Surprisingly, this was not the case, and these two constructs seem to be (rather) independent. The present work should be a starting point to dive deeper into the study of AI attitudes, a highly relevant research theme for societies standing at the eve of the coming AI wave. (shrink)