Perceptions of the Impact of High-Level-Machine-Intelligence from University Students in Taiwan: The Case for Human Professions, Autonomous Vehicles, and Smart Homes

Bosses without a heart: socio-demographic and cross-cultural determinants of attitude toward Emotional AI in the workplace

Biometric technologies are becoming more pervasive in the workplace, augmenting managerial processes such as hiring, monitoring and terminating employees. Until recently, these devices consisted mainly of GPS tools that track location, software that scrutinizes browser activity and keyboard strokes, and heat/motion sensors that monitor workstation presence. Today, however, a new generation of biometric devices has emerged that can sense, read, monitor and evaluate the affective state of a worker. More popularly known by its commercial moniker, Emotional AI, the technology stems from advancements in affective computing. But whereas previous generations of biometric monitoring targeted the exterior physical body of the worker, concurrent with the writings of Foucault and Hardt, we argue that emotion-recognition tools signal a far more invasive disciplinary gaze that exposes and makes vulnerable the inner regions of the worker-self. Our paper explores attitudes towards empathic surveillance by analyzing a survey of 1015 responses of future job-seekers from 48 countries with Bayesian statistics. Our findings reveal affect tools, left unregulated in the workplace, may lead to heightened stress and anxiety among disadvantaged ethnicities, gender and income class. We also discuss a stark cross-cultural discrepancy whereby East Asians, compared to Western subjects, are more likely to profess a trusting attitude toward EAI-enabled automated management. While this emerging technology is driven by neoliberal incentives to optimize the worksite and increase productivity, ultimately, empathic surveillance may create more problems in terms of algorithmic bias, opaque decisionism, and the erosion of employment relations. Thus, this paper nuances and extends emerging literature on emotion-sensing technologies in the workplace, particularly through its highly original cross-cultural study.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00146-021-01290-1.

Preparing Society for Automated Vehicles: Perceptions of the Importance and Urgency of Emerging Issues of Governance, Regulations, and Wider Impacts

This study explores the overall picture of how people perceive the importance level and urgency level regarding issues associated with automated vehicles, by sorting out ten issues, developing a questionnaire with 66 measurement items, and investigating how Artificial Intelligence (AI) experts and Computer Science (CS)/Electrical Engineering (EE) majors assessed these issues. The findings suggest that AI experts in Taiwan believed that the top five issues for preparing a society for autonomous vehicles (AVs) should include (1) data privacy and cybersecurity, (2) regulation considerations, (3) infrastructure, (4) governance, and (5) public acceptance. On the other hand, for their student counterparts, the results (1) demonstrate a somewhat different order from the third to the fifth place, (2) show an attention-focused profile on the issue of cybersecurity and data privacy, and (3) indicate that gender and a few wider-impact variables (technology innovation, infrastructure) are significant predictors for the assessment on the importance level of AVs, while some wider-impact variables (technology innovation, governance, economic benefits, infrastructure), which are positively associated, as well as concerns variables (cybersecurity and data privacy, regulations), which are negatively associated, could be predictors for the urgency level of AVs. Suggestions for future research and policymakers are provided.