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.

Emotional AI and the future of wellbeing in the post-pandemic workplace.

This paper interrogates the growing pervasiveness of affect recognition tools as an emerging layer human-centric automated management in the global workplace. While vendors tout the neoliberal incentives of emotion-recognition technology as a pre-eminent tool of workplace wellness, we argue that emotional AI recalibrates the horizons of capital not by expanding outward into the consumer realm (like surveillance capitalism). Rather, as a new genus of digital Taylorism, it turns inward, passing through the corporeal exterior to extract greater surplus value and managerial control from the affective states of workers. Thus, empathic surveillance signals a profound shift in the ontology of human labor relations. In the emotionally quantified workplace, employees are no longer simply seen as physical capital, but conduits of actuarial and statistical intelligence gleaned from their most intimate subjective states. As a result, affect-driven automated management means that priority is often given to actuarial rather than human-centered managerial decisions.

Artificial intelligence applications and robotic systems in Parkinson's disease (Review).

Parkinson's disease (PD) is the second most frequent neurodegenerative disorder following Alzheimer's disease. Advanced stages of PD, 4 or 5 of the Hoehn and Yahr Scale, are characterized by severe motor complications, limited mobility without assistance, risk of falling, and non-motor complications. The aim of this review was to provide a practical overview on specific artificial intelligence (AI) systems for the management of advanced stages of PD, as well as relevant technological limitations. The authors conducted a systematic search on PubMed and EMBASE with predefined keywords searching for studies published until December 2020. Full articles that satisfied the inclusion criteria were included in the systematic review. To minimize results bias, the reference list was manually searched for pertinent articles to identify any additional relevant missed publications. Exclusion criteria included the following: Other stages of PD than 4 and 5 of the Hoehn and Yahr Scale, case reports, reviews, practice guidelines, commentaries, opinions, letters, editorials, short surveys, articles in press, conference abstracts, conference papers, and abstracts published without a full article. The search identified 21 studies analyzing AI-based applications and robotic systems used for the management of advanced stages of PD, out of which 6 articles analyzed AI-based applications for autonomous management of pharmacologic therapy, 5 articles analyzed home-based telemedicine systems and 10 articles analysed robot-assisted gait training systems. The authors identified significant evidence demonstrating that current AI-based technologies are feasible for automatic management of patients with advanced stages of PD. Improving the quality of care and reducing the cost for patients and healthcare systems are the most important advantages.

Analysis of "Artificial Pancreas (AP) Systems for People With Type 2 Diabetes: Conception and Design of the European CLOSE Project".

In an article in Journal of Diabetes Science and Technology, Schliess and coauthors describe the conception and design of the European Automated Glu cose Contro l at H ome for People with Chronic Di sease (CLOSE) initiative for the implementation of artificial pancreas (AP) systems for people with diabetes. The CLOSE consortium aims to develop integrated AP solutions (APplus) tailored to the needs of individuals with type 2 diabetes (T2D) by developing superior risk- and cost-benefit scenarios for AP operation to achieve acceptance by users and caregivers and a high likelihood for reimbursement. CLOSE is integrating the AP platform into the center of a comprehensive product and service package specifically tailored to defined T2D patient groups and care environments, leading to an interactive collaboration with users, health care providers, and other stakeholders in diabetes care. This is a very ambitious but well-conceived and delineated project which takes into consideration most of the relevant factors that may influence AP implementation in T2D care.

[OISO, automatic treatment of patients management in oncogenetics]. / OISO, traitement informatisé de la prise en charge en oncogénétique clinique.

INTRODUCTION: Oncogenetics is a long-term process, which requires a close relation between patients and medical teams, good familial links allowing lifetime follow-up. Numerous documents are exchanged in between the medical team, which has to frequently interact. We present here a new tool that has been conceived specifically for this management. METHODS: The tool has been developed according to a model-view-controler approach with the relational system PostgreSQL 9.3. The web site used PHP 5.3, HTML5 and CSS3 languages, completed with JavaScript and jQuery-AJAX functions and two additional modules, FPDF and PHPMailer. RESULTS: The tool allows multiple interactions, clinical data management, mailing and emailing, follow-up plannings. Requests are able to follow all patients and planning automatically, to send information to a large number of patients or physicians, and to report activity. DISCUSSION: The tool has been designed for oncogenetics and adapted to its different aspects. The CNIL delivered an authorization for use. Secured web access allows the management at a regional level. Its simple concept makes it evolutive according to the constant updates of genetic and clinical management of patients.