Robots and Organization Studies: Why Robots Might Not Want to Steal Your Job

A number of recent high-profile studies of robotics and artificial intelligence (or AI) in economics and sociology have predicted that many jobs will soon disappear due to automation, with few new ones replacing them. While techno-optimists and techno-pessimists contest whether a jobless future is a positive development or not, this paper points to the elephant in the room. Despite successive waves of computerization (including advanced machine learning), jobs have not disappeared. And probably won’t in the near future. To explain why, some basic insights from organization studies can make a contribution. I propose the concept of ‘bounded automation’ to demonstrate how organizational forces mould the application of technology in the employment sector. If work does not vanish in the age of AI, then poorly paid jobs will most certainly proliferate, I argue. Finally, a case is made for the scholarly community to engage with wider social justice concerns. This I term public organization studies

Partitioning the Heritability of Tourette Syndrome and Obsessive Compulsive Disorder Reveals Differences in Genetic Architecture

The direct estimation of heritability from genome-wide common variant data as implemented in the program Genome-wide Complex Trait Analysis (GCTA) has provided a means to quantify heritability attributable to all interrogated variants. We have quantified the variance in liability to disease explained

Naturalizing psychopathology—towards a quantitative real-world psychiatry

Psychiatric disorders continue to be on the rise around the globe. Meanwhile, efforts and investments directed to early diagnosis and appropriate interventions for mental health problems are lagging resulting in ‘substantial loss of human capabilities and avoidable suffering’ [1]. A major component of our inability to address mental health problems resides in the persistent lack of objective measures for evaluating such difficulties in the daily life of individuals, complicating the detection of clinically relevant changes in the patients’ well-being [2]. Similarly, most studies into the neurobiology of psychiatric disorders lack a detailed description of individual functioning despite influential calls for quantitative approaches to psychopathology

Minds made for sharing: initiating joint attention recruits reward-related neurocircuitry

■ The ability and motivation to share attention is a unique aspect of human cognition. Despite its significance, the neural basis remains elusive. To investigate the neural correlates of joint attention, we developed a novel, interactive research paradigm in which participants ʼ gaze behavior—as measured by an eye tracking device—was used to contingently control the gaze of a computer-animated character. Instructed that the character on screen was controlled by a real person outside the scanner, 21 participants interacted with the virtual other while undergoing functional magnetic resonance imaging (fMRI). Experimental variations focused on leading versus following the gaze of the character when fixating one of three objects also shown on th

Meta-Analytically Informed Network Analysis of Resting State fMRI Reveals Hyperconnectivity in an Introspective Socio-Affective Network in Depression

<div><p>Alterations of social cognition and dysfunctional interpersonal expectations are thought to play an important role in the etiology of depression and have, thus, become a key target of psychotherapeutic interventions. The underlying neurobiology, however, remains elusive. Based upon the idea of a close link between affective and introspective processes relevant for social interactions and alterations thereof in states of depression, we used a meta-analytically informed network analysis to investigate resting-state functional connectivity in an introspective socio-affective (ISA) network in individuals with and without depression. Results of our analysis demonstrate significant differences between the groups with depressed individuals showing hyperconnectivity of the ISA network. These findings demonstrate that neurofunctional alterations exist in individuals with depression in a neural network relevant for introspection and socio-affective processing, which may contribute to the interpersonal difficulties that are linked to depressive symptomatology.</p></div