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Winning in the robotic workplace : how to prosper in the automation age
\"This book will examine the history of robotics and explicate what massive automation means for the present and future of labor in all its forms, from mills and factories to the white-collar offices of suburbia and more\"-- Provided by publisher.
Book
Endogenous opioids regulate social threat learning in humans
Many fearful expectations are shaped by observation of aversive outcomes to others. Yet, the neurochemistry regulating social learning is unknown. Previous research has shown that during direct (Pavlovian) threat learning, information about personally experienced outcomes is regulated by the release of endogenous opioids, and activity within the amygdala and periaqueductal gray (PAG). Here we report that blockade of this opioidergic circuit enhances social threat learning through observation in humans involving activity within the amygdala, midline thalamus and the PAG. In particular, anticipatory responses to learned threat cues (CS) were associated with temporal dynamics in the PAG, coding the observed aversive outcomes to other (observational US). In addition, pharmacological challenge of the opioid receptor function is classified by distinct brain activity patterns during the expression of conditioned threats. Our results reveal an opioidergic circuit that codes the observed aversive outcomes to others into threat responses and long-term memory in the observer.
Though humans often learn about negative outcomes from observing the response of others, the neurochemistry underlying this learning is unknown. Here, authors show that blocking opioid receptors enhances social threat learning and describe the brain regions underlying this effect.
Journal Article
Rational Inattention
We review the recent literature on rational inattention, identify the main theoretical mechanisms, and explain how it helps us understand a variety of phenomena across fields of economics. The theory of rational inattention assumes that agents cannot process all available information, but they can choose which exact pieces of information to attend to. Several important results in economics have been built around imperfect information. Nowadays, many more forms of information than ever before are available due to new technologies, and yet we are able to digest little of it. Which form of imperfect information we possess and act upon is thus largely determined by which information we choose to pay attention to. These choices are driven by current economic conditions and imply behavior that features numerous empirically supported departures from standard models. Combining these insights about human limitations with the optimizing approach of neoclassical economics yields a new, generally applicable model.
Journal Article
Neural modulation of social reinforcement learning by intranasal oxytocin in male adults with high-functioning autism spectrum disorder: a randomized trial
Reduced social motivation is a hallmark of individuals with autism spectrum disorders (ASDs). Although the exact neural mechanisms are unclear, oxytocin has been shown to enhance motivation and attention to social stimuli, suggesting a potential to augment social reinforcement learning as the central mechanism of behavioral interventions in ASD. We tested how reinforcement learning in social contexts and associated reward prediction error (RPE) signals in the nucleus accumbens (NAcc) were modulated by intranasal oxytocin. Male adults with a childhood diagnosis of ASD (n = 15) and healthy controls (n = 24; aged 18–26 years) performed a probabilistic reinforcement learning task during functional magnetic resonance imaging in a single-center (research center in Germany), randomized double-blind, placebo-controlled cross-over trial. The interventions were intranasal oxytocin (Syntocinon®, Novartis; 10 puffs = 20 international units (IUs) per treatment) and placebo spray. Using computational modeling of behavioral data, trial-by-trial RPE signals were assessed and related to brain activation in NAcc during reinforcing feedback in social and non-social contexts. The order of oxytocin/placebo was randomized for 60 participants. Twenty-one participants were excluded from analyses, leaving 39 for the final analysis. Behaviorally, individuals with ASD showed enhanced learning under oxytocin when the learning target as well as feedback was social as compared to non-social (social vs. non-social target: 87.09% vs. 71.29%, 95% confidence interval (CI): 7.28–24.33, p = .003; social vs. non-social feedback: 81.00% vs. 71.29%, 95% CI: 2.81–16.61, p = .027). Correspondingly, oxytocin enhanced the correlation of the RPE signal with NAcc activation during social (vs. non-social) feedback in ASD (3.48 vs. −1.12, respectively, 95% CI: 2.98–6.22, p = .000), whereas in controls, this effect was found in the placebo condition (2.90 vs. −1.14, respectively, 95% CI: 1.07–7.01, p = .010). In ASD, a similar pattern emerged when the learning target was social (3.00 vs. −0.64, respectively, 95% CI: −0.13 to 7.41, p = .057), whereas controls showed a reduced correlation for social learning targets under oxytocin (−0.70 vs. 2.72, respectively, 95% CI: −5.86 to 0.98, p = .008). The current data suggest that intranasal oxytocin has the potential to enhance social reinforcement learning in ASD. Future studies are warranted that investigate whether oxytocin can potentiate social learning when combined with behavioral therapies, resulting in greater treatment benefits than traditional behavior-only approaches.
Journal Article
Psychosocial Effects of the COVID-19 Pandemic: Large-scale Quasi-Experimental Study on Social Media
The COVID-19 pandemic has caused several disruptions in personal and collective lives worldwide. The uncertainties surrounding the pandemic have also led to multifaceted mental health concerns, which can be exacerbated with precautionary measures such as social distancing and self-quarantining, as well as societal impacts such as economic downturn and job loss. Despite noting this as a \"mental health tsunami\", the psychological effects of the COVID-19 crisis remain unexplored at scale. Consequently, public health stakeholders are currently limited in identifying ways to provide timely and tailored support during these circumstances.
Our study aims to provide insights regarding people's psychosocial concerns during the COVID-19 pandemic by leveraging social media data. We aim to study the temporal and linguistic changes in symptomatic mental health and support expressions in the pandemic context.
We obtained about 60 million Twitter streaming posts originating from the United States from March 24 to May 24, 2020, and compared these with about 40 million posts from a comparable period in 2019 to attribute the effect of COVID-19 on people's social media self-disclosure. Using these data sets, we studied people's self-disclosure on social media in terms of symptomatic mental health concerns and expressions of support. We employed transfer learning classifiers that identified the social media language indicative of mental health outcomes (anxiety, depression, stress, and suicidal ideation) and support (emotional and informational support). We then examined the changes in psychosocial expressions over time and language, comparing the 2020 and 2019 data sets.
We found that all of the examined psychosocial expressions have significantly increased during the COVID-19 crisis-mental health symptomatic expressions have increased by about 14%, and support expressions have increased by about 5%, both thematically related to COVID-19. We also observed a steady decline and eventual plateauing in these expressions during the COVID-19 pandemic, which may have been due to habituation or due to supportive policy measures enacted during this period. Our language analyses highlighted that people express concerns that are specific to and contextually related to the COVID-19 crisis.
We studied the psychosocial effects of the COVID-19 crisis by using social media data from 2020, finding that people's mental health symptomatic and support expressions significantly increased during the COVID-19 period as compared to similar data from 2019. However, this effect gradually lessened over time, suggesting that people adapted to the circumstances and their \"new normal.\" Our linguistic analyses revealed that people expressed mental health concerns regarding personal and professional challenges, health care and precautionary measures, and pandemic-related awareness. This study shows the potential to provide insights to mental health care and stakeholders and policy makers in planning and implementing measures to mitigate mental health risks amid the health crisis.
Journal Article