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Rubinstein's basic assertion, which is that economic theory tells us more about economic models than it tells us about economic reality, is a warning: We should listen not only to economists when it comes to predicting the future of work; we should listen also to historians, who often bring a deeper historical perspective to their predictions. Automation will significantly change many people's lives in ways that may be painful and enduring.

People feel they understand complex phenomena with far greater precision, coherence, and depth than they really do; they are subject to an illusion-an illusion of explanatory depth. The illusion is far stronger for explanatory knowledge than many other kinds of knowledge, such as that for facts, procedures or narratives. The illusion for explanatory knowledge is most robust where the environment supports real-time explanations with visible mechanisms. We demonstrate the illusion of depth with explanatory knowledge in Studies 1-6. Then we show differences in overconfidence about knowledge across different knowledge domains in Studies 7-10. Finally, we explore the mechanisms behind the initial confidence and behind overconfidence in Studies 11 and 12. Implications for the roles of intuitive theories in models of concepts and cognition are discussed.

In anticipation of his forthcoming article on Social Democracy in PSL Quarterly, and a Phenomenal World series on the topic, we begin this interview by discussing alternatives to financial liberalization, before turning to a discussion on the future of welfare politics, development strategy, and contemporary models of economic growth.

There is a parallel between today's stock market and Fischer random chess. The last time we faced a global pandemic was in 1918, and this might as well have been in the BC era. Few of us were alive then, but even the history books are not that useful, as the structure of the US and global economy, the central bank system, the diversity and dynamism of society, and the state of technological progress are nothing like the world knew then. Most of the mental models we as investors rely on are based on an environment that no longer exists. The only common denominator between now and then is that humans have not really changed that much - it takes a few millennia to rewire our DNA and thus our fundamental behavior.

Ultraviolet light endangers the integrity of human genetic information and may cause skin cancer. For the first time, researchers at Karlsruhe Institute of Technology (KIT) have demonstrated that DNA damage may also occur far away from the point of incidence of the radiation. They produced an artificially modeled DNA sequence in new architecture and succeeded in detecting DNA damage at a distance of 30 DNA building blocks. The results are reported in Angewandte Chemie.

new study uses satellite data over the Southern Hemisphere to understand global cloud composition during the industrial revolution. This research tackles one of the largest uncertainties in today's climate models-the long-term effect of tiny atmospheric particles on climate change.

The model, called Deep Claim, predicts both when and how much an insurance company will pay for a given claim in advance of any payment they make. It was trained with three million de-identified claims including parameters like demographic information, diagnoses, treatments, and billed amounts. Using this information, Deep Claim can not only predict the date and amount of payments with reasonable certainty, but also the likeliest reasonings for any claim denial in play.

This article traces the travel of biometric data of Syrian refugees in Jordan through a hastily evolving political economy characterized by a pervasive craving for the extraction, storage and brokering of displacement data. It analyzes iris-enrollment as problematic acts of quasi-citizenship for the displaced requiring the performance of social and economic docility in order to attain identity, cash and service provision. Quasi-objects in the form of digital footprints are fashioned through infrastructures that simultaneously seek to model, yet fail to capture, socioeconomic existence in displacement contexts. Discourses of anti-fraud, donor dictates, upward accountability and strategies of financial inclusion of 'the unbanked', facilitate the marketization of the creation of data-doubles in laboratories of displacement and loopholes for externalization. Driven by increasingly blurred lines between technological, humanitarian and financial interests, this development has transformative effects on both those displaced, and on a humanitarian sector tasked with safeguarding their rights.

People the world over have acquired a passing familiarity with epidemic models, critical threshold values for transmission (R0), comorbidities, and exponential growth. But these insights into the pandemic are like Harrison's H1-3; they focus on a few elements of the problem. The pandemic is every bit as much a problem of the non-linear dynamics of markets, the cognitive biases of decision-makers, the collective dynamics of groups, and the coevolution of biological species - humans, mammalian food sources, and viral agents.

Toothpaste, face creams, hair gel, mayonnaise and ketchup are household items that most people don't think twice about, but in terms of their flow behavior, they have unusual properties. They're all elasto-visco-plastic (EVP) materials, which behave like solids when at rest, but can yield to flow like liquids when placed under enough stress. Despite their ubiquity, the ability to model and predict their behavior relies on a theory that has only been shown to work under certain conditions.