Broadening access to both computational and educational resources is crit- ical to diffusing machine learning (ML) innovation. However, today, most ML resources and experts are siloed in a few countries and organizations. In this article, we describe our pedagogical approach to increasing access to applied ML through a massive open online course (MOOC) on Tiny Machine Learning (TinyML). We suggest that TinyML, applied ML on resource-constrained embedded devices, is an attractive means to widen access because TinyML leverages low-cost and globally (...) accessible hardware and encourages the development of complete, self-contained applications, from data collection to deployment. To this end, a collaboration between academia and industry produced a four part MOOC that provides application-oriented instruction on how to develop solutions using TinyML. The series is openly available on the edX MOOC platform, has no prerequisites beyond basic programming, and is designed for global learners from a variety of backgrounds. It introduces real-world applications, ML algorithms, data-set engineering, and the ethi- cal considerations of these technologies through hands-on programming and deployment of TinyML applications in both the cloud and on their own microcontrollers. To facili- tate continued learning, community building, and collaboration beyond the courses, we launched a standalone website, a forum, a chat, and an optional course-project com- petition. We also open-sourced the course materials, hoping they will inspire the next generation of ML practitioners and educators and further broaden access to cutting-edge ML technologies. (shrink)

Evolutionary psychologists have suggested that confidence and conservatism promoted aggression in our ancestral past, and that this may have been an adaptive strategy given the prevailing costs and benefits of conflict. However, in modern environments, where the costs and benefits of conflict can be very different owing to the involvement of mass armies, sophisticated technology, and remote leadership, evolved tendencies toward high levels of confidence and conservatism may continue to be a contributory cause of aggression despite leading to greater costs (...) and fewer benefits. The purpose of this paper is to test whether confidence and conservatism are indeed associated with greater levels of aggression—in an explicitly political domain. We present the results of an experiment examining people’s levels of aggression in response to hypothetical international crises (a hostage crisis, a counter-insurgency campaign, and a coup). Levels of aggression (which range from concession to negotiation to military attack) were significantly predicted by subjects’ (1) confidence that their chosen policy would succeed, (2) score on a liberal-conservative scale, (3) political party affiliation, and (4) preference for the use of military force in real-world U.S. policy toward Iraq and Iran. We discuss the possible adaptive and maladaptive implications of confidence and conservatism for the prospects of war and peace in the modern world. (shrink)

We compared the punitiveness of two groups following a manipulation in which participants were either able to cheat on a simple number-matching task, by taking more money then they rightfully earned, or prevented from doing so on the same task. After completing the task, participants read a number of small vignettes of politicians who had acted questionably, and then were asked to rate the scenarios on both how wrong the behavior was and how much punishment it deserved. Participants given the (...) opportunity to cheat with impunity were significantly less punitive when judging questionable behavior on the part of elected officials. (shrink)

Why is it hard to solve the climate crisis, and what can we do? This book answers these questions, which are of interest to the public, academics, and businesspeople. Using stories from the front lines of the energy transition, we show how to unlock the climate impasse.