A provocative argument that eating meat is not what made humans human and that the future is not necessarily carnivorous. Humans are eating more meat than ever. Despite ubiquitous Sweetgreen franchises and the example set by celebrity vegans, demand for meat is projected to grow at twice the rate of demand for plant-based foods over the next thirty years. Between 1960 and 2010, per capita meat consumption in the developing world more than doubled; in China, meat consumption grew ninefold. It has even been claimed that meat made us human—that our disproportionately large human brains evolved because our early human ancestors ate meat. In The Meat Question, Josh Berson argues that not only did meat not make us human, but the contemporary increase in demand for meat is driven as much by economic insecurity as by affluence. Considering the full sweep of meat's history, Berson concludes provocatively that the future is not necessarily carnivorous. Berson, an anthropologist and historian, argues that we have the relationship between biology and capitalism backward. We may associate meat-eating with wealth, but in fact, meat-eating is a sign of poverty; cheap meat—hunger killing, easy to prepare, eaten on the go—enables a capitalism defined by inequality. To answer the meat question, says Berson, we need to think about meat-eating in a way that goes beyond Paleo diets and PETA protests to address the deeply entwined economic and political lives of humans and animals past, present, and future.

Many instances of large-scale coordination occur in real-life social situations without the explicit awareness of the individuals involved. While the majority of research to date has examined dyadic interactions – those between two individuals – during intentional or deliberate coordination, the present review surveys the handful of recent studies investigating behavioral and physiological synchrony across groups of more than two people when coordination was not an explicit goal. Both minimal (e.g., visual information, shared location) and naturalistic (e.g., choir voice section, family relationship) group interactions appear to promote unintentional group synchrony although they have so far only been studied separately. State differences in unintentional group synchrony, or the relative presence of coordination in various conditions, have tended to be assessed differently, such as using correlation-type relationships, compared to its temporal dynamics, or changes over time in the degree of coordination, which appear to be best captured using phase differences. Simultaneously evaluating behavioral, physiological, and social responses as well systematically comparing different synchrony measures could further our understanding of the influences on and measures of group synchrony, allowing us to move away from studying individual persons responding to static laboratory stimuli and toward investigating collective experiences in natural, dynamic social interactions.

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For Hubbub, the anthropologist Josh Berson designed a field study with the aim of integrating physiological, phenomenological and environmental measures with place and time, and of giving study participants a chance to reflect on the experience of monitoring their movements. Here, Josh outlines how treating rest as a phenomenon with a spectral envelope emerged as a natural way to emphasize the non-linear interaction of all these factors.

In March 2016, Microsoft launched a bot, a natural language software automaton, on Twitter under the screen name @TayandYou. “Tay” was an effort to build goodwill with Millennial social media users, but it was also a serious experiment in allowing a software agent to evolve under unconstrained natural‐language input from hundreds of thousands of speakers. The results were not encouraging. Within 24 hours, Tay's maintainers were forced to take the bot offline after a loose cadre of users centered on the 4chan discussion board /pol/ took control of the bot's tone, flooding it with racist, sexist, and right‐wing conspiracy theory messages until Tay started broadcasting variants on those messages to its more than 200,000 followers. Tay is but one example of how language haunts artificial, or machine, intelligence. This entry considers the history of efforts to operationalize language in such a way as to make it amenable to a machine generation. As a rule these efforts start by excluding pragmatics from the set of phenomena that make language distinctive. We address the persistence of the information processing view of language in the face of failures such as Tay and recent critiques from the philosophy of embodied cognition.

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