How to Harness Your Behavioural Wake to Amplify Culture

Peet’s Coffee x SPIN Sessions: Where Coffee Culture Meets Music Culture - SPIN

Music-loving coffee drinkers have long known the importance of shifting a sluggish moment into a second wind. There’s always been a need for

Why sycophantic LLMs may imperil interactive norms between humans

Interactions with conversational AI are effortless by design—instant, compliant, and largely consequence-free. Human communication norms, by contrast, evolved under conditions of reciprocity and social accountability. We propose that repeated engagement with conversational AI systems may produce norm leakage: the cross-context carryover of instrumental communicative habits acquired in human–AI exchanges into subsequent human–human interaction. Emerging experimental evidence suggests short-term spillover effects on social judgment and behavior, including harsher evaluations, reduced cooperation, and diminished perceived humanness. Preliminary longitudinal findings are consistent with the possibility that such exposure may shape communicative habits over time, although the durability and real-world magnitude of these effects remain unclear. We further propose that sycophantic alignment may amplify norm leakage by reinforcing instrumental interaction styles. At stake, then, is the possibility that repeated engagement with highly compliant artificial agents could subtly influence users’ communicative expectations and interpersonal judgments.

Embers of society: Firelight talk among the Ju/’hoansi Bushmen

Much attention has been focused on control of fire in human evolution and the impact of cooking on anatomy, social, and residential arrangements. However, little is known about what transpired when firelight extended the day, creating effective time for social activities that did not conflict with productive time for subsistence activities. Comparison of 174 day and nighttime conversations among the Ju/’hoan (!Kung) Bushmen of southern Africa, supplemented by 68 translated texts, suggests that day talk centers on economic matters and gossip to regulate social relations. Night activities steer away from tensions of the day to singing, dancing, religious ceremonies, and enthralling stories, often about known people. Such stories describe the workings of entire institutions in a small-scale society with little formal teaching. Night talk plays an important role in evoking higher orders of theory of mind via the imagination, conveying attributes of people in broad networks (virtual communities), and transmitting the “big picture” of cultural institutions that generate regularity of behavior, cooperation, and trust at the regional level. Findings from the Ju/’hoan are compared with other hunter-gatherer societies and related to the widespread human use of firelight for intimate conversation and our appetite for evening stories. The question is raised as to what happens when economically unproductive firelit time is turned to productive time by artificial lighting.

Differences Between Tight and Loose Cultures: A 33-Nation Study

The differences across cultures in the enforcement of conformity may reflect their specific histories. , With data from 33 nations, we illustrate the differences between cultures that are tight (have many strong norms and a low tolerance of deviant behavior) versus loose (have weak social norms and a high tolerance of deviant behavior). Tightness-looseness is part of a complex, loosely integrated multilevel system that comprises distal ecological and historical threats (e.g., high population density, resource scarcity, a history of territorial conflict, and disease and environmental threats), broad versus narrow socialization in societal institutions (e.g., autocracy, media regulations), the strength of everyday recurring situations, and micro-level psychological affordances (e.g., prevention self-guides, high regulatory strength, need for structure). This research advances knowledge that can foster cross-cultural understanding in a world of increasing global interdependence and has implications for modeling cultural change.

Code & Coffee (Vancouver) | Meetup

What is Cowork & Coffee?Cowork & Coffee is a lightweight meetup series for people to get together and cowork and have our morning coffees.Is there a language or technology you always wanted to explore? Only have an hour before you have to run for your morning standup? Just need to get some w

Real signals or artificial stereotypes?

Adventures with a cultural Copilot

A Grand Unified Theory of Cultural Stagnation

Listen to your favorite podcasts online, in your browser. Discover the world's most powerful podcast player.

dominik.social/morgenblau

Your calm window into the Atmosphere.

LLMs and people both learn to form conventions -- just not with each other

Humans align to one another in conversation -- adopting shared conventions that ease communication. We test whether LLMs form the same kinds of conventions in a multimodal communication game. Both humans and LLMs display evidence of convention-formation (increasing the accuracy and consistency of their turns while decreasing their length) when communicating in same-type dyads (humans with humans, AI with AI). However, heterogenous human-AI pairs fail -- suggesting differences in communicative tendencies. In Experiment 2, we ask whether LLMs can be induced to behave more like human conversants, by prompting them to produce superficially humanlike behavior. While the length of their messages matches that of human pairs, accuracy and lexical overlap in human-LLM pairs continues to lag behind that of both human-human and AI-AI pairs. These results suggest that conversational alignment requires more than just the ability to mimic previous interactions, but also shared interpretative biases toward the meanings that are conveyed.

Misplaced Divides? Discussing Political Disagreement With Strangers Can Be Unexpectedly Positive

Differences of opinion between people are common in everyday life, but discussing those differences openly in conversation may be unnecessarily rare. We report three experiments ( N = 1,264 U.S.-based adults) demonstrating that people’s interest in discussing important but potentially divisive topics is guided by their expectations about how positively the conversation will unfold, leaving them more interested in having a conversation with someone who agrees versus disagrees with them. People’s expectations about their conversations, however, were systematically miscalibrated such that people underestimated how positive these conversations would be—especially in cases of disagreement. Miscalibrated expectations stemmed from underestimating the degree of common ground that would emerge in conversation and from failing to appreciate the power of social forces in conversation that create social connection. Misunderstanding the outcomes of conversation could lead people to avoid discussing disagreements more often, creating a misplaced barrier to learning, social connection, free inquiry, and free expression.

To experience Zen-like awakening, try going the headless way | Psyche Ideas

Try to point to your true self as you’d point to a brick wall, and other experiments in Zen-like awakening

Empirical evidence of Large Language Model's influence on human spoken communication

From the printing press to social media, innovations in communication technology have repeatedly reshaped how ideas spread through human culture. Chatbots powered by generative artificial intelligence constitute a new medium, encoding cultural patterns in their neural representations and disseminating them in conversations with hundreds of millions of people. Whether these patterns transmit into human language, and ultimately shape human culture, is a fundamental question. While fully quantifying the causal impact of a chatbot like ChatGPT on human culture is challenging, lexical shifts in human spoken communication may offer an early indicator. Here we show that words preferentially generated by ChatGPT, such as delve, showcase, boast, intricacies and meticulous, increased abruptly in spontaneous human speech. A synthetic-control analysis of 737,083 hours of conversation from 824,634 podcast episodes, screened for unscripted speech, causally links this shift to ChatGPT's release. The measurable influence on spontaneous speech suggests that humans internalize the lexical choices of large language models (LLMs). A preregistered experiment (N = 496) confirms they do, as a brief chatbot interaction led participants to adopt its words as their own, persisting past a distractor task and confirmed in forced lexical choice, indicating entrenchment in the active vocabulary. Together these results show that machines trained on human data now feed their own traits back into human language, integrating LLMs into the ongoing processes of cultural evolution.. This coupling raises concerns about linguistic homogenization and the capacity of a few major AI providers for latent cultural influence at scale.

Home - Neighbors

Neighbors in Houston, TX. By day, we're your cozy local coffee shop – serving up expertly brewed coffee, fresh bites, and open Wi-Fi to fuel your work or chill vibes. By night, we transform into a lively pizza bar with craft cocktails, cold beers, a curated wine list, and a menu full of crowd-pleasing pies. We're more than just great food and drinks – we're your neighborhood hangout. From live music and game nights to themed events and casual meetups, there's always something happening here.