The Social Physics of Conversation: Why Communication Patterns Matter

(PDF) Algorithmically Mediating Communication to Enhance Collective Decision-Making in Online Social Networks

PDF | Many collective decision-making contexts involve communication among group members. Sometimes this communication helps the collective reach an... | Find, read and cite all the research you need on ResearchGate

The network science of collective intelligence

In the last few years, breakthroughs in computational and experimental techniques have produced several key discoveries in the science of networks and human collective intelligence. This review presents the latest scientific findings from two key fields of research: collective problem-solving and the wisdom of the crowd. I demonstrate the core theoretical tensions separating these research traditions and show how recent findings offer a new synthesis for understanding how network dynamics alter collective intelligence, both positively and negatively.

Social Physics by Alex Pentland: 9780143126331 | PenguinRandomHouse.com: Books

From one of the world’s leading data scientists, a landmark tour of the new science of idea flow, offering revolutionary insights into the mysteries of collective intelligence and social influence...

Human–AI Collaboration at Scale: Task Criticality, Agency, and Friction Across 250,000 Conversations

Stanford University researchers analyzed nearly 250,000 real-world human-AI conversations from Claude.ai to understand collaborative dynamics, finding that over half of interactions involve...

Exploring Conversation Design: Applications and Benefits

Discover the what, why and how of Conversation Design, including its definition, applications, and benefits.

Small talk acts like social glue – here’s how to get better at it

Maybe think of small talk as a technology: a human invention for accomplishing social goals.

A bias for social information in human cultural transmission

Evolutionary theories concerning the origins of human intelligence suggest that cultural transmission might be biased toward social over non‐social information. This was tested by passing social and non‐social information along multiple chains of participants. Experiment 1 found that gossip, defined as information about intense third‐party social relationships, was transmitted with siginificantly greater accuracy and in significantly greater quantity than equivalent non‐social information concerning individual behaviour or the physical environment. Experiment 2 replicated this finding controlling for narrative coherence, and additionally found that information concerning everyday non‐gossip social interactions was transmitted just as well as the intense gossip interactions. It was therefore concluded that human cultural transmission is biased toward information concerning social interactions over equivalent non‐social information.

Theory and Memory: Two Forces Shaping Software Team Knowledge

How insights from cognitive science and social psychology explain why software knowledge is so hard to preserve

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.

When moving fast, talking is the first thing to break

When you make speed and “moving fast” the biggest priority on a project or in an organization, the first thing to breakdown is talking to each other. Talking takes time. Consensus is expensive and slow. In a pressurized environment there’s no time to schedule calls, get input from subject matter experts, or resolve key differences of opinion. ASAP makes a big assumption that all relevant parties are already in the room.

Mnemonic convergence in social networks: The emergent properties of cognition at a collective level

Significance Human memory is highly malleable. Because of this malleability, jointly remembering the past along with another individual often results in increased similarity between the conversational partners’ memories. We propose an approach that examines the conversation between a pair of participants as part of a larger network of social interactions that has the potential to reveal how human communities form collective memories. Empirical evidence indicating that dyadic-level conversational alignment processes give rise to community-wide shared memories is presented. We find that individual-level memory updating phenomena and social network structure are two fundamental factors that contribute to the emergence of collective memories. , The development of shared memories, beliefs, and norms is a fundamental characteristic of human communities. These emergent outcomes are thought to occur owing to a dynamic system of information sharing and memory updating, which fundamentally depends on communication. Here we report results on the formation of collective memories in laboratory-created communities. We manipulated conversational network structure in a series of real-time, computer-mediated interactions in fourteen 10-member communities. The results show that mnemonic convergence, measured as the degree of overlap among community members’ memories, is influenced by both individual-level information-processing phenomena and by the conversational social network structure created during conversational recall. By studying laboratory-created social networks, we show how large-scale social phenomena (i.e., collective memory) can emerge out of microlevel local dynamics (i.e., mnemonic reinforcement and suppression effects). The social-interactionist approach proposed herein points to optimal strategies for spreading information in social networks and provides a framework for measuring and forging collective memories in communities of individuals.

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.

We need to talk about the social graph - Philip Sheldrake

Concepts are the fundamental building blocks of thinking, of designing. While there are plenty of things in the mix when it comes to contemplating system design, if the primary concepts remain unchallenged and unchanged from what came before, then the outcome will likely look very familiar.

Cognition in a Social Context: A Social-Interactionist Approach to Emergent Phenomena

The formation of collective memories, emotions, and beliefs is a fundamental characteristic of human communities. These emergent outcomes are thought to be the result of a dynamical system of communicative interactions among individuals. But despite recent psychological research on collective phenomena, no programmatic framework to explore the processes involved in their formation exists. Here, we propose a social-interactionist approach that bridges cognitive and social psychology to illuminate how microlevel cognitive phenomena give rise to large-scale social outcomes. It involves first establishing the boundary conditions of cognitive phenomena, then investigating how cognition is influenced by the social context in which it is manifested, and finally studying how dyadic-level influences propagate in social networks. This approach has the potential to (a) illuminate the large-scale consequences of well-established cognitive phenomena, (b) lead to interdisciplinary dialogues between psychology and the other social sciences, and (c) be more relevant for public policy than existing approaches.