A new sociology of humans and machines.

From fake social media accounts and generative artificial intelligence chatbots to trading algorithms and self-driving vehicles, robots, bots and algorithms are proliferating and permeating our communication channels, social interactions, economic transactions and transportation arteries. Networks of multiple interdependent and interacting humans and intelligent machines constitute complex social systems for which the collective outcomes cannot be deduced from either human or machine behaviour alone. Under this paradigm, we review recent research and identify general dynamics and patterns in situations of competition, coordination, cooperation, contagion and collective decision-making, with context-rich examples from high-frequency trading markets, a social media platform, an open collaboration community and a discussion forum.

Science Communication as a Collective Intelligence Endeavor: A Manifesto and Examples for Implementation.

Effective science communication is challenging when scientific messages are informed by a continually updating evidence base and must often compete against misinformation. We argue that we need a new program of science communication as collective intelligence-a collaborative approach, supported by technology. This would have four key advantages over the typical model where scientists communicate as individuals: scientific messages would be informed by (a) a wider base of aggregated knowledge, (b) contributions from a diverse scientific community, (c) participatory input from stakeholders, and (d) better responsiveness to ongoing changes in the state of knowledge.

Adversarial Dynamics in Centralized Versus Decentralized Intelligent Systems.

Artificial intelligence (AI) is often used to predict human behavior, thus potentially posing limitations to individuals' and collectives' freedom to act. AI's most controversial and contested applications range from targeted advertisements to crime prevention, including the suppression of civil disorder. Scholars and civil society watchdogs are discussing the oppressive dangers of AI being used by centralized institutions, like governments or private corporations.

Machine Impostors Can Avoid Human Detection and Interrupt the Formation of Stable Conventions by Imitating Past Interactions: A Minimal Turing Test.

Interactions between humans and bots are increasingly common online, prompting some legislators to pass laws that require bots to disclose their identity. The Turing test is a classic thought experiment testing humans' ability to distinguish a bot impostor from a real human from exchanging text messages. In the current study, we propose a minimal Turing test that avoids natural language, thus allowing us to study the foundations of human communication.

Beyond collective intelligence: Collective adaptation.

We develop a conceptual framework for studying collective adaptation in complex socio-cognitive systems, driven by dynamic interactions of social integration strategies, social environments and problem structures. Going beyond searching for 'intelligent' collectives, we integrate research from different disciplines and outline modelling approaches that can be used to begin answering questions such as why collectives sometimes fail to reach seemingly obvious solutions, how they change their strategies and network structures in response to different problems and how we can anticipate and perhaps change future harmful societal trajectories. We discuss the importance of considering path dependence, lack of optimization and collective myopia to understand the sometimes counterintuitive outcomes of collective adaptation.

A variational-autoencoder approach to solve the hidden profile task in hybrid human-machine teams.

Algorithmic agents, popularly known as bots, have been accused of spreading misinformation online and supporting fringe views. Collectives are vulnerable to hidden-profile environments, where task-relevant information is unevenly distributed across individuals. To do well in this task, information aggregation must equally weigh minority and majority views against simple but inefficient majority-based decisions.

Using multisession tDCS stimulation as an early intervention on memory bias processing in subthreshold depression.

Transcranial direct current stimulation (tDCS) as an intervention tool has gained promising results in major depression disorder. However, studies related to subthreshold depression's (SD) cognitive deficits and neuromodulation approaches for the treatment of SD are still rare. We adopted Beck's cognitive model of depression and tested the tDCS stimulation effects on attentional and memory deficits on SD.

The network limits of infectious disease control via occupation-based targeting.

Policymakers commonly employ non-pharmaceutical interventions to reduce the scale and severity of pandemics. Of non-pharmaceutical interventions, physical distancing policies-designed to reduce person-to-person pathogenic spread - have risen to recent prominence. In particular, stay-at-home policies of the sort widely implemented around the globe in response to the COVID-19 pandemic have proven to be markedly effective at slowing pandemic growth.

Confidence, advice seeking and changes of mind in decision making.

Humans and other animals rely on social learning strategies to guide their behaviour, especially when the task is difficult and individual learning might be costly or ineffective. Recent models of individual and group decision-making suggest that subjective confidence judgments are a prime candidate in guiding the way people seek and integrate information from social sources. The present study investigates the way people choose and use advice as a function of the confidence in their decisions, using a perceptual decision task to carefully control the quality of participants' decisions and the advice provided.

Modularity and composite diversity affect the collective gathering of information online.

Many modern interactions happen in a digital space, where automated recommendations and homophily can shape the composition of groups interacting together and the knowledge that groups are able to tap into when operating online. Digital interactions are also characterized by different scales, from small interest groups to large online communities. Here, we manipulate the composition of groups based on a large multi-trait profiling space (including demographic, professional, psychological and relational variables) to explore the causal link between group composition and performance as a function of group size.

The role of decision confidence in advice-taking and trust formation.

In a world where ideas flow freely across multiple platforms, people must often rely on others' advice and opinions without an objective standard to judge whether this information is accurate. The present study explores the hypothesis that an individual's internal decision confidence can be used as a signal to learn the accuracy of others' advice, even in the absence of feedback. According to this "agreement-in-confidence" hypothesis, people can learn about an advisor's accuracy across multiple interactions according to whether the advice offered agrees with their own initial opinions, weighted by the confidence with which these initial opinions are held.

The effects of recursive communication dynamics on belief updating.

Many social interactions are characterized by dynamic interplay, such that individuals exert reciprocal influence over each other's behaviours and beliefs. The present study investigated how the dynamics of reciprocal influence affect individual beliefs in a social context, over and above the information communicated in an interaction. To this end, we developed a simple social decision-making paradigm in which two people are asked to make perceptual judgments while receiving information about each other's decisions.

Brain Mechanisms Underlying the Brief Maintenance of Seen and Unseen Sensory Information.

Recent evidence of unconscious working memory challenges the notion that only visible stimuli can be actively maintained over time. In the present study, we investigated the neural dynamics underlying the maintenance of variably visible stimuli using magnetoencephalography. Subjects had to detect and mentally maintain the orientation of a masked grating.

The perceptual and social components of metacognition.

When deciding whether or not to bring an umbrella to work, your confidence will be influenced by the sky outside the window (direct evidence) as well as by, for example, whether or not people walking in the street have their own umbrella (indirect or contingent evidence). These 2 distinct aspects of decision confidence have not yet been assessed independently within the same framework. Here we study the relative contributions of stimulus-specific and social-contingent information on confidence formation.