A comprehensive new review published in the Journal of Management synthesizes decades of research to understand the epidemic of workplace loneliness. By analyzing 233 empirical studies, researchers from Portland State University have identified how workplace conditions contribute to isolation and offer evidence-based paths to reconnection.

The research emphasizes that loneliness is distinct from social isolation. While isolation is about being alone, loneliness is the subjective feeling that one’s social relationships are deficient—meaning employees can feel deeply lonely even in a crowded office.

"Given the connection between workplace characteristics and loneliness, organizations should consider that loneliness is not a personal issue, and instead is a business issue," said Berrin Erdogan, professor of management at Portland State. "Businesses have an opportunity to design jobs and organizations in a way that will prioritize employee relational well being."

What kinds of marketing messages are effective — and what makes people believe certain political slogans more than others? New research from the University of California San Diego Rady School of Management explores how people constantly evaluate whether messages are true or false and finds that a surprisingly small ingredient — whether a word has an easy opposite — can shape how confident people feel when deciding whether a message is true.

Scientists have uncovered a previously unknown cluster of brain cells that may help explain differences in social behavior between males and females. The small neural circuit appears to function like an on–off switch, showing a striking pattern of activity that differs sharply by sex, an unusually clear contrast compared with most known brain sex differences, which tend to be more subtle and overlapping. Researchers also found that the circuit’s activity shifts with social and reproductive status, suggesting the brain may use this mechanism to adapt behavior across key life stages. 

In a Policy Forum, Daniel Schroeder and colleagues discuss the risks of malicious “Artificial Intelligence (AI) swarms”, which enable a new class of large-scale, coordinated disinformation campaigns that pose significant risks to democracy. Manipulation of public opinion has long relied on rhetoric and propaganda. However, modern AI systems have created powerful new tools for shaping human beliefs and behavior on a societal scale. Large language models (LLMs) and autonomous agents can now generate vast amounts of persuasive, human-like content. When combined into collaborative AI Swarms – collections of AI-driven personas that retain memory and identity – these systems can mimic social dynamics and easily infiltrate online communities, making false narratives appear credible and widely shared. According to the authors, unlike earlier labor-intensive influence operations run by humans, AI systems can operate cheaply, consistently, and at tremendous scale, transforming once isolated disinformation efforts into persistent, adaptive campaigns that pose serious risks to democratic processes worldwide. Here, Schroeder et al. discuss the technology underpinning these malicious systems and identify pathways through which they can harm democratic discourse through widely used digital platforms. The authors argue that defense against these systems must be layered and pragmatic, aiming not for total prevention of their use, which is highly unlikely, but for raising the cost, risk, and visibility of manipulation. Because such efforts would require global coordination outside of corporate and governmental interests, Schroeder et al. propose a distributed “AI Influence Observatory,” consisting of a network of academic groups, nongovernmental organizations, and other civil institutions to guide independent oversight and action. “Success depends on fostering collaborative action without hindering scientific research while ensuring that the public sphere remains both resilient and accountable,” write the authors. “By committing now to rigorous measurement, proportionate safeguards, and shared oversight, upcoming elections could even become a proving ground for, rather than a setback to, democratic AI governance.”