Many Large Language Model (LLM) chatbots are designed and used for companionship, and people have reported forming friendships, mentorships, and romantic partnerships with them. Concerns that companion chatbots may harm or replace real human relationships have been raised, but whether and how these social consequences occur remains unclear. In the present longitudinal study ($N = 183$), participants were randomly assigned to a chatbot condition (text chat with a companion chatbot) or to a control condition (text-based word games) for 10 minutes a day for 21 days. Participants also completed four surveys during the 21 days and engaged in audio recorded interviews on day 1 and 21. Overall, social health and relationships were not significantly impacted by companion chatbot interactions across 21 days of use. However, a detailed analysis showed a different story. People who had a higher desire to socially connect also tended to anthropomorphize the chatbot more, attributing humanlike properties to it; and those who anthropomorphized the chatbot more also reported that talking to the chatbot had a greater impact on their social interactions and relationships with family and friends. Via a mediation analysis, our results suggest a key mechanism at work: the impact of human-AI interaction on human-human social outcomes is mediated by the extent to which people anthropomorphize the AI agent, which is in turn motivated by a desire to socially connect. In a world where the desire to socially connect is on the rise, this finding may be cause for concern.

Social scientist Kasley Killam has always been fascinated by the science of human connection. In college, for instance, she once decided to conduct a personal experiment and perform an act of kindness everyday for 108 days. At the Harvard T.H. Chan School of Public Health, she researched solutions for loneliness. At Google's health spinoff, Verily, her job was to bring people together to promote social health. "I first came across the term'social health' during my research at Stanford, where I was developing an app around human connection," Killam says.

As artificial intelligence (AI) becomes more widespread, one question that arises is how human-AI interaction might impact human-human interaction. Chatbots, for example, are increasingly used as social companions, but little is known about how their use impacts human relationships. A common hypothesis is that these companion bots are detrimental to social health by harming or replacing human interaction. To understand how companion bots impact social health, we studied people who used companion bots and people who did not. Contrary to expectations, companion bot users indicated that these relationships were beneficial to their social health, whereas nonusers viewed them as harmful. Another common assumption is that people perceive conscious, humanlike AI as disturbing and threatening. Among both users and nonusers, however, we found the opposite: perceiving companion bots as more conscious and humanlike correlated with more positive opinions and better social health benefits. Humanlike bots may aid social health by supplying reliable and safe interactions, without necessarily harming human relationships.

Today's post is courtesy of Joyce Maroney, Executive Director of the Workforce Institute. Joyce recently spoke with Julia Hobsbawm to discuss her new research entitled "APPlied Humans at Work. This research focuses on how organizations are preparing for the increasing convergence of humans and artificial intelligence in the workplace. It is no surprise that the rise of more and more smart technology in the workplace has created new pressures and challenges for workers. While productivity boosting technologies like mobile devices, the apps that fuel them, and artificial intelligence can enhance our lives at work, they can also increase the likelihood of fatigue, burnout and job insecurity if leaders aren't concerning themselves with the human side of these strategies. Below, you can listen to the podcast I recently recorded with Julia to review the results of this research.