Despite decades of initiatives to address healthcare inequities in the U.S., disparities across race, gender, geography, and income remain stubbornly persistent.

Workplace stress, on the rise for decades, has been treated by many organizations as a personal issue instead of a business-critical risk that merits executive oversight.

We propose that AI-driven wellness apps powered by large language models can foster extreme emotional attachments and dependencies akin to human relationships—posing risks like ambiguous loss and dysfunctional dependence—that challenge current regulatory frameworks and necessitate safeguards and informed interventions within these platforms.

How companies market their AI systems affects the repercussions they face when their products fail. Marketers must promote their AI products with potential failure in mind.

Based on a review of relevant literature, we propose that the proliferation of AI with human-like and social features presents an unprecedented opportunity to address the underlying cognitive and affective drivers of prejudice.

Chatbots are now able to engage in sophisticated conversations with consumers in the domain of relationships, providing a potential coping solution to widescale societal loneliness.

This study explores public preferences for algorithmic and human decision-makers (DMs) in high-stakes contexts, how these preferences are shaped by performance metrics, and whether public evaluations of performance differ depending on the type of DM.

For as long as there has been work, there has been a “future of work,” through humans’ ingenuity and drive to get things done easier, faster, and better.

AI companion applications—designed to serve as synthetic interaction partners—have recently become capable enough to reduce loneliness, a growing public health concern.

As consumers increasingly interact with AI applications specialized for social relationships, what is the nature and depth of these relationships among actual users, and can company actions influence these dynamics? We find that active users of the US-based AI companion, Replika, feel closer to their AI companion than even their best human friend, and anticipate mourning the loss of their AI companion more than any other technology.

Research involving multiple experiments found that consumers have biased views of their driving abilities relative to those of other drivers and automated vehicles.

From Apple to Merck to Wikipedia, more and more organizations are turning to crowds for help in solving their most vexing innovation and research questions, but managers remain understandably cautious.

We present the results of a field experiment conducted at Harvard Medical School to understand the extent to which search costs affect matching among scientific collaborators.

Mid-career women are often surprised by the levels of bias and discrimination they encounter in the workplace, especially if they’ve successfully avoided it earlier in their careers.

As machine learning black boxes are increasingly being deployed in critical domains such as healthcare and criminal justice, there has been a growing emphasis on developing techniques for explaining these black boxes in a post hoc manner.

Agrowing number of companies are engaging with sustainability issues, driven by a greater aware -ness of environmental and social problems and a changing set of institutions and social expec -tations about the role of business in society.