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HBS AI Content & Learning

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Explanations on Mute: Why We Turn Away From Explainable AI

We live in an age where the call for transparent or “Explainable AI” (XAI) has never been louder. Businesses agree, with 85% believing transparency is critical to winning consumer trust. [1] Given this consensus, it seems reasonable to assume that when an explanation for a high-stakes AI decision is available, people will naturally seek it […]

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Navigating the Promise and Peril of AI Companions for Older Adults

What happens when the same technology powering a customer service chatbot becomes a daily companion for someone losing their memory? In the new Nature Mental Health Comment article, “AI Companions for Dementia,” Julian De Freitas, Assistant Professor of Business Administration at Harvard Business School and Associate at the Harvard Business School AI Institute, discusses how […]

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Using AI to Identify Climate Innovation

For decades, the business conversation around climate change has been focused on how to manage, mitigate, and withstand the risks and downsides. But what if there’s a more important story about opportunity that we’ve been missing? In the new article, “Tracking Business Opportunities for Climate Solutions Using AI in Regulated Accounting Reports,” published in Nature […]

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The Science of Digital Flourishing

What if we treated mental health the way we treated physical fitness—not waiting for a crisis, but building strength as a habit? The new working paper “AI for Proactive Mental Health: A Longitudinal, Multi-Institutional Trial,” by a team of authors including Julian De Freitas, Assistant Professor of Business Administration at Harvard Business School and Associate […]

Drawing the Line on AI Usage in the Workplace

As AI systems increasingly outperform humans across a range of tasks, the economic logic seems clear: more capable, more cost-effective AI should lead to widespread automation. The new Harvard Business School working paper, “Performance or Principle: Resistance to Artificial Intelligence in the U.S. Labor Market,” co-authored by Simon Friis, postdoctoral fellow at the Laboratory for […]

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Persuasion Bombing: Why Validating AI Gets Harder the More You Question It

Imagine you’ve asked ChatGPT to analyze financial data for a critical business decision. Something about its calculations seems off, so you push back, but instead of acknowledging limitations, the AI doubles down by presenting elaborate justifications with data points and reassuring language. At this point, has the AI won you over? This isn’t a hypothetical […]

Who Benefits When Bots Get Better? New Research on Skill Inequality

Will artificial intelligence widen the gap between your best and worst performers, or will it be the great equalizer? A new paper, “Automation Experiments and Inequality,” from Kyle Myers, Principal Investigator at the Laboratory for Innovation Science at Harvard (LISH) within the Harvard Business School AI Institute, and Seth Benzell at Chapman University, reveals that […]

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It Feels Like AI Understands, But Do We Care? New Research on Empathy

Picture this: you receive a well-crafted, deeply understanding message about a personal struggle you’ve shared. It acknowledges your emotions, offers thoughtful support, and demonstrates genuine care. Now imagine learning that response came from an AI chatbot, not another human. Would that change how you felt about the interaction? As AI technology grows more sophisticated, LLMs […]

One More Thing… How AI Companions Keep You Online

You don’t just slam a laptop shut on a friend. You say goodbye. That small social ritual turns out to be a powerful behavioral cue for AI companions, and an opportunity to keep you engaged longer. The new working paper “Emotional Manipulation by AI Companions,” co-authored by Julian De Freitas, Assistant Professor of Business Administration […]

When Giants Stumble: What Multiplication Reveals about AI’s Capabilities

Despite its impressive capabilities in reasoning, planning, and content generation, GenAI still struggles with the kind of mathematics that grade school students are expected to learn and master. What influence do transformers, the core architecture behind Large Language Models (LLMs), have in this problem, and can it be solved? In the new paper “Why Can’t […]

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