D^3 Insights & Experiences

As AI continues to evolve at a breakneck pace, the quest for aligning these systems with human values has become paramount. However, a recent study, “More RLHF, More Trust? On The Impact of Preference Alignment on Trustworthiness”, by Aaron J. Li, a master’s student at the Harvard John A. Paulson School of Engineering and Applied […]

As the global economy grapples with the pressing challenges of climate change, a new paradigm is emerging in the world of finance and investment. In their working paper, “Climate Solutions, Transition Risk, and Stock Returns,“ researchers Shirley Lu, Assistant Professor of Business Administration at Harvard Business School (HBS) and an affiliate of the HBS Digital […]

In an era where artificial intelligence (AI) increasingly shapes our digital landscape, the concept of “machine unlearning” (ML) has emerged as a potential solution to various challenges in AI governance. First authors A. Feder Cooper, Faculty Associate at The Berkman Klein Center for Internet & Society at Harvard University; Christopher A. Choquette-Choo, Research Scientist at […]

A recent post from the blackbox Lab at Harvard Business School’s Digital Data and Design (D^3) Institute, “Bridging the Care Gap: How RE-Assist Enhances Healthcare Access,” featured a conversation between James W. Riley, Principal Investigator of the lab and Assistant Professor of Business Administration at HBS, and Ashley Barrow, Principal Product Owner of RE-Assist. Their […]

In an era where data is constantly evolving and privacy concerns are paramount, the work of Monika Henzinger, a Professor at the Institute of Science and Technology in Austria; Roodabeh Safavi, a PhD student at the Institute of Science and Technology in Austria; and Salil Vadhan, the Vicky Joseph Professor of Computer Science and Applied […]

The business world is increasingly aware of the risks and opportunities climate change presents. Companies are developing and commercializing new products and services that contribute to a low-carbon economy, or “climate solutions” (CS). In the recent HBS working paper, “The Financial Anatomy of Climate Solutions: A Large Language Model Approach to Company Classification and Analysis,” […]

As businesses increasingly adopt large-scale AI models, optimizing training efficiency is crucial. In “How Does Critical Batch Size Scale in Pre-training?”, Hanlin Zhang and a group of colleagues (see below for author details) explore critical batch size (CBS)—the threshold at which data parallelism, which distributes training data across multiple processors, stops yielding significant returns from […]

In the rapidly evolving field of artificial intelligence (AI), a recent study by Yuda Song, PhD student at Carnegie Mellon University; Hanlin Zhang, PhD student at Harvard; Sham M. Kakade, Co-director of the Kempner Institute at Harvard, and a team of researchers (see the Meet the Authors section for details) explores the concept of AI […]

Data is a vital input for machine learning (ML), but data management remains a significant challenge. A new metadata format called Croissant, introduced by Mubashara Akhtar, a PhD student at King’s College London, Satyapriya Krishna, a PhD student at the Harvard School of Engineering and Applied Sciences (SEAS) and the Trustworthy AI Lab at the […]

As artificial intelligence (AI) capabilities rapidly advance, organizations are exploring new ways to leverage these technologies for creative problem-solving and innovation. A recent HBS working paper, “The Crowdless Future? Generative AI and Creative Problem Solving”, – by Léonard Boussioux, Assistant Professor at the University of Washington; Jacqueline N. Lane, Assistant Professor at Harvard Business School […]