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 […]
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 […]
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 […]
The promise of Generative AI (GenAI) often sounds like this: give any employee access to AI tools, and they’ll suddenly be able to perform tasks outside their domain of expertise with remarkable proficiency and speed. As discussed in the new working paper “The GenAI Wall Effect: Examining the Limits to Horizontal Expertise Transfer Between Occupational […]
As businesses continue to navigate the complexities of product development and innovation, generative AI has the potential to be a powerful new tool for market research. In their recent article for the Harvard Business Review, “Using Gen AI for Early-Stage Market Research,” Ayelet Israeli, co-founder of the Customer Intelligence Lab at the Digital Data Design […]
In the ever-evolving AI landscape, are you truly ready to integrate new technologies effectively, taking advantage of the radical opportunities they present for productivity increases and better operating models? Karim R. Lakhani, Dorothy and Michael Hintze Professor of Business Administration at Harvard Business School and faculty chair and co-founder of the Digital Data Design (D^3) […]
On May 13, 2025, the Digital Data Design (D^3) Institute at Harvard held a university-wide Generative AI Symposium in partnership with the Office of the Vice Provost for Research, the Office of the Vice Provost for Advances in Learning, the Faculty of Arts and Sciences, the Harvard John A. Paulson School of Engineering and Applied […]
As artificial intelligence systems become increasingly complex, understanding their behavior has become a critical challenge for businesses and researchers alike. In a recent preprint paper, “Towards Unified Attribution in Explainable AI, Data-Centric AI, and Mechanistic Interpretability,” authors Shichang Zhang, a postdoctoral fellow in the Trustworthy AI Lab at the Digital Data Design (D^3) Institute at […]
Large language models (LLMs) have exhibited remarkable capabilities across various domains; from finance to healthcare, education to content creation, their potential seems limitless. However, as businesses increasingly embrace these powerful tools, understanding their nuances becomes crucial. One critical aspect is fine-tuning, a process that adapts LLMs to specific tasks. While fine-tuning promises enhanced performance, research […]
In their recent blog post, “Partnering Data Science and Social Impact at Howard University”, D^3’s blackbox Lab, led by James Riley, Principal Investigator of the lab and Assistant Professor at Harvard Business School, showcases how their partnership with Howard University empowers students and faculty to leverage data-driven solutions for addressing real-world challenges in underrepresented communities. […]
