In an era dominated by oceans of data, D^3 hosts a community of practice that offers a discerning perspective on the intricate tapestry of data governance, privacy, security, and regulatory compliance. Participants in this community engage in a comprehensive discourse amongst industry experts, exploring responsible AI and the dynamic realm of regulations, industry standards, and best practices. The community explores how to harness the immense potential of data for strategic business advancement while ensuring the safeguarding of sensitive information, upholding privacy rights, and establishing or integrating resilient and ethical frameworks that underpin success in data-driven endeavors.
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 […]
As digital platforms continue to reshape markets, the intersection of competition, innovation, and regulation demands nuanced understanding. On April 17–18, 2025, Digital Data Design Institute’s Platform Lab and Harvard Business School hosted the third annual Digital Competition and Tech Regulation Conference, convening over 70 leading academics, industry practitioners, and policymakers from around the world. With […]
As generative AI transforms the business landscape, a concerning trend demands immediate attention from executives and policymakers alike. In the recent Harvard Business School (HBS) working paper, “Global Evidence on Gender Gaps and Generative AI,” authors Nicholas G. Otis, PhD candidate at the Berkeley Haas School of Business; Solène Delecourt, Assistant Professor at the Berkeley […]
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 […]
