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,” […]
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 […]
A recent post, “Shaping the Future of Music in the Creator Economy,” from D^3 blackbox Lab, described how the music industry is undergoing a transformation driven by digital tools and shifting business models. The blog outlined a panel discussion hosted by James Riley, Principal Investigator of the lab and Assistant Professor at HBS, that featured […]
In a recent blog post, D^3’s blackbox Lab formally introduced itself to its readership, highlighting its mission to explore the intersection of race, culture, technology, and business in digital spaces. Led by James Riley, Assistant Professor at Harvard Business School, the Lab focuses on understanding value creation in digital market platforms and addressing historic inequities. […]
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. […]
As large language model (LLM) systems grow in complexity, the challenge of ensuring their outputs align with human intentions has become critical. Interpretability—the ability to explain how models reach their decisions—and control—the ability to steer them toward desired outcomes—are two sides of the same coin. “Towards Unifying Interpretability and Control: Evaluation via Intervention”—research by Usha […]
D^3’s blackbox Lab, led by James Riley, Principal Investigator of the lab and Assistant Professor at Harvard Business School, recently featured a blog post highlighting key points from a discussion with Lewis Long, Founder and President of Long Gallery Harlem and Harvard Business School graduate (‘91). The blog post, “A Vision for Cultural Innovation and […]
In today’s data-driven world, businesses face the dual challenge of leveraging vast datasets to gain insights while ensuring compliance with stringent data privacy regulations. The concept of machine unlearning, a method for efficiently removing the influence of specific data points from machine learning models, represents a paradigm shift in managing data responsibly. Recent research explores […]
