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Industry 4.0

It is no surprise that the inception of the Industrial Revolution remains an epicenter for innovation and growth in the digital economy. Smart factories, advancements in supply chain management, and transformations of traditional manufacturing relationships – all are markers of the new face of industry in the digital age.

Enhancing AI through Self-Verification

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 […]

Croissant: A Game-Changing Metadata Format for Machine Learning Datasets

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 […]

The Creative Edge: How Human-AI Collaboration is Reshaping Problem-Solving

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 […]

Music in the Digital Age: Empowering Creators

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 […]

Your Guide to the blackbox Lab

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. […]

Understanding and Addressing Managerial Sabotage in Organizations

In today’s competitive corporate landscape, the workplace can be a battleground of ambition and performance. While healthy competition can fuel innovation and productivity, research (“Determinants of Top-Down Sabotage”) by Hashim Zaman, Post-Doctoral Fellow at the Laboratory for Innovation Science at Harvard (LISH) and Karim R. Lakhani, Professor of Business Administration at Harvard Business School, founder […]

The Future of Decision-Making: How Generative AI Transforms Innovation Evaluation

As businesses grapple with an ever-growing volume of ideas, products, and solutions to evaluate, decision-making processes are being reshaped by artificial intelligence (AI). Generative AI, in particular, has emerged as a game-changer in creative problem-solving and evaluation, as demonstrated by a recent field experiment described in the working paper “The Narrative AI Advantage? A Field […]

Data Science and Social Impact: A collaboration between Howard University and D^3’s Blackbox Lab

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. […]

Bridging the Gap Between Understanding and Control: Insights into AI Interpretability

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 […]

Revolutionizing Data Privacy: Machine Unlearning in Action

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 […]

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