This community of practice elevates participants’ comprehension of performance measurement and metrics within the realm of business. Here, academic luminaries and industry experts converge to scrutinize the latest methodologies, tools, and best practices in quantifying success and driving strategic decision-making. Participants immerse themselves in the realms of experimentation, data analytics, and benchmarking to unearth profound insights that catalyze enhanced organizational and financial performance. Together, they explore how to advance and harness the formidable power of data-driven decision-making, elevating businesses to new echelons of excellence.
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 […]
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 […]
As artificial intelligence (AI) continues to advance rapidly, its potential to transform strategic decision-making processes in business is becoming increasingly apparent, but how can strategists be sure their AI tools are getting it right? A recent study, “Generative Artificial Intelligence and Evaluating Strategic Decisions”, by researchers Anil R. Doshi, Assistant Professor of Strategy and Entrepreneurship […]
As artificial intelligence systems become more prevalent in our daily lives, ensuring these technologies are fair and representative of diverse populations is increasingly critical. A recent study, “Multi-Group Proportional Representation in Retrieval”, conducted by Flavio du Pin Calmon, an Associate Professor of Electrical Engineering at Harvard’s John A. Paulson School of Engineering and Applied Sciences, […]
