Today we’re joined by Robert Osazuwa Ness, a senior researcher at Microsoft Research, to break down the latest trends in the world of causal modeling. In our conversation with Robert, we explore advances in areas like causal discovery, causal representation learning, and causal judgements. We also discuss the impact causality could have on large language models, especially in some of the recent use cases we’ve seen like Bing Search and ChatGPT. Finally, we discuss the benchmarks for causal modeling, the top causality use cases, and the most exciting opportunities in the field.  The complete show notes for this episode can be found at twimlai.com/go/616.

Today we’re joined by Robert Osazuwa Ness, a senior researcher at Microsoft Research, Professor at Northeastern University, and Founder of Altdeep.ai. In our conversation with Robert, we explore whether large language models, specifically GPT-3, 3.5, and 4, are good at causal reasoning. We discuss the benchmarks used to evaluate these models and the limitations they have in answering specific causal reasoning questions, while Robert highlights the need for access to weights, training data, and architecture to correctly answer these questions. The episode discusses the challenge of generalization in causal relationships and the importance of incorporating inductive biases, explores the model's ability to generalize beyond the provided benchmarks, and the importance of considering causal factors in decision-making processes.The complete show notes for this episode can be found at twimlai.com/go/638.

Madeleine Daepp, a Microsoft senior researcher specializing in generative AI's political impact, and Robert Osazuwa Ness, who focuses on the reliability of large language models, delve into AI's role in democracy. They discuss the challenges of disinformation, especially during elections, and emphasize the innovations in Taiwan and India’s voting systems. The conversation also highlights the dual-edged nature of AI—its potential benefits and risks—alongside the necessity for media literacy and innovative solutions to combat misinformation.