High Signal: Data Science | Career | AI

Chiara Farronato, an Associate Professor at Harvard Business School specializing in digital platforms, shares insights on the transformation of sectors through companies like Airbnb and Uber. She highlights the critical need for effective communication between managers and data scientists to foster better collaboration. Chiara discusses the importance of bridging gaps in understanding, particularly in product management, and explores the challenges traditional industries face in adopting data-driven cultures. Her experiences offer valuable lessons for business leaders navigating platform-based innovation.

Hugo Bowne-Anderson chats with Andrew Gelman, a Columbia University professor specializing in statistics and political science. They delve into the necessity of high-quality data and the vital role of causal inference in decision-making. Andrew emphasizes the importance of simulations to avoid misleading conclusions, while also discussing the significance of a coder’s mindset in statistical analysis. The conversation wraps up with insights on voting's impact and the challenges of generalizing from sample data in polling, shedding light on the complexities of statistical interpretation.

Michael Jordan, a leading Professor at UC Berkeley, dives into the future of AI and its planetary-scale potential. He discusses the integration of machine learning, computer science, and economics to tackle complex challenges. The conversation highlights the issues of uncertainty in AI, the importance of collective intelligence in decision-making, and how reliable data can enhance predictive accuracy. Jordan emphasizes the need for responsible technology that positively impacts society, balancing innovation with the necessity for authentic human creativity.