The past decade has seen extraordinary advances in AI and data-driven decision-making. These tools now shape, and often govern, nearly every dimension of how businesses and individuals operate. Yet alongside their promise, they have revealed themselves to be a mixed blessing, at best: algorithms interact with society in subtle ways that generate feedback loops, amplify bias, and create unintended consequences. This seminar dives headfirst into these challenges. We’ll grapple with how firms can make sense of machine-learning predictions and act on them responsibly, what it really takes to keep data fair and unbiased, and how generative AI and large language models are transforming how organizations create value and compete. We’ll unpack why misinformation races ahead of truth on social media, driven by algorithms built to maximize engagement and amplify outrage. We’ll also examine the societal tradeoffs of automation, the human-technology interface, the emerging governance challenges around compute regulation and global AI supply chains, and the use of AI in the public sphere (policing, courts, and government services), where algorithms can shape civic life as powerfully as they shape markets. The course is designed as an interactive forum: students will lead discussions, analyze case studies, and connect academic research to real-world practice. Like all Research-to-Practice seminars, the emphasis is on developing analytical rigor and critical perspective managers need to navigate the increasingly complex intersection of AI and society. This course meets the Ethics and Social Responsibility (ESR) requirement.