People Analytics

3 Credits · Level: Undergraduate

Generative AI is changing how people make decisions and you will gain a competitive advantage in any industry if you hone your ability to critically assess metrics and clearly communicate data-driven insights. We connect themes from *Moneyball* to psychology and behavioral economics research. You will leverage class topics to propose an algorithm in order to solve a “big-picture” societal or business problem (no math necessary). Then, you will develop your idea to strategize how to best deploy your proposed algorithm. How will your algorithm solve real-world people problems? TOPICS: Generative AI & The Future of Work, Human Judgment, The Last Mile Problem, Moneyball, Collective Intelligence, Algorithmic Societal Risks and Solutions, AI Safety: Ethics & the Greater Good. COURSE GOAL: *Data analytics needs psychology* to understand how people respond to advice from GenAI and algorithms and improve decision-making in the age of big data and automation. COURSE OBJECTIVES: Empirical Literacy 1) Critically evaluate evidence, 2) Identify and scope consequential problems to build an algorithmic or GenAI start-up, 3) Identify the most appropriate metrics to leverage data effectively for your venture, 4) Persuasively communicate insights by pitching your venture