Teaching

Artificial Intelligence (AI) is changing how value is created and captured in the economy.

We're witnessing a paradigm shift: You have your direct labor, the work that you signed up to do for your employer or the work you do to build your own business. At the same time, your work generates data about your work, including your process, your expertise and your style. Your employees and mentees are also generating data about their work while on-the-job. In the era of AI, these data are valuable and in some instances, more valuable than the direct work itself. These data allow our capabilities to be recombined with other capabilities, enhanced over time, duplicated at little cost and potentially commoditized to destroy its uniqueness and value if unprotected. In light of this paradigm shift, the way we create and claim value in the labor market must also change.

This is a course that considers how you should navigate your career and develop and value your expertise. The lessons will be useful to anyone entering today's labor market, entrepreneurs starting new ventures, and investors. Students will develop their strategy through labor economics frameworks, practice in the field codifying expertise along-side experts, as well as through exposure to guest speakers witnessing the labor market transition.

To get a sense for the fundamental shift in navigating today's labor market, consider the following public example of expertise codification: in Tom Hank's film Here (2024), an AI model of Tom's acting expertise based on past footage can be used to face-swap and age him such that Tom Hanks himself is no longer necessary in the filming process, and the film can capture Tom Hanks ages 18 to 80. Using similar technology, the emails, presentations and digital trail of your judgement on-the-job can be transformed into a model of your expertise that is disembodied, scaled, recombined and sold like an asset. How should you manage, price and negotiate over the data generated by your work? What will be different about the organization you join? What if instead, you find yourself the owner of data generated by people you employ? How should you use it to remain competitive? What are the legal, ethical and social implications of the choices you make? We will use theory and evidence from economics, law, and psychology to understand what your best strategy is, and to anticipate how the labor market and economy will be transformed by these negotiations in aggregate.