A scalable machine leaning approach to improving human decision making
cyvy Research Project
As technological development accelerates, millions of low-skilled workers are destined to lose their jobs to automation. To mitigate the resulting societal problems, this project aims to develop a scientific and technological foundation for rapidly and inexpensively teaching people the skills they will need to stay or become employable in the workplace of the future, which will be increasingly cognitively demanding.
Building on computational models of human learning and decision-making, Falk Lieder’s group proposes a general and scalable approach that leverages machine learning and artificial intelligence to teach workers the strategies they will need to meet the self-management challenges of the knowledge economy.
The researchers will test this approach by developing a series of intelligent tutors that develop and teach optimal decision strategies for increasingly realistic scenarios. They will illustrate the potential of this approach by developing and evaluating a simulation-based intelligent tutor that teaches high-level employees, freelancers, entrepreneurs, and academics far-sighted strategies for planning their projects, prioritizing their tasks, and managing themselves more effectively.