Helping people, teams, and organizations achieve important goals may be one of the most effective ways to increase productivity and promote human progress. To achieve their goals, many organizations employ financial incentives or game elements, such as points, levels, and badges, to motivate employees to become more productive. This project develops a theoretical foundation and computational tools for designing better incentive structures to help people achieve their goals. The project connects the crucial challenges of goal achievement studied in psychology to the computational methods from artificial intelligence that can be used to solve them. By bridging this gap the project provides a new way for artificial intelligence to communicate with people and empowers them to overcome the motivational obstacles and cognitive limitations that might otherwise prevent them from making good decisions.
At the heart of this project is a mathematical theory for optimizing incentive structures to help people make better decisions in complex, partially unknown environments. This theory is used as the basis for two cognitive prostheses that leverage artificial intelligence and gamification to help people achieve their goals: an intelligent to-do list gamification system that helps people become more productive and procrastinate less and an app that reinforces good habits. Field experiments are used to evaluate whether these cognitive prostheses are effective in the real world, working towards the development of intelligent systems that can aid people in setting and achieving their goals.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
