Research Statement: My research is focused on developing collaborative agents for mixed-initiative systems that use both human
and machine computation to solve problems quickly and reliably. I co-developed Legion, a system for real-time
collaborative control of user interfaces. Legion employs a model that lets the crowd, a dynamic group of workers of
varying reliability, act as a single reliable worker. I am currently working to develop human-machine hybrid versions
of traditional AI solvers that are robust enough to be deployed in the real world. These systems are designed to
work now because of crowd input but so that AI handle increasingly larger portions of the workload as it advances.
Legion
Legion enables real-time crowd control of existing interfaces by
making the crowd act as a single, more reliable, worker. While most current crowdsourcing systems
enable offline human computation, Legion utilizes a continuous closed-loop interface with workers
to allow real-time control. Each worker functions independantly, and Legion
combines their input into a single control stream using a selectible input mediator.
Real-time Crowdsourcing for AT
Assistive techonology (AT) aims to help disabled users
by enabling greater independance. However, tasks such as supplementing the users sensing
capability is often closely tied to cognition, and as such, requires greater amounts of
intelligence then currently available. We use the crowd to support greater functionality
in these systems by leveraging human computation to fill in where automated systems and AI fall short.




