By Chris Sciacca
AAAI recognizes Watson for what it can, and will do
The Association for the Advancement of Artificial Intelligence (AAAI) awarded IBM Research’s Watson team the 2013 Feigenbaum Prize “for recognizing and encouraging outstanding Artificial Intelligence research advances that are made by using experimental methods of computer science.” IBM Watson Technologies Director Dr. Eric Brown, and his colleagues Drs. Chris Welty and Jennifer Chu-Carroll accepted the award, and donated the monetary portion of the prize to Wikimedia, on behalf of the team.
Brown, Welty, and Chu-Carroll have spoken extensively about Watson since its Jeopardy! win in 2011, with Brown most-recently creating a TED-Ed lesson on cognitive computing that featured Watson’s latest work. They answered a few questions about their work in AI, what’s next for Watson, and what it means to win the Feigenbaum Prize.
Watson now works in healthcare and customer service. What is the team “teaching” Watson, today?
Our team continues to focus on the medical domain to drive Watson’s improvements. We like working in this area because one, it has important societal benefits, but also because of how it forces us to think about how to develop Watson’s technology.
Healthcare problems are complex. And every health issue a patient deals with has years’ worth of background information associated with it. Physicians can’t have all of this information assimilated into their brains. Watson relieves them of that cognitive burden by accessing that information – helping them make more informed decisions.
As we develop new and better ways to support how a doctor makes a decision, we’re also thinking about how the system can replicate across other domains. Because new domains require system modifications, a big part of what we’re doing is coming up with automatic techniques that adapt to these new domains.
Remember, when Watson played Jeopardy, while the clues reached across subjects and required understanding of wordplay, ultimately it needed just one correct answer. Applying the technology in something like healthcare is actually a dialogue. Watson produces possible answers, ranked in order of which ones it thinks are most correct, surfaces evidence of why it thought of those answers and can incorporate feedback from the user.
It’s an interesting challenge for us to make Watson a more natural problem-solving collaborator.
Watson harnessed an amazing amount of already-available computer horsepower to play Jeopardy! What will be needed, from a systems perspective, to advance AI?
One of the reasons Watson succeeds is that it’s an architecture designed to allow the integration of different kinds of analytics techniques. From a software engineering point of view, this lets experts from all different backgrounds to contribute to the system. To that end, it allows our team to be very creative.
This ability gets to one of the reasons for earning the Feigenbaum Prize. The prize recognizes Artificial Intelligence advances based on an experimental approach that emphasizes architectures, systems, and applications to real world problems. We’ve certainly followed that approach with Watson and believe that an experimental approach, especially one that leverages big data and a hybrid of rule-based and statistical techniques, will continue to be the best way to drive advances in AI.
Edward Feigenbaum is a pioneer in AI research. What does it mean to the team to earn this Prize? And why donate the prize money to the Wikimedia Foundation?
We were pleasantly surprised. It’s an honor, and particularly significant that the entire AI community is recognizing Watson’s accomplishment. The fact that the Prize looks for advances in AI based on an overall systems approach is an affirmation of our approach to applying Watson to solve problems.
We chose the Wikimedia foundation to recognize the contribution that Wikipedia and WikiData made to the Watson system that won on Jeopardy! The quality and coverage of Wikipedia was well suited as a source for answers to Jeopardy!’s clues.