Voice-controlled digital assistants like Siri and Alexa have become more and more adept at responding appropriately to user requests — but enabling users to hold a real conversation with such bots remains a huge challenge. Anyone who’s played around with these AIs knows there’s a world of difference between, say, getting the bot play a requested song from your music library and engaging the bot in a satisfying exchange of opinions about that song.
That’s just one example of the difficulty of conversational AI, a field that has raised AI researchers’ attention in recent years through Amazon’s Alexa Prize Challenge, which since 2017 has pit university teams against one another to build the most engaging social chatbot. Under the supervision of faculty advisor Christopher Manning, who also directs the Stanford Artificial Intelligence Lab and serves as an associate director of the Stanford Institute for Human-centered AI, Stanford’s team placed second in the most recent competition and just recently made its chatbot’s code available to the public.
Study co-lead Abi See is a 2018 Lieberman Fellow.