An Interactive Intelligent Advisor Roger Schank. Ray Bareiss, Chris Riesbeck, Wendy Lehnert The incredible amount of hype that Artificial Intelligence is currently receiving is mystifying to those of us who have spent our lives as AI researchers. "Novel written by Al wins contest in Japan" is the headline you see until later you find out it's not quite true. Or "Al wins at Go" until later you find out that this was just a computationally intensive neural net which is quite different than true artificial intelligence. Or "Watson wins jeopardy" until later you find out that Watson can barely understand any English sentences. The main issue in Al has always been the same: There are those who think that any program that beats a chess or Go master, no matter how, is "intelligent," and there are others who think that being able to do massive computation does not have very much to do with intelligence. The latter group, to which we belong, would like to build systems that really do display some intelligence. What would that look like? For one thing intelligent entities can explain what they did and why they did it. For another, intelligent entities can communicate through natural language and actually can at least act like they understand what they are being told. Intelligent four year olds don't understand everything you say to them, but they do have goals of their own, plans to achieve those goals, ways of explaining their actions, and ways of understanding what you might want from them. Let's take this as our basis for defining what a real Al system should be. Now let's ask the question: What can we build now that would be both intelligent and useful? Whatever we build must have three distinct capabilities that correspond to three integral parts of human intelligence. These capabilities are: 1. Natural language comprehension 2. A model of the world 3. An appropriately indexed memory of experience and expertise. Let's talk about each in a bit mor