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Machines Like Us

Machines Like Us interviews: Ben Goertzel

Saturday, 20 October 2007

As the Singularity Institute's Director of Research, Ben Goertzel, Ph.D., is responsible for overseeing the direction of the Institute's research division. He has contributed over 70 publications, concentrating on cognitive science and AI, including Chaotic Logic, Creating Internet Intelligence, Artificial General Intelligence (edited with Cassio Pennachin), and Hidden Pattern. He is chief science officer and acting CEO of Novamente, a software company aimed at creating applications in the area of natural language question-answering.

He also oversees Biomind, an AI and bioinformatics firm that licenses software for bioinformatics data analysis to the NIH's National Institute for Allergies and Infectious Diseases and CDC. Previously, he was founder and CTO of Webmind, a 120+ employee thinking-machine company. He has a Ph.D. in mathematics from Temple University, and has held several university positions in mathematics, computer science, and psychology, in the US, New Zealand, and Australia.

Interview conducted by Norm Nason.

MLU: It's a pleasure being able to talk to you, Ben. Thanks for joining me.

BG: Thanks for having me. I've enjoyed your site for a while, so it's a pleasure to be an active participant.

MLU: Perhaps we can begin by defining a few terms. What is intelligence? What is artificial general intelligence?

BG: Sure. Whenever I talk about AI I like to make the distinction between

  • narrow AI – programs that solve particular, highly specialized types of problems
  • general AI or AGI – programs with the autonomy and self-understanding to come to grips with novel problem domains and hence solve a wide variety of problem types

Unlike an AGI, a narrow AI program need not understand itself or what it is doing, and it need not be able to generalize what it has learned beyond its narrowly constrained problem domain.

Pretty much the whole field of AI deals with narrow-AI systems -- systems that do one or another special thing intelligently. But if you want to apply such a system to a new sort of problem, you need to change the program itself -- these programs aren't flexibly adaptable. They lack general intelligence.