Skip to main content

Four Way Interview - Hector Levesque

Hector Levesque is Professor Emeritus in the Department of Computer Science at the University of Toronto. He worked in the area of knowledge representation and reasoning in artificial intelligence. He is the co-author of a graduate textbook and co-founder of a conference in this area. He received the Computers and Thought Award in 1985 near the start of his career, and the Research Excellence Award in 2013 near the end, both from IJCAI (the International Joint Conferences on Artificial Intelligence). His latest title is Common Sense, The Turing Test, and the Quest for Real AI.

Why computer science?

Computer science is not really the science of computers, but the science of computation, a certain kind of information processing, with only a marginal connection to electronics. (I prefer the term used in French and other languages, informatics, but it never really caught on in North America.) Information is somewhat like gravity: once you are made aware of it, you realize that it is everywhere. You certainly cannot have a Theory of Everything without a clear understanding of the role of information. 

Why this book?

AI is the part of computer science concerned with the use of information in the sort of intelligent behaviour exhibited by people. While there is an incredible amount of buzz (and money) surrounding AI technology these days, it is mostly concerned with what can be learned by training on massive amounts of data. My book makes the case that this is an overly narrow view of intelligence, that what people are able to do, and what early AI researchers first proposed to study, goes well beyond this.

What's next?

I have a technical monograph with Gerhard Lakemeyer published in 2000 by MIT Press on the logic of knowledge bases, that is, on the relationship between large-scale symbolic representations and abstract states of knowledge. We are working on a new edition that would incorporate some of what we have learned about knowledge and knowledge bases since then. 

What's exciting you at the moment?

For me, the most exciting work in AI these days, at least in the theoretical part of AI, concerns the general mathematical and computational integration of logical and probabilistic reasoning seen, for example, in the work of Vaishak Belle. It's pretty clear to all but diehards that both types of knowledge will be needed, but previous solutions have been somewhat ad hoc and required giving up something out of one or the other.

Comments

Popular posts from this blog

Philip Ball - How Life Works Interview

Philip Ball is one of the most versatile science writers operating today, covering topics from colour and music to modern myths and the new biology. He is also a broadcaster, and was an editor at Nature for more than twenty years. He writes regularly in the scientific and popular media and has written many books on the interactions of the sciences, the arts, and wider culture, including Bright Earth: The Invention of Colour, The Music Instinct, and Curiosity: How Science Became Interested in Everything. His book Critical Mass won the 2005 Aventis Prize for Science Books. Ball is also a presenter of Science Stories, the BBC Radio 4 series on the history of science. He trained as a chemist at the University of Oxford and as a physicist at the University of Bristol. He is also the author of The Modern Myths. He lives in London. His latest title is How Life Works . Your book is about the ’new biology’ - how new is ’new’? Great question – because there might be some dispute about that! Many

Stephen Hawking: Genius at Work - Roger Highfield ****

It is easy to suspect that a biographical book from highly-illustrated publisher Dorling Kindersley would be mostly high level fluff, so I was pleasantly surprised at the depth Roger Highfield has worked into this large-format title. Yes, we get some of the ephemera so beloved of such books, such as a whole page dedicated to Hawking's coxing blazer - but there is plenty on Hawking's scientific life and particularly on his many scientific ideas. I've read a couple of biographies of Hawking, but I still came across aspects of his lesser fields here that I didn't remember, as well as the inevitable topics, ranging from Hawking radiation to his attempts to quell the out-of-control nature of the possible string theory universes. We also get plenty of coverage of what could be classified as Hawking the celebrity, whether it be a photograph with the Obamas in the White House, his appearances on Star Trek TNG and The Big Bang Theory or representations of him in the Simpsons. Ha

The Blind Spot - Adam Frank, Marcelo Gleiser and Evan Thompson ****

This is a curate's egg - sections are gripping, others rather dull. Overall the writing could be better... but the central message is fascinating and the book gets four stars despite everything because of this. That central message is that, as the subtitle says, science can't ignore human experience. This is not a cry for 'my truth'. The concept comes from scientists and philosophers of science. Instead it refers to the way that it is very easy to make a handful of mistakes about what we are doing with science, as a result of which most people (including many scientists) totally misunderstand the process and the implications. At the heart of this is confusing mathematical models with reality. It's all too easy when a mathematical model matches observation well to think of that model and its related concepts as factual. What the authors describe as 'the blind spot' is a combination of a number of such errors. These include what the authors call 'the bifur