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

The Art of Statistics - David Spiegelhalter *****

Statistics have a huge impact on us - we are bombarded with them in the news, they are essential to medical trials, fundamental science, some court cases and far more. Yet statistics is also a subject than many struggle to deal with (especially when the coupled subject of probability rears its head). Most of us just aren't equipped to understand what we're being told, or to question it when the statistics are dodgy. What David Spiegelhalter does here is provide a very thorough introductory grounding in statistics without making use of mathematical formulae*. And it's remarkable.

What will probably surprise some who have some training in statistics, particularly if (like mine) it's on the old side, is that probability doesn't come into the book until page 205. Spiegelhalter argues that as probability is the hardest aspect for us to get an intuitive feel for, this makes a lot of sense - and I think he's right. That doesn't mean that he doesn't cover all …

Six Impossible Things - John Gribbin *****

On first handling John Gribbin's book, it's impossible not to think of Carlo Rovelli's Seven Brief Lessons in Physics - both are very slim, elegant hardbacks with a numbered set of items within - yet Six Impossible Things is a far, far better book than its predecessor. Where Seven Brief Lessons uses purple prose and vagueness in what feels like a scientific taster menu, Gribbin gives us a feast of precision and clarity, with a phenomenal amount of information for such a compact space. It's a TARDIS of popular science books, and I loved it.

Like rather a lot of titles lately (notably Philip Ball's excellent Beyond Weird), what Gribbin is taking on is not the detail of quantum physics itself - although he does manage to get across its essence in two 'fits' (named after the sections of Hunting of the Snark - Gribbin includes Lewis Carroll's epic poem in his recommended reading, though it's such a shame that the superb version annotated by Martin Gardi…

Elizabeth Bear - Four Way Interview

Elizabeth Bear won the John W. Campbell award for Best New Writer in 2005 and has since published 15 novels and numerous short stories. She writes in both the SF and fantasy genres and has won critical acclaim in both. She has won the Hugo Award more than once. She lives in Massachusetts. Her latest title is Ancestral Night.

Why science fiction?

I've been a science fiction fan my entire life, and I feel like SF is the ideal framework for stories about humanity and how we can be better at it. Not just cautionary tales - though there's certainly also value in cautionary tales - but stories with some hope built in that we might, in fact, mature as a species and take some responsibility for things like reflexive bigotry and hate crimes (as I'm writing this, the heartbreaking news about the terrorist attack on Muslim worshipers in Christchurch is everywhere) and global climate destabilization. These are not intractable problems, but we need, as a species, the will to see that we …