I'm Alan Bundy.
I'm Professor of Automated Reasoning at the University
of Edinburgh in Scotland.
Great, cool.
Thank you for coming.
So how did you get into the field
of artificial intelligence?
I went to Edinburgh in '71 having
done a PhD in mathematical logic in Leicester in England,
and I got very unhappy with my research in logic.
I felt that it was--
it kind of lost its motivation, and I
was looking for something more application oriented.
And I discovered about the work at Edinburgh
on automated reasoning, which was using the kind of logic
that I'd been learning about, so this seemed
like an ideal opportunity.
So I applied for a research fellow position at Edinburgh.
Went to Edinburgh to work under Bernard Meltzer, who
was running automated theorem [INAUDIBLE] in Edinburgh.
Cool.
What other kinds of research were
going on in that lab at the time?
In the whole of Edinburgh, there were four main groups,
so there was one run by Donald Michie,
and I guess the major research there was the Freddy the Robot
project, which I think Harry Barron spoke to about earlier
today.
So I probably don't need to dwell on that too much.
There was a bionics research lab, which
was then run by Jim Howard.
Previously been run by Richard Gregory, who's
famous for his work on optical illusions, but he left by then.
And its main interest was in education, computers
and education.
It'd done some work on touchscreens,
but the big project that they started working on soon after I
arrived there was on Logo.
So they were following the MIT work on Logo,
but they were principally interested in the evaluation
of it in an educational context.
So we had a lot of school kids running around in the lab.
Were there turtles?
With turtles and so on, and programming the computer,
and so on.
Then there was another group, the theoretical unit run
by Christopher Longuet-Higgins.
Its main interest there was in language,
so it did a lot of contextual linguistic stuff.
But they also had an interest in neural nets,
and in fact Geoffrey Hinton, for instance,
was there as a student at that time.
Lots of people who've gone on to be big names in the field
actually were in Edinburgh around that time.
Was this the Edinburgh Artificial Intelligence
Laboratory?
Well, it was actually then called
the Department of Machine Intelligence and Perception,
and it changed its name in 74 to the Department
of Artificial Intelligence.
But it always been called machine intelligence.
About how many people were there?
Oh, I guess it depends who you count.
There were, in terms of tenured members of staff,
about half a dozen, but then there
were quite of our research fellows and PhD students.
So maybe 30, 40 people altogether.
I know, in Minsky's room, they had a playpen.
Did you have any similar installment?
No, not really, no, but we did have--
yeah, we did have the Freddy project, Freddy robot.
My own group, as I said, was concerned
with automated reasoning, and at that time,
I said, there was some very notable people there,
so that when I joined the group, Pat Hayes was there,
who went on to become world famous for his work
on knowledge representation.
He'd already written a seminal paper
with John McCarthy, McCarthy [INAUDIBLE]
who's one of the seminal papers in the field.
Bob Kowalski was there, who went on
to become the founder of the logic programming
and famous for his work in Prolog
and logic programming generally.
And Bob Boyer and Jane Moore were there,
so they were doing pioneering work on the inductive theory
proving and its application to formal verification.
So that went on.
They just, in fact, won the ACM Systems award for that work
after all these years, so that was another.
That started in about '73 at Edinburgh.
And my own work then had two themes.
One was on meta level inference and the way
in which one could reason about reasoning in order
to guide reasoning.
And the other one was about how one forms representations
of knowledge automatically from, let's
say, a description in English and then goes on
to use that for reasoning.
That's been the dominant theme of my work ever since.
When you're looking for inspiration
about how to develop the field, did you look to philosophy?
What other things were--
Actually, I was just thinking about this
because I know you were particularly
interested in the MIT AI Lab at this time.
So actually, one of the major influences was the MIT AI Lab,
but it was kind of controversial because there would been--
our group had been founded on resolution theorem proving,
and Robinson was a frequent visitor to our group,
and that had become very fashionable for a while in AI.
But Minsky and others at MIT had been extremely critical
of that whole approach, and I think a lot of what we did
was actually in reaction to that.
So if you look at Pat's work on common sense reasoning
you can see him being heavily influenced
by that critique of logic, which he set out to defend,
but also it influenced his approach
in a very constructive way.
It certainly influenced my approach.
The whole meta level reasoning thing
was a way of trying to get a handle on how you would guide
reasoning processes, which is one of the major criticisms,
that these resolution systems were just completely unguided.
I think the Boyer-Moore approach was similarly, in that respect,
looking for heuristics as a way of guiding reasoning,
and certainly, Bob Kowalski's promotion
of logic as a programming language
rather than as a common sense reasoning engine,
I think, it was also, in a way, influenced by that.
So I think that was a major driver, in a way.
It was a major point of discussion,
that whole criticism, from what we saw at the MIT school
at the time.
Cool.
And then how did you know about what was going on
and the alternate labs?
Was it more through publications?
Oh, no, we met these guys.
Conferences?
The field was very small.
Yeah, so IJCAI conferences, for instance,
which happened every two years.
They started in '69, so one of the first conferences--
actually, the first conference I ever
went to is the IJCAI which was in London in '71.
So people came from all over the world,
so I would meet most of the US researchers and so on there.
So in that first meeting, where from
the world were people coming--
Oh, all over the world.
The trip-- I guess, apart from Britain,
because the conference was being held in Britain,
and of course, there'd be a lot of British people,
the other major place was in the US.
So at the time that the Edinburgh lab was founded,
which Michie came in '63, and the Department of Machine
Intelligence and Perception was soon after that,
I think in '67.
So around that time, there were really
only four labs in the world that were doing AI.
I mean, there were small groups elsewhere,
but the big labs were MIT, Stanford, Carnegie Mellon,
and Edinburgh.
And so we had very close contacts with all those people.
There was a lot travel.
In '73, IJCAI was in Stanford.
I went across to that.
I think there was about 300 people there,
so you more or less knew everybody, even
people in other fields like language or vision,
which I wasn't directly involved in the research.
I would know a lot of people there.
And we had particularly strong relations
with some of the other labs.
So I would say the strongest was probably with Stanford and SRI
because they shared a very similar logic oriented
approach to the field.
And so with McCarthy and Nils Nilsson, particularly
on the Shakey project, a lot of interaction between the Shakey
project and the Freddy project.
Yeah, so, is there a lot--
how's the atmosphere of Edinburgh changed since then?
Oh, you mean like the social atmosphere,
or the academic atmosphere?
Both.
Well, socially, Edinburgh at that time
was famous for its arguments amongst the professors.
So there was a kind of war amongst the senior professors.
It was very well known and highly controversial,
and it led to exciting times in the Chinese curse
sense of that word.
I think-- why did it happen?
Yeah.
I think it takes a certain kind of person
to set up a totally new field, people
with very strong wills, very strong ideas about where they
want the field to go, a lot of hutzpah, as it were, to create,
persuade people that something new needs to be set up.
And I mean, the AI department, or the Machine Intelligence
and Perception department was set up de novo at Edinburgh.
I mean, most new departments spin out
from other departments, but here is something completely new.
And so it took a certain, very strong personality,
and Donald Michie had gathered together
some very strong people, like Richard Gregory,
like Christopher Longuet-Higgins.
And Bernard Meltzer and so on, to set up
these different groups.
And they were all strong personalities,
and they didn't always get on.
Things settled down in '74, when we
created the Department of Artificial Intelligence
but before that, it was a lot of argument.
So now, it seems to me much smoother
because I lived through those times.
But technically, I mean, it was a very exciting time
because everything was new, and people were trying out
all sorts of different approaches,
and there was lots of discussion about that.
I think people were very exploratory.
So now, there are lots of well recognized mechanisms
that have been developed within the field
and have been theoretically explored,
and so the properties of them are known.
There are very good implementations
which have been well tested, and if you build a system nowadays,
you build it out of components, which
you will get a lot of those from elsewhere
and put them together, and you won't do much sort of de
novo programming yourself.
I mean, there'll be some, but you will
build on other people's work.
Then, everything was new, so there
was very little to build on.
So more or less, everybody started from scratch,
and some of the programming was very ad hoc and rough,
and the mechanisms were not well understood.
And so the programs were much briefer things
because things were poorly understood.
Things would just break down a whole lot more.
So I remember reading a paper about the [INAUDIBLE] system
which had been built, I guess, by the the [INAUDIBLE]
people mostly in the early '70s.
And there was this wonderful quote that said,
most AI systems simulate intelligence
only on the example in the thesis.
On another example, they simulate total failure
or death.
And that is very true, and I think it's not true now.
I think systems are much more robust--
Do you think we're going to see artificial intelligence
majors come up in the undergraduate program?
Oh, we've been--
As a common feature?
We've been teaching undergraduates since 1974
at Edinburgh.
We had a--
They can major in AI?
Oh, yeah.
Oh, great.
Absolutely, yeah, so we had--
I was actually responsible for organizing the very first
undergraduate course.
There was a second year, a sophomore course in AI.
It was just a specialized course, but within a few years,
we had joint degrees.
Our first joint degree was actually with linguistics.
At Edinburgh, we've always had very strong connections
between the AI work and the linguistics department,
and lots of work on computational linguistics.
So that was our first joint degree,
and then we had joint degrees with the computer science
department, which was a separate department then,
and with mathematics and then with psychology and so on.
And now, we have a single subject AI degree.
Wow, what does it consist of?
Oh, well, there's so much material now.
I mean, that's one of the things that's
happened in the last 30 years.
Since I've been in the field, so much has happened,
so there's no shortage of material.
I mean, we teach-- in our second year,
we use the Russell Norvig book and maybe use culture of it.
[INTERPOSING VOICES]
You could probably get most of the contents
of a degree [INAUDIBLE] and that was
the whole of that book, a tremendous amount [INAUDIBLE]..
Why don't I just take [INAUDIBLE]..
I'll give it to him.
You'll get something back if you just tell me who--
We'll just cut this part.
OK.
Do you want to-- do you want to stop?
No, I'll give you a--
I have one more question.
Do you guys want to do that out in the hallway maybe, Matt?
And then we can just close and cut this part.
In fact I think I have Tom's card.
He gave it to me.
We're waiting for you because we can't
record while you're talking.
I think-- OK, OK, I'll remember Tom and I have his direction.
OK, the light is directional.
OK, so you'll get it.
Sorry.
So what are you--
what are your hopes for the future, just to close out?
So I've got very interested again
in this area of representational formation and evolution
and repair.
So I'm getting very excited about that at the moment.
I think it's a very neglected area,
so I think there's lots of interesting things to do.
It's had a very liberating effect on my own thinking
because all kinds of issues, which
I thought were hard or intractable, become--
you just got a different perspective on them,
and they become much more tractable.
So that's an exciting area that I
want to push on myself in the next few years.
Great.
Thank you so much.