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0:54

AI. Another

1:03

day is here and you're ready for it. What

1:05

to wear? Check. Breakfast,

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lunch and dinner? Check. Planning for

1:09

what's next and how to save for it? That's where Bank of America

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What would you like the power to do?

1:27

Mobile banking requires downloading the app and is only available for

1:29

select devices. Message and data rates may apply. Bank

1:31

of America, NAA member FDIC. Welcome

1:39

to Spycast, the official podcast of

1:42

the International Spy Museum. I'm

1:44

your host, Dr. Andrew Hammond,

1:46

the museum's historian and curator.

1:49

Each week we explore some aspect

1:52

of the past, present or future

1:54

of intelligence and espionage. If

1:56

you enjoy the show, can you please ask that you

1:59

leave us a... 5 star review

2:01

that really helps other listeners find us

2:03

and will take less than a minute

2:05

of your time. Coming

2:07

up next on Spiker. Always

2:10

hanging by a thread is one

2:13

of the expressions that they use.

2:16

You know a whole thing that flaps with any

2:18

man. This

2:29

week is the 70th anniversary of Alan

2:31

Turing's untimely death at the age of

2:34

41. Turing

2:36

was a British mathematician best

2:38

known for his contributions to theoretical

2:40

computer science and code breaking. Work

2:44

that was critical in cracking the German

2:46

Enigma code during World War II. To

2:49

commemorate his life and achievements

2:51

we spoke with Dr. Andrew

2:53

Hodges, an emeritus professor

2:55

of mathematics at the University of

2:58

Oxford. In 1983

3:00

Andrew published one of the first books

3:03

to explore Turing's story and

3:05

his work on Enigma, a

3:07

book that would later become the inspiration for

3:09

the hit 2014 film featuring Benedict

3:12

Cumberbatch, The Imitation Game.

3:15

In this episode Andrew and I discuss Turing's

3:19

foundations for artificial intelligence,

3:22

interwar code breaking or

3:24

cryptanalysis, Bletchley Park,

3:27

Hot 8 and British naval

3:29

intelligence and the mechanics of

3:31

the Bomba machine. The original

3:33

podcast on intelligence since 2006, we are Spycast.

3:39

Now sit back, relax and

3:41

enjoy the show. So

3:46

thanks ever so much for speaking to

3:49

me Andrew. As my colleague Erin pointed

3:51

out it's one AH speaking

3:53

to another AH today so

3:55

I really appreciate you coming on the

3:58

show to talk to me. Well,

4:01

thank you for inviting me, A.H. It's

4:04

a pleasure to be on your program. So

4:08

I think it would be interesting just to start off.

4:11

Tell us how you first came to

4:13

be interested in Alan Turing. Well

4:16

that goes back a very long

4:18

way. I think it was in

4:20

1969 when I

4:23

was 19 and an undergraduate student

4:25

at Cambridge University. When

4:27

I was reading around about things in

4:29

the background mathematics of computers and I

4:32

came across his name then, just a

4:34

name really. But

4:37

then shortly after that, in

4:39

the early 70s, I

4:41

came across his name in quite a different way

4:43

as a gay man

4:45

who'd suffered very considerably

4:49

in the prosecution after the war. And

4:53

so that was interesting for a start. But

4:55

then what really got me going was

4:58

in 1977, I

5:01

learned that really he'd been the most important

5:03

person in the color-breaking effort during the Second

5:05

World War, which at that stage

5:07

was just emerging into public knowledge. I mean

5:10

not many people knew about it. It had

5:12

all been kept very secret for 30 years.

5:16

But in a funny way, I was one

5:18

of the few people who caught

5:20

on to all these different strands. I

5:24

knew about serious mathematics and mathematics and science.

5:26

That was my business. By that

5:28

time, I was a PhD in maths. And

5:33

I knew about the gay history part of

5:35

it too. I had a real feeling for

5:37

that and how the times, what

5:39

they were like in the 1950s. And

5:43

also then there was this amazing historical

5:45

story, which was just breaking out. And

5:48

as it turned out, he'd not only

5:50

been in it, but was really the

5:52

most important scientific figure in the British

5:55

and in fact in the

5:57

Anglo-American effort between 1939. and

6:00

45 and that's an amazing story really

6:02

I just wanted to do something about

6:04

it. And

6:08

tell us the the Turing that

6:10

you found when you started conducting

6:12

the research for your book. So

6:14

for our listeners your book comes out in 1983 or the

6:16

first edition comes out in 1983 and this

6:21

is a seminal book on Turing

6:23

and but now all

6:26

these years later where he's on the 50

6:29

pound no and there's an Alan Turing

6:31

Institute and Gordon Brown issue the official

6:33

apology and there's the you know

6:36

people that were convicted for

6:39

homosexual offenses in that era have

6:41

been pardoned and so forth but

6:44

I'm assuming it was very different when you were

6:46

doing the research for the book leading up to

6:48

1983 what was Turing's status

6:50

amongst the the general public or

6:52

in British history when you took

6:55

up the the Python so to

6:57

speak. I forget that I mean

6:59

he certainly wasn't famous in the way that

7:01

you've been explained. In

7:04

mathematics he was well fairly well

7:06

known as the concept of the

7:08

Turing machine which is

7:10

really this formalization of an algorithm. Algorithms

7:12

now get a very bad press

7:14

but they didn't know that hasn't always been

7:16

the case and he was the person who

7:18

really defined what an algorithm is. That

7:21

was his thing before the war. So

7:24

that was known in mathematics and then

7:26

there was a famous prize

7:28

in computing science for instance the A.M.

7:30

Turing prize that had been established in

7:32

the 1960s. He was not an unknown

7:35

figure and in

7:37

that way but not so the

7:39

general public no he was not known at

7:42

all there's a certain amount of

7:45

not more scientific public would have known a bit

7:48

more about his interest in artificial

7:50

intelligence because he wrote very lively

7:53

very readable very well funny

7:55

really paper about artificial intelligence

7:58

in 1950. Which is always

8:01

i think the most what

8:03

is being my most access to the

8:05

quality papers in the field ever since

8:07

that was known about. What

8:10

was the name of the store still isn't

8:12

really no no is that. In

8:14

between those things between the code

8:17

breaking and the and the artificial

8:19

intelligence ideas. He invented the

8:21

computer i mean that's what he did in

8:23

nineteen forty five it came out

8:26

of the code breaking work

8:28

putting the algorithms and technology

8:31

and is there anything i did together. He

8:33

had the most involved computer plan in the

8:36

world in nineteen forty six

8:38

but he was picked by john

8:40

von Neumann who is now famous really

8:42

as me as the creator of the

8:44

modern computer. They

8:47

were very much on the level they

8:49

are on a par really and that

8:51

is big argument about how much on

8:53

the women got from sharing a phone

8:55

very complicated story but that was the.

8:58

What is the central benefit

9:00

really that was the thing which

9:02

made him the founder of computer

9:04

science. The beginning of

9:07

the whole digital world really everything you

9:09

do with the digital everything that we're

9:11

doing now for these computers. Flows

9:14

from his perceptions and that in

9:16

turn. Came through these

9:18

practical experience during the second world

9:21

war on breaking enemy

9:23

codes. So we

9:25

have a variety of different contributions then

9:27

we have have contributions in

9:29

mathematics artificial intelligence computing

9:32

cryptography. Just

9:35

really across the whole variety of different

9:37

fields. Absolutely the bread

9:40

of interest is really quite extraordinary

9:42

and he would have called himself

9:44

a mathematician. That is

9:47

his profession but he's doing

9:49

way outside of that into

9:52

philosophy and theory of minds

9:54

and how a machine cannot.

9:57

And you like what am I does. What

10:00

is the much more than

10:02

other mathematicians engineer you got

10:04

really seriously interested in electronic

10:07

and actually design electronic. Components

10:09

and the computer

10:12

that is very unusual things

10:14

to do and that is

10:17

really what makes the story very interesting and

10:19

causing them to make it very

10:21

easy for me to go to find out

10:23

all these different things. Coming

10:26

back to your question about what it was like.

10:29

Starting on all this i think

10:31

the thing i'd go through is really the

10:33

people the people who knew the friends he

10:35

had the colleagues he had. Good

10:38

will that he left behind which i

10:40

was very grateful to get know that

10:42

is coming on to me. Add

10:46

and then and the whole sense of the story.

10:49

I don't know that flow down

10:51

and what people could tell me and

10:54

putting together with all the bits and

10:56

pieces of papers and memos and letters

10:58

on. It was

11:00

a fascinating business to get into

11:03

and for me just asking about

11:05

that it was like living a previous life

11:07

it was like getting to know someone who

11:10

is. That he is older

11:13

than me and had a

11:15

nice cut short and ready getting into

11:17

the head as much as i could not close

11:19

no i'm really can but i did my best. And

11:24

as an emeritus professor oxford you

11:26

maybe don't have this feeling but

11:28

whenever i do a podcast on

11:30

people like cheering i always feel

11:32

like a chronic underachiever. Encounters

11:36

for the ordinary search for your. I'm

11:42

excited well and then the thing is

11:44

great now quality of the real story

11:46

to it this real it's

11:49

more than most people i think and that. You

11:53

went from something that was just

11:55

thinking and very but he had

11:57

this great wish to do

11:59

something. something in his life, do

12:02

something with his hands, really very down to

12:04

earth concrete thing. And that, first

12:06

of all, that was, came about through

12:08

the code breaking work, which you probably come

12:10

on to later. And then

12:12

a bigger way really through the idea of

12:15

the computer, everything you can do with the

12:17

computer. So that

12:19

makes the story of growth and

12:21

then sort of process theory of what's going to

12:23

come in the future. I mean, it's

12:26

more complicated than that. You did lots of other

12:28

things as well, you did things in pure mathematics,

12:30

you work in biology.

12:33

There was a wonderful sense that I enjoy

12:36

very much of a

12:38

storytelling narrative of

12:41

growth and discovery. And

12:44

I just want to touch on this

12:47

briefly before we get into more depth

12:49

about Enigma and his contribution at Bletchley

12:51

Park and so forth. So whenever you

12:54

do research on Turing, you inevitably come

12:56

across two papers and I believe that

12:58

one of them you've probably already referred

13:01

to, which is the Can

13:03

Machines Think and then the other one,

13:05

which is the opposite end

13:07

of the spectrum in terms of approachability,

13:10

is the what on computable numbers. So

13:12

just for the lay person, what's

13:15

the contribution of both of those papers

13:17

for like a lay person? Yes, absolutely.

13:19

You're absolutely right. Those are the two

13:21

papers or things. And

13:24

the pre-war one is the one in 1936. And

13:28

it's what I referred to as the

13:31

way that he defined an algorithm. And

13:35

that's what he did in this paper,

13:38

which had the peculiar name, but that

13:41

was the thing he was most famous for in

13:43

mathematics. And he actually

13:46

related those two papers because they're

13:48

both about the question of mind

13:50

and how a machine can

13:52

emulate what a mind does. So

13:54

even in the pre-war work, he was thinking

13:56

about human minds. He wasn't actually thinking about

13:59

physical machines so much. He was thinking about

14:01

the question of what can

14:03

a person do and what

14:06

is a person doing when they're following

14:08

something that you call a method, as

14:11

we now call an algorithm. He formalized

14:13

this in a very clever way into

14:15

this concept of a Turing machine. What

14:18

became very

14:22

striking after the war was that

14:24

he came up with this concept of a

14:26

universal machine, which

14:29

could perform any process.

14:32

Then, of course, it's exactly what we think

14:34

of a digital computer as doing. It can

14:37

play any program that you give it to

14:39

do. That was completely new. That

14:41

was foreshadowed in the 1936 work,

14:44

but then flowered completely in 1945 and gave

14:47

an entirely new picture of what computation

14:50

was all about. Now, essentially,

14:52

it's taking over the world. I'm

14:54

talking to a universal machine. You're

14:57

using everyone's process. There are hundreds

14:59

of millions of them around. That

15:01

really all flows in his perception, which

15:04

was really completely new. The

15:08

other day, I had a little

15:10

smile to myself when I thought

15:12

of how much excitement Turing would

15:14

get if he came back

15:16

to the future just now and saw a

15:19

chat, GPT, or all of the

15:21

discussions about artificial intelligence

15:23

and generative AI and so

15:25

forth. Well, that's absolutely

15:27

true. In fact,

15:29

it's quite uncanny how the

15:32

text message formalism that he

15:34

thought of, what you

15:36

would imagine doing is a testing

15:38

machine as to whether you thought it could

15:40

be considered as having intelligence or not. He

15:43

had this text message protocol. The

15:46

point was there were

15:48

messages with jokes and

15:50

subtleties and fooling and

15:53

risque observations and so on. It's

15:56

just so like what people actually do.

16:00

possibly known. I mean, this is, he wrote this when there

16:02

are only a couple of computers working

16:04

in the world. But

16:06

he did see this human level to

16:09

it. And that's what actually people

16:11

didn't like very much at the time, all

16:13

the more serious, more

16:16

conventionally serious people at the time, they'd

16:18

know no computers, they're just doing calculations.

16:21

He did say a long way beyond that, he

16:24

imagined a world in which people would be

16:27

communicating and doing everything

16:29

in life. In

16:32

terms of confusing, and

16:35

then pose these questions about what you'd call

16:37

intelligence and so on. So

16:41

yes, he would have seen this very

16:43

direct thing. And I

16:45

mean, I even think about this with

16:48

recapture, which is a true

16:50

as understand, correct me if I'm wrong, is

16:52

a kind of Turing test

16:54

to tell humans and machines apart. And

16:56

this is something that people are doing

16:58

like very, very often. Yes,

17:01

that gives you a little flavor. I mean, that's

17:03

nothing compared with a scale that

17:06

he envisaged. But he does give the flavor

17:08

of it. It's trying to, as

17:10

he said, it's a capture something that you

17:14

imagine only the human knows, namely what

17:16

a motorcycle is, or what a lap

17:18

host is, and those sort of things.

17:21

And you think it'd be very difficult for a machine to

17:24

do. Well, of course, actually, machines can actually do quite

17:26

a lot of those things. It's not

17:29

really a clear cut. But

17:32

that's it. That is the

17:34

sort of thing that it was in

17:36

his mind. Yes. And

17:39

just very briefly, before we move on to

17:41

Edna Kemal, what's a Turing machine for the

17:43

average person on the street? Well, it's an

17:45

algorithm. I mean, it's just a computer program.

17:48

And one way of putting what he did

17:50

in 1936 is that the

17:53

abstract question in mathematics was

17:57

how you define what you call a method or

17:59

a procedure. And he

18:01

found an answer to that and his answer was, it's

18:04

a computer program. I mean,

18:06

that's a very definite answer. Something actually writes

18:08

down the list of symbols and the computer

18:11

can do it. But computers didn't

18:13

then exist. So he

18:15

had to invent the computer so as to

18:17

make sense of that definition. Well, of course,

18:19

I'm talking in

18:21

a very literal way because you can't

18:24

really invent something that doesn't exist. That

18:28

gives an impression of how what

18:31

he did was important and how it was ahead

18:33

of his time and how it

18:35

came up with the idea of

18:37

the computer well before any machines

18:39

actually existed. And

18:42

now, incidentally, I mean, you have a very

18:44

direct sense of what a machine is because

18:47

if you click on an app on

18:50

your phone, you are

18:52

simply moving the operation

18:54

from one type of process

18:57

to another type, just a millisecond.

19:00

And it goes from doing

19:03

GPS mapping to doing

19:05

voice recordings, to doing calculations,

19:07

to doing scrolling through

19:09

your messages. You just add a thick, it

19:11

just changes from one thing to another.

19:14

And that really is the principle of the universal

19:17

machine that you can do all of those things

19:19

without you doing anything to the hardware of the

19:21

machine. It's all done, as

19:23

with now, by software. And

19:26

that was really his idea. I

19:28

think looking back in those 1930s, when

19:30

he did this, no one, I don't

19:32

think, had ever come up with this

19:34

concept of a universal machine. And

19:37

there was loads of talk about machines

19:39

that Victorians are fascinated by machines, lots

19:42

of H.G. Wells and people like that

19:44

were very interested in machines.

19:46

But they all thought about different

19:49

machines and different tasks. And

19:51

it was quite a breakthrough

19:53

idea, which took a long time

19:55

to catch on commercially after the

19:57

war, That you would have one machine. The

20:00

just always isn't. Think. I

20:02

could decide if it calculations and to

20:05

be doing of. He. Aura invoices

20:07

allow and be writing letters or whatever

20:09

but that you don't need months off

20:11

machine and that is very new. System.

20:17

So soon credible in. So fascinating

20:19

how he precision the world than

20:21

what we currently lessons of anyways.

20:32

You may have heard the story

20:34

of how the same as Apple

20:36

logo send on the back of

20:38

your tablets, laptops and phones was

20:40

inspired by our cheering. For

20:43

anyone about loss of so human,

20:45

I'll ensuring died at his home

20:48

and june of Nineteen Fifty four

20:50

of cyanide poisoning, his phone by

20:52

a housekeeper discovered cheering rather peacefully

20:55

and his bed with an apple

20:57

lying half eaten next them. As

21:00

death as a pet a mystery

21:03

ruled a suicide by most are

21:05

believed to be accidental by quite

21:07

a few years. Whatever

21:09

the nature of his untimely death,

21:11

a smidge of an awful with

21:14

a be taken out of It

21:16

was thought to have been the

21:18

inspiration behind Steve Jobs his company

21:20

logo us makes sense as we've

21:22

mentioned the Nus episode already because

21:25

touring as one of the father's

21:27

the Modern Computer. Unfortunately,

21:29

the seed it has nothing but

21:32

an urban legend the company has

21:34

confirmed as nothing to do with

21:36

cheering as clever as.would have. Felt

21:39

Awful. Local may not have

21:41

been inspired by him. Plenty

21:43

of other studies, organizations and

21:46

inventions be of his name.

21:48

For example the Alan Turing

21:50

and The Truth Your Kids

21:52

National Institute for Artificial Intelligence,

21:54

The Alan Turing Building That

21:56

The Universe at Manchester, and

21:58

the Annual. To the award

22:01

given by the Association of

22:03

Computing Machinery among many many

22:05

others says Twenty Twenty One.

22:07

Meanwhile, I'll Ensuring has been

22:09

featured on the reverse side

22:11

of the Cessna and on

22:13

Someone's No Need A Ticket.

22:36

Be be right back after the. Vip

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24:16

think it would be interesting now to pivot

24:18

onto Bletch and the

24:21

Park and Enigma. So tell our listeners how

24:23

did he first get

24:25

caught up in all of this?

24:27

Was it through his networks like

24:29

King's College Cambridge? How did he

24:31

get recruited into a cord breaking?

24:34

Right. Well, there's a very interesting story

24:36

here. Of course, there's a social academic

24:38

side to it that he came from

24:40

a leech background, was at a top

24:42

Cambridge College and was surrounded

24:44

by people who are all in

24:47

with the Maynard Kens in

24:49

particular, the economists, very close

24:51

to top people in government. And we

24:53

knew all about the First

24:56

World War code breaking business. And so

24:58

he was just an open door for

25:00

him to push out there. That's on

25:02

the social level. But

25:04

on the international level, a very interesting thing is

25:06

that he started thinking about

25:09

codes and ciphers in 1936.

25:11

It was a

25:13

spinoff from the work that I've just

25:15

been describing about what an algorithm is.

25:18

He thought what would an

25:20

algorithm be if it was doing a

25:22

code or breaking a code

25:24

or whatever. I mean, he went into that

25:26

area then, right? Straight away in 1936. And

25:30

not only that, but he

25:32

devised a particular new type of

25:34

cipher system, which he built out

25:37

of electromagnetic parts when he was

25:39

away at Princeton in 1937. So he had a

25:42

real hands-on interest in the subject. And

25:45

that's together with the

25:47

social background and of course, the

25:49

political background, what everyone would see

25:51

that Waller with Germany was coming.

25:54

That is what propelled him to

25:57

make an approach. to

26:00

the predecessor of the GCHQ

26:02

as it is now, but

26:05

the nationally powerful organization, the

26:08

government organization that dealt

26:10

with CO-breaking. And he did

26:12

that in summer of 1938, well

26:15

before the war started. In

26:17

fact, he was really almost invited in. They

26:19

were looking for people with

26:21

a mathematical, scientific basis who could

26:23

do something for them. That

26:26

the problem of the enigma was that it

26:29

was much more scientifically based than

26:31

the first world war coding system

26:33

had been. They needed someone

26:35

who would cope with that material. They

26:37

were actively looking to recruit

26:40

such people. And really Alan Turing

26:42

was absolutely perfect for it. He

26:44

was exactly what they wanted. A

26:48

very good theoretical understanding of

26:50

what coding was all

26:52

about, what information is all about,

26:54

what symbols are about, and manipulating

26:56

symbols. A very high level of theoretical

26:59

understanding. But he had this real

27:02

practical sense as well, and together with

27:04

an engineering sense of what you would

27:06

be able to do with the machinery

27:09

that existed in those days, which is

27:11

essentially automatic telephone exchange

27:13

type equipment. So

27:16

it was a marvelous thing where it was just

27:18

the right person at the right time in the right

27:20

place. The

27:23

other ingredients that really got things going

27:25

was the mathematical work done in Poland.

27:29

The Poles in their crypto organization

27:31

were miles ahead of anyone else

27:34

and had made mathematical understanding

27:37

of the enigma coding system, which I'll

27:39

say a little bit more later. They

27:42

transferred that to the British and

27:44

French just before

27:46

the war started in July 1939.

27:50

That was a tremendous stimulus. And

27:53

Turing took off from those ideas. And

27:56

that meant everything, and then they just went off

27:58

like, well... It

28:00

just exploded from that going on

28:03

very early after the war was

28:05

declared in September 1939. And

28:11

I'm just trying to get a sense of the sweep

28:14

from World War I through to

28:16

World War II, Andrew. So I'm

28:18

thinking of World War I and

28:20

Room 40, so the British

28:22

Navy, the Admiralty Unit that's trying to

28:25

crack German codes. We've

28:27

got these archaeologists,

28:31

classicists and so forth,

28:33

Dilly Knox, Alistair Deniston,

28:35

and all these types of people that are around

28:37

in the First World War. And some of them

28:39

carry over into the Second World War. But as

28:42

I understand it and tell me if I'm wrong,

28:44

in the First World War, it's more people

28:47

that are looking at languages, people that are

28:49

looking at archaeology, people that are looking at

28:52

papyri and so forth. Whereas when you get to

28:54

the Second World War, it's much more mathematical

28:57

and engineering and so

28:59

forth. Is that a fear

29:02

and is that because of the shift in

29:04

technology? Well, you're absolutely right

29:06

there. And the

29:08

more literary people that were very

29:10

good, obviously very competent on the

29:12

First World War type of codes

29:14

based on code books. And

29:17

Dilly Knox, who you've mentioned, was

29:19

clearly a very ingenious character altogether

29:22

and actually did make headway on

29:24

the simplest form of the

29:26

Enigma, which was in use by

29:28

Germany and indeed from other

29:31

countries in Europe in the 1920s and

29:33

30s. But

29:36

the key word is still machine.

29:39

The machine, it was more mathematical

29:42

and it did need a mathematical

29:44

approach to it. And none

29:46

of the people who came from

29:49

that First World War

29:51

generation had quite that skill.

29:53

They were actively looking for people

29:55

to beef up their abilities in

29:57

that area. And during what's called the Enigma,

30:00

anyone, but he was the first one

30:02

really, and he fitted that bill perfectly.

30:05

I would say, I mean, it's usually thought that the...

30:08

Oh, yeah, it's another important thing is that

30:10

the... about the enigma, it's

30:13

often thought that... I think you've indicated

30:15

that it wasn't the great sort

30:18

of mystery, the basic enigma, it was a commercial

30:20

machine that had been invented out 1920,

30:22

and lots of people had it. The

30:25

point about the German military use of it was

30:27

that it was a very considerably

30:29

enhanced with extra complication.

30:32

But the basic form of the machine was

30:34

not a mystery at all. Did that

30:36

experience of the British experience of World

30:39

War One cryptography, did that in any

30:41

way spill over

30:43

into... to affect

30:45

mathematics and the interwar period, or

30:48

the types of things that

30:50

people were looking at, or even the invention of the

30:52

enigma machine in the 20s and 30s? Did

30:55

that in any way spill over,

30:57

or were the mathematicians really sort

30:59

of reacting during the Second World War to

31:01

the developments that had taken place? Yes, well,

31:04

I think a lot of elements there. The

31:07

machine scientists were not really a development

31:09

out of those first World War methods,

31:11

and there were various different types of

31:13

rodent machines, which went back

31:15

a long way into the 19th century. And

31:18

that was really quite a different thing from the

31:20

book codes that we used in the First

31:23

World War. But there was a

31:26

lot of crossover in technique and

31:28

understanding of what was going on.

31:31

I mean, Darwin, look, Knox certainly

31:33

took to Turing and they got on very well

31:35

in the early part of the war. And

31:38

Knox's whole familiarity

31:40

with the whole business of cryptography,

31:42

I'm sure, was actually very important

31:44

in getting into the whole thing.

31:47

And just because you had machine methods, that

31:50

didn't mean that you lost sight

31:52

of the psychological aspects

31:56

of what coding was all about. I mean,

31:58

they would use... I

32:00

did based on what the general rages with

32:02

doing on the machine when they set them

32:04

up and you did a lot of very

32:06

fine getting to get

32:08

going on these things so

32:11

the human element here is

32:13

the government the guess what part of it. They

32:17

playing around with what i'm thinking

32:19

of getting probable words in

32:21

the message that was very very

32:23

important and you need some understanding

32:26

of material who is sending

32:28

it who was getting it how long it

32:30

was when it was coming so far to

32:32

keep understanding of what the message is lacking

32:34

about. That was essential

32:37

to the mechanical code breaking method

32:39

so it's not just an either or

32:42

machines do this and the throw away the

32:44

human. I'm intuition and perception

32:47

and analysis not at all i have

32:49

to work together. I'm

32:52

sorry i'm not mad at all sorry

32:54

i'm in fact what you did from

32:56

the algorithm for the

32:58

name of what is really the development

33:01

of mathematical theory of statistics which

33:03

is then use throughout the

33:05

war. But he would

33:07

have known very well that he needs a lot of good

33:10

guessing and other human knowledge of

33:12

military knowledge and common

33:14

sense to get the

33:16

whole thing going and i'm sure you have a lot

33:18

of respect for that as well. You

33:22

can see how all of these components

33:24

come together the practical experience the more

33:27

humanistic interpretive skills that the mathematical

33:29

skills that you can see how

33:31

they all work together

33:33

during this period and. I

33:36

find it really interesting and also quite

33:39

difficult because in the one hand. You

33:42

know when you're telling the story of

33:45

of actually part for example you

33:47

want to highlight that this is

33:49

a in some ways an industrial

33:52

operation with thousands of people and

33:54

various components but then on the other hand. You

33:58

know there's the. role

34:00

that people like Turing have played and by

34:02

all any yards that kids generally considered

34:05

a genius. So on the

34:07

one hand it's this single genius correct enigma, we

34:10

know that's not the case but on the other

34:12

hand it wasn't just

34:14

the industrialized method that did take

34:16

the contribution of people like Turing

34:18

to actually make the breakthrough. So

34:20

I'm just wondering how would you

34:22

best describe that kind of interplay to

34:24

our listeners? Well there's enormous

34:27

growth you see. I mean it

34:29

started off with a small department

34:31

about 30 or so people

34:34

and very informal working,

34:37

close working together and

34:39

not a lot of machines or anything. And

34:42

then that grows throughout the war especially

34:44

with the growth of war operations and

34:46

the growth of

34:49

Anglo-American allies as well

34:51

and spread into the Japanese

34:53

war and everything else. Into

34:56

this enormous operation in which thousands of

34:58

people were involved essentially taking

35:00

over pretty well like the

35:03

whole British higher education sector.

35:05

It's like our university at work on German

35:09

and Japanese codes. But

35:12

that's not how it started. It started

35:14

off in this funny country house atmosphere

35:16

very 1930s a bit like

35:19

Agatha Christie or P.G. Woodhouse setting

35:22

something like that quite

35:24

upper class and

35:27

lots of games

35:31

and atmosphere of being

35:34

very exciting but

35:37

a life of party game. It's

35:39

a little to express I think but

35:41

they managed to keep a human level

35:43

to it all the way through. But

35:46

there is enormous growth and

35:48

but Turing wasn't in right from the very

35:50

start. I mean before it started. And

35:53

it was his seminal idea which gave

35:55

rise to these particular machines called

35:59

the bombs. I'm after

36:02

the polls about the

36:05

machine and those

36:07

were the essential work horses of the

36:09

name of breaking. Add

36:12

you that was

36:14

that was cheering when i say

36:16

that is cheering for actually had a lot of help

36:19

from the polls and also from

36:21

a colleague gordon welchman important idea

36:23

she missed. I got it

36:25

together very quickly that's

36:27

something which i think is not always understood. During

36:31

that got his ideas together and

36:34

the machine was being built already

36:37

in november nineteen thirty nine it

36:39

was first tested in march nineteen

36:41

forty long before. What really

36:44

got started before church or

36:47

the very very effective stop on

36:49

the whole business and

36:51

that's important because i think they haven't

36:53

got that stop. They

36:56

were far more difficult to catch up later

36:58

on. The

37:01

german systems using a

37:03

name made much more complicated and

37:06

the car because they got in at the beginning of

37:08

the air able to get some. Make

37:12

a make a increase their

37:14

attack and keep up with it

37:17

so the timing is terribly

37:19

important. I need with

37:21

the miracle really that sharing have those ideas

37:23

and to put them together with.

37:26

I'm not implementation in

37:29

working car machinery in

37:31

a way that he did nearly

37:33

five of nineteen forty. Give

37:37

us a brief anatomy of of

37:39

let's look park so we hear about

37:42

cheering hot what was hot what did

37:44

it do how many people were there

37:46

and what were some of the other

37:48

significant parts of the enterprise. Think

37:51

about how to use would you mention is

37:53

that it handled the naval signals and

37:56

that's what you're going to go over in

37:59

nineteen forty. It was

38:01

seen as most difficult and

38:03

it was the most one that

38:05

had the most security around it,

38:09

most complicated systems using the Make-Know-It-Is,

38:13

but he took it on as a challenge. And

38:16

it was not at all straightforward doing

38:18

it. It wasn't just broken like that.

38:20

There are lots of difficulties with it.

38:23

But that's what House 80 is. They've got

38:25

naval messages, which meant both

38:27

surface ships, Mediterranean and elsewhere,

38:29

and also the U-boats. And

38:31

of course, those parts of the

38:33

war, those naval aspects are the

38:36

most dependent on information. You

38:39

see absolutely that naval

38:42

war is all about information. You've got

38:44

to know where the ships are, where

38:46

the U-boats are, having an

38:49

attack or defense. It's

38:51

all about information. And so

38:53

getting actual

38:56

first-hand messages

38:59

in real time is absolutely the

39:01

most vital thing in that

39:03

period, I think, throughout the

39:06

Second World War. But

39:09

there are the HUTS. The HUTS-6

39:11

dealt with Army and Air Force. HUTS-4

39:14

was for interpreting the messages,

39:16

which is not much in

39:18

Jerry's business. But

39:20

they all had to work together because you had

39:23

to know a lot of the content of the messages in order

39:25

to break them. And

39:28

the two things, they're symbiotic. And

39:31

then, as I said, the number of

39:35

people working and the number of

39:37

machines that were working increased

39:40

enormously. There were 211

39:42

of these heartbreaking bombs in

39:45

the Bletchley area by the end of the war,

39:48

and more built in the United States as well. We

39:51

just started with one, you see, and they just grew and grew.

39:54

All of them needed operatives

39:57

to look after them. and

40:00

went through the procedures to

40:02

load them with the instructions and so

40:05

on. And then it did

40:07

become an enormous business. And

40:11

just out of interest, why was Turing sent to

40:13

Hot 8? Was it because it was the most

40:15

difficult one to break? Was it

40:17

intentional or was it happens once? He

40:20

wanted it. I mean, he

40:22

took it on because it was seen as

40:24

most difficult. And

40:26

he did indeed come up with a

40:29

very ingenious, well,

40:31

several very ingenious ideas. But

40:33

they were very stuck to begin with. Well,

40:37

there were several reasons for this. The

40:40

first reason is that the enigma used

40:43

for the naval messages simply had

40:45

more rotors than the others. It

40:47

had eight rotors. He

40:49

looked three out of a choice of eight

40:52

rather than three out of a choice of five.

40:54

That's made far more possibilities to

40:57

work through. So

41:00

that was why they didn't have rotors. They had

41:02

to capture those off Norway in 1940.

41:06

And then the other thing was that it's

41:08

all very well using the machines as they

41:10

did to break a single message. If

41:13

you can guess what's in the message, then

41:16

these machines were such that they

41:18

could, by working through

41:20

all the possibilities, work out

41:22

what the setting the enigma machine was for

41:24

that message in a matter of hours. Well,

41:27

that's already a great breakthrough, but that's not enough.

41:30

You want to break all the messages. I mean,

41:32

you can't do that for every single message. You

41:35

want to have a system. You want to know

41:37

the system by which the

41:39

keys to the other messages are

41:41

all hidden inside the transmitted messages.

41:44

Now, that system was the thing

41:47

that's actually breaking. It's

41:49

a mistake to think that the enigma machine itself

41:52

as a great secret, it wasn't. It was bound

41:54

to be captured in warfare and it was. What's

41:58

important is what we now think of as... the

42:00

software is how you use that key,

42:02

the instructions we're using the machine, how

42:04

it's set up, how the

42:08

password essentially is encoded within the

42:10

message itself. That's

42:13

what you've got to figure out and that's what we

42:15

had to work out and there was a rather complicated

42:17

way that this was done for the Naval Vests, which

42:20

they didn't get into until they

42:22

managed to capture some papers in

42:25

1941, only 1941. And

42:30

even that shouldn't have been the end of the

42:32

matter here. Well, it wasn't the end

42:34

of the matter, but they managed

42:36

to keep going until in 1942, the

42:42

German Navy introduced a

42:44

four-rosier enigma, which

42:46

is that much more complicated again. The

42:50

numbers were such that that just really should

42:52

have pushed it off the edge of what

42:54

was practical to break. As

42:56

it was, they had the very ingenious ways of

42:58

getting around there and in

43:00

collaboration with the United States, building a whole

43:02

lot more of these machines, they

43:04

were able to keep on top of

43:06

the business risk of the war. But I

43:08

want to emphasize there wasn't just one

43:11

moment of breaking the enigma, Turing's

43:13

basic algorithm, which he saw and

43:15

put together other people's ideas.

43:19

And the very beginning of war was an

43:21

essential part of the process and he's

43:23

famous for that algorithm,

43:26

but that was just the beginning. You

43:28

had to make this thing actually work

43:30

in practice and he did enormous amounts

43:32

of every trick in

43:34

the book, really, to guess the messages and

43:37

then get one message coming out and

43:39

then get from that message to

43:41

all the other messages in the key in

43:44

the same system. And

43:48

that was essentially what it's

43:51

like a major scientific program, you see. That's

43:53

how they attacked it. But

43:57

with the difference in the scientific program.

44:00

Is that they didn't have a long run is

44:03

not in the long run by the water is

44:05

not a yes they have done it didn't have

44:07

a long run it was a matter of months.

44:10

Day sweet and

44:14

it's things are changing all the time. And

44:17

the systems could be changed any moment

44:19

as they were in 1942 and always

44:22

hanging by hanging by three is

44:24

one of the expressions that they

44:27

use the new it whole thing

44:29

that collapsed any moment very very

44:31

exciting story. As

44:41

we've mentioned the touring work in hot

44:43

it the branch of Bletch Le

44:45

part the work to break German naval costs.

44:48

And this interlude we want to give you

44:50

a brief idea of what was at stake

44:52

for the team and hot it. This

44:55

was no mere intellectual exercise. The

44:58

fate of their country was on the line.

45:02

Naval intelligence was absolutely critical

45:04

to the second world. The

45:08

church believed that the Germans had the

45:10

best chance to defeat the allies on

45:13

sea. They think after the

45:15

war the only thing that

45:17

really frightened me during the war

45:19

was the you both peril. I

45:22

was even more anxious about this battle

45:24

that I had been about the glorious

45:26

air fight called the Battle of Britain.

45:30

The so-called Battle of the Atlantic waged on

45:32

for the entirety of the war from 1939

45:34

to 1945. The

45:38

ability to read the enemy covert

45:40

communications meant the possibility

45:42

of knowing the location of German you

45:45

both and better

45:47

protecting allied merchant ships carrying

45:49

priceless resources and supplies to

45:51

the British and to the

45:53

Soviets. Thus the

45:56

importance of touring an entire team at

45:58

a hot it's work. cannot

46:00

be understated. The

46:02

British relied on receiving supplies from

46:04

North America. Yes,

46:09

many factors contributed to the Allies

46:11

eventual success and the gradual weakening

46:14

of Nazi forces both on land

46:16

and in the air, but

46:18

winning the Battle of the Atlantic was

46:21

perhaps one of the most vital elements

46:23

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while saving businesses billions. Here

47:48

at the Spy Museum, we have a

47:51

three rotor and a four rotor enigma,

47:53

but you just tell the listeners a

47:55

bit more about that. The

47:57

story that we normally hear is the the

48:00

German Navy especially just felt like something

48:02

was up so they added an extra

48:04

rotor and the Allies were locked

48:06

back out of Enigma for a period of time. Could

48:08

you tell our listeners a little bit more about that

48:10

story? Well, yes, it was introduced

48:12

in February 1, 1942 before the Rode machine, only on

48:14

the Atlantic

48:17

U-Birds, I think. And

48:19

it's clear, obviously, they thought something was going

48:21

wrong. I mean, clearly, they wouldn't have done

48:23

this. They thought Enigma was perfectly around as

48:26

it was. But as I said, the Enigma

48:29

was not the most advanced

48:31

or perfect well-thought-out system

48:33

you could possibly have. And

48:35

the British actually had done a better

48:37

enhancement of it. And if

48:40

the German military and Navy had done that

48:42

right from the beginning, I don't think they

48:44

would ever have had their codes broken. And

48:46

it's really, it's quite a basic thing about

48:49

numbers here. Even basically

48:53

they've got a million or so settings

48:56

of the three-roader machine to go through.

48:58

And that just takes even

49:00

two hours. These are

49:16

the basic solutions. That sort

49:18

of thing they would do many times

49:20

a second. And if by going on for

49:22

hours, you would get through a million or

49:24

so, that's the basic numbers. Well,

49:28

if the numbers have been 20 times bigger,

49:31

every hour would have been turned into a day.

49:33

And they said, miracle, already, that it was just

49:35

possible. The pressure was

49:37

always on to speed up the machine.

49:39

So electronics came into the

49:42

picture in 1940, serving in 1942, trying

49:48

to make the things faster. But

49:50

Enigma wasn't really very suitable for

49:52

that. Electronics are much more suitable

49:54

for the binary type things, a

49:56

different type of cipher system which came in later. There's

50:00

always this pressure, always this difficulty, and

50:02

always the sense of only just working.

50:06

Have Jove made a

50:09

more wholesale change all

50:11

at once without any overlap

50:13

of messages or anything at all? They

50:15

probably would have succeeded. I think they

50:17

actually did do something like that right

50:19

at the very end of the war

50:21

and it's too late. It's not a

50:24

simple story at all about breaking the

50:27

code. It's breaking and re-breaking and then

50:29

breaking off and then breaking back and

50:33

the game that's been played between the two sides

50:35

where neither of them knows quite what the others

50:37

do. We spoke about

50:39

this previously, the bomb. Can you

50:41

just tell the listeners a little bit more about

50:44

that? I'm just trying

50:46

to get a... We know that he's in hot

50:48

A. What was Turing's signature

50:50

contribution as I understand it from your

50:52

book, The Bomb, as part of that?

50:54

Can you tell our listeners what

50:57

his contribution was and what the bomb was?

50:59

Yes. The bomb was

51:01

a basic workhouse. If

51:04

you had a cipher message and

51:06

if you could guess about 23 letters

51:08

of it, what they actually were as

51:11

plaintext and you could

51:13

put the two against each other, you could

51:15

set that up on this machine and

51:18

it would work throughout all the possibilities

51:20

for the settings of the machine and

51:23

with any luck would come

51:25

up with the answer. If you

51:27

could guess it absolutely correctly. By

51:29

miracle, they could just do that.

51:33

That needed a very clever algorithm for

51:36

eliminating all the settings that couldn't possibly

51:39

be true and that

51:41

was Turing's contribution. I

51:43

think that together with the knowledge

51:45

that this could be implemented in

51:47

the kind of moving path technology

51:49

that were used for telephone exchanges

51:51

at that time, this is pre-electronic

51:53

era. He did

51:56

that and in taking in

51:58

other people's ideas. as

52:00

well. And very quickly, as

52:02

I said, that was put in operation

52:05

with a really quite amazing speed

52:07

by early 1940, well

52:09

before it walked off really going. So

52:12

that's what he did. But as I said,

52:14

that was just the beginning. See, the

52:17

just that you can bring one message, it

52:19

doesn't mean that's not much use really, you

52:21

want to get more, to get any

52:23

sense of what's going on. And

52:26

that's where it needs a much

52:28

more systematic attack on the on

52:30

the using the nature of the

52:32

key system, how the key to

52:34

each message is encoded within

52:36

the message itself. And

52:39

this is the most problem in

52:41

any kind of cryptography now. You

52:43

know, it's always a problem

52:45

with secret keys of how the

52:47

sender and the receiver are going

52:49

to agree on the key to

52:51

each message. Do you arrange it all

52:53

in advance? Do you hide

52:56

it in the message itself? Or what you

52:58

see is whatever, every way has got some

53:00

difficulty. And

53:02

the only way out of it really

53:04

is what's in the coming in the

53:07

1970s is public key cryptography, which

53:09

relies on a completely different way of looking at it.

53:12

But that's not not relevant. So the

53:14

second world war period. So

53:17

that was yeah, that was Turing's first

53:19

major contribution was the

53:21

machine. As I

53:24

said, they built hundreds of them eventually, dealing

53:26

with all these different types of the enigma and

53:30

just just grew and grew until the end of

53:32

the war. But

53:35

what he had to do was much, much more than that.

53:38

Just as we get towards the end

53:40

here, what was it like for you,

53:42

you know, you're

53:44

doing this pathbreaking biography

53:46

of Turing, you know,

53:49

many years ago now in 1983. And

53:52

then in more recent decades and years,

53:54

he started to get more and more

53:56

that the public appreciation of

53:58

him has got wider. He's known

54:01

around the world and so

54:03

forth. What was that like

54:05

for you? You're a mathematician and you're

54:07

also a gay man like Turing and

54:09

you come along and you write

54:11

this book and the recognition

54:13

increases. So what was that like for

54:16

you, Andrew, just to almost be

54:18

vindicated if you want to put it like that? Yeah,

54:22

well, of course, it is in life's story,

54:24

really. Of course, it's not the only thing

54:26

I've done. So my whole, my main

54:29

career really has been in theoretical

54:31

physics, working with Roger Penrose, actually,

54:33

who's Nobel Prize winner. And

54:35

I've made some contributions to his ways

54:38

of looking at physics, that's been my

54:40

main job there, and teaching mathematics. Twester

54:42

Thiele has the right. Right, at Oxford

54:44

University. So it's not my whole life

54:46

being all about this. But it is

54:48

a fascinating thing. And of course, well,

54:51

the thing that strikes

54:53

everyone, of course, is

54:55

the whole social political change that's

54:57

taken place. There's no question that

54:59

Turing's become a far more acceptable

55:01

figure because it's everything

55:03

regarded as a very

55:07

regrettable and not really nice

55:09

to talk about end of

55:12

his life. It's now something that

55:14

we talked about as part

55:16

of social developing, social

55:18

history and the beginning of

55:21

a whole change of attitudes,

55:23

of which has now been

55:26

very wholesale change in Western

55:29

society. So that's really

55:31

been the main change. It's also true, of course,

55:33

that man has said that his

55:36

universal machines now in everyone's pocket and they're

55:38

all bleeping and clicking away

55:40

like mad. But I'm

55:42

not sure that's the reason really why he's

55:44

more famous. I think it's more that that

55:47

has become more acceptable to

55:51

have all these things named after him and

55:53

celebrating him. So

55:56

that's really, well, that's not for me to

55:58

do. public, you

56:00

know, to the side really.

56:03

That's a very... That's

56:05

the whole question in itself really. I mean, how

56:07

people are regarded, how science is

56:10

regarded, how history is regarded, how

56:12

sexuality is regarded. It's a huge

56:14

business and I was just rather

56:16

lucky to be in a very

56:18

interesting point where all of these things

56:21

intersected. I

56:23

think that your, you know, your broader

56:25

career and the main things that you've done

56:27

during your career,

56:29

I think that they feed into the biography

56:32

too because, you know, I feel

56:34

like you describe a lot of

56:36

the mechanical, a lot of the

56:38

more technical parts of this enterprise in

56:41

a way that I think is much more

56:43

lucid than people that are maybe coming to

56:45

it from a different perspective. So yeah, I

56:47

appreciate your contribution. And

56:49

final question, Andrew, what was it like to

56:51

be on stage at the Royal Albert Hall

56:53

with the Pet Shop Boys

56:55

to honor Turing? And Erin has

56:57

put in here, she can't find the video

56:59

anywhere, does it exist and can't review it? Well,

57:03

the BBC, well, there's not a

57:05

video of it as far as

57:07

I know. There's some photographs of

57:09

it, but it went down to an

57:12

audio only concert

57:15

on the BBC radio in July

57:17

2014. Well,

57:19

that was it. Yeah, well,

57:21

I love the Pet Shop Boys. So that

57:23

was something as magic, I must say. And

57:29

that was another of these extraordinary

57:31

coincidences where the BBC had commissioned

57:33

them to do something

57:37

for their Promenade concert series in

57:39

the summer of 2014. And

57:42

I may happen to know about my

57:44

story and go on to meet and I'm

57:46

all wonderful to work with. And

57:49

they used my words and so they

57:51

got it right, I think, and picked

57:53

out some of the main points. And

57:57

I was put it extraordinary. musical

58:00

thing to it. And

58:02

yeah, it's the only time in my life

58:04

when I've appeared on stage now with hope.

58:07

That's pretty true. Wow.

58:13

That's a pretty incredible story. Yeah, I've been

58:15

singing as a sin pretty much all day

58:17

in the build up tour conversation. So

58:20

I'm a pet shop boy as well.

58:22

So it's been a real pleasure to

58:24

speak to you, Andrew. Thanks for sharing

58:26

your expertise and your insights. I really

58:28

appreciate that. Ryan

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