1
00:00:00,000 --> 00:00:03,204
(Toby Walsh) I wanna talk 
about artificial intelligence: it's --

2
00:00:03,674 --> 00:00:05,089
I'm a professor of artificial intelligence

3
00:00:05,089 --> 00:00:09,271
and its a great time, 2015, 
to be working in AI.

4
00:00:09,544 --> 00:00:10,544
We're making real palpable progress

5
00:00:10,544 --> 00:00:12,820
and there's loads of money 
being thrown at us.

6
00:00:12,820 --> 00:00:17,000
Google just spent 
five hundred million dollars --

7
00:00:17,000 --> 00:00:21,989
pounds buying an AI startup called Deep Mind a couple of weeks ago,

8
00:00:21,989 --> 00:00:25,172
today they announced that they were 
going to spend a billion dollars

9
00:00:25,671 --> 00:00:28,469
setting up an AI lab in Silicon Valley.

10
00:00:29,001 --> 00:00:31,591
IBM is betting about 
a third of the company

11
00:00:31,830 --> 00:00:34,858
on their cognitive AI computing effort.

12
00:00:35,084 --> 00:00:38,216
So it's really interesting time to be working in AI.

13
00:00:38,631 --> 00:00:41,782
But the first thing I wanted to 
help inform you about

14
00:00:42,250 --> 00:00:46,792
is what is the state of art, 
what progress have we made in AI

15
00:00:46,792 --> 00:00:51,187
because Hollywood paints 
all these pictures,

16
00:00:51,187 --> 00:00:53,488
these mostly dystopian pictures of AI.

17
00:00:53,495 --> 00:00:58,672
Whenever the next science fiction movie
comes out, I put my head in my hands

18
00:00:58,672 --> 00:01:01,755
and think Oh my God, what do people think
that we're doing?

19
00:01:01,755 --> 00:01:08,729
So, I wanted to start by just giving you
a feel for what actually is really capable.

20
00:01:09,081 --> 00:01:13,872
So a couple of years ago, IBM Watson
won the game show Jeopardy 1,

21
00:01:13,872 --> 00:01:19,737
the million dollar prize in the game show,
Jeopardy P, the reigning human champions.

22
00:01:19,737 --> 00:01:23,357
Now, you might think, well that's just
a party trick, isn't it?

23
00:01:23,357 --> 00:01:27,625
It's a -- pour enough of Wikipedia 
and the internet into a computer,

24
00:01:27,625 --> 00:01:30,543
and it can answer general knowledge
questions.

25
00:01:30,543 --> 00:01:33,204
Well, you guys are being a bit unfair to
IBM Watson,

26
00:01:33,204 --> 00:01:35,881
there are the cryptic questions
they are answering.

27
00:01:35,881 --> 00:01:40,878
But just to give you a real feel for 
what is technically possible today,

28
00:01:40,878 --> 00:01:43,586
something that was announced
just two days ago:

29
00:01:43,834 --> 00:01:51,869
some colleagues of mine at NII in Japan
passed the University Entrance Exam

30
00:01:51,869 --> 00:01:53,433
with an AI program.

31
00:01:53,433 --> 00:01:56,326
Now, I thought long and hard about
putting up a page of maths.

32
00:01:56,326 --> 00:01:58,007
I thought, well, I'm going to get --

33
00:01:58,007 --> 00:02:00,007
half of the audience is going to 
leave immediately

34
00:02:00,007 --> 00:02:01,354
if I put up a page of math

35
00:02:01,354 --> 00:02:03,133
But I wanted you to see, just to feel

36
00:02:03,962 --> 00:02:07,403
the depth of questions 
that they were answering.

37
00:02:07,403 --> 00:02:11,507
So this is from the maths paper, you know,
a non trivial, sort of,

38
00:02:11,507 --> 00:02:15,148
if you come from the UK, 
A-level-like math question

39
00:02:15,148 --> 00:02:16,468
that they were able to answer

40
00:02:17,272 --> 00:02:21,889
Here is a physics question
about Newtonian dynamics

41
00:02:21,889 --> 00:02:23,552
that they were able to answer.

42
00:02:23,552 --> 00:02:28,545
Now they got 511 points, out of
a maximum of 950.

43
00:02:28,939 --> 00:02:32,391
That's more than the average score
of Japanese students

44
00:02:32,391 --> 00:02:34,007
sitting the entrance exam.

45
00:02:34,007 --> 00:02:38,542
They would have got into most 
Japanese universities with a score of 511.

46
00:02:38,908 --> 00:02:40,621
That's what's possible today.

47
00:02:40,621 --> 00:02:44,134
Their ambition in 10 years' time is to get
into Tokyo, University of Tokyo,

48
00:02:44,134 --> 00:02:46,434
which is one of the best universities
in the world.

49
00:02:48,488 --> 00:02:50,475
So, this is why I put up 
a picture of Terminator,

50
00:02:50,475 --> 00:02:53,468
because whenever I talk to the media
about what we do in AI,

51
00:02:53,476 --> 00:02:55,769
they put up a picture of Terminator,
right?

52
00:02:55,769 --> 00:02:58,098
So I don't want you to worry 
about Terminator,

53
00:02:58,098 --> 00:03:02,117
Terminator is at least 
50 to 100 years away.

54
00:03:02,582 --> 00:03:05,985
and there are lots of reasons why
we don't have to worry about it,

55
00:03:05,985 --> 00:03:07,248
about Terminator.

56
00:03:07,248 --> 00:03:08,979
I'm not going to go and spend
too much time

57
00:03:08,979 --> 00:03:11,348
on why you don't have to worry about Terminator.

58
00:03:11,676 --> 00:03:13,334
But there is actually things 
that you should worry about,

59
00:03:13,334 --> 00:03:15,352
much nearer than Terminator.

60
00:03:17,007 --> 00:03:20,160
Many people have said, 
Stephen Hawkins has said

61
00:03:20,160 --> 00:03:22,713
that, you know, AI is going to spell
the end of the human race.

62
00:03:23,295 --> 00:03:27,961
Elon Musk chimed in afterwards, said
"It's our biggest existential threat."

63
00:03:29,793 --> 00:03:32,841
Bill Gates followed on by saying,
"Elon Musk was right."

64
00:03:33,498 --> 00:03:39,519
Lots of people have said that's a --
AI is a real existential threat to us.

65
00:03:39,519 --> 00:03:42,887
I don't want you to worry about
the existential threat that AI

66
00:03:42,887 --> 00:03:44,900
or Terminator is going to bring.

67
00:03:45,953 --> 00:03:47,711
There's actually a very common confusion,

68
00:03:48,121 --> 00:03:51,139
which is that it's not the AI 
that's going to be the existential threat,

69
00:03:51,139 --> 00:03:52,139
it's autonomy, it's autonomous systems.

70
00:03:54,386 --> 00:03:56,042
What's in the (check) --

71
00:03:56,042 --> 00:03:57,972
it isn't it going to wake up 
any time in the morning and say:

72
00:03:57,972 --> 00:04:02,109
"You know what? I'm tired 
of playing Jeopardy,

73
00:04:02,109 --> 00:04:04,173
"I want to play Who Wants to Be a Millionaire!

74
00:04:05,299 --> 00:04:07,468
"Or wait a second, I'm tired of playing 
game shows,

75
00:04:07,468 --> 00:04:09,393
I want to take over the universe."

76
00:04:09,821 --> 00:04:12,195
It's just not in its code, there is no way,

77
00:04:12,195 --> 00:04:15,065
it's not given any freedom to think 
about anything other

78
00:04:15,065 --> 00:04:17,000
than maximizing its Jeopardy score.

79
00:04:18,219 --> 00:04:21,209
And it has no desires, no other desires than,

80
00:04:21,228 --> 00:04:23,482
other to improve its maximum scores.

81
00:04:23,482 --> 00:04:26,256
So I don't want you to worry about Terminator,

82
00:04:27,350 --> 00:04:29,102
but I do want you to worry about jobs.

83
00:04:29,974 --> 00:04:32,166
Because lots of people, 
lots of very serious people,

84
00:04:32,166 --> 00:04:35,076
have been saying 
hat AI is going to end jobs,

85
00:04:35,076 --> 00:04:38,157
and that is a very great consequence 
for anyone working in education,

86
00:04:38,157 --> 00:04:42,269
because, certainly, the jobs that are going 
to exist in the future

87
00:04:42,269 --> 00:04:44,925
are going to be different 
than the jobs that exist today.

88
00:04:46,880 --> 00:04:49,724
Now, who has an odd birthday?

89
00:04:51,251 --> 00:04:52,938
Well, I haven't told you 
what an odd birthday is yet,

90
00:04:52,938 --> 00:04:54,990
so someone has an odd birthday, like me.

91
00:04:54,990 --> 00:04:57,858
OK. Who was born on an odd-number 
day of the month?

92
00:04:57,858 --> 00:04:59,995
I was born on the 11th of April, right?

93
00:05:00,824 --> 00:05:03,368
Come on, it's half the room, 
I know it's half the room.

94
00:05:03,368 --> 00:05:04,923
(Laughter)

95
00:05:04,923 --> 00:05:08,690
OK.Well, you want to have 
an odd birthday, by the way,

96
00:05:09,059 --> 00:05:12,504
because that means, in 20 years' time, 
you will be a person with a job.

97
00:05:13,426 --> 00:05:16,277
As opposed to the even people, 
who won't have jobs.

98
00:05:16,277 --> 00:05:20,662
That's certainty -- if you believe 
lots of serious people,

99
00:05:22,141 --> 00:05:25,010
you might have missed this news 
on Friday the 13th,

100
00:05:25,010 --> 00:05:27,778
I thought this was a rather
depressing news story

101
00:05:27,778 --> 00:05:29,748
....... (check) comparison otherwise ...... (check)

102
00:05:29,777 --> 00:05:31,527
but the chief economist, Bank of England,

103
00:05:31,922 --> 00:05:36,230
went on the record saying 50% of jobs 
were under threat in the UK.

104
00:05:36,948 --> 00:05:40,420
And he's not the first serious person
who should know what he's talking about

105
00:05:40,420 --> 00:05:42,736
who said similar things.

106
00:05:43,029 --> 00:05:46,255
There was a very influential Merrill Lynch
report that came out a month or to ago

107
00:05:46,270 --> 00:05:49,430
saying very similar things about 
the impact of AI,

108
00:05:49,430 --> 00:05:51,375
robotics, automation on jobs.

109
00:05:53,439 --> 00:05:56,278
And some of this goes back to, I think, 
one of the first reports

110
00:05:56,278 --> 00:05:59,288
that really hit the press, 
that really got people's attention,

111
00:05:59,288 --> 00:06:02,075
was a report that came out of 
the Oxford Martin School.

112
00:06:02,075 --> 00:06:05,702
They predicted that 47% of jobs 
in the United States

113
00:06:06,110 --> 00:06:08,550
were under threat of automation 
in the next 20 years.

114
00:06:10,234 --> 00:06:13,594
We followed that up 
with a very similar study and analysis

115
00:06:13,880 --> 00:06:15,961
for jobs in Australia, where I work.

116
00:06:16,865 --> 00:06:19,323
And because it's a slightly different 
profile of workers,

117
00:06:19,323 --> 00:06:24,329
of the work force in Australia, we came up
with a number of around 40%.

118
00:06:24,329 --> 00:06:27,129
These are non trivial numbers, right? 
40-50%.

119
00:06:27,589 --> 00:06:32,497
No, just an aside: 47%, I don't know 
why they didn't say 47.2%, right?

120
00:06:32,497 --> 00:06:35,551
You can't believe a number 
that's far too precise

121
00:06:35,551 --> 00:06:37,842
when you're predicting the future,
but nevertheless,

122
00:06:37,842 --> 00:06:39,532
the fact that it's of this sort of scale,

123
00:06:39,532 --> 00:06:44,601
you've got to take away: it wasn't 4%, 
it was roughly about half the jobs.

124
00:06:47,784 --> 00:06:50,495
Now, let's put some context to this.

125
00:06:50,495 --> 00:06:52,413
I mean, is this really a credible claim?

126
00:06:52,413 --> 00:06:55,549
The Number One job 
in the United States today: truck driver.

127
00:06:55,962 --> 00:06:57,526
Now you might have noticed,

128
00:06:57,536 --> 00:07:00,079
the autonomous cars
are coming to us very soon.

129
00:07:00,506 --> 00:07:03,579
We're going to be having -- tried
the first trial of autonomous cars

130
00:07:03,579 --> 00:07:06,760
on the roads, public roads of Australia, 
three weeks ago.

131
00:07:07,371 --> 00:07:09,657
The Google Car has driven 
over a million kilometers

132
00:07:09,657 --> 00:07:12,542
-- or the Google cars, rather, 
have driven over a million kilometers,

133
00:07:12,907 --> 00:07:15,050
autonomously, on the roads of California.

134
00:07:15,893 --> 00:07:18,553
In 20 years' time, we are going to have 
autonomous cars.

135
00:07:18,553 --> 00:07:20,255
We're also going to have 
autonomous trucks.

136
00:07:21,033 --> 00:07:24,769
So if you are in the Number One profession
in the United States,

137
00:07:24,769 --> 00:07:28,480
you have to worry that your job 
is not going to be automated away.

138
00:07:29,712 --> 00:07:32,494
The Number Two job in the United States 
is salesperson.

139
00:07:33,343 --> 00:07:36,248
Again, since we use the internet,

140
00:07:36,248 --> 00:07:39,618
we've actually mostly automated 
that process ourselves,

141
00:07:39,618 --> 00:07:43,382
but it's clear that a lot of those jobs 
are going to be disappearing.

142
00:07:43,382 --> 00:07:46,736
So I think these claims 
have a lot of credibility.

143
00:07:48,896 --> 00:07:53,104
There's actually a nice dinner party game 
that my colleagues in AI play

144
00:07:53,104 --> 00:07:55,736
at the end of our conferences,
where we sit around

145
00:07:55,736 --> 00:07:58,250
and the game is, you have to name a job

146
00:07:59,115 --> 00:08:02,671
and then, someone has to put up 
some credible evidence

147
00:08:02,671 --> 00:08:05,748
that we're actually well on the way 
to actually automating that.

148
00:08:05,748 --> 00:08:08,152
And this game is almost impossible to win.

149
00:08:08,737 --> 00:08:10,423
If I had more time, 
I'd play the game with you.

150
00:08:11,293 --> 00:08:15,260
The only -- about the only winning answer
is politician.

151
00:08:15,650 --> 00:08:17,931
(Laughter)

152
00:08:17,931 --> 00:08:20,747
They will certainly regulate that
they'll be the last to be automated.

153
00:08:20,747 --> 00:08:22,731
But that's about 
the only winning answer we have.

154
00:08:24,049 --> 00:08:28,836
So -- and it's not just technology 
that is the cause of this.

155
00:08:28,836 --> 00:08:33,035
There's many other, really, 
sort of rather unhelpful trends.

156
00:08:33,035 --> 00:08:35,558
If you were trying to set up 
the world's economy,

157
00:08:35,558 --> 00:08:38,842
you would not put these things 
all down on the table at the same time:

158
00:08:38,842 --> 00:08:40,825
the global, 
ongoing global financial crisis,

159
00:08:40,825 --> 00:08:43,840
which seems like 
it will never disappear, I think;

160
00:08:44,755 --> 00:08:48,013
the fact that we're all living longer: 
this is great, great news for us

161
00:08:48,013 --> 00:08:50,333
but bad news for employment;

162
00:08:50,961 --> 00:08:54,425
the impact of globalization, the fact that 
we can outsource our work

163
00:08:54,425 --> 00:08:56,191
to cheaper economies.

164
00:08:56,191 --> 00:09:00,191
All of these things 
are compounding the impact

165
00:09:00,191 --> 00:09:02,957
that technology is having 
on the nature of work.

166
00:09:04,749 --> 00:09:09,725
And this transformation is going to be 
different than the last one,

167
00:09:09,725 --> 00:09:11,357
the Industrial revolution.

168
00:09:12,021 --> 00:09:15,591
There's no hard and fast 
rule of economics that says:

169
00:09:16,911 --> 00:09:20,039
"As many jobs need to be created 
by a new technology as destroyed."

170
00:09:20,039 --> 00:09:22,952
Every time we have a new technology, 
of course, new jobs are created.

171
00:09:22,952 --> 00:09:25,883
There's lots of, there's thousands, 
hundreds of thousands of new jobs

172
00:09:26,204 --> 00:09:27,848
enabled by technology today.

173
00:09:28,355 --> 00:09:32,484
But there's no reason that they have to 
balance exactly those that are destroyed.

174
00:09:33,092 --> 00:09:36,199
In the last -- in the last revolution, 
that did happen to be the case.

175
00:09:36,853 --> 00:09:40,930
A third of the population was working 
out in the fields, in agriculture.

176
00:09:40,930 --> 00:09:44,552
Now, worldwide, 
it's 3 or 4% of the world's population

177
00:09:44,552 --> 00:09:45,657
working in agriculture.

178
00:09:45,657 --> 00:09:48,029
Those people are working 
in factories and offices now.

179
00:09:48,029 --> 00:09:51,920
We employ far more people than we did 
at the turn of the 19th century.

180
00:09:52,629 --> 00:09:55,993
But this one looks different, this 
information revolution looks different.

181
00:09:55,993 --> 00:10:00,233
It looks like it has the potential 
to take away more jobs, perhaps,

182
00:10:00,233 --> 00:10:01,529
than it does.

183
00:10:01,529 --> 00:10:03,684
And one of the other things is that 
we used to think

184
00:10:03,684 --> 00:10:05,293
it was the blue-collar jobs.

185
00:10:06,509 --> 00:10:10,937
And that's true: if you go 
to a car factory today, sure enough,

186
00:10:10,937 --> 00:10:12,578
there are robots 
that are doing the painting,

187
00:10:12,578 --> 00:10:14,800
there are robots 
that are doing the welding.

188
00:10:14,800 --> 00:10:16,584
But nowadays, it's white-collar jobs:

189
00:10:16,584 --> 00:10:20,006
it's journalists, it's lawyers, 
it's accountants,

190
00:10:20,006 --> 00:10:21,667
these jobs that are under threat.

191
00:10:21,667 --> 00:10:25,444
These graphs here show 
the percentage change in employment

192
00:10:25,444 --> 00:10:31,244
and the change in employment rates.

193
00:10:31,660 --> 00:10:34,672
And it's the middle, the middle class, 
white-collar professions

194
00:10:34,672 --> 00:10:37,923
that we thought that you would go 
to university to make yourself safe,

195
00:10:37,926 --> 00:10:40,624
but it seems to be the ones 
that are most under threat.

196
99:59:59,999 --> 99:59:59,999
If you are a ....... (check) 
it's probably --

197
99:59:59,999 --> 99:59:59,999
you're too cheap to be replaced 
by something automated.

198
99:59:59,999 --> 99:59:59,999
But if you're a more expensive person, 
and this means (check)

199
99:59:59,999 --> 99:59:59,999
that the rich are getting richer and 
inequalities that we are seeing in society

200
99:59:59,999 --> 99:59:59,999
that are distressing our societies to day,

201
99:59:59,999 --> 99:59:59,999
seem to be magnified 
by these technological changes.

202
99:59:59,999 --> 99:59:59,999
And there is so many frightening graphs,

203
99:59:59,999 --> 99:59:59,999
if you're going to read 
Thomas Picketty (check), I encourage you.

204
99:59:59,999 --> 99:59:59,999
Go and look at one of his books
and you can see here

205
99:59:59,999 --> 99:59:59,999
that we're seeing 
a constant improvement in productivity.

206
99:59:59,999 --> 99:59:59,999
Technology is buying us 
those improvements in productivity,

207
99:59:59,999 --> 99:59:59,999
is increasing our wealth,
but there's a leveling off of employment.

208
99:59:59,999 --> 99:59:59,999
And so, the challenge, then, is how

209
99:59:59,999 --> 99:59:59,999
-- it's a question for society, 
not for a technologist like myself --

210
99:59:59,999 --> 99:59:59,999
how do we all benefit 
from this rising tide,

211
99:59:59,999 --> 99:59:59,999
not so that it is the rich get richer 
and the rest of us get further behind.

212
99:59:59,999 --> 99:59:59,999
So, many parts of many jobs 
looks likely (check) to be automated.

213
99:59:59,999 --> 99:59:59,999
One confusion is this: people say 
these jobs are going to disappear.

214
99:59:59,999 --> 99:59:59,999
Actually, it seems to be more likely that 
many parts of your job will be automated.

215
99:59:59,999 --> 99:59:59,999
But that still means that there is 
perhaps less employment around.

216
99:59:59,999 --> 99:59:59,999
So how can you make yourself 
more future-proof?

217
99:59:59,999 --> 99:59:59,999
Well, I have two pieces of advice 
as a technologist,

218
99:59:59,999 --> 99:59:59,999
in terms of what's going to be 
technically possible in AI.

219
99:59:59,999 --> 99:59:59,999
Either you've got to embrace the future, 
so become like me,

220
99:59:59,999 --> 99:59:59,999
become someone who's working 
on trying to invent that future.

221
99:59:59,999 --> 99:59:59,999
And if you're not technically minded, 
that's fine:

222
99:59:59,999 --> 99:59:59,999
I've got the other part of the equation, 
the other answer to your question

223
99:59:59,999 --> 99:59:59,999
which is completely at the other end 
of the spectrum, which is:

224
99:59:59,999 --> 99:59:59,999
focus on those things that find as AI, (check)
the hardest things,

225
99:59:59,999 --> 99:59:59,999
making a future that's more creative,

226
99:59:59,999 --> 99:59:59,999
making a future that can understand 
your emotional state,

227
99:59:59,999 --> 99:59:59,999
focusing on emotional terms 
and not intellectual intelligence. 12:23