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do you trust this computer eng

Feb 5th, 2019
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  3. INDOXXI
  4. Support dengan like & share :)
  5.  
  6. 1
  7. 00:00:30,000 --> 00:00:33,500
  8. Correction and synchronisation:
  9. Mazrim Taim
  10.  
  11. 2
  12. 00:00:35,078 --> 00:00:41,302
  13. What we're on the brink of is
  14. a world of increasingly intense,
  15.  
  16. 3
  17. 00:00:41,345 --> 00:00:45,219
  18. sophisticated artificial intelligence.
  19.  
  20. 4
  21. 00:00:45,262 --> 00:00:48,396
  22. Technology is evolving
  23. so much faster than our society
  24.  
  25. 5
  26. 00:00:48,439 --> 00:00:51,181
  27. has the ability
  28. to protect us as citizens.
  29.  
  30. 6
  31. 00:00:51,486 --> 00:00:55,707
  32. The robots are coming,
  33. and they will destroy our livelihoods.
  34.  
  35. 7
  36. 00:01:01,887 --> 00:01:04,238
  37. You have a networked intelligence
  38. that watches us,
  39.  
  40. 8
  41. 00:01:04,281 --> 00:01:08,590
  42. knows everything about us,
  43. and begins to try to change us.
  44.  
  45. 9
  46. 00:01:08,633 --> 00:01:12,768
  47. Twitter has become
  48. the world's number-one news site.
  49.  
  50. 10
  51. 00:01:12,811 --> 00:01:15,205
  52. Technology is never good or bad.
  53.  
  54. 11
  55. 00:01:15,249 --> 00:01:18,948
  56. It's what we do
  57. with the technology.
  58.  
  59. 12
  60. 00:01:18,991 --> 00:01:22,734
  61. Eventually, millions of people
  62. are gonna be thrown out of jobs
  63.  
  64. 13
  65. 00:01:22,778 --> 00:01:25,737
  66. because their skills
  67. are going to be obsolete.
  68.  
  69. 14
  70. 00:01:25,781 --> 00:01:27,435
  71. Mass unemployment...
  72.  
  73. 15
  74. 00:01:27,478 --> 00:01:31,727
  75. greater inequalities,
  76. even social unrest.
  77.  
  78. 16
  79. 00:01:32,570 --> 00:01:35,530
  80. Regardless of whether
  81. to be afraid or not afraid,
  82.  
  83. 17
  84. 00:01:35,573 --> 00:01:38,185
  85. the change is coming,
  86. and nobody can stop it.
  87.  
  88. 18
  89. 00:01:44,582 --> 00:01:48,146
  90. We've invested huge amounts of money,
  91. and so it stands to reason
  92.  
  93. 19
  94. 00:01:48,148 --> 00:01:50,893
  95. that the military,
  96. with their own desires,
  97.  
  98. 20
  99. 00:01:50,936 --> 00:01:53,330
  100. are gonna start to use
  101. these technologies.
  102.  
  103. 21
  104. 00:01:53,374 --> 00:01:57,552
  105. Autonomous weapons systems
  106. could lead to a global arms race
  107.  
  108. 22
  109. 00:01:57,595 --> 00:02:00,032
  110. to rival the Nuclear Era.
  111.  
  112. 23
  113. 00:02:02,339 --> 00:02:05,429
  114. We know what the answer is.
  115. They'll eventually be killing us.
  116.  
  117. 24
  118. 00:02:10,826 --> 00:02:15,874
  119. These technology leaps
  120. are gonna yield incredible miracles
  121.  
  122. 25
  123. 00:02:15,918 --> 00:02:18,181
  124. and incredible horrors.
  125.  
  126. 26
  127. 00:02:24,274 --> 00:02:29,323
  128. We created it,
  129. so I think, as we move forward,
  130.  
  131. 27
  132. 00:02:29,366 --> 00:02:33,762
  133. this intelligence
  134. will contain parts of us.
  135.  
  136. 28
  137. 00:02:33,805 --> 00:02:35,981
  138. And I think the question is:
  139.  
  140. 29
  141. 00:02:36,025 --> 00:02:39,463
  142. Will it contain
  143. the good parts...
  144.  
  145. 30
  146. 00:02:39,507 --> 00:02:41,378
  147. or the bad parts?
  148.  
  149. 31
  150. 00:03:04,836 --> 00:03:08,840
  151. The survivors
  152. called the war "Judgment Day."
  153.  
  154. 32
  155. 00:03:08,884 --> 00:03:12,583
  156. They lived only to face
  157. a new nightmare:
  158.  
  159. 33
  160. 00:03:12,627 --> 00:03:14,319
  161. The war against the machines.
  162.  
  163. 34
  164. 00:03:15,456 --> 00:03:18,023
  165. I think
  166. we've completely fucked this up.
  167.  
  168. 35
  169. 00:03:18,067 --> 00:03:21,549
  170. I think Hollywood has managed
  171. to inoculate the general public
  172.  
  173. 36
  174. 00:03:21,592 --> 00:03:24,247
  175. against this question.
  176.  
  177. 37
  178. 00:03:24,291 --> 00:03:28,251
  179. The idea of machines
  180. that will take over the world.
  181.  
  182. 38
  183. 00:03:28,295 --> 00:03:30,645
  184. Open the pod bay doors, HAL.
  185.  
  186. 39
  187. 00:03:30,688 --> 00:03:33,561
  188. I'm sorry, Dave.
  189.  
  190. 40
  191. 00:03:33,604 --> 00:03:35,911
  192. I'm afraid I can't do that.
  193.  
  194. 41
  195. 00:03:37,434 --> 00:03:38,696
  196. HAL?
  197.  
  198. 42
  199. 00:03:38,740 --> 00:03:40,437
  200. We've cried wolf enough times...
  201.  
  202. 43
  203. 00:03:40,481 --> 00:03:42,483
  204. ...that the public
  205. has stopped paying attention,
  206.  
  207. 44
  208. 00:03:42,484 --> 00:03:44,120
  209. because it feels like
  210. science fiction.
  211.  
  212. 45
  213. 00:03:44,121 --> 00:03:46,001
  214. Even sitting here talking
  215. about it right now,
  216.  
  217. 46
  218. 00:03:46,002 --> 00:03:48,301
  219. it feels a little bit silly,
  220. a little bit like,
  221.  
  222. 47
  223. 00:03:48,302 --> 00:03:51,697
  224. "Oh, this is an artifact
  225. of some cheeseball movie."
  226.  
  227. 48
  228. 00:03:51,709 --> 00:03:56,584
  229. The WOPR spends all its time
  230. thinking about World War III.
  231.  
  232. 49
  233. 00:03:56,627 --> 00:03:59,064
  234. But it's not.
  235.  
  236. 50
  237. 00:03:59,108 --> 00:04:02,111
  238. The general public is about
  239. to get blindsided by this.
  240.  
  241. 51
  242. 00:04:11,555 --> 00:04:13,514
  243. As a society and as individuals,
  244.  
  245. 52
  246. 00:04:13,557 --> 00:04:18,954
  247. we're increasingly surrounded
  248. by machine intelligence.
  249.  
  250. 53
  251. 00:04:18,997 --> 00:04:22,653
  252. We carry this pocket device
  253. in the palm of our hand
  254.  
  255. 54
  256. 00:04:22,697 --> 00:04:24,829
  257. that we use to make
  258. a striking array
  259.  
  260. 55
  261. 00:04:24,873 --> 00:04:26,831
  262. of life decisions right now,
  263.  
  264. 56
  265. 00:04:26,875 --> 00:04:29,007
  266. aided by a set
  267. of distant algorithms
  268.  
  269. 57
  270. 00:04:29,051 --> 00:04:30,748
  271. that we have no understanding.
  272.  
  273. 58
  274. 00:04:34,186 --> 00:04:36,537
  275. We're already pretty jaded
  276. about the idea
  277.  
  278. 59
  279. 00:04:36,580 --> 00:04:37,929
  280. that we can talk to our phone,
  281.  
  282. 60
  283. 00:04:37,973 --> 00:04:40,062
  284. and it mostly understands us.
  285.  
  286. 61
  287. 00:04:40,105 --> 00:04:42,456
  288. I found quite a number
  289. of action films.
  290.  
  291. 62
  292. 00:04:42,499 --> 00:04:44,327
  293. Five years ago -- no way.
  294.  
  295. 63
  296. 00:04:44,371 --> 00:04:47,678
  297. Robotics.
  298. Machines that see and speak...
  299.  
  300. 64
  301. 00:04:47,722 --> 00:04:48,897
  302. ...and listen.
  303.  
  304. 65
  305. 00:04:48,940 --> 00:04:50,202
  306. All that's real now.
  307.  
  308. 66
  309. 00:04:50,246 --> 00:04:51,639
  310. And these technologies
  311.  
  312. 67
  313. 00:04:51,682 --> 00:04:54,886
  314. are gonna fundamentally
  315. change our society.
  316.  
  317. 68
  318. 00:04:55,730 --> 00:05:00,212
  319. Now we have this great
  320. movement of self-driving cars.
  321.  
  322. 69
  323. 00:05:00,256 --> 00:05:01,953
  324. Driving a car autonomously
  325.  
  326. 70
  327. 00:05:01,997 --> 00:05:05,688
  328. can move people's lives
  329. into a better place.
  330.  
  331. 71
  332. 00:05:06,131 --> 00:05:09,570
  333. I've lost a number of family members,
  334. including my mother,
  335.  
  336. 72
  337. 00:05:09,613 --> 00:05:11,876
  338. my brother and sister-in-law
  339. and their kids,
  340.  
  341. 73
  342. 00:05:11,920 --> 00:05:14,009
  343. to automobile accidents.
  344.  
  345. 74
  346. 00:05:14,052 --> 00:05:18,405
  347. It's pretty clear we could
  348. almost eliminate car accidents
  349.  
  350. 75
  351. 00:05:18,448 --> 00:05:20,102
  352. with automation.
  353.  
  354. 76
  355. 00:05:20,145 --> 00:05:21,843
  356. 30,000 lives in the U.S. alone.
  357.  
  358. 77
  359. 00:05:21,886 --> 00:05:24,955
  360. About a million around the world
  361. per year.
  362.  
  363. 78
  364. 00:05:25,499 --> 00:05:27,501
  365. In healthcare, early indicators
  366.  
  367. 79
  368. 00:05:27,544 --> 00:05:29,503
  369. are the name of the game
  370. in that space,
  371.  
  372. 80
  373. 00:05:29,546 --> 00:05:33,158
  374. so that's another place where
  375. it can save somebody's life.
  376.  
  377. 81
  378. 00:05:33,202 --> 00:05:35,726
  379. Here in
  380. the breast-cancer center,
  381.  
  382. 82
  383. 00:05:35,770 --> 00:05:38,381
  384. all the things that
  385. the radiologist's brain
  386.  
  387. 83
  388. 00:05:38,425 --> 00:05:43,386
  389. does in two minutes,
  390. the computer does instantaneously.
  391.  
  392. 84
  393. 00:05:43,430 --> 00:05:47,303
  394. The computer has looked
  395. at 1 billion mammograms,
  396.  
  397. 85
  398. 00:05:47,347 --> 00:05:49,261
  399. and it takes that data
  400. and applies it
  401.  
  402. 86
  403. 00:05:49,305 --> 00:05:51,438
  404. to this image instantaneously,
  405.  
  406. 87
  407. 00:05:51,481 --> 00:05:54,441
  408. so the medical application
  409. is profound.
  410.  
  411. 88
  412. 00:05:56,399 --> 00:05:59,402
  413. Another really exciting area that
  414. we're seeing a lot of development in
  415.  
  416. 89
  417. 00:05:59,446 --> 00:06:03,275
  418. is actually understanding
  419. our genetic code
  420.  
  421. 90
  422. 00:06:03,319 --> 00:06:06,104
  423. and using that
  424. to both diagnose disease
  425.  
  426. 91
  427. 00:06:06,148 --> 00:06:07,758
  428. and create
  429. personalized treatments.
  430.  
  431. 92
  432. 00:06:11,675 --> 00:06:14,112
  433. The primary application
  434. of all these machines
  435.  
  436. 93
  437. 00:06:14,156 --> 00:06:17,246
  438. will be to extend
  439. our own intelligence.
  440.  
  441. 94
  442. 00:06:17,289 --> 00:06:19,422
  443. We'll be able to make
  444. ourselves smarter,
  445.  
  446. 95
  447. 00:06:19,466 --> 00:06:22,543
  448. and we'll be better
  449. at solving problems.
  450.  
  451. 96
  452. 00:06:22,586 --> 00:06:25,075
  453. We don't have to age.
  454. We'll actually understand aging.
  455.  
  456. 97
  457. 00:06:25,076 --> 00:06:27,126
  458. We'll be able to stop it.
  459.  
  460. 98
  461. 00:06:27,169 --> 00:06:29,519
  462. There's really no limit
  463. to what intelligent machines
  464.  
  465. 99
  466. 00:06:29,563 --> 00:06:30,868
  467. can do for the human race.
  468.  
  469. 100
  470. 00:06:36,308 --> 00:06:39,399
  471. How could a smarter machine
  472. not be a better machine?
  473.  
  474. 101
  475. 00:06:42,053 --> 00:06:44,708
  476. It's hard to say exactly
  477. when I began to think
  478.  
  479. 102
  480. 00:06:44,752 --> 00:06:46,971
  481. that that was a bit naive.
  482.  
  483. 103
  484. 00:06:56,503 --> 00:07:00,898
  485. Stuart Russell, he's basically a god
  486. in the field of artificial intelligence.
  487.  
  488. 104
  489. 00:07:00,942 --> 00:07:04,380
  490. He wrote the book that almost
  491. every university uses.
  492.  
  493. 105
  494. 00:07:04,424 --> 00:07:06,948
  495. I used to say it's the
  496. best-selling AI textbook.
  497.  
  498. 106
  499. 00:07:06,991 --> 00:07:10,255
  500. Now I just say "It's the PDF
  501. that's stolen most often."
  502.  
  503. 107
  504. 00:07:13,694 --> 00:07:17,306
  505. Artificial intelligence is
  506. about making computers smart,
  507.  
  508. 108
  509. 00:07:17,349 --> 00:07:19,830
  510. and from the point
  511. of view of the public,
  512.  
  513. 109
  514. 00:07:19,874 --> 00:07:21,484
  515. what counts as AI
  516. is just something
  517.  
  518. 110
  519. 00:07:21,528 --> 00:07:23,268
  520. that's surprisingly intelligent
  521.  
  522. 111
  523. 00:07:23,312 --> 00:07:25,488
  524. compared to what
  525. we thought computers
  526.  
  527. 112
  528. 00:07:25,532 --> 00:07:28,004
  529. would typically be able to do.
  530.  
  531. 113
  532. 00:07:28,448 --> 00:07:33,801
  533. AI is a field of research
  534. to try to basically simulate
  535.  
  536. 114
  537. 00:07:33,844 --> 00:07:36,717
  538. all kinds of human capabilities.
  539.  
  540. 115
  541. 00:07:36,760 --> 00:07:38,719
  542. We're in the AI era.
  543.  
  544. 116
  545. 00:07:38,762 --> 00:07:40,503
  546. Silicon Valley
  547. has the ability to focus
  548.  
  549. 117
  550. 00:07:40,547 --> 00:07:42,462
  551. on one bright, shiny thing.
  552.  
  553. 118
  554. 00:07:42,505 --> 00:07:45,508
  555. It was social networking and
  556. social media over the last decade,
  557.  
  558. 119
  559. 00:07:45,552 --> 00:07:48,119
  560. and it's pretty clear
  561. that the bit has flipped.
  562.  
  563. 120
  564. 00:07:48,163 --> 00:07:50,557
  565. And it starts
  566. with machine learning.
  567.  
  568. 121
  569. 00:07:50,600 --> 00:07:54,343
  570. When we look back at this moment,
  571. what was the first AI?
  572.  
  573. 122
  574. 00:07:54,386 --> 00:07:57,389
  575. It's not sexy, and it isn't the thing
  576. we could see at the movies,
  577.  
  578. 123
  579. 00:07:57,433 --> 00:08:00,741
  580. but you'd make a great case
  581. that Google created,
  582.  
  583. 124
  584. 00:08:00,784 --> 00:08:03,395
  585. not a search engine,
  586. but a godhead.
  587.  
  588. 125
  589. 00:08:03,439 --> 00:08:06,486
  590. A way for people to ask
  591. any question they wanted
  592.  
  593. 126
  594. 00:08:06,529 --> 00:08:08,270
  595. and get the answer they needed.
  596.  
  597. 127
  598. 00:08:08,313 --> 00:08:11,273
  599. Most people are not
  600. aware that what Google is doing
  601.  
  602. 128
  603. 00:08:11,316 --> 00:08:13,710
  604. is actually a form of
  605. artificial intelligence.
  606.  
  607. 129
  608. 00:08:13,754 --> 00:08:16,234
  609. They just go there,
  610. they type in a thing.
  611.  
  612. 130
  613. 00:08:16,278 --> 00:08:18,323
  614. Google gives them the answer.
  615.  
  616. 131
  617. 00:08:18,367 --> 00:08:21,444
  618. With each search,
  619. we train it to be better.
  620.  
  621. 132
  622. 00:08:21,445 --> 00:08:24,108
  623. Sometimes we're typing a search,
  624. and it tell us the answer
  625.  
  626. 133
  627. 00:08:24,109 --> 00:08:27,434
  628. before you've finished
  629. asking the question.
  630.  
  631. 134
  632. 00:08:27,463 --> 00:08:29,944
  633. You know, who is the president
  634. of Kazakhstan?
  635.  
  636. 135
  637. 00:08:29,987 --> 00:08:31,685
  638. And it'll just tell you.
  639.  
  640. 136
  641. 00:08:31,728 --> 00:08:34,818
  642. You don't have to go to the Kazakhstan
  643. national website to find out.
  644.  
  645. 137
  646. 00:08:34,862 --> 00:08:37,081
  647. You didn't used to be able to do that.
  648.  
  649. 138
  650. 00:08:37,125 --> 00:08:39,475
  651. That is artificial intelligence.
  652.  
  653. 139
  654. 00:08:39,519 --> 00:08:42,783
  655. Years from now when we try
  656. to understand, we will say,
  657.  
  658. 140
  659. 00:08:42,826 --> 00:08:44,567
  660. "How did we miss it?"
  661.  
  662. 141
  663. 00:08:44,611 --> 00:08:48,484
  664. It's one of the striking contradictions
  665. that we're facing.
  666.  
  667. 142
  668. 00:08:48,528 --> 00:08:52,053
  669. Google and Facebook, et al,
  670. have built businesses on giving us,
  671.  
  672. 143
  673. 00:08:52,096 --> 00:08:54,185
  674. as a society, free stuff.
  675.  
  676. 144
  677. 00:08:54,229 --> 00:08:56,013
  678. But it's a Faustian bargain.
  679.  
  680. 145
  681. 00:08:56,057 --> 00:09:00,017
  682. They're extracting something
  683. from us in exchange,
  684.  
  685. 146
  686. 00:09:00,061 --> 00:09:01,628
  687. but we don't know
  688.  
  689. 147
  690. 00:09:01,671 --> 00:09:03,760
  691. what code is running
  692. on the other side and why.
  693.  
  694. 148
  695. 00:09:03,804 --> 00:09:05,846
  696. We have no idea.
  697.  
  698. 149
  699. 00:09:06,589 --> 00:09:08,591
  700. It does strike
  701. right at the issue
  702.  
  703. 150
  704. 00:09:08,635 --> 00:09:11,028
  705. of how much we should
  706. trust these machines.
  707.  
  708. 151
  709. 00:09:14,162 --> 00:09:18,166
  710. I use computers
  711. literally for everything.
  712.  
  713. 152
  714. 00:09:18,209 --> 00:09:21,386
  715. There are so many
  716. computer advancements now,
  717.  
  718. 153
  719. 00:09:21,430 --> 00:09:23,824
  720. and it's become such
  721. a big part of our lives.
  722.  
  723. 154
  724. 00:09:23,867 --> 00:09:26,174
  725. It's just incredible
  726. what a computer can do.
  727.  
  728. 155
  729. 00:09:26,217 --> 00:09:29,090
  730. You can actually carry
  731. a computer in your purse.
  732.  
  733. 156
  734. 00:09:29,133 --> 00:09:31,571
  735. I mean, how awesome is that?
  736.  
  737. 157
  738. 00:09:31,614 --> 00:09:35,052
  739. I think most technology is meant
  740. to make things easier
  741.  
  742. 158
  743. 00:09:35,096 --> 00:09:37,315
  744. and simpler for all of us,
  745.  
  746. 159
  747. 00:09:37,359 --> 00:09:40,362
  748. so hopefully that just
  749. remains the focus.
  750.  
  751. 160
  752. 00:09:40,405 --> 00:09:43,147
  753. I think everybody loves
  754. their computers.
  755.  
  756. 161
  757. 00:09:51,721 --> 00:09:53,810
  758. People don't realize
  759. they are constantly
  760.  
  761. 162
  762. 00:09:53,854 --> 00:09:59,076
  763. being negotiated with
  764. by machines;
  765.  
  766. 163
  767. 00:09:59,120 --> 00:10:02,993
  768. whether that's the price
  769. of products in your Amazon cart,
  770.  
  771. 164
  772. 00:10:03,037 --> 00:10:05,517
  773. whether you can get
  774. on a particular flight,
  775.  
  776. 165
  777. 00:10:05,561 --> 00:10:08,912
  778. whether you can reserve
  779. a room at a particular hotel.
  780.  
  781. 166
  782. 00:10:08,956 --> 00:10:11,959
  783. What you're experiencing
  784. are machine-learning algorithms
  785.  
  786. 167
  787. 00:10:12,002 --> 00:10:14,265
  788. that have determined
  789. that a person like you
  790.  
  791. 168
  792. 00:10:14,309 --> 00:10:17,791
  793. is willing to pay 2 cents more
  794. and is changing the price.
  795.  
  796. 169
  797. 00:10:21,795 --> 00:10:24,014
  798. Now, a computer looks
  799. at millions of people
  800.  
  801. 170
  802. 00:10:24,058 --> 00:10:28,105
  803. simultaneously for
  804. very subtle patterns.
  805.  
  806. 171
  807. 00:10:28,149 --> 00:10:31,369
  808. You can take seemingly
  809. innocent digital footprints,
  810.  
  811. 172
  812. 00:10:31,413 --> 00:10:34,677
  813. such as someone's playlist
  814. on Spotify,
  815.  
  816. 173
  817. 00:10:34,721 --> 00:10:37,201
  818. or stuff that they
  819. bought on Amazon,
  820.  
  821. 174
  822. 00:10:37,245 --> 00:10:40,291
  823. and then use algorithms
  824. to translate this
  825.  
  826. 175
  827. 00:10:40,335 --> 00:10:44,513
  828. into a very detailed and a
  829. very accurate, intimate profile.
  830.  
  831. 176
  832. 00:10:47,603 --> 00:10:50,911
  833. There is a dossier on
  834. each of us that is so extensive
  835.  
  836. 177
  837. 00:10:50,954 --> 00:10:52,695
  838. it would be possibly
  839. accurate to say
  840.  
  841. 178
  842. 00:10:52,739 --> 00:10:55,698
  843. that they know more about you
  844. than your mother does.
  845.  
  846. 179
  847. 00:11:04,098 --> 00:11:06,883
  848. The major cause
  849. of the recent AI breakthrough
  850.  
  851. 180
  852. 00:11:06,927 --> 00:11:08,580
  853. isn't just that some dude
  854.  
  855. 181
  856. 00:11:08,624 --> 00:11:11,583
  857. had a brilliant insight
  858. all of a sudden,
  859.  
  860. 182
  861. 00:11:11,627 --> 00:11:14,325
  862. but simply that we have
  863. much bigger data
  864.  
  865. 183
  866. 00:11:14,369 --> 00:11:18,242
  867. to train them on
  868. and vastly better computers.
  869.  
  870. 184
  871. 00:11:18,286 --> 00:11:19,940
  872. The magic is in the data.
  873.  
  874. 185
  875. 00:11:19,983 --> 00:11:21,463
  876. It's a ton of data.
  877.  
  878. 186
  879. 00:11:21,506 --> 00:11:23,726
  880. I mean, it's data
  881. that's never existed before.
  882.  
  883. 187
  884. 00:11:23,770 --> 00:11:26,686
  885. We've never had
  886. this data before.
  887.  
  888. 188
  889. 00:11:26,729 --> 00:11:30,733
  890. We've created technologies
  891. that allow us to capture
  892.  
  893. 189
  894. 00:11:30,777 --> 00:11:33,040
  895. vast amounts of information.
  896.  
  897. 190
  898. 00:11:33,083 --> 00:11:35,738
  899. If you think of a billion
  900. cellphones on the planet
  901.  
  902. 191
  903. 00:11:35,782 --> 00:11:38,393
  904. with gyroscopes
  905. and accelerometers
  906.  
  907. 192
  908. 00:11:38,436 --> 00:11:39,786
  909. and fingerprint readers...
  910.  
  911. 193
  912. 00:11:39,829 --> 00:11:42,005
  913. couple that with the GPS
  914. and the photos they take
  915.  
  916. 194
  917. 00:11:42,049 --> 00:11:43,964
  918. and the tweets that you send,
  919.  
  920. 195
  921. 00:11:44,007 --> 00:11:47,750
  922. we're all giving off huge
  923. amounts of data individually.
  924.  
  925. 196
  926. 00:11:47,794 --> 00:11:50,274
  927. Cars that drive as the cameras
  928. on them suck up information
  929.  
  930. 197
  931. 00:11:50,318 --> 00:11:52,059
  932. about the world around them.
  933.  
  934. 198
  935. 00:11:52,102 --> 00:11:54,844
  936. The satellites that are now
  937. in orbit the size of a toaster.
  938.  
  939. 199
  940. 00:11:54,888 --> 00:11:57,629
  941. The infrared about
  942. the vegetation on the planet.
  943.  
  944. 200
  945. 00:11:57,673 --> 00:12:01,024
  946. The buoys that are out in the oceans
  947. to feed into the climate models.
  948.  
  949. 201
  950. 00:12:05,072 --> 00:12:08,902
  951. And the NSA, the CIA,
  952. as they collect information
  953.  
  954. 202
  955. 00:12:08,945 --> 00:12:12,644
  956. about the
  957. geopolitical situations.
  958.  
  959. 203
  960. 00:12:12,688 --> 00:12:15,604
  961. The world today is literally
  962. swimming in this data.
  963.  
  964. 204
  965. 00:12:20,609 --> 00:12:22,480
  966. Back in 2012,
  967.  
  968. 205
  969. 00:12:22,524 --> 00:12:25,875
  970. IBM estimated
  971. that an average human being
  972.  
  973. 206
  974. 00:12:25,919 --> 00:12:31,098
  975. leaves 500 megabytes
  976. of digital footprints every day.
  977.  
  978. 207
  979. 00:12:31,141 --> 00:12:34,841
  980. If you wanted to back up
  981. on the one day worth of data
  982.  
  983. 208
  984. 00:12:34,884 --> 00:12:36,494
  985. that humanity produces
  986.  
  987. 209
  988. 00:12:36,538 --> 00:12:39,062
  989. and imprint it out
  990. on a letter-sized paper,
  991.  
  992. 210
  993. 00:12:39,106 --> 00:12:43,806
  994. double-sided, font size 12,
  995. and you stack it up,
  996.  
  997. 211
  998. 00:12:43,850 --> 00:12:46,113
  999. it would reach from
  1000. the surface of the Earth
  1001.  
  1002. 212
  1003. 00:12:46,156 --> 00:12:49,116
  1004. to the sun four times over.
  1005.  
  1006. 213
  1007. 00:12:49,159 --> 00:12:51,292
  1008. That's every day.
  1009.  
  1010. 214
  1011. 00:12:51,335 --> 00:12:53,816
  1012. The data itself
  1013. is not good or evil.
  1014.  
  1015. 215
  1016. 00:12:53,860 --> 00:12:55,470
  1017. It's how it's used.
  1018.  
  1019. 216
  1020. 00:12:55,513 --> 00:12:58,342
  1021. We're relying, really,
  1022. on the goodwill of these people
  1023.  
  1024. 217
  1025. 00:12:58,386 --> 00:13:01,171
  1026. and on the policies
  1027. of these companies.
  1028.  
  1029. 218
  1030. 00:13:01,215 --> 00:13:03,870
  1031. There is no legal requirement
  1032. for how they can
  1033.  
  1034. 219
  1035. 00:13:03,913 --> 00:13:06,307
  1036. and should use
  1037. that kind of data.
  1038.  
  1039. 220
  1040. 00:13:06,350 --> 00:13:09,266
  1041. That, to me, is at the heart
  1042. of the trust issue.
  1043.  
  1044. 221
  1045. 00:13:11,007 --> 00:13:13,793
  1046. Right now there's a
  1047. giant race for creating machines
  1048.  
  1049. 222
  1050. 00:13:13,836 --> 00:13:15,751
  1051. that are as smart as humans.
  1052.  
  1053. 223
  1054. 00:13:15,795 --> 00:13:18,071
  1055. Google -- They're working on
  1056. what's really the kind of
  1057.  
  1058. 224
  1059. 00:13:18,072 --> 00:13:20,074
  1060. Manhattan Project
  1061. of artificial intelligence.
  1062.  
  1063. 225
  1064. 00:13:20,075 --> 00:13:22,686
  1065. They've got the most money.
  1066. They've got the most talent.
  1067.  
  1068. 226
  1069. 00:13:22,714 --> 00:13:27,067
  1070. They're buying up AI companies
  1071. and robotics companies.
  1072.  
  1073. 227
  1074. 00:13:27,110 --> 00:13:29,069
  1075. People still think
  1076. of Google as a search engine
  1077.  
  1078. 228
  1079. 00:13:29,112 --> 00:13:30,722
  1080. and their e-mail provider
  1081.  
  1082. 229
  1083. 00:13:30,766 --> 00:13:33,943
  1084. and a lot of other things
  1085. that we use on a daily basis,
  1086.  
  1087. 230
  1088. 00:13:33,987 --> 00:13:39,383
  1089. but behind that search box
  1090. are 10 million servers.
  1091.  
  1092. 231
  1093. 00:13:39,427 --> 00:13:43,910
  1094. That makes Google the most powerful
  1095. computing platform in the world.
  1096.  
  1097. 232
  1098. 00:13:43,953 --> 00:13:47,217
  1099. Google is now working
  1100. on an AI computing platform
  1101.  
  1102. 233
  1103. 00:13:47,261 --> 00:13:50,133
  1104. that will have
  1105. 100 million servers.
  1106.  
  1107. 234
  1108. 00:13:52,179 --> 00:13:53,963
  1109. So when you're interacting
  1110. with Google,
  1111.  
  1112. 235
  1113. 00:13:54,007 --> 00:13:56,052
  1114. we're just seeing
  1115. the toenail of something
  1116.  
  1117. 236
  1118. 00:13:56,096 --> 00:13:58,881
  1119. that is a giant beast
  1120. in the making.
  1121.  
  1122. 237
  1123. 00:13:58,925 --> 00:14:00,622
  1124. And the truth is,
  1125. I'm not even sure
  1126.  
  1127. 238
  1128. 00:14:00,665 --> 00:14:02,798
  1129. that Google knows
  1130. what it's becoming.
  1131.  
  1132. 239
  1133. 00:14:11,546 --> 00:14:15,811
  1134. If you look inside of what algorithms
  1135. are being used at Google,
  1136.  
  1137. 240
  1138. 00:14:15,855 --> 00:14:20,076
  1139. it's technology
  1140. largely from the '80s.
  1141.  
  1142. 241
  1143. 00:14:20,120 --> 00:14:23,863
  1144. So these are models that you
  1145. train by showing them a 1, a 2,
  1146.  
  1147. 242
  1148. 00:14:23,906 --> 00:14:27,344
  1149. and a 3, and it learns not
  1150. what a 1 is or what a 2 is --
  1151.  
  1152. 243
  1153. 00:14:27,388 --> 00:14:30,434
  1154. It learns what the difference
  1155. between a 1 and a 2 is.
  1156.  
  1157. 244
  1158. 00:14:30,478 --> 00:14:32,436
  1159. It's just a computation.
  1160.  
  1161. 245
  1162. 00:14:32,480 --> 00:14:35,396
  1163. In the last half decade,
  1164. where we've made this rapid progress,
  1165.  
  1166. 246
  1167. 00:14:35,439 --> 00:14:38,268
  1168. it has all been
  1169. in pattern recognition.
  1170.  
  1171. 247
  1172. 00:14:38,312 --> 00:14:41,184
  1173. Most of the good, old-fashioned AI
  1174.  
  1175. 248
  1176. 00:14:41,228 --> 00:14:44,057
  1177. was when we would tell our computers
  1178.  
  1179. 249
  1180. 00:14:44,100 --> 00:14:46,798
  1181. how to play a game like chess...
  1182.  
  1183. 250
  1184. 00:14:46,842 --> 00:14:49,584
  1185. from the old paradigm where
  1186. you just tell the computer
  1187.  
  1188. 251
  1189. 00:14:49,627 --> 00:14:51,895
  1190. exactly what to do.
  1191.  
  1192. 252
  1193. 00:14:54,502 --> 00:14:57,505
  1194. This is "Jeopardy!"
  1195.  
  1196. 253
  1197. 00:14:59,420 --> 00:15:02,510
  1198. "The IBM Challenge"!
  1199.  
  1200. 254
  1201. 00:15:02,553 --> 00:15:05,730
  1202. No one at the time
  1203. had thought that a machine
  1204.  
  1205. 255
  1206. 00:15:05,774 --> 00:15:08,298
  1207. could have the precision
  1208. and the confidence
  1209.  
  1210. 256
  1211. 00:15:08,342 --> 00:15:11,475
  1212. and the speed to play "Jeopardy!"
  1213. well enough against the best humans.
  1214.  
  1215. 257
  1216. 00:15:11,519 --> 00:15:14,609
  1217. Let's play "Jeopardy!"
  1218.  
  1219. 258
  1220. 00:15:18,569 --> 00:15:20,354
  1221. What is "shoe"?
  1222.  
  1223. 259
  1224. 00:15:20,397 --> 00:15:21,877
  1225. You are right.
  1226. You get to pick.
  1227.  
  1228. 260
  1229. 00:15:21,921 --> 00:15:24,836
  1230. Literary Character APB
  1231. for $800.
  1232.  
  1233. 261
  1234. 00:15:24,880 --> 00:15:28,014
  1235. Answer --
  1236. the Daily Double.
  1237.  
  1238. 262
  1239. 00:15:28,057 --> 00:15:31,539
  1240. Watson actually got its
  1241. knowledge by reading Wikipedia
  1242.  
  1243. 263
  1244. 00:15:31,582 --> 00:15:34,672
  1245. and 200 million pages
  1246. of natural-language documents.
  1247.  
  1248. 264
  1249. 00:15:34,716 --> 00:15:36,674
  1250. You can't program every line
  1251.  
  1252. 265
  1253. 00:15:36,718 --> 00:15:38,502
  1254. of how the world works.
  1255.  
  1256. 266
  1257. 00:15:38,546 --> 00:15:40,722
  1258. The machine has to learn
  1259. by reading.
  1260.  
  1261. 267
  1262. 00:15:40,765 --> 00:15:42,202
  1263. Now we come to Watson.
  1264.  
  1265. 268
  1266. 00:15:42,245 --> 00:15:43,986
  1267. "Who is Bram Stoker?"
  1268.  
  1269. 269
  1270. 00:15:44,030 --> 00:15:45,988
  1271. And the wager?
  1272.  
  1273. 270
  1274. 00:15:46,032 --> 00:15:49,165
  1275. Hello! $17,973.
  1276.  
  1277. 271
  1278. 00:15:49,209 --> 00:15:50,993
  1279. $41,413.
  1280.  
  1281. 272
  1282. 00:15:51,037 --> 00:15:53,343
  1283. And a two-day total
  1284. of $77--
  1285.  
  1286. 273
  1287. 00:15:53,387 --> 00:15:56,694
  1288. Watson's trained
  1289. on huge amounts of text,
  1290.  
  1291. 274
  1292. 00:15:56,738 --> 00:15:59,628
  1293. but it's not like it
  1294. understands what it's saying.
  1295.  
  1296. 275
  1297. 00:15:59,671 --> 00:16:02,309
  1298. It doesn't know that water makes
  1299. things wet by touching water
  1300.  
  1301. 276
  1302. 00:16:02,352 --> 00:16:04,441
  1303. and by seeing the way
  1304. things behave in the world
  1305.  
  1306. 277
  1307. 00:16:04,485 --> 00:16:06,182
  1308. the way you and I do.
  1309.  
  1310. 278
  1311. 00:16:06,226 --> 00:16:10,143
  1312. A lot of language AI today
  1313. is not building logical models
  1314.  
  1315. 279
  1316. 00:16:10,186 --> 00:16:11,622
  1317. of how the world works.
  1318.  
  1319. 280
  1320. 00:16:11,666 --> 00:16:15,365
  1321. Rather, it's looking at
  1322. how the words appear
  1323.  
  1324. 281
  1325. 00:16:15,409 --> 00:16:18,238
  1326. in the context of other words.
  1327.  
  1328. 282
  1329. 00:16:18,281 --> 00:16:20,196
  1330. David Ferrucci
  1331. developed IBM's Watson,
  1332.  
  1333. 283
  1334. 00:16:20,240 --> 00:16:23,547
  1335. and somebody asked him,
  1336. "Does Watson think?"
  1337.  
  1338. 284
  1339. 00:16:23,591 --> 00:16:26,660
  1340. And he said,
  1341. "Does a submarine swim?"
  1342.  
  1343. 285
  1344. 00:16:26,903 --> 00:16:29,331
  1345. And what they meant was,
  1346. when they developed submarines,
  1347.  
  1348. 286
  1349. 00:16:29,332 --> 00:16:32,949
  1350. they borrowed basic principles
  1351. of swimming from fish.
  1352.  
  1353. 287
  1354. 00:16:33,035 --> 00:16:36,525
  1355. But a submarine swims farther and faster
  1356. than fish and can carry a huge payload.
  1357.  
  1358. 288
  1359. 00:16:36,569 --> 00:16:39,411
  1360. It out-swims fish.
  1361.  
  1362. 289
  1363. 00:16:39,955 --> 00:16:43,741
  1364. Watson winning the game of "Jeopardy!"
  1365. will go down in the history of AI
  1366.  
  1367. 290
  1368. 00:16:43,785 --> 00:16:46,370
  1369. as a significant milestone.
  1370.  
  1371. 291
  1372. 00:16:46,614 --> 00:16:49,269
  1373. We tend to be amazed
  1374. when the machine does so well.
  1375.  
  1376. 292
  1377. 00:16:49,312 --> 00:16:52,663
  1378. I'm even more amazed when the
  1379. computer beats humans at things
  1380.  
  1381. 293
  1382. 00:16:52,707 --> 00:16:55,188
  1383. that humans are
  1384. naturally good at.
  1385.  
  1386. 294
  1387. 00:16:55,231 --> 00:16:58,060
  1388. This is how we make progress.
  1389.  
  1390. 295
  1391. 00:16:58,104 --> 00:17:00,671
  1392. In the early days of
  1393. the Google Brain project,
  1394.  
  1395. 296
  1396. 00:17:00,715 --> 00:17:02,804
  1397. I gave the team a very
  1398. simple instruction,
  1399.  
  1400. 297
  1401. 00:17:02,847 --> 00:17:05,807
  1402. which was, "Build the biggest
  1403. neural network possible,
  1404.  
  1405. 298
  1406. 00:17:05,850 --> 00:17:08,157
  1407. like 1,000 computers."
  1408.  
  1409. 299
  1410. 00:17:08,201 --> 00:17:12,161
  1411. A neural net is something very close
  1412. to a simulation of how the brain works.
  1413.  
  1414. 300
  1415. 00:17:12,205 --> 00:17:16,818
  1416. It's very probabilistic,
  1417. but with contextual relevance.
  1418.  
  1419. 301
  1420. 00:17:16,819 --> 00:17:18,456
  1421. In your brain,
  1422. you have long neurons
  1423.  
  1424. 302
  1425. 00:17:18,457 --> 00:17:20,372
  1426. that connect to thousands
  1427. of other neurons,
  1428.  
  1429. 303
  1430. 00:17:20,373 --> 00:17:22,592
  1431. and you have these pathways
  1432. that are formed and forged
  1433.  
  1434. 304
  1435. 00:17:22,593 --> 00:17:24,769
  1436. based on what
  1437. the brain needs to do.
  1438.  
  1439. 305
  1440. 00:17:24,782 --> 00:17:28,960
  1441. When a baby tries something and
  1442. it succeeds, there's a reward,
  1443.  
  1444. 306
  1445. 00:17:29,004 --> 00:17:32,312
  1446. and that pathway that created
  1447. the success is strengthened.
  1448.  
  1449. 307
  1450. 00:17:32,355 --> 00:17:34,662
  1451. If it fails at something,
  1452. the pathway is weakened,
  1453.  
  1454. 308
  1455. 00:17:34,705 --> 00:17:36,794
  1456. and so, over time,
  1457. the brain becomes honed
  1458.  
  1459. 309
  1460. 00:17:36,838 --> 00:17:40,120
  1461. to be good at
  1462. the environment around it.
  1463.  
  1464. 310
  1465. 00:17:40,363 --> 00:17:43,279
  1466. Really, it's just getting
  1467. machines to learn by themselves.
  1468.  
  1469. 311
  1470. 00:17:43,323 --> 00:17:45,538
  1471. This is called "deep learning,"
  1472. and "deep learning"
  1473.  
  1474. 312
  1475. 00:17:45,539 --> 00:17:48,834
  1476. and "neural networks"
  1477. mean roughly the same thing.
  1478.  
  1479. 313
  1480. 00:17:48,835 --> 00:17:52,391
  1481. Deep learning
  1482. is a totally different approach
  1483.  
  1484. 314
  1485. 00:17:52,419 --> 00:17:55,161
  1486. where the computer learns
  1487. more like a toddler,
  1488.  
  1489. 315
  1490. 00:17:55,204 --> 00:17:56,466
  1491. by just getting a lot of data
  1492.  
  1493. 316
  1494. 00:17:56,510 --> 00:18:00,340
  1495. and eventually
  1496. figuring stuff out.
  1497.  
  1498. 317
  1499. 00:18:00,383 --> 00:18:03,125
  1500. The computer just gets
  1501. smarter and smarter
  1502.  
  1503. 318
  1504. 00:18:03,169 --> 00:18:05,997
  1505. as it has more experiences.
  1506.  
  1507. 319
  1508. 00:18:06,041 --> 00:18:09,697
  1509. Imagine, if you will, a neural network,
  1510. you know, like 1,000 computers.
  1511.  
  1512. 320
  1513. 00:18:09,740 --> 00:18:11,438
  1514. And it wakes up
  1515. not knowing anything.
  1516.  
  1517. 321
  1518. 00:18:11,481 --> 00:18:14,093
  1519. And we made it watch YouTube
  1520. for a week.
  1521.  
  1522. 322
  1523. 00:18:25,408 --> 00:18:28,194
  1524. Charlie!
  1525. That really hurt!
  1526.  
  1527. 323
  1528. 00:18:36,245 --> 00:18:38,508
  1529. And so, after watching
  1530. YouTube for a week,
  1531.  
  1532. 324
  1533. 00:18:38,552 --> 00:18:39,988
  1534. what would it learn?
  1535.  
  1536. 325
  1537. 00:18:40,031 --> 00:18:42,103
  1538. We had a hypothesis that
  1539. it would learn to detect
  1540.  
  1541. 326
  1542. 00:18:42,146 --> 00:18:44,384
  1543. commonly occurring objects
  1544. in videos.
  1545.  
  1546. 327
  1547. 00:18:44,427 --> 00:18:47,517
  1548. And so, we know that human faces
  1549. appear a lot in videos,
  1550.  
  1551. 328
  1552. 00:18:47,561 --> 00:18:49,302
  1553. so we looked,
  1554. and, lo and behold,
  1555.  
  1556. 329
  1557. 00:18:49,345 --> 00:18:52,008
  1558. there was a neuron that had
  1559. learned to detect human faces.
  1560.  
  1561. 330
  1562. 00:18:52,052 --> 00:18:55,865
  1563. Leave Britney alone!
  1564.  
  1565. 331
  1566. 00:18:56,309 --> 00:18:58,354
  1567. Well, what else
  1568. appears in videos a lot?
  1569.  
  1570. 332
  1571. 00:19:00,095 --> 00:19:01,792
  1572. So, we looked,
  1573. and to our surprise,
  1574.  
  1575. 333
  1576. 00:19:01,836 --> 00:19:05,082
  1577. there was actually a neuron
  1578. that had learned to detect cats.
  1579.  
  1580. 334
  1581. 00:19:14,892 --> 00:19:17,068
  1582. I still remember seeing recognition.
  1583.  
  1584. 335
  1585. 00:19:17,112 --> 00:19:20,071
  1586. "Wow, that's a cat. Okay, cool.
  1587. Great."
  1588.  
  1589. 336
  1590. 00:19:23,162 --> 00:19:26,295
  1591. It's all pretty innocuous when
  1592. you're thinking about the future.
  1593.  
  1594. 337
  1595. 00:19:26,339 --> 00:19:29,733
  1596. It all seems kind of
  1597. harmless and benign.
  1598.  
  1599. 338
  1600. 00:19:29,777 --> 00:19:33,520
  1601. But we're making cognitive architectures
  1602. that will fly farther and faster than us
  1603.  
  1604. 339
  1605. 00:19:33,563 --> 00:19:37,437
  1606. and carry a bigger payload,
  1607. and they won't be warm and fuzzy.
  1608.  
  1609. 340
  1610. 00:19:37,480 --> 00:19:41,702
  1611. I think that, in three to five years,
  1612. you will see a computer system
  1613.  
  1614. 341
  1615. 00:19:41,745 --> 00:19:45,401
  1616. that will be able
  1617. to autonomously learn
  1618.  
  1619. 342
  1620. 00:19:45,445 --> 00:19:49,013
  1621. how to understand,
  1622. how to build understanding,
  1623.  
  1624. 343
  1625. 00:19:49,057 --> 00:19:51,364
  1626. not unlike the way
  1627. the human mind works.
  1628.  
  1629. 344
  1630. 00:19:53,931 --> 00:19:56,891
  1631. Whatever that lunch was,
  1632. it was certainly delicious.
  1633.  
  1634. 345
  1635. 00:19:56,934 --> 00:19:59,807
  1636. Simply some of
  1637. Robby's synthetics.
  1638.  
  1639. 346
  1640. 00:19:59,850 --> 00:20:01,635
  1641. He's your cook, too?
  1642.  
  1643. 347
  1644. 00:20:01,678 --> 00:20:04,551
  1645. Even manufactures
  1646. the raw materials.
  1647.  
  1648. 348
  1649. 00:20:04,594 --> 00:20:06,944
  1650. Come around here, Robby.
  1651.  
  1652. 349
  1653. 00:20:06,988 --> 00:20:09,773
  1654. I'll show you
  1655. how this works.
  1656.  
  1657. 350
  1658. 00:20:11,122 --> 00:20:13,342
  1659. One introduces
  1660. a sample of human food
  1661.  
  1662. 351
  1663. 00:20:13,386 --> 00:20:15,344
  1664. through this aperture.
  1665.  
  1666. 352
  1667. 00:20:15,388 --> 00:20:17,738
  1668. Down here there's a small
  1669. built-in chemical laboratory,
  1670.  
  1671. 353
  1672. 00:20:17,781 --> 00:20:19,218
  1673. where he analyzes it.
  1674.  
  1675. 354
  1676. 00:20:19,261 --> 00:20:21,263
  1677. Later, he can reproduce
  1678. identical molecules
  1679.  
  1680. 355
  1681. 00:20:21,307 --> 00:20:22,482
  1682. in any shape or quantity.
  1683.  
  1684. 356
  1685. 00:20:22,525 --> 00:20:24,614
  1686. Why, it's a housewife's dream.
  1687.  
  1688. 357
  1689. 00:20:24,958 --> 00:20:26,834
  1690. Meet Baxter,
  1691.  
  1692. 358
  1693. 00:20:26,877 --> 00:20:30,490
  1694. revolutionary new category of robots,
  1695. with common sense.
  1696.  
  1697. 359
  1698. 00:20:30,533 --> 00:20:31,839
  1699. Baxter...
  1700.  
  1701. 360
  1702. 00:20:31,882 --> 00:20:33,449
  1703. Baxter is
  1704. a really good example
  1705.  
  1706. 361
  1707. 00:20:33,493 --> 00:20:36,887
  1708. of the kind of competition
  1709. we face from machines.
  1710.  
  1711. 362
  1712. 00:20:36,931 --> 00:20:42,676
  1713. Baxter can do almost anything
  1714. we can do with our hands.
  1715.  
  1716. 363
  1717. 00:20:42,719 --> 00:20:45,722
  1718. Baxter costs about
  1719. what a minimum-wage worker
  1720.  
  1721. 364
  1722. 00:20:45,766 --> 00:20:47,507
  1723. makes in a year.
  1724.  
  1725. 365
  1726. 00:20:47,550 --> 00:20:50,318
  1727. But Baxter won't be taking the place
  1728. of one minimum-wage worker --
  1729.  
  1730. 366
  1731. 00:20:50,319 --> 00:20:51,930
  1732. He'll be taking
  1733. the place of three,
  1734.  
  1735. 367
  1736. 00:20:51,931 --> 00:20:55,531
  1737. because they never get tired,
  1738. they never take breaks.
  1739.  
  1740. 368
  1741. 00:20:55,558 --> 00:20:57,865
  1742. That's probably the
  1743. first thing we're gonna see --
  1744.  
  1745. 369
  1746. 00:20:57,908 --> 00:20:59,475
  1747. displacement of jobs.
  1748.  
  1749. 370
  1750. 00:20:59,519 --> 00:21:04,088
  1751. They're gonna be done quicker,
  1752. faster, cheaper by machines.
  1753.  
  1754. 371
  1755. 00:21:04,132 --> 00:21:07,657
  1756. Our ability to even stay current
  1757. is so insanely limited
  1758.  
  1759. 372
  1760. 00:21:07,701 --> 00:21:10,138
  1761. compared to
  1762. the machines we build.
  1763.  
  1764. 373
  1765. 00:21:10,181 --> 00:21:13,446
  1766. For example, now we have this
  1767. great movement of Uber and Lyft
  1768.  
  1769. 374
  1770. 00:21:13,489 --> 00:21:16,505
  1771. kind of making transportation cheaper
  1772. and democratizing transportation,
  1773.  
  1774. 375
  1775. 00:21:16,506 --> 00:21:17,768
  1776. which is great.
  1777.  
  1778. 376
  1779. 00:21:17,769 --> 00:21:21,189
  1780. The next step is gonna be that they're
  1781. all gonna be replaced by driverless cars
  1782.  
  1783. 377
  1784. 00:21:21,192 --> 00:21:25,936
  1785. and then all the Uber and Lyft drivers
  1786. have to find something new to do.
  1787.  
  1788. 378
  1789. 00:21:25,980 --> 00:21:29,723
  1790. There are 4 million professional drivers
  1791. in the United States.
  1792.  
  1793. 379
  1794. 00:21:29,766 --> 00:21:31,638
  1795. They're unemployed soon.
  1796.  
  1797. 380
  1798. 00:21:31,681 --> 00:21:34,075
  1799. 7 million people that do data entry.
  1800.  
  1801. 381
  1802. 00:21:34,118 --> 00:21:37,339
  1803. Those people are gonna be jobless.
  1804.  
  1805. 382
  1806. 00:21:37,383 --> 00:21:40,342
  1807. A job isn't just about money, right?
  1808.  
  1809. 383
  1810. 00:21:40,386 --> 00:21:42,605
  1811. On a biological level,
  1812. it serves a purpose.
  1813.  
  1814. 384
  1815. 00:21:42,649 --> 00:21:45,391
  1816. It becomes a defining thing.
  1817.  
  1818. 385
  1819. 00:21:45,434 --> 00:21:48,350
  1820. When the jobs went away
  1821. in any given civilization,
  1822.  
  1823. 386
  1824. 00:21:48,394 --> 00:21:50,987
  1825. it doesn't take long
  1826. until that turns into violence.
  1827.  
  1828. 387
  1829. 00:21:59,622 --> 00:22:02,016
  1830. We face a giant divide
  1831. between rich and poor,
  1832.  
  1833. 388
  1834. 00:22:02,059 --> 00:22:05,019
  1835. because that's what automation
  1836. and AI will provoke --
  1837.  
  1838. 389
  1839. 00:22:05,062 --> 00:22:08,588
  1840. a greater divide between
  1841. the haves and the have-nots.
  1842.  
  1843. 390
  1844. 00:22:08,631 --> 00:22:10,807
  1845. Right now, it's working
  1846. into the middle class,
  1847.  
  1848. 391
  1849. 00:22:10,851 --> 00:22:12,896
  1850. into white-collar jobs.
  1851.  
  1852. 392
  1853. 00:22:12,940 --> 00:22:15,334
  1854. IBM's Watson does
  1855. business analytics
  1856.  
  1857. 393
  1858. 00:22:15,377 --> 00:22:20,600
  1859. that we used to pay a business analyst
  1860. $300 an hour to do.
  1861.  
  1862. 394
  1863. 00:22:20,643 --> 00:22:23,037
  1864. Today, you're going
  1865. to college to be a doctor,
  1866.  
  1867. 395
  1868. 00:22:23,080 --> 00:22:25,082
  1869. to be an accountant,
  1870. to be a journalist.
  1871.  
  1872. 396
  1873. 00:22:25,126 --> 00:22:28,608
  1874. It's unclear that there's
  1875. gonna be jobs there for you.
  1876.  
  1877. 397
  1878. 00:22:28,651 --> 00:22:32,612
  1879. If someone's planning for
  1880. a 40-year career in radiology,
  1881.  
  1882. 398
  1883. 00:22:32,655 --> 00:22:34,222
  1884. just reading images,
  1885.  
  1886. 399
  1887. 00:22:34,265 --> 00:22:37,120
  1888. I think that could be a challenge
  1889. to the new graduates of today.
  1890.  
  1891. 400
  1892. 00:22:58,507 --> 00:23:02,729
  1893. The da Vinci robot is currently utilized
  1894.  
  1895. 401
  1896. 00:23:02,772 --> 00:23:07,516
  1897. by a variety of surgeons
  1898. for its accuracy and its ability
  1899.  
  1900. 402
  1901. 00:23:07,560 --> 00:23:12,303
  1902. to avoid the inevitable
  1903. fluctuations of the human hand.
  1904.  
  1905. 403
  1906. 00:23:23,402 --> 00:23:28,494
  1907. Anybody who watches this
  1908. feels the amazingness of it.
  1909.  
  1910. 404
  1911. 00:23:30,931 --> 00:23:34,674
  1912. You look through the scope,
  1913. and you're seeing the claw hand
  1914.  
  1915. 405
  1916. 00:23:34,717 --> 00:23:36,893
  1917. holding that woman's ovary.
  1918.  
  1919. 406
  1920. 00:23:36,937 --> 00:23:42,638
  1921. Humanity was resting right here
  1922. in the hands of this robot.
  1923.  
  1924. 407
  1925. 00:23:42,682 --> 00:23:46,947
  1926. People say it's the future,
  1927. but it's not the future --
  1928.  
  1929. 408
  1930. 00:23:46,990 --> 00:23:50,516
  1931. It's the present.
  1932.  
  1933. 409
  1934. 00:23:50,559 --> 00:23:52,474
  1935. If you think about
  1936. a surgical robot,
  1937.  
  1938. 410
  1939. 00:23:52,475 --> 00:23:54,894
  1940. there's often not a lot
  1941. of intelligence in these things,
  1942.  
  1943. 411
  1944. 00:23:54,895 --> 00:23:58,567
  1945. but over time, as we put more and more
  1946. intelligence into these systems,
  1947.  
  1948. 412
  1949. 00:23:58,611 --> 00:24:02,281
  1950. the surgical robots can actually
  1951. learn from each robot surgery.
  1952.  
  1953. 413
  1954. 00:24:02,284 --> 00:24:04,581
  1955. They're tracking the movements,
  1956. they're understanding
  1957.  
  1958. 414
  1959. 00:24:04,582 --> 00:24:06,423
  1960. what worked
  1961. and what didn't work.
  1962.  
  1963. 415
  1964. 00:24:06,424 --> 00:24:09,023
  1965. And eventually, the robot
  1966. for routine surgeries
  1967.  
  1968. 416
  1969. 00:24:09,024 --> 00:24:12,362
  1970. is going to be able to perform
  1971. that entirely by itself...
  1972.  
  1973. 417
  1974. 00:24:12,363 --> 00:24:14,056
  1975. or with human supervision.
  1976.  
  1977. 418
  1978. 00:24:35,038 --> 00:24:37,214
  1979. It seems that we're
  1980. feeding it and creating it,
  1981.  
  1982. 419
  1983. 00:24:37,258 --> 00:24:42,785
  1984. but, in a way, we are a slave
  1985. to the technology,
  1986.  
  1987. 420
  1988. 00:24:42,829 --> 00:24:45,701
  1989. because we can't go back.
  1990.  
  1991. 421
  1992. 00:24:50,053 --> 00:24:52,882
  1993. The machines are taking
  1994. bigger and bigger bites
  1995.  
  1996. 422
  1997. 00:24:52,926 --> 00:24:57,147
  1998. out of our skill set
  1999. at an ever-increasing speed.
  2000.  
  2001. 423
  2002. 00:24:57,191 --> 00:24:59,236
  2003. And so we've got to run
  2004. faster and faster
  2005.  
  2006. 424
  2007. 00:24:59,280 --> 00:25:00,890
  2008. to keep ahead of the machines.
  2009.  
  2010. 425
  2011. 00:25:02,675 --> 00:25:04,677
  2012. How do I look?
  2013.  
  2014. 426
  2015. 00:25:04,720 --> 00:25:06,374
  2016. Good.
  2017.  
  2018. 427
  2019. 00:25:10,030 --> 00:25:11,553
  2020. Are you attracted to me?
  2021.  
  2022. 428
  2023. 00:25:11,597 --> 00:25:14,251
  2024. What?
  2025. - Are you attracted to me?
  2026.  
  2027. 429
  2028. 00:25:14,295 --> 00:25:17,777
  2029. You give me indications
  2030. that you are.
  2031.  
  2032. 430
  2033. 00:25:17,820 --> 00:25:20,562
  2034. I do?
  2035. - Yes.
  2036.  
  2037. 431
  2038. 00:25:20,606 --> 00:25:22,608
  2039. This is the future we're headed into.
  2040.  
  2041. 432
  2042. 00:25:22,651 --> 00:25:26,046
  2043. We want to design
  2044. our companions.
  2045.  
  2046. 433
  2047. 00:25:26,089 --> 00:25:29,266
  2048. We're gonna like to see
  2049. a human face on AI.
  2050.  
  2051. 434
  2052. 00:25:29,310 --> 00:25:33,967
  2053. Therefore, gaming our emotions
  2054. will be depressingly easy.
  2055.  
  2056. 435
  2057. 00:25:34,010 --> 00:25:35,272
  2058. We're not that complicated.
  2059.  
  2060. 436
  2061. 00:25:35,316 --> 00:25:38,101
  2062. We're simple.
  2063. Stimulus-response.
  2064.  
  2065. 437
  2066. 00:25:38,145 --> 00:25:42,763
  2067. I can make you like me basically
  2068. by smiling at you a lot.
  2069.  
  2070. 438
  2071. 00:25:43,106 --> 00:25:45,974
  2072. AI's are gonna be fantastic
  2073. at manipulating us.
  2074.  
  2075. 439
  2076. 00:25:54,683 --> 00:25:56,946
  2077. So, you've developed a technology
  2078.  
  2079. 440
  2080. 00:25:56,990 --> 00:26:00,036
  2081. that can sense
  2082. what people are feeling.
  2083.  
  2084. 441
  2085. 00:26:00,080 --> 00:26:03,387
  2086. Right. We've developed technology
  2087. that can read your facial expressions
  2088.  
  2089. 442
  2090. 00:26:03,431 --> 00:26:06,521
  2091. and map that to a number
  2092. of emotional states.
  2093.  
  2094. 443
  2095. 00:26:06,565 --> 00:26:08,697
  2096. 15 years ago,
  2097. I had just finished
  2098.  
  2099. 444
  2100. 00:26:08,741 --> 00:26:11,482
  2101. my undergraduate studies
  2102. in computer science,
  2103.  
  2104. 445
  2105. 00:26:11,526 --> 00:26:15,008
  2106. and it struck me that I was
  2107. spending a lot of time
  2108.  
  2109. 446
  2110. 00:26:15,051 --> 00:26:17,793
  2111. interacting with my laptops
  2112. and my devices,
  2113.  
  2114. 447
  2115. 00:26:17,837 --> 00:26:23,582
  2116. yet these devices had absolutely
  2117. no clue how I was feeling.
  2118.  
  2119. 448
  2120. 00:26:23,625 --> 00:26:26,802
  2121. I started thinking,
  2122. "What if this device could sense
  2123.  
  2124. 449
  2125. 00:26:26,846 --> 00:26:29,326
  2126. that I was stressed
  2127. or I was having a bad day?
  2128.  
  2129. 450
  2130. 00:26:29,370 --> 00:26:31,067
  2131. What would that open up?"
  2132.  
  2133. 451
  2134. 00:26:32,721 --> 00:26:34,418
  2135. Hi, first-graders!
  2136.  
  2137. 452
  2138. 00:26:34,462 --> 00:26:35,855
  2139. How are you?
  2140.  
  2141. 453
  2142. 00:26:35,898 --> 00:26:37,813
  2143. Can I get a hug?
  2144.  
  2145. 454
  2146. 00:26:37,857 --> 00:26:40,773
  2147. We had kids interact
  2148. with the technology.
  2149.  
  2150. 455
  2151. 00:26:40,816 --> 00:26:44,472
  2152. A lot of it is still in development,
  2153. but it was just amazing.
  2154.  
  2155. 456
  2156. 00:26:44,515 --> 00:26:46,648
  2157. Who likes robots?
  2158. - Me!
  2159.  
  2160. 457
  2161. 00:26:46,692 --> 00:26:48,911
  2162. Who wants to have a robot
  2163. in their house?
  2164.  
  2165. 458
  2166. 00:26:48,955 --> 00:26:51,479
  2167. What would you use
  2168. a robot for, Jack?
  2169.  
  2170. 459
  2171. 00:26:51,522 --> 00:26:56,353
  2172. I would use it to ask my mom
  2173. very hard math questions.
  2174.  
  2175. 460
  2176. 00:26:56,397 --> 00:26:58,181
  2177. Okay.
  2178. What about you, Theo?
  2179.  
  2180. 461
  2181. 00:26:58,225 --> 00:27:02,272
  2182. I would use it
  2183. for scaring people.
  2184.  
  2185. 462
  2186. 00:27:02,316 --> 00:27:04,666
  2187. All right.
  2188. So, start by smiling.
  2189.  
  2190. 463
  2191. 00:27:04,710 --> 00:27:06,625
  2192. Nice.
  2193.  
  2194. 464
  2195. 00:27:06,668 --> 00:27:09,018
  2196. Brow furrow.
  2197.  
  2198. 465
  2199. 00:27:09,062 --> 00:27:10,890
  2200. Nice one.
  2201. Eyebrow raise.
  2202.  
  2203. 466
  2204. 00:27:10,933 --> 00:27:15,068
  2205. This generation, technology is just
  2206. surrounding them all the time.
  2207.  
  2208. 467
  2209. 00:27:15,111 --> 00:27:17,853
  2210. It's almost like they expect
  2211. to have robots in their homes,
  2212.  
  2213. 468
  2214. 00:27:17,897 --> 00:27:22,336
  2215. and they expect these robots
  2216. to be socially intelligent.
  2217.  
  2218. 469
  2219. 00:27:22,379 --> 00:27:25,252
  2220. What makes robots smart?
  2221.  
  2222. 470
  2223. 00:27:25,295 --> 00:27:29,648
  2224. Put them in, like, a math
  2225. or biology class.
  2226.  
  2227. 471
  2228. 00:27:29,691 --> 00:27:32,259
  2229. I think you would
  2230. have to train it.
  2231.  
  2232. 472
  2233. 00:27:32,302 --> 00:27:35,218
  2234. All right.
  2235. Let's walk over here.
  2236.  
  2237. 473
  2238. 00:27:35,262 --> 00:27:37,394
  2239. So, if you smile and you
  2240. raise your eyebrows,
  2241.  
  2242. 474
  2243. 00:27:37,438 --> 00:27:39,005
  2244. it's gonna run over to you.
  2245.  
  2246. 475
  2247. 00:27:39,048 --> 00:27:40,833
  2248. It's coming over!
  2249. It's coming over! Look.
  2250.  
  2251. 476
  2252. 00:27:43,183 --> 00:27:45,272
  2253. But if you look angry,
  2254. it's gonna run away.
  2255.  
  2256. 477
  2257. 00:27:46,534 --> 00:27:48,797
  2258. -Awesome!
  2259. -Oh, that was good.
  2260.  
  2261. 478
  2262. 00:27:48,841 --> 00:27:52,366
  2263. We're training computers to read
  2264. and recognize emotions.
  2265.  
  2266. 479
  2267. 00:27:52,409 --> 00:27:53,846
  2268. Ready? Set? Go!
  2269.  
  2270. 480
  2271. 00:27:53,889 --> 00:27:57,414
  2272. And the response so far
  2273. has been really amazing.
  2274.  
  2275. 481
  2276. 00:27:57,458 --> 00:27:59,590
  2277. People are integrating this
  2278. into health apps,
  2279.  
  2280. 482
  2281. 00:27:59,634 --> 00:28:03,865
  2282. meditation apps, robots, cars.
  2283.  
  2284. 483
  2285. 00:28:04,508 --> 00:28:06,728
  2286. We're gonna see
  2287. how this unfolds.
  2288.  
  2289. 484
  2290. 00:28:09,470 --> 00:28:11,602
  2291. Robots can contain AI,
  2292.  
  2293. 485
  2294. 00:28:11,646 --> 00:28:14,388
  2295. but the robot is just
  2296. a physical instantiation,
  2297.  
  2298. 486
  2299. 00:28:14,431 --> 00:28:16,782
  2300. and the artificial intelligence
  2301. is the brain.
  2302.  
  2303. 487
  2304. 00:28:16,825 --> 00:28:19,872
  2305. And so brains can exist purely
  2306. in software-based systems.
  2307.  
  2308. 488
  2309. 00:28:19,915 --> 00:28:22,483
  2310. They don't need to have
  2311. a physical form.
  2312.  
  2313. 489
  2314. 00:28:22,526 --> 00:28:25,094
  2315. Robots can exist without
  2316. any artificial intelligence.
  2317.  
  2318. 490
  2319. 00:28:25,138 --> 00:28:28,097
  2320. We have a lot of
  2321. dumb robots out there.
  2322.  
  2323. 491
  2324. 00:28:28,141 --> 00:28:31,753
  2325. But a dumb robot can be
  2326. a smart robot overnight,
  2327.  
  2328. 492
  2329. 00:28:31,797 --> 00:28:34,103
  2330. given the right software,
  2331. given the right sensors.
  2332.  
  2333. 493
  2334. 00:28:34,147 --> 00:28:38,629
  2335. We can't help but impute
  2336. motive into inanimate objects.
  2337.  
  2338. 494
  2339. 00:28:38,673 --> 00:28:41,502
  2340. We do it with machines.
  2341. We'll treat them like children.
  2342.  
  2343. 495
  2344. 00:28:41,545 --> 00:28:43,330
  2345. We'll treat them like surrogates.
  2346.  
  2347. 496
  2348. 00:28:43,373 --> 00:28:45,027
  2349. Goodbye!
  2350.  
  2351. 497
  2352. 00:28:45,071 --> 00:28:48,204
  2353. And we'll pay the price.
  2354.  
  2355. 498
  2356. 00:29:08,616 --> 00:29:10,792
  2357. Okay, welcome to the ATR.
  2358.  
  2359. 499
  2360. 00:29:18,000 --> 00:29:20,800
  2361. My purpose is to have
  2362. a more human-like robot
  2363.  
  2364. 500
  2365. 00:29:20,801 --> 00:29:24,001
  2366. which has human-like
  2367. intentions and desires.
  2368.  
  2369. 501
  2370. 00:29:36,000 --> 00:29:38,400
  2371. The name of the robot is Erica.
  2372.  
  2373. 502
  2374. 00:29:39,501 --> 00:29:43,901
  2375. Erica is the most advanced
  2376. human-like robot in the world, I think.
  2377.  
  2378. 503
  2379. 00:29:44,202 --> 00:29:47,202
  2380. Erica can gaze at your face.
  2381.  
  2382. 504
  2383. 00:29:51,528 --> 00:29:52,791
  2384. Konnichiwa.
  2385.  
  2386. 505
  2387. 00:29:53,592 --> 00:29:57,092
  2388. Robots can be pretty good
  2389. as conversation partners,
  2390.  
  2391. 506
  2392. 00:29:57,093 --> 00:30:00,493
  2393. especially for the elderly
  2394. and younger children,
  2395.  
  2396. 507
  2397. 00:30:00,494 --> 00:30:02,494
  2398. handicapped people.
  2399.  
  2400. 508
  2401. 00:30:03,094 --> 00:30:06,294
  2402. When we talk to the robot
  2403. we don't fear the social barriers,
  2404.  
  2405. 509
  2406. 00:30:06,295 --> 00:30:08,095
  2407. social pressures.
  2408.  
  2409. 510
  2410. 00:30:08,396 --> 00:30:15,796
  2411. Finally everybody accepts the android
  2412. as just our friend or partner.
  2413.  
  2414. 511
  2415. 00:30:15,997 --> 00:30:18,997
  2416. We have implemented simple desires.
  2417.  
  2418. 512
  2419. 00:30:18,998 --> 00:30:22,798
  2420. She wanted to be well recognized
  2421. and she wanted to go rest.
  2422.  
  2423. 513
  2424. 00:30:29,299 --> 00:30:32,299
  2425. If a robot could have
  2426. intentions and desires,
  2427.  
  2428. 514
  2429. 00:30:32,300 --> 00:30:36,300
  2430. the robot can understand other people's
  2431. intentions and desires.
  2432.  
  2433. 515
  2434. 00:30:44,300 --> 00:30:47,100
  2435. That is tied to
  2436. relationships with people
  2437.  
  2438. 516
  2439. 00:30:47,101 --> 00:30:49,201
  2440. and that means
  2441. they like eachother.
  2442.  
  2443. 517
  2444. 00:30:50,302 --> 00:30:53,302
  2445. That means, well, I'm not sure,
  2446. to rub eachother.
  2447.  
  2448. 518
  2449. 00:30:56,985 --> 00:30:58,682
  2450. We build artificial intelligence,
  2451.  
  2452. 519
  2453. 00:30:58,726 --> 00:31:01,948
  2454. and the very first thing
  2455. we want to do is replicate us.
  2456.  
  2457. 520
  2458. 00:31:02,991 --> 00:31:05,341
  2459. I think the key point will come
  2460.  
  2461. 521
  2462. 00:31:05,385 --> 00:31:08,858
  2463. when all the major senses
  2464. are replicated.
  2465.  
  2466. 522
  2467. 00:31:09,302 --> 00:31:11,130
  2468. Sight...
  2469.  
  2470. 523
  2471. 00:31:11,173 --> 00:31:12,871
  2472. touch...
  2473.  
  2474. 524
  2475. 00:31:12,914 --> 00:31:14,611
  2476. smell.
  2477.  
  2478. 525
  2479. 00:31:14,655 --> 00:31:17,919
  2480. When we replicate our senses,
  2481. is that when it becomes alive?
  2482.  
  2483. 526
  2484. 00:31:27,624 --> 00:31:31,019
  2485. So many of our machines
  2486. are being built to understand us.
  2487.  
  2488. 527
  2489. 00:31:32,847 --> 00:31:35,005
  2490. But what happens when
  2491. an anthropomorphic creature
  2492.  
  2493. 528
  2494. 00:31:35,006 --> 00:31:37,474
  2495. discovers that they can
  2496. adjust their loyalty,
  2497.  
  2498. 529
  2499. 00:31:37,475 --> 00:31:40,043
  2500. adjust their courage,
  2501. adjust their avarice,
  2502.  
  2503. 530
  2504. 00:31:40,072 --> 00:31:42,291
  2505. adjust their cunning?
  2506.  
  2507. 531
  2508. 00:31:44,859 --> 00:31:48,645
  2509. The average person, they don't see
  2510. killer robots going down the streets.
  2511.  
  2512. 532
  2513. 00:31:48,689 --> 00:31:50,996
  2514. They're like,
  2515. "What are you talking about?"
  2516.  
  2517. 533
  2518. 00:31:51,039 --> 00:31:56,245
  2519. Man, we want to make sure that we don't
  2520. have killer robots going down the street.
  2521.  
  2522. 534
  2523. 00:31:57,089 --> 00:31:59,439
  2524. Once they're going down
  2525. the street, it is too late.
  2526.  
  2527. 535
  2528. 00:32:05,053 --> 00:32:08,578
  2529. The thing that worries me right now,
  2530. that keeps me awake,
  2531.  
  2532. 536
  2533. 00:32:08,622 --> 00:32:11,842
  2534. is the development
  2535. of autonomous weapons.
  2536.  
  2537. 537
  2538. 00:32:27,815 --> 00:32:32,733
  2539. Up to now, people have expressed
  2540. unease about drones,
  2541.  
  2542. 538
  2543. 00:32:32,776 --> 00:32:35,127
  2544. which are remotely
  2545. piloted aircraft.
  2546.  
  2547. 539
  2548. 00:32:39,827 --> 00:32:43,309
  2549. If you take a drone's camera
  2550. and feed it into the AI system,
  2551.  
  2552. 540
  2553. 00:32:43,352 --> 00:32:47,443
  2554. it's a very easy step from here
  2555. to fully autonomous weapons
  2556.  
  2557. 541
  2558. 00:32:47,487 --> 00:32:50,881
  2559. that choose their own targets
  2560. and release their own missiles.
  2561.  
  2562. 542
  2563. 00:33:12,729 --> 00:33:15,080
  2564. The expected life-span
  2565. of a human being
  2566.  
  2567. 543
  2568. 00:33:15,123 --> 00:33:19,420
  2569. in that kind of battle environment
  2570. would be measured in seconds.
  2571.  
  2572. 544
  2573. 00:33:20,563 --> 00:33:23,740
  2574. At one point,
  2575. drones were science fiction,
  2576.  
  2577. 545
  2578. 00:33:23,784 --> 00:33:28,832
  2579. and now they've become
  2580. the normal thing in war.
  2581.  
  2582. 546
  2583. 00:33:28,876 --> 00:33:33,402
  2584. There's over 10,000 in
  2585. U.S. military inventory alone.
  2586.  
  2587. 547
  2588. 00:33:33,446 --> 00:33:35,274
  2589. But they're not
  2590. just a U.S. phenomena.
  2591.  
  2592. 548
  2593. 00:33:35,317 --> 00:33:39,060
  2594. There's more than 80 countries
  2595. that operate them.
  2596.  
  2597. 549
  2598. 00:33:39,104 --> 00:33:41,932
  2599. It stands to reason
  2600. that people making some
  2601.  
  2602. 550
  2603. 00:33:41,976 --> 00:33:44,587
  2604. of the most important and
  2605. difficult decisions in the world
  2606.  
  2607. 551
  2608. 00:33:44,631 --> 00:33:46,328
  2609. are gonna start to use
  2610. and implement
  2611.  
  2612. 552
  2613. 00:33:46,372 --> 00:33:48,591
  2614. artificial intelligence.
  2615.  
  2616. 553
  2617. 00:33:50,767 --> 00:33:53,596
  2618. The Air Force just designed
  2619. a $400-billion jet program
  2620.  
  2621. 554
  2622. 00:33:53,640 --> 00:33:55,555
  2623. to put pilots in the sky,
  2624.  
  2625. 555
  2626. 00:33:55,598 --> 00:34:01,300
  2627. and a $500 AI, designed by
  2628. a couple of graduate students,
  2629.  
  2630. 556
  2631. 00:34:01,343 --> 00:34:03,432
  2632. is beating the best human pilots
  2633.  
  2634. 557
  2635. 00:34:03,476 --> 00:34:05,782
  2636. with a relatively
  2637. simple algorithm.
  2638.  
  2639. 558
  2640. 00:34:09,438 --> 00:34:13,399
  2641. AI will have as big an impact
  2642. on the military
  2643.  
  2644. 559
  2645. 00:34:13,442 --> 00:34:17,490
  2646. as the combustion engine
  2647. had at the turn of the century.
  2648.  
  2649. 560
  2650. 00:34:17,533 --> 00:34:21,233
  2651. It will literally touch everything
  2652. that the military does,
  2653.  
  2654. 561
  2655. 00:34:21,276 --> 00:34:25,324
  2656. from driverless convoys
  2657. delivering logistical supplies,
  2658.  
  2659. 562
  2660. 00:34:25,367 --> 00:34:27,021
  2661. to unmanned drones
  2662.  
  2663. 563
  2664. 00:34:27,065 --> 00:34:30,764
  2665. delivering medical aid,
  2666. to computational propaganda,
  2667.  
  2668. 564
  2669. 00:34:30,807 --> 00:34:34,246
  2670. trying to win the hearts
  2671. and minds of a population.
  2672.  
  2673. 565
  2674. 00:34:34,289 --> 00:34:38,337
  2675. And so it stands to reason
  2676. that whoever has the best AI
  2677.  
  2678. 566
  2679. 00:34:38,380 --> 00:34:41,688
  2680. will probably achieve
  2681. dominance on this planet.
  2682.  
  2683. 567
  2684. 00:34:45,561 --> 00:34:47,650
  2685. At some point in
  2686. the early 21st century,
  2687.  
  2688. 568
  2689. 00:34:47,694 --> 00:34:51,219
  2690. all of mankind was
  2691. united in celebration.
  2692.  
  2693. 569
  2694. 00:34:51,263 --> 00:34:53,830
  2695. We marveled
  2696. at our own magnificence
  2697.  
  2698. 570
  2699. 00:34:53,874 --> 00:34:56,833
  2700. as we gave birth to AI.
  2701.  
  2702. 571
  2703. 00:34:56,877 --> 00:34:58,966
  2704. AI?
  2705.  
  2706. 572
  2707. 00:34:59,009 --> 00:35:00,489
  2708. You mean
  2709. artificial intelligence?
  2710.  
  2711. 573
  2712. 00:35:00,533 --> 00:35:01,751
  2713. A singular consciousness
  2714.  
  2715. 574
  2716. 00:35:01,795 --> 00:35:05,886
  2717. that spawned
  2718. an entire race of machines.
  2719.  
  2720. 575
  2721. 00:35:05,929 --> 00:35:09,716
  2722. We don't know
  2723. who struck first -- us or them,
  2724.  
  2725. 576
  2726. 00:35:09,759 --> 00:35:12,980
  2727. but we know that it was us
  2728. that scorched the sky.
  2729.  
  2730. 577
  2731. 00:35:14,677 --> 00:35:16,766
  2732. There's a long history
  2733. of science fiction,
  2734.  
  2735. 578
  2736. 00:35:16,810 --> 00:35:19,987
  2737. not just predicting the future,
  2738. but shaping the future.
  2739.  
  2740. 579
  2741. 00:35:26,863 --> 00:35:30,389
  2742. Arthur Conan Doyle
  2743. writing before World War I
  2744.  
  2745. 580
  2746. 00:35:30,432 --> 00:35:34,393
  2747. on the danger of how
  2748. submarines might be used
  2749.  
  2750. 581
  2751. 00:35:34,436 --> 00:35:38,048
  2752. to carry out civilian blockades.
  2753.  
  2754. 582
  2755. 00:35:38,092 --> 00:35:40,399
  2756. At the time
  2757. he's writing this fiction,
  2758.  
  2759. 583
  2760. 00:35:40,442 --> 00:35:43,402
  2761. the Royal Navy made fun
  2762. of Arthur Conan Doyle
  2763.  
  2764. 584
  2765. 00:35:43,445 --> 00:35:45,230
  2766. for this absurd idea
  2767.  
  2768. 585
  2769. 00:35:45,273 --> 00:35:47,623
  2770. that submarines
  2771. could be useful in war.
  2772.  
  2773. 586
  2774. 00:35:53,455 --> 00:35:55,370
  2775. One of the things
  2776. we've seen in history
  2777.  
  2778. 587
  2779. 00:35:55,414 --> 00:35:58,243
  2780. is that our attitude
  2781. towards technology,
  2782.  
  2783. 588
  2784. 00:35:58,286 --> 00:36:01,942
  2785. but also ethics,
  2786. are very context-dependent.
  2787.  
  2788. 589
  2789. 00:36:01,985 --> 00:36:03,726
  2790. For example, the submarine...
  2791.  
  2792. 590
  2793. 00:36:03,770 --> 00:36:06,468
  2794. nations like Great Britain
  2795. and even the United States
  2796.  
  2797. 591
  2798. 00:36:06,512 --> 00:36:09,863
  2799. found it horrifying
  2800. to use the submarine.
  2801.  
  2802. 592
  2803. 00:36:09,906 --> 00:36:13,214
  2804. In fact, the German use of the
  2805. submarine to carry out attacks
  2806.  
  2807. 593
  2808. 00:36:13,258 --> 00:36:18,480
  2809. was the reason why the United
  2810. States joined World War I.
  2811.  
  2812. 594
  2813. 00:36:18,524 --> 00:36:20,613
  2814. But move the timeline forward.
  2815.  
  2816. 595
  2817. 00:36:20,656 --> 00:36:23,529
  2818. The United States
  2819. of America was suddenly
  2820.  
  2821. 596
  2822. 00:36:23,572 --> 00:36:28,403
  2823. and deliberately attacked
  2824. by the empire of Japan.
  2825.  
  2826. 597
  2827. 00:36:28,447 --> 00:36:32,190
  2828. Five hours after Pearl Harbor,
  2829. the order goes out
  2830.  
  2831. 598
  2832. 00:36:32,233 --> 00:36:36,498
  2833. to commit unrestricted
  2834. submarine warfare against Japan.
  2835.  
  2836. 599
  2837. 00:36:39,936 --> 00:36:43,589
  2838. So Arthur Conan Doyle
  2839. turned out to be right.
  2840.  
  2841. 600
  2842. 00:36:44,332 --> 00:36:46,856
  2843. That's the great old line
  2844. about science fiction --
  2845.  
  2846. 601
  2847. 00:36:46,900 --> 00:36:48,336
  2848. It's a lie that tells the truth.
  2849.  
  2850. 602
  2851. 00:36:48,380 --> 00:36:51,470
  2852. Fellow executives,
  2853. it gives me great pleasure
  2854.  
  2855. 603
  2856. 00:36:51,513 --> 00:36:54,821
  2857. to introduce you to the future
  2858. of law enforcement...
  2859.  
  2860. 604
  2861. 00:36:54,864 --> 00:36:56,562
  2862. ED-209.
  2863.  
  2864. 605
  2865. 00:37:03,656 --> 00:37:05,919
  2866. This isn't just a question
  2867. of science fiction.
  2868.  
  2869. 606
  2870. 00:37:05,962 --> 00:37:09,488
  2871. This is about what's next,
  2872. about what's happening right now.
  2873.  
  2874. 607
  2875. 00:37:13,970 --> 00:37:19,324
  2876. The role of intelligent systems is
  2877. growing very rapidly in warfare.
  2878.  
  2879. 608
  2880. 00:37:19,367 --> 00:37:22,152
  2881. Everyone is pushing
  2882. in the unmanned realm.
  2883.  
  2884. 609
  2885. 00:37:26,418 --> 00:37:28,898
  2886. Today, the Secretary of Defense
  2887. is very, very clear --
  2888.  
  2889. 610
  2890. 00:37:28,942 --> 00:37:32,337
  2891. We will not create fully
  2892. autonomous attacking vehicles.
  2893.  
  2894. 611
  2895. 00:37:32,380 --> 00:37:34,643
  2896. Not everyone
  2897. is gonna hold themselves
  2898.  
  2899. 612
  2900. 00:37:34,687 --> 00:37:36,515
  2901. to that same set of values.
  2902.  
  2903. 613
  2904. 00:37:36,558 --> 00:37:40,693
  2905. And when China and Russia start
  2906. deploying autonomous vehicles
  2907.  
  2908. 614
  2909. 00:37:40,736 --> 00:37:45,611
  2910. that can attack and kill, what's
  2911. the move that we're gonna make?
  2912.  
  2913. 615
  2914. 00:37:50,006 --> 00:37:51,617
  2915. You can't say,
  2916. "Well, we're gonna use
  2917.  
  2918. 616
  2919. 00:37:51,660 --> 00:37:53,967
  2920. autonomous weapons
  2921. for our military dominance,
  2922.  
  2923. 617
  2924. 00:37:54,010 --> 00:37:56,796
  2925. but no one else
  2926. is gonna use them."
  2927.  
  2928. 618
  2929. 00:37:56,839 --> 00:38:00,495
  2930. If you make these weapons,
  2931. they're gonna be used to attack
  2932.  
  2933. 619
  2934. 00:38:00,539 --> 00:38:03,324
  2935. human populations
  2936. in large numbers.
  2937.  
  2938. 620
  2939. 00:38:12,551 --> 00:38:14,596
  2940. Autonomous weapons are,
  2941. by their nature,
  2942.  
  2943. 621
  2944. 00:38:14,640 --> 00:38:16,468
  2945. weapons of mass destruction,
  2946.  
  2947. 622
  2948. 00:38:16,511 --> 00:38:19,862
  2949. because it doesn't need a
  2950. human being to guide it or carry it.
  2951.  
  2952. 623
  2953. 00:38:19,906 --> 00:38:22,517
  2954. You only need one person,
  2955. to, you know,
  2956.  
  2957. 624
  2958. 00:38:22,561 --> 00:38:25,781
  2959. write a little program.
  2960.  
  2961. 625
  2962. 00:38:25,825 --> 00:38:30,220
  2963. It just captures
  2964. the complexity of this field.
  2965.  
  2966. 626
  2967. 00:38:30,264 --> 00:38:32,571
  2968. It is cool.
  2969. It is important.
  2970.  
  2971. 627
  2972. 00:38:32,614 --> 00:38:34,573
  2973. It is amazing.
  2974.  
  2975. 628
  2976. 00:38:34,616 --> 00:38:37,053
  2977. It is also frightening.
  2978.  
  2979. 629
  2980. 00:38:37,097 --> 00:38:38,968
  2981. And it's all about trust.
  2982.  
  2983. 630
  2984. 00:38:42,102 --> 00:38:44,583
  2985. It's an open letter about
  2986. artificial intelligence,
  2987.  
  2988. 631
  2989. 00:38:44,626 --> 00:38:47,063
  2990. signed by some of
  2991. the biggest names in science.
  2992.  
  2993. 632
  2994. 00:38:47,107 --> 00:38:48,413
  2995. What do they want?
  2996.  
  2997. 633
  2998. 00:38:48,456 --> 00:38:50,763
  2999. Ban the use of
  3000. autonomous weapons.
  3001.  
  3002. 634
  3003. 00:38:50,806 --> 00:38:52,373
  3004. The author stated,
  3005.  
  3006. 635
  3007. 00:38:52,417 --> 00:38:54,375
  3008. "Autonomous weapons
  3009. have been described
  3010.  
  3011. 636
  3012. 00:38:54,419 --> 00:38:56,595
  3013. as the third revolution
  3014. in warfare."
  3015.  
  3016. 637
  3017. 00:38:56,638 --> 00:38:58,853
  3018. ...thousand
  3019. artificial-intelligence specialists
  3020.  
  3021. 638
  3022. 00:38:58,855 --> 00:39:01,875
  3023. calling for a global ban
  3024. on killer robots.
  3025.  
  3026. 639
  3027. 00:39:01,876 --> 00:39:04,357
  3028. This open letter basically says
  3029.  
  3030. 640
  3031. 00:39:04,385 --> 00:39:07,954
  3032. that we should redefine the goal
  3033. of the field of artificial intelligence
  3034.  
  3035. 641
  3036. 00:39:07,997 --> 00:39:11,610
  3037. away from just creating pure,
  3038. undirected intelligence,
  3039.  
  3040. 642
  3041. 00:39:11,653 --> 00:39:13,655
  3042. towards creating
  3043. beneficial intelligence.
  3044.  
  3045. 643
  3046. 00:39:13,699 --> 00:39:16,092
  3047. The development of AI
  3048. is not going to stop.
  3049.  
  3050. 644
  3051. 00:39:16,136 --> 00:39:18,094
  3052. It is going to continue
  3053. and get better.
  3054.  
  3055. 645
  3056. 00:39:18,138 --> 00:39:19,835
  3057. If the international community
  3058.  
  3059. 646
  3060. 00:39:19,879 --> 00:39:21,968
  3061. isn't putting
  3062. certain controls on this,
  3063.  
  3064. 647
  3065. 00:39:22,011 --> 00:39:24,666
  3066. people will develop things
  3067. that can do anything.
  3068.  
  3069. 648
  3070. 00:39:24,710 --> 00:39:27,365
  3071. The letter says
  3072. that we are years, not decades,
  3073.  
  3074. 649
  3075. 00:39:27,408 --> 00:39:30,106
  3076. away from these weapons being deployed.
  3077. So first of all...
  3078.  
  3079. 650
  3080. 00:39:30,150 --> 00:39:32,413
  3081. We had 6,000 signatories
  3082. of that letter,
  3083.  
  3084. 651
  3085. 00:39:32,457 --> 00:39:35,155
  3086. including many of
  3087. the major figures in the field.
  3088.  
  3089. 652
  3090. 00:39:37,026 --> 00:39:39,942
  3091. I'm getting a lot of visits
  3092. from high-ranking officials
  3093.  
  3094. 653
  3095. 00:39:39,986 --> 00:39:42,989
  3096. who wish to emphasize that
  3097. American military dominance
  3098.  
  3099. 654
  3100. 00:39:43,032 --> 00:39:45,731
  3101. is very important,
  3102. and autonomous weapons
  3103.  
  3104. 655
  3105. 00:39:45,774 --> 00:39:50,083
  3106. may be part of
  3107. the Defense Department's plan.
  3108.  
  3109. 656
  3110. 00:39:50,126 --> 00:39:52,433
  3111. That's very, very scary,
  3112. because a value system
  3113.  
  3114. 657
  3115. 00:39:52,477 --> 00:39:54,479
  3116. of military developers
  3117. of technology
  3118.  
  3119. 658
  3120. 00:39:54,522 --> 00:39:57,307
  3121. is not the same as a value system
  3122. of the human race.
  3123.  
  3124. 659
  3125. 00:40:00,789 --> 00:40:02,922
  3126. Out of the concerns
  3127. about the possibility
  3128.  
  3129. 660
  3130. 00:40:02,965 --> 00:40:06,665
  3131. that this technology might be
  3132. a threat to human existence,
  3133.  
  3134. 661
  3135. 00:40:06,708 --> 00:40:08,144
  3136. a number of the technologists
  3137.  
  3138. 662
  3139. 00:40:08,188 --> 00:40:09,972
  3140. have funded
  3141. the Future of Life Institute
  3142.  
  3143. 663
  3144. 00:40:10,016 --> 00:40:12,192
  3145. to try to grapple
  3146. with these problems.
  3147.  
  3148. 664
  3149. 00:40:13,193 --> 00:40:14,847
  3150. All of these guys are secretive,
  3151.  
  3152. 665
  3153. 00:40:14,890 --> 00:40:16,805
  3154. and so it's interesting
  3155. to me to see them,
  3156.  
  3157. 666
  3158. 00:40:16,849 --> 00:40:19,735
  3159. you know, all together.
  3160.  
  3161. 667
  3162. 00:40:20,679 --> 00:40:24,030
  3163. Everything we have is a result
  3164. of our intelligence.
  3165.  
  3166. 668
  3167. 00:40:24,073 --> 00:40:26,641
  3168. It's not the result
  3169. of our big, scary teeth
  3170.  
  3171. 669
  3172. 00:40:26,685 --> 00:40:29,470
  3173. or our large claws
  3174. or our enormous muscles.
  3175.  
  3176. 670
  3177. 00:40:29,514 --> 00:40:32,473
  3178. It's because we're actually
  3179. relatively intelligent.
  3180.  
  3181. 671
  3182. 00:40:32,517 --> 00:40:35,520
  3183. And among my generation,
  3184. we're all having
  3185.  
  3186. 672
  3187. 00:40:35,563 --> 00:40:37,086
  3188. what we call "holy cow,"
  3189.  
  3190. 673
  3191. 00:40:37,130 --> 00:40:39,045
  3192. or "holy something else"
  3193. moments,
  3194.  
  3195. 674
  3196. 00:40:39,088 --> 00:40:41,003
  3197. because we see
  3198. that the technology
  3199.  
  3200. 675
  3201. 00:40:41,047 --> 00:40:44,180
  3202. is accelerating faster
  3203. than we expected.
  3204.  
  3205. 676
  3206. 00:40:44,224 --> 00:40:46,705
  3207. I remember sitting
  3208. around the table there
  3209.  
  3210. 677
  3211. 00:40:46,748 --> 00:40:50,099
  3212. with some of the best and
  3213. the smartest minds in the world,
  3214.  
  3215. 678
  3216. 00:40:50,143 --> 00:40:52,058
  3217. and what really
  3218. struck me was,
  3219.  
  3220. 679
  3221. 00:40:52,101 --> 00:40:56,149
  3222. maybe the human brain
  3223. is not able to fully grasp
  3224.  
  3225. 680
  3226. 00:40:56,192 --> 00:40:58,673
  3227. the complexity of the world
  3228. that we're confronted with.
  3229.  
  3230. 681
  3231. 00:40:58,717 --> 00:41:01,415
  3232. As it's currently constructed,
  3233.  
  3234. 682
  3235. 00:41:01,459 --> 00:41:04,766
  3236. the road that AI is following
  3237. heads off a cliff,
  3238.  
  3239. 683
  3240. 00:41:04,810 --> 00:41:07,595
  3241. and we need to change
  3242. the direction that we're going
  3243.  
  3244. 684
  3245. 00:41:07,639 --> 00:41:10,729
  3246. so that we don't take
  3247. the human race off the cliff.
  3248.  
  3249. 685
  3250. 00:41:13,558 --> 00:41:17,126
  3251. Google acquired DeepMind
  3252. several years ago.
  3253.  
  3254. 686
  3255. 00:41:17,170 --> 00:41:22,088
  3256. DeepMind operates as a
  3257. semi-independent subsidiary of Google.
  3258.  
  3259. 687
  3260. 00:41:22,131 --> 00:41:24,960
  3261. The thing that makes
  3262. DeepMind unique
  3263.  
  3264. 688
  3265. 00:41:25,004 --> 00:41:26,919
  3266. is that DeepMind
  3267. is absolutely focused
  3268.  
  3269. 689
  3270. 00:41:26,962 --> 00:41:30,313
  3271. on creating digital
  3272. superintelligence --
  3273.  
  3274. 690
  3275. 00:41:30,357 --> 00:41:34,056
  3276. an AI that is vastly smarter
  3277. than any human on Earth
  3278.  
  3279. 691
  3280. 00:41:34,100 --> 00:41:36,624
  3281. and ultimately smarter than
  3282. all humans on Earth combined.
  3283.  
  3284. 692
  3285. 00:41:36,668 --> 00:41:40,715
  3286. This is from the DeepMind
  3287. reinforcement learning system.
  3288.  
  3289. 693
  3290. 00:41:40,759 --> 00:41:43,544
  3291. Basically wakes up
  3292. like a newborn baby
  3293.  
  3294. 694
  3295. 00:41:43,588 --> 00:41:46,852
  3296. and is shown the screen
  3297. of an Atari video game
  3298.  
  3299. 695
  3300. 00:41:46,895 --> 00:41:50,508
  3301. and then has to learn
  3302. to play the video game.
  3303.  
  3304. 696
  3305. 00:41:50,551 --> 00:41:55,600
  3306. It knows nothing about objects,
  3307. about motion, about time.
  3308.  
  3309. 697
  3310. 00:41:57,602 --> 00:41:59,604
  3311. It only knows that there's
  3312. an image on the screen
  3313.  
  3314. 698
  3315. 00:41:59,647 --> 00:42:02,563
  3316. and there's a score.
  3317.  
  3318. 699
  3319. 00:42:02,607 --> 00:42:06,436
  3320. So, if your baby woke up
  3321. the day it was born
  3322.  
  3323. 700
  3324. 00:42:06,480 --> 00:42:08,090
  3325. and, by late afternoon,
  3326.  
  3327. 701
  3328. 00:42:08,134 --> 00:42:11,093
  3329. was playing
  3330. 40 different Atari video games
  3331.  
  3332. 702
  3333. 00:42:11,137 --> 00:42:15,315
  3334. at a superhuman level,
  3335. you would be terrified.
  3336.  
  3337. 703
  3338. 00:42:15,358 --> 00:42:19,101
  3339. You would say,
  3340. "My baby is possessed. Send it back."
  3341.  
  3342. 704
  3343. 00:42:19,145 --> 00:42:23,584
  3344. The DeepMind system
  3345. can win at any game.
  3346.  
  3347. 705
  3348. 00:42:23,628 --> 00:42:27,588
  3349. It can already beat all
  3350. the original Atari games.
  3351.  
  3352. 706
  3353. 00:42:27,632 --> 00:42:29,155
  3354. It is superhuman.
  3355.  
  3356. 707
  3357. 00:42:29,198 --> 00:42:31,636
  3358. It plays the games at superspeed
  3359. in less than a minute.
  3360.  
  3361. 708
  3362. 00:42:37,076 --> 00:42:38,643
  3363. DeepMind turned
  3364. to another challenge,
  3365.  
  3366. 709
  3367. 00:42:38,686 --> 00:42:40,558
  3368. and the challenge
  3369. was the game of Go,
  3370.  
  3371. 710
  3372. 00:42:40,601 --> 00:42:42,603
  3373. which people
  3374. have generally argued
  3375.  
  3376. 711
  3377. 00:42:42,647 --> 00:42:45,084
  3378. has been beyond
  3379. the power of computers
  3380.  
  3381. 712
  3382. 00:42:45,127 --> 00:42:48,304
  3383. to play with
  3384. the best human Go players.
  3385.  
  3386. 713
  3387. 00:42:48,348 --> 00:42:51,264
  3388. First, they challenged
  3389. a European Go champion.
  3390.  
  3391. 714
  3392. 00:42:53,222 --> 00:42:55,834
  3393. Then they challenged
  3394. a Korean Go champion.
  3395.  
  3396. 715
  3397. 00:42:55,877 --> 00:42:57,836
  3398. Please start the game.
  3399.  
  3400. 716
  3401. 00:42:57,879 --> 00:42:59,838
  3402. And they were able
  3403. to win both times
  3404.  
  3405. 717
  3406. 00:42:59,881 --> 00:43:02,797
  3407. in kind of striking fashion.
  3408.  
  3409. 718
  3410. 00:43:02,841 --> 00:43:05,017
  3411. You were reading articles
  3412. in New York Times years ago
  3413.  
  3414. 719
  3415. 00:43:05,060 --> 00:43:09,761
  3416. talking about how Go would take
  3417. 100 years for us to solve.
  3418.  
  3419. 720
  3420. 00:43:09,804 --> 00:43:13,460
  3421. People said, "Well, you know,
  3422. but that's still just a board.
  3423.  
  3424. 721
  3425. 00:43:13,503 --> 00:43:15,027
  3426. Poker is an art.
  3427.  
  3428. 722
  3429. 00:43:15,070 --> 00:43:16,419
  3430. Poker involves reading people.
  3431.  
  3432. 723
  3433. 00:43:16,463 --> 00:43:18,073
  3434. Poker involves lying
  3435. and bluffing.
  3436.  
  3437. 724
  3438. 00:43:18,117 --> 00:43:19,553
  3439. It's not an exact thing.
  3440.  
  3441. 725
  3442. 00:43:19,597 --> 00:43:21,381
  3443. That will never be,
  3444. you know, a computer.
  3445.  
  3446. 726
  3447. 00:43:21,424 --> 00:43:22,861
  3448. You can't do that."
  3449.  
  3450. 727
  3451. 00:43:22,904 --> 00:43:24,932
  3452. They took the best
  3453. poker players in the world,
  3454.  
  3455. 728
  3456. 00:43:25,176 --> 00:43:30,520
  3457. and it took seven days for the computer
  3458. to start demolishing the humans.
  3459.  
  3460. 729
  3461. 00:43:30,564 --> 00:43:32,461
  3462. So it's the best poker player
  3463. in the world,
  3464.  
  3465. 730
  3466. 00:43:32,462 --> 00:43:35,012
  3467. it's the best Go player in the
  3468. world, and the pattern here
  3469.  
  3470. 731
  3471. 00:43:35,013 --> 00:43:37,454
  3472. is that AI might take a little while
  3473.  
  3474. 732
  3475. 00:43:37,484 --> 00:43:40,443
  3476. to wrap its tentacles
  3477. around a new skill,
  3478.  
  3479. 733
  3480. 00:43:40,487 --> 00:43:44,883
  3481. but when it does, when it
  3482. gets it, it is unstoppable.
  3483.  
  3484. 734
  3485. 00:43:52,020 --> 00:43:55,110
  3486. DeepMind's AI has
  3487. administrator-level access
  3488.  
  3489. 735
  3490. 00:43:55,154 --> 00:43:57,156
  3491. to Google's servers
  3492.  
  3493. 736
  3494. 00:43:57,199 --> 00:44:00,768
  3495. to optimize energy usage
  3496. at the data centers.
  3497.  
  3498. 737
  3499. 00:44:00,812 --> 00:44:04,816
  3500. However, this could be
  3501. an unintentional Trojan horse.
  3502.  
  3503. 738
  3504. 00:44:04,859 --> 00:44:07,253
  3505. DeepMind has to have complete
  3506. control of the data centers,
  3507.  
  3508. 739
  3509. 00:44:07,296 --> 00:44:08,950
  3510. so with a little
  3511. software update,
  3512.  
  3513. 740
  3514. 00:44:08,994 --> 00:44:10,691
  3515. that AI could take
  3516. complete control
  3517.  
  3518. 741
  3519. 00:44:10,735 --> 00:44:12,214
  3520. of the whole Google system,
  3521.  
  3522. 742
  3523. 00:44:12,258 --> 00:44:13,607
  3524. which means
  3525. they can do anything.
  3526.  
  3527. 743
  3528. 00:44:13,651 --> 00:44:16,131
  3529. They could look at all your data.
  3530. They could do anything.
  3531.  
  3532. 744
  3533. 00:44:20,135 --> 00:44:23,051
  3534. We're rapidly heading towards
  3535. digital superintelligence
  3536.  
  3537. 745
  3538. 00:44:23,095 --> 00:44:24,313
  3539. that far exceeds any human.
  3540.  
  3541. 746
  3542. 00:44:24,357 --> 00:44:26,402
  3543. I think it's very obvious.
  3544.  
  3545. 747
  3546. 00:44:26,446 --> 00:44:29,710
  3547. The problem is, we're not gonna
  3548. suddenly hit human-level intelligence
  3549.  
  3550. 748
  3551. 00:44:29,754 --> 00:44:33,105
  3552. and say,
  3553. "Okay, let's stop research."
  3554.  
  3555. 749
  3556. 00:44:33,148 --> 00:44:35,015
  3557. It's gonna go beyond
  3558. human-level intelligence
  3559.  
  3560. 750
  3561. 00:44:35,016 --> 00:44:39,459
  3562. into what's called "superintelligence,"
  3563. and that's anything smarter than us.
  3564.  
  3565. 751
  3566. 00:44:39,502 --> 00:44:42,810
  3567. AI at the superhuman level,
  3568. if we succeed with that, will be
  3569.  
  3570. 752
  3571. 00:44:42,854 --> 00:44:46,553
  3572. by far the most powerful
  3573. invention we've ever made
  3574.  
  3575. 753
  3576. 00:44:46,596 --> 00:44:50,296
  3577. and the last invention
  3578. we ever have to make.
  3579.  
  3580. 754
  3581. 00:44:50,339 --> 00:44:53,168
  3582. And if we create AI
  3583. that's smarter than us,
  3584.  
  3585. 755
  3586. 00:44:53,212 --> 00:44:54,735
  3587. we have to be open
  3588. to the possibility
  3589.  
  3590. 756
  3591. 00:44:54,779 --> 00:44:57,520
  3592. that we might actually
  3593. lose control to them.
  3594.  
  3595. 757
  3596. 00:45:00,785 --> 00:45:02,612
  3597. Let's say
  3598. you give it some objective,
  3599.  
  3600. 758
  3601. 00:45:02,656 --> 00:45:04,745
  3602. like curing cancer,
  3603. and then you discover
  3604.  
  3605. 759
  3606. 00:45:04,789 --> 00:45:06,965
  3607. that the way
  3608. it chooses to go about that
  3609.  
  3610. 760
  3611. 00:45:07,008 --> 00:45:08,444
  3612. is actually in conflict
  3613.  
  3614. 761
  3615. 00:45:08,488 --> 00:45:11,705
  3616. with a lot of other things
  3617. you care about.
  3618.  
  3619. 762
  3620. 00:45:12,448 --> 00:45:16,496
  3621. AI doesn't have to be evil
  3622. to destroy humanity.
  3623.  
  3624. 763
  3625. 00:45:16,539 --> 00:45:20,674
  3626. If AI has a goal, and humanity
  3627. just happens to be in the way,
  3628.  
  3629. 764
  3630. 00:45:20,718 --> 00:45:22,894
  3631. it will destroy humanity
  3632. as a matter of course,
  3633.  
  3634. 765
  3635. 00:45:22,937 --> 00:45:25,113
  3636. without even thinking about it.
  3637. No hard feelings.
  3638.  
  3639. 766
  3640. 00:45:25,157 --> 00:45:27,072
  3641. It's just like
  3642. if we're building a road
  3643.  
  3644. 767
  3645. 00:45:27,115 --> 00:45:29,770
  3646. and an anthill happens
  3647. to be in the way...
  3648.  
  3649. 768
  3650. 00:45:29,814 --> 00:45:31,467
  3651. We don't hate ants.
  3652.  
  3653. 769
  3654. 00:45:31,511 --> 00:45:33,165
  3655. We're just building a road.
  3656.  
  3657. 770
  3658. 00:45:33,208 --> 00:45:34,857
  3659. And so goodbye, anthill.
  3660.  
  3661. 771
  3662. 00:45:37,996 --> 00:45:40,172
  3663. It's tempting
  3664. to dismiss these concerns,
  3665.  
  3666. 772
  3667. 00:45:40,215 --> 00:45:42,783
  3668. 'cause it's, like,
  3669. something that might happen
  3670.  
  3671. 773
  3672. 00:45:42,827 --> 00:45:47,396
  3673. in a few decades or 100 years,
  3674. so why worry?
  3675.  
  3676. 774
  3677. 00:45:47,440 --> 00:45:50,704
  3678. But if you go back
  3679. to September 11, 1933,
  3680.  
  3681. 775
  3682. 00:45:50,748 --> 00:45:54,795
  3683. Ernest Rutherford, who was the most
  3684. well-known nuclear physicist of his time,
  3685.  
  3686. 776
  3687. 00:45:54,839 --> 00:45:58,668
  3688. said that the possibility of ever
  3689. extracting useful amounts of energy
  3690.  
  3691. 777
  3692. 00:45:58,712 --> 00:46:00,801
  3693. from the transmutation
  3694. of atoms, as he called it,
  3695.  
  3696. 778
  3697. 00:46:00,845 --> 00:46:03,151
  3698. was moonshine.
  3699.  
  3700. 779
  3701. 00:46:03,195 --> 00:46:06,502
  3702. The next morning, Leo Szilard,
  3703. who was a much younger physicist,
  3704.  
  3705. 780
  3706. 00:46:06,546 --> 00:46:09,984
  3707. read this and got really annoyed
  3708. and figured out
  3709.  
  3710. 781
  3711. 00:46:10,028 --> 00:46:11,943
  3712. how to make
  3713. a nuclear chain reaction
  3714.  
  3715. 782
  3716. 00:46:11,986 --> 00:46:13,379
  3717. just a few months later.
  3718.  
  3719. 783
  3720. 00:46:20,603 --> 00:46:23,693
  3721. We have spent more
  3722. than $2 billion
  3723.  
  3724. 784
  3725. 00:46:23,737 --> 00:46:27,523
  3726. on the greatest
  3727. scientific gamble in history.
  3728.  
  3729. 785
  3730. 00:46:27,567 --> 00:46:30,222
  3731. So when people say that,
  3732. "Oh, this is so far off
  3733.  
  3734. 786
  3735. 00:46:30,265 --> 00:46:32,528
  3736. in the future, we don't have
  3737. to worry about it,"
  3738.  
  3739. 787
  3740. 00:46:32,572 --> 00:46:36,271
  3741. it might only be three, four
  3742. breakthroughs of that magnitude
  3743.  
  3744. 788
  3745. 00:46:36,315 --> 00:46:40,275
  3746. that will get us from here
  3747. to superintelligent machines.
  3748.  
  3749. 789
  3750. 00:46:40,319 --> 00:46:42,974
  3751. If it's gonna take
  3752. 20 years to figure out
  3753.  
  3754. 790
  3755. 00:46:43,017 --> 00:46:45,237
  3756. how to keep AI beneficial,
  3757.  
  3758. 791
  3759. 00:46:45,280 --> 00:46:48,849
  3760. then we should start today,
  3761. not at the last second
  3762.  
  3763. 792
  3764. 00:46:48,893 --> 00:46:51,460
  3765. when some dudes
  3766. drinking Red Bull
  3767.  
  3768. 793
  3769. 00:46:51,504 --> 00:46:53,832
  3770. decide to flip the switch
  3771. and test the thing.
  3772.  
  3773. 794
  3774. 00:46:56,814 --> 00:46:58,859
  3775. We have five years.
  3776.  
  3777. 795
  3778. 00:46:58,903 --> 00:47:03,764
  3779. I think digital superintelligence
  3780. will happen in my lifetime.
  3781.  
  3782. 796
  3783. 00:47:03,908 --> 00:47:05,735
  3784. 100%.
  3785.  
  3786. 797
  3787. 00:47:05,779 --> 00:47:07,215
  3788. When this happens,
  3789.  
  3790. 798
  3791. 00:47:07,259 --> 00:47:09,696
  3792. it will be surrounded
  3793. by a bunch of people
  3794.  
  3795. 799
  3796. 00:47:09,739 --> 00:47:13,091
  3797. who are really just excited
  3798. about the technology.
  3799.  
  3800. 800
  3801. 00:47:13,134 --> 00:47:15,571
  3802. They want to see it succeed,
  3803. but they're not anticipating
  3804.  
  3805. 801
  3806. 00:47:15,615 --> 00:47:16,964
  3807. that it can get out of control.
  3808.  
  3809. 802
  3810. 00:47:25,494 --> 00:47:28,584
  3811. Oh, my God, I trust
  3812. my computer so much.
  3813.  
  3814. 803
  3815. 00:47:28,628 --> 00:47:30,195
  3816. That's an amazing question.
  3817.  
  3818. 804
  3819. 00:47:30,238 --> 00:47:31,457
  3820. I don't trust
  3821. my computer.
  3822.  
  3823. 805
  3824. 00:47:31,500 --> 00:47:32,937
  3825. If it's on,
  3826. I take it off.
  3827.  
  3828. 806
  3829. 00:47:32,980 --> 00:47:34,242
  3830. Like, even when it's off,
  3831.  
  3832. 807
  3833. 00:47:34,286 --> 00:47:35,896
  3834. I still think it's on.
  3835. Like, you know?
  3836.  
  3837. 808
  3838. 00:47:35,897 --> 00:47:37,694
  3839. Like, you really cannot tru--
  3840. Like, the webcams,
  3841.  
  3842. 809
  3843. 00:47:37,695 --> 00:47:39,625
  3844. you don't know if, like,
  3845. someone might turn it...
  3846.  
  3847. 810
  3848. 00:47:39,639 --> 00:47:41,249
  3849. You don't know, like.
  3850.  
  3851. 811
  3852. 00:47:41,293 --> 00:47:42,903
  3853. I don't trust my computer.
  3854.  
  3855. 812
  3856. 00:47:42,947 --> 00:47:46,907
  3857. Like, in my phone,
  3858. every time they ask me
  3859.  
  3860. 813
  3861. 00:47:46,951 --> 00:47:49,475
  3862. "Can we send your
  3863. information to Apple?"
  3864.  
  3865. 814
  3866. 00:47:49,518 --> 00:47:50,998
  3867. every time, I...
  3868.  
  3869. 815
  3870. 00:47:51,042 --> 00:47:53,087
  3871. So, I don't trust my phone.
  3872.  
  3873. 816
  3874. 00:47:53,131 --> 00:47:56,743
  3875. Okay. So, part of it is,
  3876. yes, I do trust it,
  3877.  
  3878. 817
  3879. 00:47:56,786 --> 00:48:00,660
  3880. because it would be really
  3881. hard to get through the day
  3882.  
  3883. 818
  3884. 00:48:00,703 --> 00:48:04,011
  3885. in the way our world is
  3886. set up without computers.
  3887.  
  3888. 819
  3889. 00:48:10,975 --> 00:48:13,368
  3890. Trust is such a human experience.
  3891.  
  3892. 820
  3893. 00:48:21,289 --> 00:48:25,119
  3894. I have a patient coming in
  3895. with an intracranial aneurysm.
  3896.  
  3897. 821
  3898. 00:48:30,037 --> 00:48:31,691
  3899. They want to look
  3900. in my eyes and know
  3901.  
  3902. 822
  3903. 00:48:31,734 --> 00:48:34,955
  3904. that they can trust
  3905. this person with their life.
  3906.  
  3907. 823
  3908. 00:48:34,999 --> 00:48:39,129
  3909. I'm not horribly concerned
  3910. about anything.
  3911.  
  3912. 824
  3913. 00:48:39,138 --> 00:48:40,204
  3914. Good.
  3915.  
  3916. 825
  3917. 00:48:40,206 --> 00:48:42,920
  3918. Part of that is because I
  3919. have confidence in you.
  3920.  
  3921. 826
  3922. 00:48:50,753 --> 00:48:57,151
  3923. This procedure we're doing today,
  3924. 20 years ago was essentially impossible.
  3925.  
  3926. 827
  3927. 00:48:57,195 --> 00:49:00,328
  3928. We just didn't have the
  3929. materials and the technologies.
  3930.  
  3931. 828
  3932. 00:49:22,698 --> 00:49:26,485
  3933. So, the coil is barely
  3934. in there right now.
  3935.  
  3936. 829
  3937. 00:49:26,528 --> 00:49:29,923
  3938. It's just a feather
  3939. holding it in.
  3940.  
  3941. 830
  3942. 00:49:29,967 --> 00:49:32,012
  3943. It's nervous time.
  3944.  
  3945. 831
  3946. 00:49:36,190 --> 00:49:40,673
  3947. We're just in purgatory,
  3948. intellectual, humanistic purgatory,
  3949.  
  3950. 832
  3951. 00:49:40,716 --> 00:49:43,632
  3952. and AI might know
  3953. exactly what to do here.
  3954.  
  3955. 833
  3956. 00:49:50,639 --> 00:49:52,554
  3957. We've got the coil
  3958. into the aneurysm.
  3959.  
  3960. 834
  3961. 00:49:52,598 --> 00:49:54,556
  3962. But it wasn't in
  3963. tremendously well
  3964.  
  3965. 835
  3966. 00:49:54,600 --> 00:49:56,428
  3967. that I knew that it would stay,
  3968.  
  3969. 836
  3970. 00:49:56,471 --> 00:50:01,041
  3971. so with a maybe 20% risk
  3972. of a very bad situation,
  3973.  
  3974. 837
  3975. 00:50:01,085 --> 00:50:04,436
  3976. I elected
  3977. to just bring her back.
  3978.  
  3979. 838
  3980. 00:50:04,479 --> 00:50:05,959
  3981. Because of my relationship
  3982. with her
  3983.  
  3984. 839
  3985. 00:50:06,003 --> 00:50:08,222
  3986. and knowing the difficulties
  3987. of coming in
  3988.  
  3989. 840
  3990. 00:50:08,266 --> 00:50:11,051
  3991. and having the procedure,
  3992. I consider things,
  3993.  
  3994. 841
  3995. 00:50:11,095 --> 00:50:14,272
  3996. when I should only consider
  3997. the safest possible route
  3998.  
  3999. 842
  4000. 00:50:14,315 --> 00:50:16,361
  4001. to achieve success.
  4002.  
  4003. 843
  4004. 00:50:16,404 --> 00:50:19,755
  4005. But I had to stand there for
  4006. 10 minutes agonizing about it.
  4007.  
  4008. 844
  4009. 00:50:19,799 --> 00:50:21,757
  4010. The computer feels nothing.
  4011.  
  4012. 845
  4013. 00:50:21,801 --> 00:50:24,760
  4014. The computer just does
  4015. what it's supposed to do,
  4016.  
  4017. 846
  4018. 00:50:24,804 --> 00:50:26,284
  4019. better and better.
  4020.  
  4021. 847
  4022. 00:50:30,331 --> 00:50:32,551
  4023. I want to be AI in this case.
  4024.  
  4025. 848
  4026. 00:50:35,945 --> 00:50:38,861
  4027. But can AI be compassionate?
  4028.  
  4029. 849
  4030. 00:50:43,083 --> 00:50:47,827
  4031. I mean, it's everybody's
  4032. question about AI.
  4033.  
  4034. 850
  4035. 00:50:47,870 --> 00:50:51,961
  4036. We are the sole
  4037. embodiment of humanity,
  4038.  
  4039. 851
  4040. 00:50:52,005 --> 00:50:55,269
  4041. and it's a stretch for us
  4042. to accept that a machine
  4043.  
  4044. 852
  4045. 00:50:55,313 --> 00:50:58,794
  4046. can be compassionate
  4047. and loving in that way.
  4048.  
  4049. 853
  4050. 00:51:05,149 --> 00:51:07,281
  4051. Part of me doesn't believe in magic,
  4052.  
  4053. 854
  4054. 00:51:07,325 --> 00:51:09,805
  4055. but part of me has faith
  4056. that there is something
  4057.  
  4058. 855
  4059. 00:51:09,849 --> 00:51:11,546
  4060. beyond the sum of the parts,
  4061.  
  4062. 856
  4063. 00:51:11,590 --> 00:51:15,637
  4064. that there is at least a oneness
  4065. in our shared ancestry,
  4066.  
  4067. 857
  4068. 00:51:15,681 --> 00:51:19,738
  4069. our shared biology,
  4070. our shared history.
  4071.  
  4072. 858
  4073. 00:51:20,381 --> 00:51:23,210
  4074. Some connection there
  4075. beyond machine.
  4076.  
  4077. 859
  4078. 00:51:30,348 --> 00:51:32,567
  4079. So, then, you have
  4080. the other side of that, is,
  4081.  
  4082. 860
  4083. 00:51:32,611 --> 00:51:37,137
  4084. does the computer know it's conscious,
  4085. or can it be conscious, or does it care?
  4086.  
  4087. 861
  4088. 00:51:37,181 --> 00:51:40,009
  4089. Does it need to be conscious?
  4090.  
  4091. 862
  4092. 00:51:40,053 --> 00:51:42,011
  4093. Does it need to be aware?
  4094.  
  4095. 863
  4096. 00:51:52,892 --> 00:51:56,417
  4097. I do not think that a robot
  4098. could ever be conscious.
  4099.  
  4100. 864
  4101. 00:51:56,461 --> 00:51:58,376
  4102. Unless they programmed it that way.
  4103.  
  4104. 865
  4105. 00:51:58,419 --> 00:52:00,639
  4106. Conscious? No.
  4107.  
  4108. 866
  4109. 00:52:00,682 --> 00:52:03,163
  4110. No.
  4111.  
  4112. 867
  4113. 00:52:03,207 --> 00:52:06,035
  4114. I mean, think a robot could be
  4115. programmed to be conscious.
  4116.  
  4117. 868
  4118. 00:52:06,079 --> 00:52:09,648
  4119. How are they programmed
  4120. to do everything else?
  4121.  
  4122. 869
  4123. 00:52:09,691 --> 00:52:12,390
  4124. That's another big part
  4125. of artificial intelligence,
  4126.  
  4127. 870
  4128. 00:52:12,433 --> 00:52:15,741
  4129. is to make them conscious
  4130. and make them feel.
  4131.  
  4132. 871
  4133. 00:52:22,443 --> 00:52:27,709
  4134. Back in 2005, we started trying to
  4135. build machines with self-awareness.
  4136.  
  4137. 872
  4138. 00:52:33,106 --> 00:52:37,284
  4139. This robot, to begin with,
  4140. didn't know what it was.
  4141.  
  4142. 873
  4143. 00:52:37,328 --> 00:52:40,244
  4144. All it knew was that it needed
  4145. to do something like walk.
  4146.  
  4147. 874
  4148. 00:52:44,117 --> 00:52:45,597
  4149. Through trial and error,
  4150.  
  4151. 875
  4152. 00:52:45,640 --> 00:52:49,731
  4153. it figured out how to walk
  4154. using its imagination,
  4155.  
  4156. 876
  4157. 00:52:49,775 --> 00:52:54,040
  4158. and then it walked away.
  4159.  
  4160. 877
  4161. 00:52:54,083 --> 00:52:56,390
  4162. And then we did
  4163. something very cruel.
  4164.  
  4165. 878
  4166. 00:52:56,434 --> 00:52:58,653
  4167. We chopped off a leg
  4168. and watched what happened.
  4169.  
  4170. 879
  4171. 00:53:03,049 --> 00:53:07,749
  4172. At the beginning, it didn't
  4173. quite know what had happened.
  4174.  
  4175. 880
  4176. 00:53:07,793 --> 00:53:13,233
  4177. But over about a period
  4178. of a day, it then began to limp.
  4179.  
  4180. 881
  4181. 00:53:13,277 --> 00:53:16,845
  4182. And then, a year ago,
  4183. we were training an AI system
  4184.  
  4185. 882
  4186. 00:53:16,889 --> 00:53:20,240
  4187. for a live demonstration.
  4188.  
  4189. 883
  4190. 00:53:20,284 --> 00:53:24,113
  4191. We wanted to show how we wave
  4192. all these objects in front of the camera
  4193.  
  4194. 884
  4195. 00:53:24,157 --> 00:53:27,334
  4196. and the AI could
  4197. recognize the objects.
  4198.  
  4199. 885
  4200. 00:53:27,378 --> 00:53:29,031
  4201. And so, we're preparing
  4202. this demo,
  4203.  
  4204. 886
  4205. 00:53:29,075 --> 00:53:31,251
  4206. and we had on a side screen
  4207. this ability
  4208.  
  4209. 887
  4210. 00:53:31,295 --> 00:53:36,778
  4211. to watch what certain
  4212. neurons were responding to.
  4213.  
  4214. 888
  4215. 00:53:36,822 --> 00:53:41,087
  4216. And suddenly we noticed that one
  4217. of the neurons was tracking faces.
  4218.  
  4219. 889
  4220. 00:53:41,130 --> 00:53:45,483
  4221. It was tracking our faces
  4222. as we were moving around.
  4223.  
  4224. 890
  4225. 00:53:45,526 --> 00:53:48,616
  4226. Now, the spooky thing about this
  4227. is that we never trained
  4228.  
  4229. 891
  4230. 00:53:48,660 --> 00:53:52,490
  4231. the system
  4232. to recognize human faces,
  4233.  
  4234. 892
  4235. 00:53:52,533 --> 00:53:55,710
  4236. and yet, somehow,
  4237. it learned to do that.
  4238.  
  4239. 893
  4240. 00:53:57,973 --> 00:53:59,784
  4241. Even though these robots
  4242. are very simple,
  4243.  
  4244. 894
  4245. 00:53:59,785 --> 00:54:02,658
  4246. we can see there's
  4247. something else going on there.
  4248.  
  4249. 895
  4250. 00:54:02,659 --> 00:54:05,867
  4251. It's not just programming.
  4252.  
  4253. 896
  4254. 00:54:05,894 --> 00:54:08,462
  4255. So, this is just the beginning.
  4256.  
  4257. 897
  4258. 00:54:10,377 --> 00:54:14,294
  4259. I often think about
  4260. that beach in Kitty Hawk.
  4261.  
  4262. 898
  4263. 00:54:14,338 --> 00:54:18,255
  4264. The 1903 flight
  4265. by Orville and Wilbur Wright.
  4266.  
  4267. 899
  4268. 00:54:21,214 --> 00:54:24,289
  4269. It was kind of a canvas plane,
  4270. and it's wood and iron,
  4271.  
  4272. 900
  4273. 00:54:24,291 --> 00:54:26,928
  4274. and it gets off the ground for,
  4275. what, a minute and 20 seconds,
  4276.  
  4277. 901
  4278. 00:54:26,929 --> 00:54:31,006
  4279. on this windy day
  4280. before touching back down again.
  4281.  
  4282. 902
  4283. 00:54:33,270 --> 00:54:37,143
  4284. And it was
  4285. just around 65 summers or so
  4286.  
  4287. 903
  4288. 00:54:37,186 --> 00:54:43,149
  4289. after that moment that you have
  4290. a 747 taking off from JFK...
  4291.  
  4292. 904
  4293. 00:54:50,099 --> 00:54:52,184
  4294. ...where a major concern
  4295. of someone on the airplane
  4296.  
  4297. 905
  4298. 00:54:52,185 --> 00:54:55,380
  4299. might be whether or not
  4300. their salt-free diet meal
  4301.  
  4302. 906
  4303. 00:54:55,381 --> 00:54:56,917
  4304. is gonna be coming to them or not.
  4305.  
  4306. 907
  4307. 00:54:56,945 --> 00:55:01,385
  4308. We have a whole infrastructure,
  4309. with travel agents and tower control,
  4310.  
  4311. 908
  4312. 00:55:01,428 --> 00:55:03,778
  4313. and it's all casual,
  4314. and it's all part of the world.
  4315.  
  4316. 909
  4317. 00:55:07,086 --> 00:55:09,523
  4318. Right now, as far
  4319. as we've come with machines
  4320.  
  4321. 910
  4322. 00:55:09,567 --> 00:55:12,134
  4323. that think and solve problems,
  4324. we're at Kitty Hawk now.
  4325.  
  4326. 911
  4327. 00:55:12,178 --> 00:55:13,745
  4328. We're in the wind.
  4329.  
  4330. 912
  4331. 00:55:13,788 --> 00:55:17,052
  4332. We have our tattered-canvas
  4333. planes up in the air.
  4334.  
  4335. 913
  4336. 00:55:20,926 --> 00:55:23,885
  4337. But what happens
  4338. in 65 summers or so?
  4339.  
  4340. 914
  4341. 00:55:23,929 --> 00:55:27,889
  4342. We will have machines
  4343. that are beyond human control.
  4344.  
  4345. 915
  4346. 00:55:27,933 --> 00:55:30,457
  4347. Should we worry about that?
  4348.  
  4349. 916
  4350. 00:55:32,633 --> 00:55:34,853
  4351. I'm not sure it's going to help.
  4352.  
  4353. 917
  4354. 00:55:40,337 --> 00:55:44,036
  4355. Nobody has any idea today
  4356. what it means for a robot
  4357.  
  4358. 918
  4359. 00:55:44,079 --> 00:55:46,430
  4360. to be conscious.
  4361.  
  4362. 919
  4363. 00:55:46,473 --> 00:55:48,649
  4364. There is no such thing.
  4365.  
  4366. 920
  4367. 00:55:48,693 --> 00:55:50,172
  4368. There are a lot of smart people,
  4369.  
  4370. 921
  4371. 00:55:50,216 --> 00:55:53,088
  4372. and I have a great deal
  4373. of respect for them,
  4374.  
  4375. 922
  4376. 00:55:53,132 --> 00:55:57,528
  4377. but the truth is,
  4378. machines are natural psychopaths.
  4379.  
  4380. 923
  4381. 00:55:57,571 --> 00:55:59,225
  4382. Fear came back into the market.
  4383.  
  4384. 924
  4385. 00:55:59,268 --> 00:56:01,706
  4386. Went down 800,
  4387. nearly 1,000, in a heartbeat.
  4388.  
  4389. 925
  4390. 00:56:01,749 --> 00:56:03,360
  4391. I mean,
  4392. it is classic capitulation.
  4393.  
  4394. 926
  4395. 00:56:03,403 --> 00:56:07,146
  4396. There are some people who are proposing
  4397. it was some kind of fat-finger error.
  4398.  
  4399. 927
  4400. 00:56:07,189 --> 00:56:09,583
  4401. Take the Flash Crash of 2010.
  4402.  
  4403. 928
  4404. 00:56:09,627 --> 00:56:13,413
  4405. In a matter of minutes,
  4406. $1 trillion in value
  4407.  
  4408. 929
  4409. 00:56:13,457 --> 00:56:15,415
  4410. was lost in the stock market.
  4411.  
  4412. 930
  4413. 00:56:15,459 --> 00:56:18,984
  4414. The Dow dropped nearly
  4415. 1,000 points in a half-hour.
  4416.  
  4417. 931
  4418. 00:56:19,027 --> 00:56:22,553
  4419. So, what went wrong?
  4420.  
  4421. 932
  4422. 00:56:22,596 --> 00:56:26,644
  4423. By that point in time,
  4424. more than 60% of all the trades
  4425.  
  4426. 933
  4427. 00:56:26,687 --> 00:56:29,124
  4428. that took place
  4429. on the stock exchange
  4430.  
  4431. 934
  4432. 00:56:29,168 --> 00:56:32,693
  4433. were actually being
  4434. initiated by computers.
  4435.  
  4436. 935
  4437. 00:56:32,737 --> 00:56:35,783
  4438. Panic selling on the way down, and all
  4439. of a sudden it stopped on a dime.
  4440.  
  4441. 936
  4442. 00:56:35,827 --> 00:56:37,611
  4443. This is all happening
  4444. in real time, folks.
  4445.  
  4446. 937
  4447. 00:56:37,612 --> 00:56:39,883
  4448. The short story of what
  4449. happened in the Flash Crash
  4450.  
  4451. 938
  4452. 00:56:39,884 --> 00:56:42,513
  4453. is that algorithms
  4454. responded to algorithms,
  4455.  
  4456. 939
  4457. 00:56:42,514 --> 00:56:45,430
  4458. and it compounded upon itself
  4459. over and over and over again
  4460.  
  4461. 940
  4462. 00:56:45,431 --> 00:56:47,041
  4463. in a matter of minutes.
  4464.  
  4465. 941
  4466. 00:56:47,055 --> 00:56:50,972
  4467. At one point, the market
  4468. fell as if down a well.
  4469.  
  4470. 942
  4471. 00:56:51,016 --> 00:56:54,323
  4472. There is no regulatory body
  4473. that can adapt quickly enough
  4474.  
  4475. 943
  4476. 00:56:54,367 --> 00:56:57,979
  4477. to prevent potentially
  4478. disastrous consequences
  4479.  
  4480. 944
  4481. 00:56:58,023 --> 00:57:01,243
  4482. of AI operating
  4483. in our financial systems.
  4484.  
  4485. 945
  4486. 00:57:01,287 --> 00:57:03,898
  4487. They are so prime
  4488. for manipulation.
  4489.  
  4490. 946
  4491. 00:57:03,942 --> 00:57:05,639
  4492. Let's talk about the speed
  4493. with which
  4494.  
  4495. 947
  4496. 00:57:05,683 --> 00:57:08,076
  4497. we are watching
  4498. this market deteriorate.
  4499.  
  4500. 948
  4501. 00:57:08,120 --> 00:57:11,602
  4502. That's the type of AI-run-amuck
  4503. that scares people.
  4504.  
  4505. 949
  4506. 00:57:11,645 --> 00:57:13,560
  4507. When you give them a goal,
  4508.  
  4509. 950
  4510. 00:57:13,604 --> 00:57:17,225
  4511. they will relentlessly
  4512. pursue that goal.
  4513.  
  4514. 951
  4515. 00:57:17,869 --> 00:57:20,393
  4516. How many computer programs
  4517. are there like this?
  4518.  
  4519. 952
  4520. 00:57:20,437 --> 00:57:22,683
  4521. Nobody knows.
  4522.  
  4523. 953
  4524. 00:57:23,527 --> 00:57:27,444
  4525. One of the fascinating aspects
  4526. about AI in general
  4527.  
  4528. 954
  4529. 00:57:27,487 --> 00:57:31,970
  4530. is that no one really
  4531. understands how it works.
  4532.  
  4533. 955
  4534. 00:57:32,013 --> 00:57:36,975
  4535. Even the people who create AI
  4536. don't really fully understand.
  4537.  
  4538. 956
  4539. 00:57:37,018 --> 00:57:41,675
  4540. Because it has millions of elements,
  4541. it becomes completely impossible
  4542.  
  4543. 957
  4544. 00:57:41,719 --> 00:57:45,113
  4545. for a human being
  4546. to understand what's going on.
  4547.  
  4548. 958
  4549. 00:57:52,556 --> 00:57:56,037
  4550. Microsoft had set up
  4551. this artificial intelligence
  4552.  
  4553. 959
  4554. 00:57:56,081 --> 00:57:59,127
  4555. called Tay on Twitter,
  4556. which was a chatbot.
  4557.  
  4558. 960
  4559. 00:58:00,912 --> 00:58:02,696
  4560. They started out in the morning,
  4561.  
  4562. 961
  4563. 00:58:02,740 --> 00:58:06,526
  4564. and Tay was starting to tweet
  4565. and learning from stuff
  4566.  
  4567. 962
  4568. 00:58:06,570 --> 00:58:10,835
  4569. that was being sent to him
  4570. from other Twitter people.
  4571.  
  4572. 963
  4573. 00:58:10,878 --> 00:58:13,272
  4574. Because some people,
  4575. like trolls, attacked him,
  4576.  
  4577. 964
  4578. 00:58:13,315 --> 00:58:18,582
  4579. within 24 hours, the Microsoft bot
  4580. became a terrible person.
  4581.  
  4582. 965
  4583. 00:58:18,625 --> 00:58:21,367
  4584. They had to literally
  4585. pull Tay off the Net
  4586.  
  4587. 966
  4588. 00:58:21,410 --> 00:58:24,718
  4589. because he had turned
  4590. into a monster.
  4591.  
  4592. 967
  4593. 00:58:24,762 --> 00:58:30,550
  4594. A misanthropic, racist, horrible person
  4595. you'd never want to meet.
  4596.  
  4597. 968
  4598. 00:58:30,594 --> 00:58:32,857
  4599. And nobody had foreseen this.
  4600.  
  4601. 969
  4602. 00:58:35,337 --> 00:58:38,602
  4603. The whole idea of AI is that
  4604. we are not telling it exactly
  4605.  
  4606. 970
  4607. 00:58:38,645 --> 00:58:42,780
  4608. how to achieve a given
  4609. outcome or a goal.
  4610.  
  4611. 971
  4612. 00:58:42,823 --> 00:58:46,435
  4613. AI develops on its own.
  4614.  
  4615. 972
  4616. 00:58:46,479 --> 00:58:48,829
  4617. We're worried about
  4618. superintelligent AI,
  4619.  
  4620. 973
  4621. 00:58:48,873 --> 00:58:52,790
  4622. the master chess player
  4623. that will outmaneuver us,
  4624.  
  4625. 974
  4626. 00:58:52,833 --> 00:58:55,923
  4627. but AI won't have to
  4628. actually be that smart
  4629.  
  4630. 975
  4631. 00:58:55,967 --> 00:59:00,145
  4632. to have massively disruptive
  4633. effects on human civilization.
  4634.  
  4635. 976
  4636. 00:59:00,188 --> 00:59:01,886
  4637. We've seen over the last century
  4638.  
  4639. 977
  4640. 00:59:01,929 --> 00:59:05,150
  4641. it doesn't necessarily take
  4642. a genius to knock history off
  4643.  
  4644. 978
  4645. 00:59:05,193 --> 00:59:06,804
  4646. in a particular direction,
  4647.  
  4648. 979
  4649. 00:59:06,847 --> 00:59:09,589
  4650. and it won't take a genius AI
  4651. to do the same thing.
  4652.  
  4653. 980
  4654. 00:59:09,633 --> 00:59:13,158
  4655. Bogus election news stories
  4656. generated more engagement
  4657.  
  4658. 981
  4659. 00:59:13,201 --> 00:59:17,075
  4660. on Facebook
  4661. than top real stories.
  4662.  
  4663. 982
  4664. 00:59:17,118 --> 00:59:21,079
  4665. Facebook really is
  4666. the elephant in the room.
  4667.  
  4668. 983
  4669. 00:59:21,122 --> 00:59:23,777
  4670. AI running Facebook news feed --
  4671.  
  4672. 984
  4673. 00:59:23,821 --> 00:59:28,347
  4674. The task for AI
  4675. is keeping users engaged,
  4676.  
  4677. 985
  4678. 00:59:28,390 --> 00:59:29,827
  4679. but no one really understands
  4680.  
  4681. 986
  4682. 00:59:29,870 --> 00:59:34,832
  4683. exactly how this AI
  4684. is achieving this goal.
  4685.  
  4686. 987
  4687. 00:59:34,875 --> 00:59:38,792
  4688. Facebook is building an
  4689. elegant mirrored wall around us.
  4690.  
  4691. 988
  4692. 00:59:38,836 --> 00:59:41,665
  4693. A mirror that we can ask,
  4694. "Who's the fairest of them all?"
  4695.  
  4696. 989
  4697. 00:59:41,708 --> 00:59:45,016
  4698. and it will answer, "You, you,"
  4699. time and again
  4700.  
  4701. 990
  4702. 00:59:45,059 --> 00:59:48,193
  4703. and slowly begin
  4704. to warp our sense of reality,
  4705.  
  4706. 991
  4707. 00:59:48,236 --> 00:59:53,502
  4708. warp our sense of politics,
  4709. history, global events,
  4710.  
  4711. 992
  4712. 00:59:53,546 --> 00:59:57,028
  4713. until determining what's true
  4714. and what's not true,
  4715.  
  4716. 993
  4717. 00:59:57,071 --> 00:59:58,943
  4718. is virtually impossible.
  4719.  
  4720. 994
  4721. 01:00:01,032 --> 01:00:03,861
  4722. The problem is that AI
  4723. doesn't understand that.
  4724.  
  4725. 995
  4726. 01:00:03,904 --> 01:00:08,039
  4727. AI just had a mission --
  4728. maximize user engagement,
  4729.  
  4730. 996
  4731. 01:00:08,082 --> 01:00:10,041
  4732. and it achieved that.
  4733.  
  4734. 997
  4735. 01:00:10,084 --> 01:00:13,653
  4736. Nearly 2 billion people
  4737. spend nearly one hour
  4738.  
  4739. 998
  4740. 01:00:13,697 --> 01:00:17,831
  4741. on average a day
  4742. basically interacting with AI
  4743.  
  4744. 999
  4745. 01:00:17,875 --> 01:00:21,530
  4746. that is shaping
  4747. their experience.
  4748.  
  4749. 1000
  4750. 01:00:21,574 --> 01:00:24,664
  4751. Even Facebook engineers,
  4752. they don't like fake news.
  4753.  
  4754. 1001
  4755. 01:00:24,708 --> 01:00:28,015
  4756. It's very bad business.
  4757. They want to get rid of fake news.
  4758.  
  4759. 1002
  4760. 01:00:28,059 --> 01:00:32,324
  4761. It's just very difficult to do because,
  4762. how do you recognize news as fake
  4763.  
  4764. 1003
  4765. 01:00:32,367 --> 01:00:34,456
  4766. if you cannot read
  4767. all of those news personally?
  4768.  
  4769. 1004
  4770. 01:00:34,500 --> 01:00:39,418
  4771. There's so much
  4772. active misinformation
  4773.  
  4774. 1005
  4775. 01:00:39,461 --> 01:00:41,115
  4776. and it's packaged very well,
  4777.  
  4778. 1006
  4779. 01:00:41,159 --> 01:00:44,553
  4780. and it looks the same when
  4781. you see it on a Facebook page
  4782.  
  4783. 1007
  4784. 01:00:44,597 --> 01:00:47,426
  4785. or you turn on your television.
  4786.  
  4787. 1008
  4788. 01:00:47,469 --> 01:00:51,691
  4789. It's not terribly sophisticated,
  4790. but it is terribly powerful.
  4791.  
  4792. 1009
  4793. 01:00:51,735 --> 01:00:54,346
  4794. And what it means is
  4795. that your view of the world,
  4796.  
  4797. 1010
  4798. 01:00:54,389 --> 01:00:56,435
  4799. which, 20 years ago,
  4800. was determined,
  4801.  
  4802. 1011
  4803. 01:00:56,478 --> 01:01:00,004
  4804. if you watched the nightly news,
  4805. by three different networks,
  4806.  
  4807. 1012
  4808. 01:01:00,047 --> 01:01:02,528
  4809. the three anchors who endeavored
  4810. to try to get it right.
  4811.  
  4812. 1013
  4813. 01:01:02,529 --> 01:01:04,583
  4814. Might have had a little bias
  4815. one way or the other,
  4816.  
  4817. 1014
  4818. 01:01:04,584 --> 01:01:08,273
  4819. but, largely speaking, we could all
  4820. agree on an objective reality.
  4821.  
  4822. 1015
  4823. 01:01:08,316 --> 01:01:10,754
  4824. Well, that objectivity is gone,
  4825.  
  4826. 1016
  4827. 01:01:10,797 --> 01:01:13,757
  4828. and Facebook has
  4829. completely annihilated it.
  4830.  
  4831. 1017
  4832. 01:01:17,108 --> 01:01:20,807
  4833. If most of your understanding of how
  4834. the world works is derived from Facebook,
  4835.  
  4836. 1018
  4837. 01:01:20,851 --> 01:01:23,418
  4838. facilitated by algorithmic software
  4839.  
  4840. 1019
  4841. 01:01:23,462 --> 01:01:27,118
  4842. that tries to show you
  4843. the news you want to see,
  4844.  
  4845. 1020
  4846. 01:01:27,161 --> 01:01:28,815
  4847. that's a terribly
  4848. dangerous thing.
  4849.  
  4850. 1021
  4851. 01:01:28,859 --> 01:01:33,080
  4852. And the idea that we have not
  4853. only set that in motion,
  4854.  
  4855. 1022
  4856. 01:01:33,124 --> 01:01:37,258
  4857. but allowed bad-faith actors
  4858. access to that information...
  4859.  
  4860. 1023
  4861. 01:01:37,302 --> 01:01:39,565
  4862. I mean, this is a recipe
  4863. for disaster.
  4864.  
  4865. 1024
  4866. 01:01:43,177 --> 01:01:45,876
  4867. I think that there will definitely
  4868. be lots of bad actors
  4869.  
  4870. 1025
  4871. 01:01:45,919 --> 01:01:48,922
  4872. trying to manipulate the world with AI.
  4873.  
  4874. 1026
  4875. 01:01:48,966 --> 01:01:52,143
  4876. 2016 was a perfect example
  4877. of an election
  4878.  
  4879. 1027
  4880. 01:01:52,186 --> 01:01:55,015
  4881. where there was lots of AI
  4882. producing lots of fake news
  4883.  
  4884. 1028
  4885. 01:01:55,059 --> 01:01:58,323
  4886. and distributing it
  4887. for a purpose, for a result.
  4888.  
  4889. 1029
  4890. 01:01:59,890 --> 01:02:02,283
  4891. Ladies and gentlemen,
  4892. honorable colleagues...
  4893.  
  4894. 1030
  4895. 01:02:02,327 --> 01:02:04,546
  4896. it's my privilege
  4897. to speak to you today
  4898.  
  4899. 1031
  4900. 01:02:04,590 --> 01:02:07,985
  4901. about the power of big data
  4902. and psychographics
  4903.  
  4904. 1032
  4905. 01:02:08,028 --> 01:02:09,682
  4906. in the electoral process
  4907.  
  4908. 1033
  4909. 01:02:09,726 --> 01:02:12,206
  4910. and, specifically,
  4911. to talk about the work
  4912.  
  4913. 1034
  4914. 01:02:12,250 --> 01:02:14,513
  4915. that we contributed
  4916. to Senator Cruz's
  4917.  
  4918. 1035
  4919. 01:02:14,556 --> 01:02:16,558
  4920. presidential primary campaign.
  4921.  
  4922. 1036
  4923. 01:02:16,602 --> 01:02:19,910
  4924. Cambridge Analytica
  4925. emerged quietly as a company
  4926.  
  4927. 1037
  4928. 01:02:19,953 --> 01:02:21,563
  4929. that, according to its own hype,
  4930.  
  4931. 1038
  4932. 01:02:21,607 --> 01:02:26,307
  4933. has the ability to use
  4934. this tremendous amount of data
  4935.  
  4936. 1039
  4937. 01:02:26,351 --> 01:02:30,137
  4938. in order
  4939. to effect societal change.
  4940.  
  4941. 1040
  4942. 01:02:30,181 --> 01:02:33,358
  4943. In 2016, they had
  4944. three major clients.
  4945.  
  4946. 1041
  4947. 01:02:33,401 --> 01:02:34,794
  4948. Ted Cruz was one of them.
  4949.  
  4950. 1042
  4951. 01:02:34,838 --> 01:02:37,884
  4952. It's easy to forget that,
  4953. only 18 months ago,
  4954.  
  4955. 1043
  4956. 01:02:37,928 --> 01:02:42,846
  4957. Senator Cruz was one of the less
  4958. popular candidates seeking nomination.
  4959.  
  4960. 1044
  4961. 01:02:42,889 --> 01:02:47,241
  4962. So, what was not possible maybe,
  4963. like, 10 or 15 years ago,
  4964.  
  4965. 1045
  4966. 01:02:47,285 --> 01:02:49,374
  4967. was that you can send fake news
  4968.  
  4969. 1046
  4970. 01:02:49,417 --> 01:02:52,420
  4971. to exactly the people
  4972. that you want to send it to.
  4973.  
  4974. 1047
  4975. 01:02:52,464 --> 01:02:56,685
  4976. And then you could actually see
  4977. how he or she reacts on Facebook
  4978.  
  4979. 1048
  4980. 01:02:56,729 --> 01:02:58,905
  4981. and then adjust that information
  4982.  
  4983. 1049
  4984. 01:02:58,949 --> 01:03:01,778
  4985. according to the feedback
  4986. that you got.
  4987.  
  4988. 1050
  4989. 01:03:01,821 --> 01:03:03,257
  4990. So you can start developing
  4991.  
  4992. 1051
  4993. 01:03:03,301 --> 01:03:06,130
  4994. kind of a real-time management
  4995. of a population.
  4996.  
  4997. 1052
  4998. 01:03:06,173 --> 01:03:10,699
  4999. In this case, we've zoned in on
  5000. a group we've called "Persuasion."
  5001.  
  5002. 1053
  5003. 01:03:10,743 --> 01:03:13,746
  5004. These are people who are
  5005. definitely going to vote,
  5006.  
  5007. 1054
  5008. 01:03:13,790 --> 01:03:16,705
  5009. to caucus, but they need
  5010. moving from the center
  5011.  
  5012. 1055
  5013. 01:03:16,749 --> 01:03:18,490
  5014. a little bit more
  5015. towards the right.
  5016.  
  5017. 1056
  5018. 01:03:18,533 --> 01:03:19,708
  5019. in order to support Cruz.
  5020.  
  5021. 1057
  5022. 01:03:19,752 --> 01:03:22,059
  5023. They need a persuasion message.
  5024.  
  5025. 1058
  5026. 01:03:22,102 --> 01:03:23,800
  5027. "Gun rights," I've selected.
  5028.  
  5029. 1059
  5030. 01:03:23,843 --> 01:03:25,802
  5031. That narrows the field
  5032. slightly more.
  5033.  
  5034. 1060
  5035. 01:03:25,845 --> 01:03:29,066
  5036. And now we know that we need
  5037. a message on gun rights,
  5038.  
  5039. 1061
  5040. 01:03:29,109 --> 01:03:31,111
  5041. it needs to be
  5042. a persuasion message,
  5043.  
  5044. 1062
  5045. 01:03:31,155 --> 01:03:34,201
  5046. and it needs to be nuanced
  5047. according to the certain personality
  5048.  
  5049. 1063
  5050. 01:03:34,245 --> 01:03:36,029
  5051. that we're interested in.
  5052.  
  5053. 1064
  5054. 01:03:36,073 --> 01:03:39,946
  5055. Through social media, there's an
  5056. infinite amount of information
  5057.  
  5058. 1065
  5059. 01:03:39,990 --> 01:03:42,514
  5060. that you can gather
  5061. about a person.
  5062.  
  5063. 1066
  5064. 01:03:42,557 --> 01:03:45,734
  5065. We have somewhere close
  5066. to 4,000 or 5,000 data points
  5067.  
  5068. 1067
  5069. 01:03:45,778 --> 01:03:48,563
  5070. on every adult
  5071. in the United States.
  5072.  
  5073. 1068
  5074. 01:03:48,607 --> 01:03:51,915
  5075. It's about targeting
  5076. the individual.
  5077.  
  5078. 1069
  5079. 01:03:51,958 --> 01:03:55,962
  5080. It's like a weapon, which can be used
  5081. in the totally wrong direction.
  5082.  
  5083. 1070
  5084. 01:03:56,006 --> 01:03:58,051
  5085. That's the problem
  5086. with all of this data.
  5087.  
  5088. 1071
  5089. 01:03:58,095 --> 01:04:02,229
  5090. It's almost as if we built the bullet
  5091. before we built the gun.
  5092.  
  5093. 1072
  5094. 01:04:02,273 --> 01:04:06,407
  5095. Ted Cruz employed our data,
  5096. our behavioral insights.
  5097.  
  5098. 1073
  5099. 01:04:06,451 --> 01:04:09,541
  5100. He started from a base
  5101. of less than 5%
  5102.  
  5103. 1074
  5104. 01:04:09,584 --> 01:04:15,590
  5105. and had a very slow-and-steady-
  5106. but-firm rise to above 35%,
  5107.  
  5108. 1075
  5109. 01:04:15,634 --> 01:04:17,157
  5110. making him, obviously,
  5111.  
  5112. 1076
  5113. 01:04:17,201 --> 01:04:20,465
  5114. the second most threatening
  5115. contender in the race.
  5116.  
  5117. 1077
  5118. 01:04:20,508 --> 01:04:23,120
  5119. Now, clearly, the Cruz campaign
  5120. is over now,
  5121.  
  5122. 1078
  5123. 01:04:23,163 --> 01:04:28,168
  5124. but what I can tell you is that of the
  5125. two candidates left in this election,
  5126.  
  5127. 1079
  5128. 01:04:28,212 --> 01:04:30,867
  5129. one of them is using
  5130. these technologies.
  5131.  
  5132. 1080
  5133. 01:04:32,564 --> 01:04:35,959
  5134. I, Donald John Trump,
  5135. do solemnly swear
  5136.  
  5137. 1081
  5138. 01:04:36,002 --> 01:04:38,222
  5139. that I will faithfully execute
  5140.  
  5141. 1082
  5142. 01:04:38,265 --> 01:04:42,226
  5143. the office of President
  5144. of the United States.
  5145.  
  5146. 1083
  5147. 01:04:48,275 --> 01:04:50,234
  5148. Elections are
  5149. a marginal exercise.
  5150.  
  5151. 1084
  5152. 01:04:50,277 --> 01:04:53,237
  5153. It doesn't take
  5154. a very sophisticated AI
  5155.  
  5156. 1085
  5157. 01:04:53,280 --> 01:04:57,719
  5158. in order to have
  5159. a disproportionate impact.
  5160.  
  5161. 1086
  5162. 01:04:57,763 --> 01:05:02,550
  5163. Before Trump, Brexit was
  5164. another supposed client.
  5165.  
  5166. 1087
  5167. 01:05:02,594 --> 01:05:04,726
  5168. Well, at 20 minutes to 5:00,
  5169.  
  5170. 1088
  5171. 01:05:04,770 --> 01:05:08,730
  5172. we can now say
  5173. the decision taken in 1975
  5174.  
  5175. 1089
  5176. 01:05:08,774 --> 01:05:10,950
  5177. by this country to join
  5178. the common market
  5179.  
  5180. 1090
  5181. 01:05:10,994 --> 01:05:15,999
  5182. has been reversed by
  5183. this referendum to leave the EU.
  5184.  
  5185. 1091
  5186. 01:05:16,042 --> 01:05:19,828
  5187. Cambridge Analytica
  5188. allegedly uses AI
  5189.  
  5190. 1092
  5191. 01:05:19,872 --> 01:05:23,267
  5192. to push through two of
  5193. the most ground-shaking pieces
  5194.  
  5195. 1093
  5196. 01:05:23,310 --> 01:05:27,967
  5197. of political change
  5198. in the last 50 years.
  5199.  
  5200. 1094
  5201. 01:05:28,011 --> 01:05:30,709
  5202. These are epochal events,
  5203. and if we believe the hype,
  5204.  
  5205. 1095
  5206. 01:05:30,752 --> 01:05:33,755
  5207. they are connected directly
  5208. to a piece of software,
  5209.  
  5210. 1096
  5211. 01:05:33,799 --> 01:05:37,194
  5212. essentially, created
  5213. by a professor at Stanford.
  5214.  
  5215. 1097
  5216. 01:05:41,459 --> 01:05:45,593
  5217. Back in 2013, I described that
  5218. what they are doing is possible
  5219.  
  5220. 1098
  5221. 01:05:45,637 --> 01:05:49,293
  5222. and warned against this
  5223. happening in the future.
  5224.  
  5225. 1099
  5226. 01:05:49,336 --> 01:05:51,382
  5227. At the time, Michal Kosinski
  5228.  
  5229. 1100
  5230. 01:05:51,425 --> 01:05:54,994
  5231. was a young Polish researcher
  5232. working at the Psychometrics Centre.
  5233.  
  5234. 1101
  5235. 01:05:55,038 --> 01:06:00,217
  5236. So, what Michal had done was to
  5237. gather the largest-ever data set
  5238.  
  5239. 1102
  5240. 01:06:00,260 --> 01:06:03,481
  5241. of how people
  5242. behave on Facebook.
  5243.  
  5244. 1103
  5245. 01:06:03,524 --> 01:06:07,789
  5246. Psychometrics is trying
  5247. to measure psychological traits,
  5248.  
  5249. 1104
  5250. 01:06:07,833 --> 01:06:09,922
  5251. such as personality,
  5252. intelligence,
  5253.  
  5254. 1105
  5255. 01:06:09,966 --> 01:06:11,880
  5256. political views, and so on.
  5257.  
  5258. 1106
  5259. 01:06:11,924 --> 01:06:15,058
  5260. Now, traditionally,
  5261. those traits were measured
  5262.  
  5263. 1107
  5264. 01:06:15,101 --> 01:06:17,712
  5265. using tests and questions.
  5266.  
  5267. 1108
  5268. 01:06:17,756 --> 01:06:20,715
  5269. Personality test, the most benign thing
  5270. you could possibly think of.
  5271.  
  5272. 1109
  5273. 01:06:20,759 --> 01:06:24,197
  5274. Something that doesn't necessarily
  5275. have a lot of utility, right?
  5276.  
  5277. 1110
  5278. 01:06:24,241 --> 01:06:27,331
  5279. Our idea was that
  5280. instead of tests and questions,
  5281.  
  5282. 1111
  5283. 01:06:27,374 --> 01:06:30,029
  5284. we could simply look at the
  5285. digital footprints of behaviors
  5286.  
  5287. 1112
  5288. 01:06:30,073 --> 01:06:32,553
  5289. that we are all leaving behind
  5290.  
  5291. 1113
  5292. 01:06:32,597 --> 01:06:34,903
  5293. to understand openness,
  5294.  
  5295. 1114
  5296. 01:06:34,947 --> 01:06:37,732
  5297. conscientiousness,
  5298. neuroticism.
  5299.  
  5300. 1115
  5301. 01:06:37,776 --> 01:06:39,560
  5302. You can easily buy
  5303. personal data,
  5304.  
  5305. 1116
  5306. 01:06:39,604 --> 01:06:43,129
  5307. such as where you live,
  5308. what club memberships you've tried,
  5309.  
  5310. 1117
  5311. 01:06:43,173 --> 01:06:45,044
  5312. which gym you go to.
  5313.  
  5314. 1118
  5315. 01:06:45,088 --> 01:06:47,873
  5316. There are actually marketplaces
  5317. for personal data.
  5318.  
  5319. 1119
  5320. 01:06:47,916 --> 01:06:51,442
  5321. It turns out, we can discover
  5322. an awful lot about what you're gonna do
  5323.  
  5324. 1120
  5325. 01:06:51,485 --> 01:06:55,750
  5326. based on a very, very tiny
  5327. set of information.
  5328.  
  5329. 1121
  5330. 01:06:55,794 --> 01:06:58,275
  5331. We are training
  5332. deep-learning networks
  5333.  
  5334. 1122
  5335. 01:06:58,318 --> 01:07:01,278
  5336. to infer intimate traits,
  5337.  
  5338. 1123
  5339. 01:07:01,321 --> 01:07:04,759
  5340. people's political views,
  5341. personality,
  5342.  
  5343. 1124
  5344. 01:07:04,803 --> 01:07:07,806
  5345. intelligence,
  5346. sexual orientation
  5347.  
  5348. 1125
  5349. 01:07:07,849 --> 01:07:10,504
  5350. just from an image
  5351. from someone's face.
  5352.  
  5353. 1126
  5354. 01:07:17,076 --> 01:07:20,645
  5355. Now think about countries which
  5356. are not so free and open-minded.
  5357.  
  5358. 1127
  5359. 01:07:20,688 --> 01:07:23,300
  5360. If you can reveal people's
  5361. religious views
  5362.  
  5363. 1128
  5364. 01:07:23,343 --> 01:07:25,954
  5365. or political views
  5366. or sexual orientation
  5367.  
  5368. 1129
  5369. 01:07:25,998 --> 01:07:28,740
  5370. based on only profile pictures,
  5371.  
  5372. 1130
  5373. 01:07:28,783 --> 01:07:33,310
  5374. this could be literally
  5375. an issue of life and death.
  5376.  
  5377. 1131
  5378. 01:07:37,009 --> 01:07:39,751
  5379. I think there's no going back.
  5380.  
  5381. 1132
  5382. 01:07:42,145 --> 01:07:44,321
  5383. Do you know what
  5384. the Turing test is?
  5385.  
  5386. 1133
  5387. 01:07:44,364 --> 01:07:48,977
  5388. It's when a human interacts
  5389. with a computer,
  5390.  
  5391. 1134
  5392. 01:07:49,021 --> 01:07:52,546
  5393. and if the human doesn't know they're
  5394. interacting with a computer,
  5395.  
  5396. 1135
  5397. 01:07:52,590 --> 01:07:54,126
  5398. the test is passed.
  5399.  
  5400. 1136
  5401. 01:07:54,170 --> 01:07:57,247
  5402. And over the next few days,
  5403.  
  5404. 1137
  5405. 01:07:57,290 --> 01:07:59,684
  5406. you're gonna be the human
  5407. component in a Turing test.
  5408.  
  5409. 1138
  5410. 01:07:59,727 --> 01:08:02,295
  5411. Holy shit.
  5412. - That's right, Caleb.
  5413.  
  5414. 1139
  5415. 01:08:02,339 --> 01:08:04,080
  5416. You got it.
  5417.  
  5418. 1140
  5419. 01:08:04,123 --> 01:08:06,865
  5420. 'Cause if that test is passed,
  5421.  
  5422. 1141
  5423. 01:08:06,908 --> 01:08:10,825
  5424. you are dead center
  5425. of the greatest scientific event
  5426.  
  5427. 1142
  5428. 01:08:10,869 --> 01:08:12,958
  5429. in the history of man.
  5430.  
  5431. 1143
  5432. 01:08:13,001 --> 01:08:17,615
  5433. If you've created a conscious machine,
  5434. it's not the history of man.
  5435.  
  5436. 1144
  5437. 01:08:17,658 --> 01:08:19,356
  5438. That's the history of gods.
  5439.  
  5440. 1145
  5441. 01:08:26,841 --> 01:08:29,975
  5442. It's almost like technology
  5443. is a god in and of itself.
  5444.  
  5445. 1146
  5446. 01:08:33,196 --> 01:08:35,241
  5447. Like the weather.
  5448. We can't impact it.
  5449.  
  5450. 1147
  5451. 01:08:35,285 --> 01:08:39,293
  5452. We can't slow it down.
  5453. We can't stop it.
  5454.  
  5455. 1148
  5456. 01:08:39,637 --> 01:08:42,849
  5457. We feel powerless.
  5458.  
  5459. 1149
  5460. 01:08:43,293 --> 01:08:46,687
  5461. If we think of God as an unlimited
  5462. amount of intelligence,
  5463.  
  5464. 1150
  5465. 01:08:46,731 --> 01:08:50,474
  5466. the closest we can get to that is
  5467. by evolving our own intelligence
  5468.  
  5469. 1151
  5470. 01:08:50,517 --> 01:08:55,566
  5471. by merging with the artificial
  5472. intelligence we're creating.
  5473.  
  5474. 1152
  5475. 01:08:55,609 --> 01:08:58,003
  5476. Today, our computers, phones,
  5477.  
  5478. 1153
  5479. 01:08:58,046 --> 01:09:01,615
  5480. applications give us
  5481. superhuman capability.
  5482.  
  5483. 1154
  5484. 01:09:01,659 --> 01:09:04,662
  5485. So, as the old maxim says,
  5486. if you can't beat 'em, join 'em.
  5487.  
  5488. 1155
  5489. 01:09:06,968 --> 01:09:09,971
  5490. It's about
  5491. a human-machine partnership.
  5492.  
  5493. 1156
  5494. 01:09:10,015 --> 01:09:11,669
  5495. I mean, we already see how, you know,
  5496.  
  5497. 1157
  5498. 01:09:11,712 --> 01:09:14,933
  5499. our phones, for example,
  5500. act as memory prosthesis, right?
  5501.  
  5502. 1158
  5503. 01:09:14,976 --> 01:09:17,196
  5504. I don't have to remember
  5505. your phone number anymore
  5506.  
  5507. 1159
  5508. 01:09:17,240 --> 01:09:19,198
  5509. 'cause it's on my phone.
  5510.  
  5511. 1160
  5512. 01:09:19,242 --> 01:09:22,070
  5513. It's about machines
  5514. augmenting our human abilities,
  5515.  
  5516. 1161
  5517. 01:09:22,114 --> 01:09:25,248
  5518. as opposed to, like,
  5519. completely displacing them.
  5520.  
  5521. 1162
  5522. 01:09:25,249 --> 01:09:27,538
  5523. If you look at all the objects
  5524. that have made the leap
  5525.  
  5526. 1163
  5527. 01:09:27,539 --> 01:09:30,237
  5528. from analog to digital
  5529. over the last 20 years...
  5530.  
  5531. 1164
  5532. 01:09:30,238 --> 01:09:32,123
  5533. it's a lot.
  5534.  
  5535. 1165
  5536. 01:09:32,124 --> 01:09:35,388
  5537. We're the last analog object
  5538. in a digital universe.
  5539.  
  5540. 1166
  5541. 01:09:35,389 --> 01:09:37,068
  5542. And the problem with that,
  5543. of course,
  5544.  
  5545. 1167
  5546. 01:09:37,069 --> 01:09:40,609
  5547. is that the data input/output
  5548. is very limited.
  5549.  
  5550. 1168
  5551. 01:09:40,611 --> 01:09:42,613
  5552. It's this.
  5553. It's these.
  5554.  
  5555. 1169
  5556. 01:09:42,856 --> 01:09:45,355
  5557. Our eyes are pretty good.
  5558.  
  5559. 1170
  5560. 01:09:45,398 --> 01:09:48,445
  5561. We're able to take in a lot
  5562. of visual information.
  5563.  
  5564. 1171
  5565. 01:09:48,488 --> 01:09:52,536
  5566. But our information output
  5567. is very, very, very low.
  5568.  
  5569. 1172
  5570. 01:09:52,579 --> 01:09:55,669
  5571. The reason this is important --
  5572. If we envision a scenario
  5573.  
  5574. 1173
  5575. 01:09:55,713 --> 01:09:59,543
  5576. where AI's playing a more
  5577. prominent role in societies,
  5578.  
  5579. 1174
  5580. 01:09:59,586 --> 01:10:02,023
  5581. we want good ways to interact
  5582. with this technology
  5583.  
  5584. 1175
  5585. 01:10:02,067 --> 01:10:04,983
  5586. so that it ends up
  5587. augmenting us.
  5588.  
  5589. 1176
  5590. 01:10:07,855 --> 01:10:12,295
  5591. I think it's incredibly important
  5592. that AI not be "other."
  5593.  
  5594. 1177
  5595. 01:10:12,338 --> 01:10:14,562
  5596. It must be us.
  5597.  
  5598. 1178
  5599. 01:10:14,906 --> 01:10:18,605
  5600. And I could be wrong
  5601. about what I'm saying.
  5602.  
  5603. 1179
  5604. 01:10:18,649 --> 01:10:23,915
  5605. I'm certainly open to ideas if anybody
  5606. can suggest a path that's better.
  5607.  
  5608. 1180
  5609. 01:10:23,958 --> 01:10:27,266
  5610. But I think we're gonna really
  5611. have to either merge with AI
  5612.  
  5613. 1181
  5614. 01:10:27,310 --> 01:10:29,063
  5615. or be left behind.
  5616.  
  5617. 1182
  5618. 01:10:36,406 --> 01:10:38,756
  5619. It's hard to kind of
  5620. think of unplugging a system
  5621.  
  5622. 1183
  5623. 01:10:38,799 --> 01:10:41,802
  5624. that's distributed
  5625. everywhere on the planet,
  5626.  
  5627. 1184
  5628. 01:10:41,846 --> 01:10:45,806
  5629. that's distributed now
  5630. across the solar system.
  5631.  
  5632. 1185
  5633. 01:10:45,850 --> 01:10:49,375
  5634. You can't just, you know,
  5635. shut that off.
  5636.  
  5637. 1186
  5638. 01:10:49,419 --> 01:10:51,290
  5639. We've opened Pandora's box.
  5640.  
  5641. 1187
  5642. 01:10:51,334 --> 01:10:55,642
  5643. We've unleashed forces that
  5644. we can't control, we can't stop.
  5645.  
  5646. 1188
  5647. 01:10:55,686 --> 01:10:59,516
  5648. We're in the midst of essentially
  5649. creating a new life-form on Earth.
  5650.  
  5651. 1189
  5652. 01:11:05,870 --> 01:11:07,611
  5653. We don't know what happens next.
  5654.  
  5655. 1190
  5656. 01:11:07,654 --> 01:11:10,353
  5657. We don't know what shape
  5658. the intellect of a machine
  5659.  
  5660. 1191
  5661. 01:11:10,396 --> 01:11:14,531
  5662. will be when that intellect is
  5663. far beyond human capabilities.
  5664.  
  5665. 1192
  5666. 01:11:14,574 --> 01:11:17,360
  5667. It's just not something
  5668. that's possible.
  5669.  
  5670. 1193
  5671. 01:11:24,758 --> 01:11:26,976
  5672. The least scary future
  5673. I can think of is one
  5674.  
  5675. 1194
  5676. 01:11:26,978 --> 01:11:29,633
  5677. where we have at least
  5678. democratized AI.
  5679.  
  5680. 1195
  5681. 01:11:31,548 --> 01:11:34,159
  5682. Because if one company
  5683. or small group of people
  5684.  
  5685. 1196
  5686. 01:11:34,202 --> 01:11:37,031
  5687. manages to develop godlike
  5688. digital superintelligence,
  5689.  
  5690. 1197
  5691. 01:11:37,075 --> 01:11:39,739
  5692. they can take over the world.
  5693.  
  5694. 1198
  5695. 01:11:40,383 --> 01:11:44,343
  5696. At least when there's an evil dictator,
  5697. that human is going to die,
  5698.  
  5699. 1199
  5700. 01:11:44,387 --> 01:11:46,998
  5701. but, for an AI,
  5702. there would be no death.
  5703.  
  5704. 1200
  5705. 01:11:47,041 --> 01:11:49,392
  5706. It would live forever.
  5707.  
  5708. 1201
  5709. 01:11:49,435 --> 01:11:53,670
  5710. And then you have an immortal dictator
  5711. from which we can never escape.
  5712.  
  5713. 1202
  5714. 01:13:33,000 --> 01:13:36,500
  5715. Correction and synchronisation:
  5716. Mazrim Taim
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