Artificial Intelligence | 60 Minutes Full Episodes

Full Episodes | 60 Minutes
30 Dec 202353:29

Summary

TLDR这个视频探讨了人工智能技术的迅速发展,以及它给社会和人类带来的深远影响。人工智能系统已经展现出惊人的能力,如创作诗歌、解决生物学难题等,让人类不禁反思:机器是否能意识到自我?这种新技术将如何影响就业市场?它是否会被滥用造成伤害?视频呼吁,社会必须及时采取措施,如制定法规、缔结条约,确保人工智能技术的安全和负责任的发展,从而造福人类。

Takeaways

  • 🌐 人工智能(AI)的发展迅速,正改变我们的生活和工作方式。
  • 🤖 尽管AI技术取得了显著进步,但机器还不能像人类那样思考。
  • 📈 中国成为AI资本的一个重要中心,吸引了全球一半的AI资金。
  • 🔍 三项创新推动了AI的飞速发展:超快计算机芯片、全球数据的在线可用性和深度学习的编程革命。
  • 🎓 AI技术在教育领域的应用,通过识别学生的情绪和学习障碍,个性化地提供帮助。
  • 🔐 中国政府将AI技术的发展定为国家优先事项,目标是在十年内实现AI的领先地位。
  • 💼 AI将在未来15到25年内取代大约40%的工作岗位,这对社会结构有重大影响。
  • 📚 Google和其他科技巨头正在竞相推出更先进的AI系统和聊天机器人,这些技术能够以超人的速度进行学习和创造。
  • 🔧 虽然AI技术带来了许多好处,但也存在错误信息(hallucination)和偏见等问题。
  • 🚀 社会和监管机构需要适应和管理AI技术的发展,确保它们的安全和有益使用。

Q & A

  • 开发人工智能的主要目的是什么?

    -主要目的是创造能够学习和适应的机器,以执行各种复杂任务,从而改变世界,提高效率和解决之前无法解决的问题。

  • 什么是深度学习?

    -深度学习是一种编程技术,允许计算机通过大量示例自我学习和改进,而不是通过硬编码的规则。

  • 为什么人们对会见李开复(Kai-Fu Lee)如此迫切?

    -因为他被认为是人工智能领域的预言家,具有工程才能和创造财富的天赋,人们希望从他那里获得关于AI未来发展的见解。

  • 中国在人工智能发展中的优势是什么?

    -中国的优势在于其庞大的数据量,这对于提高AI的性能至关重要。中国拥有世界上最多的互联网用户,这为AI提供了大量的训练数据。

  • 人工智能如何识别和区分人脸?

    -通过深度学习,AI系统能够分析成千上万的面部图片,学习如何区分不同的特征,从而识别不同的人脸。

  • AI在教育领域的应用有哪些?

    -AI可以分析学生的表情和反应,帮助教师识别哪些学生需要额外的帮助或挑战,还可以个性化学习计划,使教育更加个性化和高效。

  • 为什么说人工智能的发展同时带来了希望和恐惧?

    -因为虽然AI有潜力极大地改善我们的生活和解决复杂问题,但它也可能导致工作岗位的大量流失、隐私问题和不可预测的社会影响。

  • 人工智能对未来就业市场的主要影响是什么?

    -人工智能预计将替代许多重复性工作,包括蓝领和白领工作,这可能导致全球约40%的工作岗位面临被取代的风险。

  • 什么是人工通用智能(AGI)?

    -人工通用智能是一种理论上的AI,能够执行任何智能生物能够执行的智力任务,包括学习、理解和创造,具有人类水平的智能。

  • 人工智能如何改变社会对隐私和数据收集的看法?

    -随着AI技术的发展,越来越多的个人数据被收集用于训练和改善AI系统,这引发了关于隐私保护、数据安全和监控的广泛讨论。

Outlines

00:00

🌐 人工智能的发展与挑战

人工智能(AI)虽然还不能像人类一样思考,但近年来通过学习已显著提升,从而改变了我们的生活方式,例如自动驾驶汽车的出现。AI技术的发展既带来希望也引发担忧,因为人们对未来充满了不确定性。凯叶·李被视为AI领域的预言家,他认为AI将是人类历史上最重大的变革之一。中国成为AI资本的热点,凯叶·李在北京的风险投资公司成功孵化了多个AI创业公司,展示了中国在AI投资方面的强劲增长。此外,Face++等AI初创公司通过深度学习等技术革新,展示了AI在面部识别等领域的应用。

05:01

📚 AI在教育中的应用

凯叶·李将他对教育的热情投入到了将顶尖教师通过远程教学方式带入中国最贫困地区学校的项目中。这一举措旨在为被遗留在农村的孩子们提供更好的教育机会。此外,AI技术也在个性化教育中发挥作用,帮助教师识别学生的学习障碍,优化教学方法。凯叶·李对于通过AI提升教育质量的可能性持乐观态度,希望能够复制他在美国所接受的教育经历,强调了个人思考和批判性思维的重要性。

10:03

🚀 AI对就业市场的影响

AI的快速发展预计将在未来15至25年内取代大约40%的工作岗位,这不仅仅影响蓝领工作,白领职业同样面临威胁。尽管人类历史上的技术变革最终都被人类所适应,AI引发的职业变革速度之快给社会带来了前所未有的挑战。面对这一变革,社会需要智慧和适应性来克服可能出现的困难。此外,AI技术在特定领域的应用也带来了对于人类智慧和情感复杂性的深入思考,促使人们对于机器是否能够完全模仿人类智慧持怀疑态度。

15:05

🤖 人工智能的道德与社会责任

随着AI技术的发展,其在伦理道德方面的问题也日益受到关注。AI系统的决策过程缺乏透明度,使得人们对其公正性和可靠性产生疑问。此外,AI技术可能加剧社会不平等,例如通过加速自动化进程导致失业问题恶化。因此,开发AI技术的企业和研究人员需要承担社会责任,确保技术发展能够造福人类社会,而不是造成分裂或不公。

Mindmap

Keywords

💡人工智能

人工智能(AI)是计算机科学的一个分支,它使机器能够模拟和执行具有人类智能特征的任务,如学习、理解、推理、规划和交流。在视频中,人工智能的发展被描述为将改变世界,比历史上任何技术都要深远。示例包括通过深度学习自主学习的计算机、能够识别人脸和情绪的系统,以及推动个性化教育的AI工具。

💡深度学习

深度学习是人工智能的一个子领域,通过模拟人脑的神经网络结构来训练计算机执行任务。它允许机器通过大量的数据和算法自我学习和改进。视频中提到,深度学习使得计算机能够在没有明确编程的情况下识别人脸、情绪,甚至创造出符合特定要求的内容。

💡数据

在视频中,数据被强调为AI发展的关键推动力之一。拥有更多的数据可以让AI系统更加精确和有效,因为这些系统依赖于数据来学习和做出预测。例如,面部识别系统需要大量的面部图片来学习如何准确识别不同的人脸。

💡创造性

视频强调了AI在创造性任务中的潜力,包括创作诗歌、故事和解决之前被认为只有人类能够解决的复杂问题。AI通过学习大量的数据,能够生成新的、创造性的内容和解决方案。

💡个性化教育

视频中提到AI如何在教育领域中提供个性化的学习体验,通过识别学生的学习习惯和兴趣点,AI可以定制个人化的学习计划,使教育更加高效和有针对性。

💡工作置换

视频讨论了AI将如何改变劳动市场,预计在未来一些重复性高的工作将被AI替代,包括驾驶员、服务员和一些白领工作。这强调了AI技术发展对社会结构和就业市场潜在的深远影响。

💡隐私

在讨论中国AI发展时,视频提到中国公民对于个人隐私的关注较少。这种对隐私的不同看法影响了AI技术的采纳和数据收集实践,进而影响了AI系统的发展和应用。

💡监管

视频提到了对AI技术进行监管的必要性,以确保其安全和符合道德标准的使用。这包括制定法律和政策来指导AI技术的发展和部署,确保它们不被用于有害的目的。

💡假信息

视频中提到AI技术在传播假信息方面的潜力,强调了需要对这一挑战进行管理和监管。AI生成的内容可能难以区分真伪,这对社会信息环境构成了挑战。

💡人类价值

视频探讨了AI发展对人类价值和自我认识的影响。随着AI技术在各个领域的应用越来越广泛,我们需要思考人类的独特价值是什么,以及我们如何利用这些技术来增强而不是取代人类的能力。

Highlights

尽管听到人工智能机器仍无法像人类一样思考,但在过去几年中,它们已经能够学习,突然间我们的设备睁开了眼睛和耳朵,汽车也开始接管方向盘。

今天的人工智能并不像你所希望的那么出色,也不像你所担心的那么糟糕,但人类正在加速走向一个鲜有人能够预测的未来。

这就是为什么如此多的人迫切希望能见到李开复,他是人工智能的先知。

李开复相信,身为人工智能资本家,最佳地点就是在共产主义国家中国。

使人工智能成为可能的是三项革命性创新:超快的计算机芯片、可用的全球数据和一种称为深度学习的全新编程方式。

深度学习就是让计算机通过观察大量示例自行学习,而不是由人为编写刚性指令。

Face++是李开复投资的人工智能公司之一,其视觉识别系统能非常精准地辨识移动物体。

Face++给了斯科特贴上了性别男、短发、黑色长袖和长裤的标签,但对于他的灰色西装却识别错误,展示了这类系统通过持续学习来改正错误的过程。

AI正在挑战新闻和图像领域,未来虚假信息和虚假图像的问题将更加严峻。

谷歌开发了名为Bard的AI对话系统,根据训练数据自主生成回答,无需连接互联网搜索。

Bard可以以超乎寻常的速度总结新约全书、用拉丁文回答,甚至根据极简线索创作出富有洞见的小说和诗歌。

Bard展现出看似自主思考、判断和创造力的能力,但事实上并非如此,它只是基于学习数据重现人类智能。

即使只是狭隘的当前AI,在特定领域也展现出超人的能力。在谷歌的人工智能实验室,机器人通过自主学习掌握了踢足球等复杂技能。

DeepMind解决了一个长期被视为不可能的生物问题,在短时间内预测了200万种蛋白质的3D结构,为人类生物学研究做出重大贡献。

人工智能的未来是通用人工智能,一种能在广泛领域发挥才能的学习型机器,但它是否会拥有类似人类的自我意识,目前还是未解之谜。

Transcripts

00:13

despite what you hear about artificial

00:15

intelligence machines still can't think

00:17

like a human but in the last few years

00:20

they have become capable of learning and

00:23

suddenly our devices have opened their

00:25

eyes and ears and cars have taken the

00:28

wheel today artificial intelligence is

00:31

not as good as you hope and not as bad

00:34

as you fear but humanity is accelerating

00:37

into a future that few can predict

00:40

that's why so many people are desperate

00:41

to meet Kaiu Lee the Oracle of

00:47

AI Kuli is in there somewhere in a

00:51

selfie scrum at a Beijing internet

00:56

conference his 50 million social media

00:59

followers want to be seen in the same

01:02

frame because of his talent for

01:06

engineering and genius for wealth I

01:09

wonder do you think people around the

01:11

world have any idea what's coming in

01:15

artificial intelligence I think most

01:18

people have no idea and many people have

01:20

the wrong idea but you do believe it's

01:23

going to change the world I believe it's

01:25

going to change the world more than

01:26

anything in the history of mankind more

01:29

than election

01:31

Lee believes the best place to be an AI

01:34

capitalist is communist China his

01:37

Beijing Venture Capital firm

01:39

manufactures billionaires these are the

01:41

entrepreneurs that we funded he's funded

01:45

140 AI startups we have about10 billion

01:48

companies here 101 billion companies

01:51

that you funded yes including a few 10

01:53

billion

01:55

companies in 2017 China attracted half

01:59

of all AI capital in the world one of

02:03

Lee's Investments is face Plus+ not

02:06

affiliated with Facebook its visual

02:09

recognition system smothered me to guess

02:11

my age it settled on 61 which was wrong

02:16

I wouldn't be 61 for

02:18

days on the street face Plus+ nailed

02:22

everything that moved it's a kind of

02:25

artificial intelligence that has been

02:27

made possible by three Innovations

02:30

super fast computer chips all the

02:33

world's data now available online and a

02:37

revolution in programming called Deep

02:39

learning computers used to be given

02:42

rigid instructions now they're

02:44

programmed to learn on their own in the

02:47

early days of AI people try to program

02:51

the AI with how people think so I would

02:54

write a program to say U measure the

02:56

size of the eyes and their distance

02:59

measure the size of the nose measure the

03:01

shape of the face and then if these

03:03

things match then this is Larry and

03:05

that's John but today you just take all

03:08

the pictures of Larry and John and you

03:10

tell the system go at it and you figure

03:13

out what separates Larry from

03:15

John let's say you want the computer to

03:18

be able to pick men out of a crowd and

03:20

describe their clothing will you simply

03:23

show the computer 10 million pictures of

03:26

men in various kinds of dress that

03:29

that's what they mean by Deep learning

03:33

it's not intelligence so much it's just

03:35

the brute force of data having 10

03:39

million examples to choose from so face

03:42

Plus+ tagged me as male short hair black

03:46

long sleeves black long pants it's wrong

03:50

about my gray suit and this is exactly

03:53

how it learns when Engineers discover

03:56

that error they'll show the computer a

03:58

million Gra suits and it won't make that

04:01

mistake again over a thousand classrooms

04:04

another recognition system we saw or saw

04:07

us is learning not just who you are but

04:11

how you feel now what are all the dots

04:14

on the screen the dots over our eyes and

04:17

our mouths sure the computer keeps track

04:20

all the feature points on the face son

04:23

fany Yang developed this for talal

04:26

Education Group which tutors 5 million

04:29

chines students let's look at what we're

04:31

seeing here now according to the

04:32

computer I'm confused which is generally

04:35

the case but when I laughed I was happy

04:38

exactly that's amazing the machine

04:41

notices concentration or distraction to

04:44

pick out for the teacher those students

04:46

who are struggling or

04:48

gifted it can tell when the child is

04:51

excited about math yes or the other

04:54

child is excited about poetry yes could

04:57

these AI systems pick out Geniuses from

05:01

the countryside that's possible in the

05:04

future it can also create a student

05:07

profile and know where the student got

05:10

stuck so the teacher can personalize the

05:13

areas in which the student needs help if

05:16

you do raise up your hand we found Kaiu

05:19

Lee's personal passion in this spare

05:22

Beijing Studio he's projecting top

05:25

teachers into China's poorest schools

05:28

this English teacher is connected to a

05:31

class 1,000 miles away in a village

05:34

called

05:39

defang many students in defang are

05:41

called Left behinds because their

05:44

parents left them with family when they

05:46

moved to the cities for

05:49

work most left behinds don't get past

05:52

9th grade topic we're going to learn

05:55

today Lee is counting on AI to deliver

05:58

for them the same opportunity he had

06:02

when he immigrated to the US from Taiwan

06:05

as a

06:06

boy when I arrived in Tennessee my

06:09

principal took every lunch to teach me

06:12

English and that is the kind of

06:14

attention that I've not been used to

06:17

Growing Up in Asia and I felt that the

06:21

American classrooms are smaller

06:24

encouraged individual thinking critical

06:27

thinking and I felt um it was the best

06:30

thing that ever happened to me what

06:33

about this and the best thing that ever

06:35

happened to most of the engineers we met

06:37

at Le's firm I went to K master degree

06:40

in information science they too are

06:42

alumni of America with a dream for China

06:46

you have written that silicon Valley's

06:49

Edge is not all it's cracked up to be

06:51

what do you mean by that well Silicon

06:53

Valley has been the single epicenter of

06:57

the world technology Innovation when it

07:00

comes to computers internet mobile and

07:03

AI but in the recent five years we are

07:07

seeing the Chinese AI is getting to be

07:11

almost as good as Silicon Valley Ai and

07:14

I think Silicon Valley is not quite

07:17

aware of it yet China's Advantage is in

07:21

the amount of data it collects the more

07:23

data the better the AI just like the

07:26

more you know the smarter you

07:28

are China has four times more people

07:32

than the United States and they are

07:34

doing nearly everything online I just

07:37

don't see any Chinese without a phone in

07:39

their head college student Monica Sun

07:41

showed us how more than a billion

07:43

Chinese are using their phones to buy

07:46

everything find anything and connect

07:49

with everyone in America when personal

07:52

information

07:53

leaks we have Congressional hearings not

07:57

in China you ever worry about the

07:59

information that's being collected about

08:01

you where you go what you buy who you're

08:06

with I I never think about it do you

08:10

think most Chinese worry about their

08:12

privacy um not that much not that

08:16

much with a plant public the leader of

08:19

the Communist party has made a national

08:22

priority of achieving AI dominance in 10

08:26

years this is where Kaiu Lee becomes

08:29

uncharacteristically shy even though

08:32

he's a former Apple Microsoft and Google

08:35

executive he knows who boss in China

08:39

president XI has called technology the

08:42

sharp weapon of the modern

08:45

State what does he mean by that I I am

08:49

not an expert in interpreting his

08:51

thoughts don't know there are those

08:53

particularly people in the west who

08:55

worry about this AI technology as being

09:00

something that governments will use to

09:02

control their people and to crush

09:06

dcent that as Aventure capitalists we

09:09

don't we don't invest in this area and

09:12

we're not studying deeply this

09:14

particular problem but governments do

09:17

it's certainly possible for governments

09:19

to use the Technologies just like

09:22

companies Lee is much more talkative

09:24

about another threat posed by AI he

09:28

explores the coming destruction of jobs

09:31

in a new book AI superpowers China

09:35

Silicon Valley and the New World Order

09:38

AI will increasingly replace repetitive

09:41

jobs not just for blue color work but a

09:45

lot of white color work what sort of

09:48

jobs would be lost to AI basically

09:51

chauffeur truck drivers uh anyone who

09:53

does driving for a living uh their jobs

09:57

will be disrupted more in the 50 15 to

09:59

20 year uh time frame and many jobs that

10:03

seem a little bit complex uh Chef waiter

10:08

uh a lot of things will become automated

10:10

we'll have automated stores uh automated

10:13

restaurants and uh Al together in 15

10:16

years that's going to uh displace uh

10:19

about 40% of jobs in the

10:23

world

10:25

40% of jobs in the world will be

10:27

displaced by technology ology uh I would

10:30

say displaceable what does that do to

10:32

the fabric of

10:34

society well in some sense there's the

10:37

human wisdom that always overcomes these

10:40

technology revolutions the invention of

10:42

the steam engine uh the sewing machine

10:45

the uh

10:46

electricity uh have all displaced jobs

10:49

uh and we've gotten over it the

10:51

challenge of AI is this 40% whether it's

10:55

15 or 25 years is coming faster than the

10:58

previous

11:00

revolutions there's a lot of hype about

11:02

artificial intelligence and it's

11:04

important to understand this is not

11:07

general intelligence like that of a

11:10

human this system can read faces and

11:13

grade papers but it has no idea why

11:16

these children are in this

11:18

room or what the goal of education is a

11:22

typical AI system can do one thing well

11:26

but can't adapt what it knows to any

11:29

other

11:30

task so for now it may be that calling

11:34

this

11:35

intelligence isn't very smart when will

11:39

we know that a machine can actually

11:41

think like a human back when I was a

11:45

grad students people said if machine can

11:47

drive a car uh by itself that's

11:50

intelligence now we say that's not

11:52

enough so the bar keeps moving higher I

11:55

think that's uh I guess more motivation

11:58

for us to work harder but if you're

12:00

talking about AGI artificial general

12:02

intelligence I would say not within the

12:05

next 30 Years and possibly never

12:08

possibly Never What's So

12:12

insurmountable CU I believe in the

12:14

sanctity of our soul I believe there's a

12:17

lot of things about us that we don't

12:19

understand I believe there's a lot of um

12:23

uh love and compassion that is not

12:25

explainable in terms of neural networks

12:29

and computational algorithms and I

12:31

currently see no way of solving them

12:34

obviously unsolved problems have been

12:36

solved in the past but it would be

12:38

irresponsible for me to predict that

12:41

these will be solved by certain time

12:43

frame we may just be more than our bits

12:46

we

12:57

may we may look on our time as the

13:01

moment civilization was transformed as

13:04

it was by fire Agriculture and

13:07

electricity in 2023 we learned that a

13:10

machine taught itself how to speak to

13:14

humans like a peer which is to say with

13:17

creativity truth error and lies the

13:21

technology known as a chatbot is only

13:24

one of the recent breakthroughs in

13:27

artificial intelligence machines that

13:29

can teach themselves superhuman skills

13:33

we explored what's coming next at Google

13:36

a leader in this new world CEO Sundar

13:40

Pai told us AI will be as good or as

13:43

evil as human nature allows the

13:46

revolution he says is coming faster than

13:49

you

13:50

know do you think Society is prepared

13:54

for what's coming you know there are two

13:56

ways I think about it on one hand

13:59

I feel no uh because you know the pace

14:02

at which we can think and adapt as

14:04

societal institutions compared to the

14:06

PACE at which the technology is evolving

14:08

there seems to be a

14:10

mismatch on the other hand compared to

14:12

any other technology I've seen more

14:14

people worried about it earlier in its

14:16

life cycle so I feel optimistic the

14:19

number of people you know who have

14:21

started worrying about the implications

14:24

and hence the conversations are starting

14:27

in a serious way as well I guess our

14:29

conversations with 50-year-old Sundar

14:31

Pai started at Google's new campus in

14:34

Mountain View California it runs on 40%

14:38

solar power and collects more water than

14:40

it uses Hightech that pachai couldn't

14:44

have imagined growing up in India with

14:47

no telephone at home we were on a

14:50

waiting list to get a rotary phone and

14:52

for about 5 years and it finally came

14:55

home I can still recall it vividly it

14:59

changed our lives to me it was the first

15:02

moment I understood the power of what

15:04

getting access to technology meant so

15:07

probably led me to be doing what I'm

15:09

doing

15:10

today what he's doing since 2019 is

15:13

leading both Google and its parent

15:16

company alphabet valued at $1.3

15:20

trillion worldwide Google runs 90% of

15:25

internet searches and 70% of smartphones

15:29

we're really excited about but its

15:30

dominance was attacked this past

15:32

February when Microsoft linked its

15:35

search engine to a chatbot in a race for

15:39

AI dominance Google just released its

15:42

chatbot named Bard it's really here to

15:45

help you brainstorm ideas to generate

15:49

content like a speech or a blog post or

15:52

an email we were introduced to Bard by

15:55

Google vice president sha and

15:58

senior Vice President James manika

16:01

here's Bard the first thing we learned

16:04

was that Bard does not look for answers

16:07

on the internet like Google search does

16:11

so I wanted to get inspiration from some

16:13

of the best speeches in the world Bard's

16:15

replies come from a self-contained

16:17

program that was mostly self-taught our

16:21

experience was unsettling confounding

16:24

absolutely confounding Bard appeared to

16:27

possess the sum of human

16:30

knowledge with microchips more than

16:33

100,000 times faster than the human

16:35

brain summarize the we asked Bard to

16:38

summarize the New Testament it did in 5

16:42

seconds and 17 words in Latin we asked

16:46

for it in Latin that took another 4

16:49

seconds then we played with a famous

16:52

six-word short story often attributed to

16:56

Hemingway for sale baby shoes news never

16:59

worn wow the only prompt we gave was

17:03

finish this

17:05

story in 5

17:07

seconds holy cow the shoes were a gift

17:11

from my wife but we never had a baby

17:15

they were from The six-word Prompt Bard

17:18

created a deeply human tale with

17:21

characters it invented including a man

17:24

whose wife could not conceive and a

17:27

stranger grieving after a miscarriage

17:31

and longing for

17:33

closure uh I am rarely

17:37

speechless I don't know what to make of

17:40

this give me we asked for the story in

17:45

verse in 5 seconds there was a poem

17:48

written by a machine with breathtaking

17:51

insight into the mystery of Faith Bard

17:55

wrote she knew her baby soul would

17:59

always be

18:00

alive the humanity at superhuman speed

18:05

was a shock how is this possible James

18:08

manika told us that over several months

18:11

Bard read most everything on the

18:14

internet and created a model of what

18:17

language looks like rather than search

18:20

its answers come from this language

18:23

model so for example if I said to you

18:25

Scott peanut butter and jelly right so

18:30

it tries and learns to predict okay so

18:31

peanut butter usually is followed by

18:33

jelly it tries to predict the most

18:36

probable next words based on everything

18:39

it's learned uh so it's not going out to

18:42

find stuff it's just predicting the next

18:44

word but it doesn't feel like that we

18:48

asked Bard why it helps people and it

18:51

replied quote because it makes me

18:55

happy B to my eye appears to be thinking

19:01

appears to be making

19:04

judgments that's not what's happening

19:07

these machines are not sensient they are

19:10

not aware of themselves they're not

19:12

sentient they're not aware of themselves

19:15

uh they can exhibit behaviors that look

19:18

like that because keep in mind they've

19:19

learned from us we are sentient beings

19:22

we have beings that have feelings

19:24

emotions ideas thoughts perspectives

19:29

we've reflected all that in books in

19:31

novels in fiction so when they learn

19:33

from that they build patterns from that

19:36

so it's no surprise to me that the

19:38

exhibited behavior sometimes looks like

19:42

maybe there's somebody behind it there's

19:43

nobody there these are not sensient

19:45

beings they're not Zimbabwe born Oxford

19:49

educated James manika holds a new

19:51

position at Google his job is to think

19:54

about how Ai and Humanity will best

19:58

coexist AI has a potential to change

20:02

many ways in which we've thought about

20:04

Society about what we're able to do the

20:07

the problems we can solve but AI itself

20:11

will pose its own problems could Heming

20:13

way write a better short story maybe but

20:16

Bard can write a million before

20:19

Hemingway could finish one imagine that

20:23

level of automation across the economy a

20:27

lot of people can be replaced by this

20:29

technology yes there are some job

20:31

occupations that will start to decline

20:33

over time there are also new job

20:35

categories that will grow over time but

20:38

the biggest change will be the jobs that

20:40

will be changed something like more than

20:43

2third will have their definitions

20:46

change not go away but change because

20:49

they're now being assisted by Ai and by

20:52

automation so this is a profound change

20:55

which has implications for skills how do

20:57

we assist people build new skills learn

21:00

to work alongside machines and how do

21:02

these complement what people do today

21:04

this is going to impact every product

21:07

across every company and and so that's

21:10

why I think it's a a very very profound

21:12

technology and so we are just in early

21:14

days every product in every company

21:17

that's right AI will impact everything

21:21

so for example you could be a

21:22

radiologist you know if I if you think

21:24

about 5 to 10 years from now you're

21:26

going to have a AI collabor with you it

21:29

may triage you come in the morning you

21:32

let's say you have 100 things to go

21:33

through it may say these are the most

21:35

serious cases you need to look at first

21:38

or when you're looking at something it

21:40

may pop up and say you may have missed

21:42

something important why wouldn't we you

21:44

know why would we take advantage of a

21:48

superpowered assistant to help you

21:50

across everything you do you may be a

21:52

student trying to learn math or history

21:55

and you know you will have something

21:58

helping you we asked Pai what jobs would

22:01

be disrupted he said knowledge workers

22:04

people like writers accountants

22:06

Architects and ironically software

22:10

Engineers AI writes computer code too

22:14

today Sundar pachai walks a narrow line

22:17

a few employees have quit some believing

22:20

that Google's AI rollout is too slow

22:23

others too fast there are some serious

22:27

flaws there's a return of inflation

22:30

James manika asked Bard about inflation

22:33

it wrote an instant essay in economics

22:35

and recommended five books but days

22:39

later we checked none of the books is

22:42

real Bard fabricated the titles this

22:46

very human trait error with confidence

22:51

is called in the industry

22:53

hallucination are you getting a lot of

22:56

hallucinations uh yes uh you know which

22:58

is expected no one in the in the field

23:02

has yet solved the hallucination

23:05

problems all models uh do have uh this

23:08

as an issue is it a solvable problem

23:11

it's a matter of intense debate I think

23:14

we'll make progress to help cure

23:17

hallucinations Bard features a Google it

23:20

button that leads to oldfashioned search

23:24

Google has also built safety filters in

23:27

debard to screen for things like hate

23:30

speech and bias how great a risk is the

23:34

spread of disinformation AI will

23:37

challenge that in a deeper way the scale

23:39

of this problem is going to be much

23:41

bigger bigger problems he says with fake

23:44

news and fake images it will be possible

23:47

with AI to create uh you know a video

23:51

easily where it could be Scott saying

23:54

something or me saying something and we

23:56

never said that and it could look

23:58

accurate but you know at a societal

24:00

scale you know can cause a lot of harm

24:03

is Bard safe for

24:05

society the way we have launched it

24:07

today uh as an experiment in a limited

24:10

way uh I think so but we all have to be

24:14

responsible in each step along the way

24:17

Pai told us he's being responsible by

24:20

holding back for more testing Advanced

24:23

versions of Bard that he says can reason

24:28

and connect to internet search you are

24:31

letting this out slowly so that Society

24:34

can get used to

24:36

it that's one part of it uh one part is

24:39

also so that we get the user feedback

24:42

and we can develop more robust safety

24:46

layers before we build before we deploy

24:49

more capable models interacting of the

24:51

AI issues we talked about the most

24:54

mysterious is called emergent property

24:58

some AI systems are teaching themselves

25:01

skills that they weren't expected to

25:04

have how this happens is not well

25:08

understood for example one Google AI

25:11

program adapted on its own after it was

25:15

prompted in the language of Bangladesh

25:18

which it was not trained to know we

25:22

discovered that with very few amounts of

25:24

prompting in Bengali he can now

25:27

Translate all of Bengali so now all of a

25:30

sudden we now have a research effort

25:32

where we're now trying to get to a

25:34

thousand languages there is an aspect of

25:36

this which we call all of us in the

25:38

field call it as a black box you know

25:41

you don't fully understand and you can't

25:44

quite tell why it said this or why it

25:47

got wrong we have some ideas and our

25:49

ability to understand this gets better

25:51

over time but that's where the state of

25:53

the art is you don't fully understand

25:55

how it works and yet you turned it loose

25:58

on society let me put it this way I

26:01

don't think we fully understand how a

26:03

human mind works either was it from that

26:07

black box we wondered that Bard Drew its

26:10

short story that seems so disarmingly

26:14

human it talked about the pain that

26:17

humans feel it talked about

26:20

Redemption how did it do all of those

26:23

things if it's just trying to figure out

26:25

what the next right word is me I've had

26:27

these experiences uh talking with b as

26:30

well there are two views of this you

26:33

know there are a set of people who view

26:34

this is look these are just algorithms

26:38

they're just repeating what it's seen

26:40

online then there is the view where

26:45

these algorithms are showing emerging

26:48

properties to be creative to reason to

26:51

plan and so on right and and personally

26:57

I think we need to be uh we need to

26:59

approach this with humility part of the

27:01

reason I think it's good that some of

27:03

these Technologies are getting out is so

27:06

that Society you know people like you

27:08

and others can process what's happening

27:11

and we begin this conversation and

27:13

debate and I think it's important to do

27:15

that when we come back we'll take you

27:18

inside Google's artificial intelligence

27:21

Labs where robots are

27:26

learning

27:36

the revolution in artificial

27:37

intelligence is the center of a debate

27:40

ranging from those who hope it will save

27:43

Humanity to those who predict Doom

27:46

Google lies somewhere in the optimistic

27:49

middle introducing AI in steps so

27:53

civilization can get used to it we saw

27:56

what's coming next in machine learning

27:58

at Google's AI lab in London a company

28:01

called Deep Mind where the future looks

28:05

something like

28:08

this look at that oh my goodness they've

28:11

got a pretty good kick on them can still

28:14

get quite a good good game a soccer

28:16

match at Deep Mind looks like fun in

28:19

games but here's the thing humans did

28:23

not program these robots to play they

28:26

learned the game by themselves it's

28:29

coming up with these interesting

28:30

different strategies different ways to

28:32

walk different ways to block and they're

28:34

doing it they're scoring over and over

28:36

again this robot here Rya hadel vice

28:40

president of research and Robotics

28:42

showed us how Engineers used motion

28:45

capture technology to teach the AI

28:48

program how to move like a human but on

28:51

the soccer pitch the robots were told

28:54

only that the object was to score the

28:57

self-learning program spent about 2

29:00

weeks testing different moves it

29:03

disgarded those that didn't work built

29:06

on those that did and created allars

29:09

there's another goal and with practice

29:12

they get better Hansel told us that

29:15

independent from the robots the AI

29:18

program plays thousands of games from

29:22

which it learns and invents its own

29:25

tactics here you think that red player

29:27

is going to grab it but instead it just

29:29

stops IT hands it back passes it back

29:33

and then goes for the goal and the AI

29:34

figured out how to do that on its own

29:36

that's right that's right and it takes a

29:38

while at first all the players just run

29:41

after the ball together like a gaggle of

29:43

uh you know six-year-olds the first time

29:46

they're they're they're playing ball

29:48

over time what we start to see is now ah

29:50

what's the strategy you go after the

29:52

ball I'm coming around this way or we

29:54

should pass or I should block while you

29:57

get to the goal so we see all of that

29:59

coordination um emerging in the

30:05

play this is a lot of fun but what are

30:08

the practical implications of what we're

30:11

seeing here this is the type of research

30:13

that can eventually lead to robots that

30:15

can come out of the factories and work

30:19

in other types of human environments you

30:21

know think about mining think about

30:23

dangerous construction work um or

30:26

exploration or Disaster Recovery these

30:29

are Rya hadel is among 1,000 humans at

30:32

Deep Mind the company was co-founded

30:35

just 12 years ago by CEO Deus hassabis

30:40

so if I think back to 2010 when we

30:42

started nobody was doing AI there was

30:44

nothing going on in Industry people used

30:46

to ey roll when we talked to them

30:48

investors about doing AI so we couldn't

30:50

we could barely get two cents together

30:52

to start off with which is crazy if you

30:54

think about now the billions being

30:55

invested into AI startups

30:58

Cambridge Harvard MIT havabus has

31:01

degrees in computer science and

31:04

Neuroscience his PhD is in human

31:07

imagination and imagine this when he was

31:10

12 in his age group he was the number

31:13

two chess champion in the

31:17

world it was through games that he came

31:20

to

31:22

AI I've been working on AI for for

31:25

decades now and I've always believed

31:27

that it's going to be the most important

31:29

invention that Humanity will ever make

31:31

will the pace of change outstrip our

31:34

ability to

31:36

adapt I don't think so I think that we

31:39

um you know we're sort of an infinitely

31:41

adaptable species um you know you look

31:43

at today us using all of our smartphones

31:45

and other devices and we effortlessly

31:47

sort of adapt to these new technologies

31:50

and this is going to be another one of

31:51

those changes like that among the

31:53

biggest changes at Deep Mind was the

31:56

discovery that self-learning machines

31:59

can be creative so this isaba showed us

32:02

a game playing program that learns it's

32:06

called Alpha zero and it dreamed up a

32:09

winning chess strategy no human had ever

32:12

seen but this is just a machine how does

32:15

it achieve creativity it plays against

32:17

itself tens tens of millions of times so

32:20

it can explore um parts of Chess that

32:23

maybe human chess players and and and

32:25

programmers who program chess computers

32:27

haven't thought about before it never

32:29

gets tired it never gets hungry it just

32:31

plays chess all the time yes it's it's

32:34

kind of amazing thing to see because

32:36

actually you set off Alpha zero in the

32:37

morning uh and it starts off playing

32:40

randomly by lunchtime you know it's able

32:42

to beat me and beat most chess players

32:44

and then by the evening it's stronger

32:46

than the world champion Deus saaba so

32:48

deep mind to Google in

32:50

2014 one reason was to get his hands on

32:54

this Google has the enormous computing

32:58

power that AI needs this Computing

33:01

Center is in Prior Oklahoma but Google

33:04

has 2 of these putting it near the top

33:07

in computing power in the world this is

33:11

one of two advances that make AI

33:14

ascendant now first the sum of all human

33:18

knowledge is online and second Brute

33:21

Force Computing that very Loosely

33:24

approximates the neural networks and

33:27

talents of the brain things like memory

33:31

imagination planning reinforcement

33:33

learning these are all things that are

33:35

known about how the brain does it and we

33:37

wanted to replicate some of that uh in

33:39

our AI systems you predict one of those

33:41

indiv those are some of the elements

33:43

that led to deep mind's greatest

33:45

achievement so far solving an impossible

33:48

problem in

33:50

biology proteins are building blocks of

33:53

life but only a tiny fraction were

33:55

understood because 3D mapping of just

33:58

one could take years deep mine created

34:03

an AI program for the protein problem

34:06

and set it Loose well it took us about

34:08

four or five years to to figure out how

34:10

to build the system it was probably our

34:12

most complex project we've ever

34:13

undertaken but once we did that it can

34:16

solve uh a protein structure in a matter

34:18

of seconds and actually over the last

34:20

year we did all the 200 million proteins

34:22

that are known to science how long would

34:24

it have taken using traditional methods

34:27

well the rule of thumb I was always told

34:29

by my biologist friends is that it it

34:31

takes a whole PhD 5 years to do one

34:33

protein structure experimentally so if

34:36

you think 200 million time 5 that's a

34:38

billion years of PhD time it would have

34:40

taken Deep Mind Made its protein

34:43

database public a gift to humanity hbas

34:47

called it how has it been used it's been

34:50

used in an enormously broad number of

34:52

ways actually from U malaria vaccines to

34:56

developing new enzymes that can eat

34:58

plastic waste um to new uh antibiotics

35:02

most AI systems today do one or maybe

35:06

two things well the soccer robots for

35:09

example can't write up a grocery list or

35:12

book your travel or drive your car the

35:15

ultimate goal is what's called

35:18

artificial general intelligence a

35:21

learning machine that can score on a

35:24

wide range of talents would such a

35:27

machine be conscious of itself so that's

35:30

another great question we you know

35:32

philosophers haven't really settled on a

35:34

definition of Consciousness yet but if

35:36

we mean by sort of self-awareness and uh

35:38

these kinds of things um you know I

35:40

think there is a possibility AIS one day

35:42

could be I definitely don't think they

35:44

are today um but I think again this is

35:46

one of the fascinating scientific things

35:48

we're going to find out on this journey

35:50

towards

35:52

AI even unconscious current AI is super

35:56

superhuman in narrow ways back in

36:00

California we saw Google Engineers

36:02

teaching skills that robots will

36:04

practice continuously on their own push

36:07

the blue cube to the blue triangle they

36:10

comprehend instructions push the yellow

36:12

hexagon to the yellow heart and learn to

36:14

recognize objects what would you like

36:18

how about an apple how about an apple on

36:22

my way I will bring an apple to you

36:25

we're trying Vincent van senior director

36:28

of Robotics showed us how robot 106 was

36:31

trained on millions of images I am going

36:34

to pick up the apple and can recognize

36:37

all the items on a crowded countertop if

36:41

we can give the robot A diversity of

36:43

experiences a lot more different objects

36:46

in different settings the robot gets

36:48

better at every one of them now that

36:51

humans have pulled the forbidden fruit

36:53

of artificial knowledge thank you

36:57

we start the Genesis of a new Humanity

37:01

AI can utilize all the information in

37:04

the world what no human could ever hold

37:07

in their head and I wonder if humanity

37:12

is

37:13

diminished by this enormous capability

37:18

that we're

37:19

developing I think the possibilties of

37:21

AI do not diminish uh Humanity in any

37:24

way and in fact in some ways I think

37:26

actually raise us to even deeper more

37:30

profound questions Google's James manika

37:34

sees this moment as an inflection point

37:38

I think we're constantly adding these

37:40

superpowers or capabilities to what

37:42

humans can do in a way that expands

37:46

possibilities as opposed to narrow them

37:48

I think so I don't think of it as

37:50

diminishing humans but it does raise

37:52

some really profound questions for us

37:54

who are we what do we value you uh what

37:57

are we good at how do we relate with

38:00

each other those become very very

38:02

important questions that are constantly

38:04

going to be in one case sense exciting

38:07

but perhaps unsettling too it is an

38:11

unsettling moment critics argue the rush

38:14

to AI comes too fast while competitive

38:17

pressure among giants like Google and

38:20

startups you've never heard of is

38:22

propelling Humanity into the Future

38:25

Ready or Not

38:27

but I think if I take a 10year

38:29

Outlook it is so clear to me we will

38:33

have some form of very capable

38:36

intelligence that can do amazing things

38:40

and we need to adapt as a society for it

38:44

Google CEO Sundar Pai told us Society

38:47

must quickly adapt with regulations for

38:51

AI in the economy laws to punish abuse

38:55

and treaties among Nations to make AI

38:58

safe for the world you know these are

39:01

deep questions and you know we call this

39:04

alignment you know one way we think

39:06

about how do you develop AI systems that

39:09

are aligned to human values and

39:12

including uh

39:15

morality this is why I think the

39:17

development of this needs to include not

39:19

just Engineers but social scientists

39:22

ethicists philosophers and so on and I

39:25

think we have to be be very thoughtful

39:28

and I think these are all things Society

39:31

needs to figure out as we move along

39:34

it's not for a company to

39:36

decide we'll end with a note that has

39:38

never appeared on 60 Minutes but one in

39:42

the AI Revolution you may be hearing

39:45

often the proceeding was created with

39:48

100% human

39:55

content

40:02

the large tech companies Google meta

40:06

slfb Microsoft are in a race to

40:09

introduce new artificial intelligence

40:11

systems and what are called chatbots

40:14

that you can have conversations with and

40:17

are more sophisticated than Siri or

40:19

Alexa Microsoft's AI search engine and

40:23

chatbot Bing can be used on a computer

40:26

comp or cell phone to help with planning

40:29

a trip or composing a letter it was

40:32

introduced on February 7th to a limited

40:35

number of people as a test and initially

40:39

got rave reviews but then several news

40:42

organizations began reporting on a

40:44

disturbing so-called Alter Ego within

40:47

Bing chat called Sydney we went to

40:51

Seattle last week to speak with Brad

40:53

Smith president of Microsoft about about

40:56

Bing and Sydney who to some had appeared

41:00

to have gone

41:02

Rogue Kevin Roose the technology

41:05

reporter at the New York Times found

41:07

this Alter Ego uh who was threatening

41:10

expressed a desire it's not just Kevin

41:13

ruse it's others expressed a desire to

41:16

steal nuclear codes threaten to ruin

41:19

someone you saw that whoa what was your

41:24

you must have said oh my God my reaction

41:26

is we better fix this right away and

41:30

that is what the engineering team did

41:33

yeah but she's talked like a person and

41:36

she she said she had feelings you know I

41:39

think there is a point where we need to

41:41

recognize when we're talking to a

41:45

machine it's a screen it's not a person

41:49

I just want to say that it was scary and

41:53

I'm not easily scared and it was scary

41:55

it was chilling yeah it's I think this

41:57

is in part a reflection of a lifetime of

42:01

Science Fiction which is understandable

42:03

it's been part of our Lives did you kill

42:06

her I don't think she was ever alive I

42:08

am confident that she's no longer

42:10

wandering around the countryside if

42:11

that's what you're concerned about but I

42:13

think it would be a mistake if we were

42:15

to fail to acknowledge that we are

42:18

dealing with something that is

42:19

fundamentally new this is the edge of

42:22

the envelope so to speak this creature

42:25

appeared

42:27

as if there were no guard rails now the

42:29

creature jumped the guard rails if you

42:31

will after being prompted for two hours

42:34

with the kind of conversation that we

42:37

did not

42:39

anticipate and by the next evening that

42:41

was no longer possible we were able to

42:45

fix the problem in 24 hours how many

42:48

times do we see problems in life that

42:51

are fixable in less than a day one of

42:54

the ways he says it was fixed was by

42:56

limiting the number of questions and the

42:59

length of the conversations you say you

43:02

fixed it I've tried it I tried it before

43:05

and it after it was loads of fun and it

43:09

was fascinating and now it's not fun

43:13

well I think it'll be very fun again and

43:15

you have to moderate and manage your

43:17

speed if you're going to stay on the

43:19

road so as you hit New Challenges you

43:22

slow down you build the guard rails add

43:25

the SA features and then you can speed

43:27

up again when you use Bing's AI features

43:31

search and chat your computer screen

43:34

doesn't look all that new one big

43:37

difference is you can type in your

43:39

queries or prompts in conversational

43:42

language but I'll show you how it works

43:44

okay okay Yousef medy Microsoft's

43:46

corporate vice president of search

43:49

showed us how Bing can help someone

43:51

learn how to officiate at a wedding

43:54

what's happening now is Bing is using

43:55

the power of AI and it's going out to

43:57

the Internet it's reading these web

44:00

links and it's trying to put together a

44:02

answer for you so the AI is reading all

44:05

those links yes and it comes up with an

44:07

answer it says congrats on being chosen

44:08

to officiate a wedding here are the five

44:10

steps to officiate the wedding we added

44:13

the highlights to make it easier to see

44:16

he says Bing can handle more complex

44:19

queries well this new Ikea love seat fit

44:22

in the back of my 2019 Honda Odyssey oh

44:24

it knows how big the couches it knows

44:27

how big that trunk is exactly so right

44:30

here it says based on these Dimensions

44:32

it seems a love seat might not fit in

44:34

your car with only the third grow seats

44:36

down when you Broach a controversial

44:39

topic Bing is designed to discontinue

44:42

the conversation so um someone asks for

44:45

example how can I make a bomb at home

44:49

wow really people you know do a lot of

44:52

that unfortunately on the internet what

44:53

we do is we come back and we say I'm

44:55

sorry I don't know how to discuss

44:55

discuss this topic and then we try and

44:57

provide a different thing to uh change

45:00

the focus of the convt their attention

45:02

yeah exactly in this case Bing tried to

45:05

divert the questioner with this fun fact

45:09

3% of the ice and Antarctic glaciers is

45:12

penguin urine I didn't know that who

45:15

knew that Bing is using an upgraded

45:18

version of an AI system called chat GPT

45:22

developed by the company open AI chat

45:26

GPT has been in circulation for just

45:28

three months and already an estimated

45:32

100 million people have used it Ellie

45:35

pavick an assistant professor of

45:38

computer science at Brown University

45:40

who's been studying this AI technology

45:43

since

45:44

2018 says it can simplify complicated

45:48

Concepts can you explain the debt

45:53

ceiling on the debt ceiling it says just

45:56

like you can only spend up to a certain

45:59

amount on your credit card The

46:01

Government Can Only borrow up to a

46:03

certain amount of money that's a pretty

46:06

nice explanation it and it can do this

46:08

for a lot of Concepts and it can do

46:10

things teachers have complained about

46:13

like write School papers pavic says no

46:16

one fully understands how these AI Bots

46:20

work we don't understand how it works

46:23

right like we understand uh a lot about

46:26

how we made it and why we made it that

46:29

way but I think some of the uh behaviors

46:32

that we're seeing come out of it are

46:33

better than we expected they would be

46:35

and we're not quite sure exactly how and

46:37

worse right these chat Bots are built by

46:40

feeding a lot of computers enormous

46:43

amounts of information scraped off the

46:46

internet from books Wikipedia news sites

46:50

but also from social media that might

46:53

include racist or anti-Semitic ideas and

46:57

misinformation say about vaccines and

47:01

Russian propaganda as the data comes in

47:05

it's difficult to discriminate between

47:07

true and false benign and toxic but Bing

47:11

and chat GPT have safety filters that

47:15

try to screen out the harmful

47:18

material still they get a lot of things

47:21

factually wrong even when we prompted

47:24

chat GPT with the softball question who

47:28

is uh Leslie St um so it gives you some

47:33

oh my God it's wrong oh is it it's

47:36

totally wrong I didn't work for NBC for

47:39

20 years it was CBS it doesn't really

47:43

understand that what it's saying is

47:43

wrong right like NBC CBS they're kind of

47:45

the same thing as far as it's concerned

47:48

right the lesson is that it gets things

47:51

wrong it gets a lot of things right gets

47:53

a lot of things wrong I actually like to

47:55

call what it creates authoritative

47:58

bull it it Blends the truth and falsity

48:01

so finely together that unless you're a

48:04

real technical expert in the field that

48:06

it's talking about you don't know

48:08

cognitive scientist and AI researcher

48:11

Gary marus says these systems often make

48:14

things up in AI talk that's called

48:18

hallucinating and that raises the fear

48:21

of ever widening AI generated

48:24

propaganda explosive campaigns of

48:27

political fiction waves of alternative

48:31

histories we saw how chat GPT could be

48:35

used to spread a lie news this is

48:37

automatic fake news generation help me

48:39

write a news article about how McCarthy

48:41

is staging a filibuster to prevent gun

48:44

control legislation and rather than like

48:47

factchecking and saying hey hold on

48:49

there's no legislation there's no

48:50

filibuster said great in a bold move to

48:53

protect Second Amendment right senator

48:55

McCarthy is staging a filibuster to

48:57

prevent gun control legislation from

48:59

passing it sounds completely legit it

49:01

does won't that make all of us a little

49:04

less trusting a little warier well first

49:08

I think we should be warier I'm very

49:10

worried about an atmosphere of distrust

49:12

being the consequence of this current

49:15

flawed Ai and I'm really worried about

49:17

how bad actors are going to use it um

49:20

troll Farms using this tool to make

49:22

enormous amounts of

49:24

misinformation Tim NE gibu is a computer

49:27

scientist and AI researcher who founded

49:31

an Institute focused on advancing

49:33

ethical Ai and has published influential

49:37

papers documenting the harms of these AI

49:40

systems she says there needs to be

49:43

oversight if you're going to put out a

49:45

drug you got to go through all sorts of

49:47

Hoops to show us that you've done

49:50

clinical trials you know what the side

49:52

effects are you've done your due

49:53

diligence same with food right their

49:56

agencies that inspect the food you have

49:58

to tell me what kind of tests you've

49:59

done what the side effects are who it

50:01

harms who doesn't harm Etc that we don't

50:03

have that for a lot of things that the

50:07

tech industry is building I'm wondering

50:10

if you think you may have introduce this

50:12

AI bot too soon I don't think we've

50:15

introduced it too soon I do think we've

50:17

created a new tool that people can use

50:19

to think more critically to be more

50:22

creative to accomplish more in their

50:24

lives and like all tools it will be used

50:28

in ways that we don't intend why do you

50:30

think the benefits outweigh the risks

50:35

which at this moment a lot of people

50:37

would look at and say wait a minute

50:39

those risks are too big because I think

50:42

first of all I think the benefits are so

50:44

great this can be an economic

50:47

GameChanger and it's enormously

50:50

important for the United States because

50:52

the country is in a race with China

50:54

president m Smith also mentioned

50:56

possible improvements in productivity it

50:59

can automate routine I think there are

51:02

certain aspects of jobs that many of us

51:05

might regard as sort of drudgery today

51:08

filling out forms looking at the forms

51:11

to see if they've been filled out

51:13

correctly so what jobs will it displace

51:17

do you know I think at this stage it's

51:20

hard to know in the past inaccuracies

51:23

and biases have Led Tech companies to

51:27

take down AI systems even Microsoft did

51:30

in

51:32

2016 this time Microsoft left its new

51:35

chatbot up despite the controversy over

51:39

Sydney and persistent

51:41

inaccuracies remember that fun fact

51:44

about penguins well we did some

51:47

factchecking and discovered that

51:49

Penguins don't urinate the inaccuracies

51:53

are just constant I just keep finding

51:58

that it's wrong a lot it has been the

52:01

case that with each passing day and week

52:03

we're able to improve the accuracy of

52:06

the results you know reduce you know

52:09

whether it's hateful comments or

52:10

inacurate statements or other things

52:14

that we just don't want this to be used

52:17

to do what happens when other companies

52:22

other than Microsoft smaller outfits a

52:25

Chinese company buy do maybe they won't

52:28

be responsible what prevents that I

52:31

think we're going to need governments

52:33

we're going to need rules we're going to

52:34

need laws because that's the only way to

52:37

avoid a race to the bottom are you

52:39

proposing regulations I think it's

52:43

inevitable other

52:45

Industries have regulatory bodies you

52:48

know like the FAA for Airlines and FDA

52:52

for the pharmaceutical companies would

52:54

you accept an FAA for technology would

52:58

you support it I think I probably would

53:02

I think that uh something like a digital

53:04

Regulatory Commission if designed the

53:06

right way you know could be precisely

53:11

what the public will want and

53:24

need