トランスクリプトEnglish

AI Whistleblower: We Are Being Gaslit By AI Companies, They’re Hiding The Truth! - Karen Hao

2h 9m 11s23,485 単語3,558 segmentsEnglish

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0:00

So much of what's happening today in the

0:02

AI industry is extremely inhumane.

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>> But this is me playing devil's advocate.

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And logically, it could be the case that

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the civilization that accelerate their

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research with AI is going to be the

0:12

superior civilization.

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>> No, it's not. This is a prediction that

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you're making, right?

0:15

>> Making Zuckerberg's making.

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>> And do you know what the common feature

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of all of them is? They profit

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enormously off of this myth. You know, I

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have all these internal documents

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showing that they're purposely trying to

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create that feeling within the public so

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that they can extract and exploit and

0:30

extract and exploit. So, what do we do

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about it?

0:32

>> We need to break up the empires of AI.

0:35

>> You know, I've been covering the tech

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industry for over 8 years, interviewed

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over 250 people, including former or

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current OpenAI employees and executives.

0:42

And I can tell you that there are many

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parallels between the empires of AI and

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the empires of old, right? like Lelay

0:48

claimed the intellectual property of

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artists, writers, and creators in the

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pursuit of training these models.

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Second, they exploit an extraordinary

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amount of labor, which breaks the career

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ladder because someone gets laid off and

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then they work to train the models on

1:00

the very job that they were just laid

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off in, which will then perpetuate more

1:03

layoffs if that model then develops that

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skill. And when they talk about that

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there's going to be some new jobs

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created that we can't even imagine, a

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lot of the jobs that are created are way

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worse than the jobs that were there. And

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then there's the environmental and

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public health crisis that these

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companies have created and how they're

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able to also spend hundreds of millions

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to try and kill every possible piece of

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legislation that gets in their way and

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will censor researchers that are

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inconvenient to the empire's agenda. But

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what I'm saying is not that these

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technologies don't have utility. It's

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that the production of these

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technologies right now is exacting a lot

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of harm on people. But we have research

1:39

that shows that the very same

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capabilities could be developed in a

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different way that doesn't have all of

1:46

these unintended consequences. So let's

1:48

talk about all of that.

1:53

This is super interesting to me. My team

1:54

given me this report to show me how many

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of you that watch this show subscribe.

1:57

And some of you have told us according

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to this that you are unsubscribed from

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all of you. Please could you check right

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now if you've hit the subscribe button

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approaching quite a significant landmark

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team, everyone here to keep this show

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free, to keep it improving year over

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year and week over week, it is just to

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I'll make sure every single week, every

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single month, we fight harder and harder

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D of Sio and I will not let you down.

2:40

Please help us. Really appreciate it.

2:42

Let's get on with the show.

2:47

Karen, how you've written this book in

2:50

front of me here called Empire of AI:

2:52

Dreams and Nightmares in Sam Alman's

2:55

Open AI. I guess my first question is

2:58

what is the research and the journey you

3:00

went on in order to write this book

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we're going to talk about and the

3:03

subjects within it today

3:04

>> I took a strange route into journalism I

3:07

studied mechanical engineering at MIT

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and so when I graduated I moved to San

3:11

Francisco I joined a tech startup I

3:13

became part of Silicon Valley and I

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basically received an education in what

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Silicon Valley is about because a few

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months into joining a very missiondriven

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startup that was focused on building

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technologies that would help facilitate

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the fight against climate change. The

3:27

board fired the CEO because the company

3:29

was not profitable. And this was in

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hindsight a very pivotal moment for me

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because I thought if this hub is

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ultimately geared towards building

3:40

profitable technologies and many of the

3:43

problems in the world that I think need

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solved are not profitable problems like

3:47

climate change. Then what are we

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actually doing here? like what how did

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we get to a point where innovation is

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not actually necessarily working in the

3:57

public benefit and sometimes even

3:58

undermining the public benefit in

4:00

pursuit of profit. In that moment, I had

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a bit of a crisis where I thought, well,

4:06

I just spent 4 years trying to set

4:10

myself up for this career that I now

4:11

don't think I am cut out for. And I

4:16

thought, well, I might as well just try

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something totally different. I've always

4:20

liked writing and that's how after 2

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years I landed at a role at MIT

4:26

technology review covering AI full-time

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and that gave me a space to then explore

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all of these questions of who gets to

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decide what technologies we build how

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does money and ideology also drive the

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production of those technologies and how

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do we ultimately make sure that we

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actually reimagine the innovation

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ecosystem to work for a broad base of

4:48

people all around the world. And so that

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is kind of how I then set off on this

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journey of ultimately writing a book. I

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didn't realize that I was working

4:58

towards writing a book, but starting in

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2018 when I took that job was

5:04

essentially the moment in which I began

5:06

researching the story that I I document

5:08

in it.

5:09

>> A very timely time to start working in

5:11

artificial intelligence. For anyone that

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doesn't know, this is pre OpenAI chat

5:14

GPT launch moment that shook the world.

5:19

But in writing this book, you

5:20

interviewed a lot of people and went to

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a lot of places. Can you give me a

5:22

flavor of how many people you've

5:24

interviewed, where it's taken you around

5:26

the world, etc.

5:27

>> I interviewed over 250 people. So over

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300 interviews, over 90 of those people

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were former or current OpenAI employees

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and executives. So the book covers the

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inside story of opening eyes's first

5:40

decade and how it ultimately got to

5:42

where it is today. But I didn't want to

5:45

write a corporate book. I felt very

5:47

strongly that in order to help people

5:49

understand the impact of the AI

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industry, we would also have to travel

5:54

well beyond Silicon Valley. These

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companies tell us that AI is going to

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benefit everyone and that's their

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mission. But you really start to see

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that rhetoric break down when you go to

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the places that look nothing like

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Silicon Valley, that speak nothing like

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Silicon Valley, and that have a history

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and culture that are fundamentally

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different as well. And that's where you

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start to really understand the true

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reality of how this industry is

6:21

unfolding around us.

6:22

>> Karen, I often try and steer

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conversations, but in this situation, I

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feel like it's probably my

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responsibility to follow. So with that

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in mind, I'm going to ask you where does

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this journey begin and where should we

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be starting if we're talking about the

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subjects of empire of AI, AI generally

6:38

artificial intelligence and also I'd say

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one thing I'm really keen to do in this

6:42

conversation which is I often see in

6:43

conversations is left out is let's

6:46

assume that our viewers know nothing

6:47

about AI.

6:48

>> Yeah. So they don't know what scaling

6:50

laws are or GPUs or comput or whatever

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