Why are we trying to build AI systemsthat are duplicative of humans? They
said that we should be building AGI, sowe say that we should be building AGI,but I would like to ask like why are we
doing that? Why is it that we are
building a technology that is ultimatelydesigned to replace and automate peopleaway? We should be building technology
and the purpose of technology throughouthistory has been to improve humanflourishing, not to replace people. Is
this the right goal? What like why are
we doing this? Why can't we just build
AI systems, which are systems that havenothing to do with the statisticalengines that they're trying to build to
duplicate the human brain?
>> That might be the most uncomfortablequestion I've heard about AI this year.Not can AI become smarter than humans,
not will AI destroy humanity, butsomething much simpler. Why are wetrying to build machines that replacepeople instead of helping people? Think
about it for a second. When cars wereinvented, they helped us travel faster.When smartphones became common, they
connected us to the whole world.Technology has always been about givinghumans more power, but for the first
ime, millions of people are asking acompletely different question. Whathappens when technology starts replacing
the person instead of just helping theperson? And that's exactly why I wanted
to react to this podcast. A 2-hourconversation between Steven Bartlett andjournalist Karen Hao, a woman who spent
8 years and over 300 interviewsinvestigating what's really happeninginside companies like OpenAI.And I need to be honest with you. Some
of what she says made me angry. Some ofit made me question things I use everyday, and one part about a small town in
Tennessee genuinely disturbed me.Let's walk through it and give my honestopinion about it.I want to give you some background first
because you can't understand the fightwithout understanding the field.>> So, this was back in 1956and [music] there were a group of
scientists that gathered at DartmouthUniversity to start a new discipline, ascientific discipline, to try and chase
an ambition. And specifically, anassistant professor at DartmouthUniversity, John McCarthy, decided to
name this discipline artificialintelligence.This was not the first name that hetried. The previous year, he tried to
name it Automata Studies. And the reasonwhy some of his colleagues wereconcerned about this name was because it
pegged the idea of this discipline torecreating human intelligence.>> His colleagues were deeply concerned
about the term artificial intelligencebecause it tied the field to the goal ofrecreating human intelligence. Both then
and now, there is absolutely noscientific consensus on what humanintelligence actually is. There is nosingle definition from biology,
psychology, or neurology, which means,as Karen points out, when today's AIcompanies talk about building AGI,
artificial general intelligence, they'rechasing a finish line that literallydoesn't have fixed coordinates.
>> Well,there are no goalposts for this field,and there are no goalposts for theindustry when they say that they are
ultimately trying to recreate AI systemsthat would be as smart as humans. How dowe even define what that means? And when
are we going to get there if we don'tknow how to define the destination?
>> Karen shows how OpenAI has redefined AGIdepending on who's in the room. When SamAltman talks to Congress, AGI is the
thing that will cure cancer, solveclimate change, cure poverty. When he'selling to regular customers like us,
it's the most amazing digital assistantyou'll ever have. When Microsoft waswriting the investment contract, AGI was
legally defined as a system thatgenerates $100 billion in revenue.>> They can use it however they want to,and they can define and redefine it
based on what is convenient for them.So, in OpenAI's history, it has definedand redefined it many times. When Sam
Altman is talking with Congress, AGI isa system that's going to cure cancer,solve climate change, cure poverty. When
he's talking with consumers that he'strying to sell his products to, it's themost amazing digital assistant that
you're going to ever going to have. Whenhe was talking with Microsoft, you know,in the deal that OpenAI and Microsoft
struck where Microsoft invested in thecompany, it was defined as a system thatwill generate a hundred billion dollars
of revenue. And on OpenAI's own website,they define it as highly autonomousystems that outperform humans in most
economically valuable work. This is likenot a coherent vision of one technology.These are very different definitions
that are spoken out loud to the audiencethat needs to be mobilized to ward offregulation or get more consumer buy-in
to the the industry's quest.>> Read that again. Same three letters,completely different meaning depending
on who needs convincing. I don't thinkthat's a coincidence. I think that's astrategy.Here's the clip that genuinely made me
sit up.>> In 2015,in a blog post that Sam Altman wrotebefore OpenAI was officially announced,he explicitly outlined the existential
risk by saying, "Development ofsuperhuman machine intelligence isprobably the greatest threat to thecontinued existence of humanity. There
are other threats that I think are morecertain to happen, for example, anengineered virus,but AI is probably the most likely way
to destroy everything.">> Back in 2015, before OpenAI officiallyexisted, Sam Altman wrote a blog posthat said, and I'm paraphrasing
carefully here, that a superhuman AI wasprobably the single biggest threat tohumanity's survival, bigger than almost
anything else.Karen's reporting shows that Altmanwrote that specific line right aroundthe time he was trying to convince Elon
Musk to co-found OpenAI with him. AndMusk, at that exact same time, was doingfamous talks, including one at MIT,
where he compared building advanced AIto summoning the demon.>> And so, in that blog post, if you lookat the the language that Altman uses
ide by side with the language that Muskwas using at the time, it mirrors theall the things that Musk was saying.
>> Yeah.>> years ago Musk was going on podcastsaying, tweeting, whatever, that thegreatest existential risk to humanity
was AI.>> Musk did end up co-founding OpenAI. Healso ended up leaving, and by his ownaccount, feeling used. The two are now
suing each other.But this next part is where Karen'sreporting feels like something you needto actually know before you open your
chatbot app again.>> And that is why I call these companiesempires of AI.>> What do you mean by an imperial agenda?
What What does that term mean?
>> Empire is the only metaphor that I've[music] ever found to fully encapsulateall of the dimensions of what these
companies do,and the scale that they operate, andwhat motivates them to do what they do.And there are many parallels that you
see between what I call the empires ofAI and the empires of old.>> Karen's whole book rests on one boldclaim: These are not just companies. She
calls them empires of AI, and she laysout four specific parallels to empiresof old. One, resource grabbing.
She says these companies lay claim toresources that aren't theirs, thepersonal data of ordinary people, the
intellectual property of artists andwriters, and land for building massivecomputing facilities. Two, labor
exploitation.Hundreds of thousands of workers aroundthe world, including in the US, arecontracted to help build these systems,
often in ways that quietly strip awaylabor protections once the tools aredeployed.Three, controlling knowledge.
These corporate empires project thefalse narrative that they are the onlyones pure enough or smart enough to
understand and guide AI safely. Theyactively gaslight the public and policymakers. Even worse, they spend hundreds
of millions of dollars to kill publicsafety legislation and ruthlessly censorany internal researchers whose findings
threaten their corporate profits.Take the case of Dr. Timnit Gebru atGoogle.She was hired to lead an ethical AI
team. But when she co-authored abrilliant paper highlighting the severebiases and environmental harms of large
language models, Google executives triedto suppress it and ultimately fired herand her co-lead, Margaret Mitchell.
Four, myth-making. This is the one thatgot me. Karen says these companies needthe public to believe two things at
once.That AI could be catastrophic and thatit could bring utopia. Why both? Because
if it's dangerous, only they should betrusted to control it. And if it'sutopian, we should hand them our trust,
our data, and our money to get therefaster. Here's a real quote she bringsup from 2017.>> the record on podcasts in their blog
posts to see how it's evolved over time.And Dario, who was the former VP ofresearch at OpenAI, and has now moved on
to Anthropic, who are taking a slightlydifferent approach to developing AI,said back in 2017 while he was still at
OpenAI, that I think at the extreme endis the Nick Bostrom style of fear thatan AGI could destroy humanity. I can't
see any reason in principle why thatcouldn't happen. My chance thatsomething goes really quitecatastrophically wrong on the scale of
human civilizationmight be somewhere between 10% and 25%.>> 10 to 25%. Read that number again.That's not a fringe blogger. That's a
man now running one of the most fundedAI labs on Earth.I thought the empire argument was themost shocking part of this conversation.
I was wrong. The next section about asmall community in Tennessee is the parthat actually stayed with me overnight.
We talk about AI like it lives in thecloud, like it's weightless. It is not.>> OpenAI's largest, one of its largest
data center projects, is being built inAbilene, Texas as part of the Stargateinitiative, which was an effort
announced at the beginning of Trump'second administration to spend $500billion on AI computing infrastructure.
That one would be the size of CentralPark.And it would run a million computerchips, and it wouldrequire the power of more than 20% of
New York City.>> Then there's a meta facility being builtin Louisiana that's reportedly fourtimes the size of that Texas one, using
about half the average power demand ofthe entire city of New York.Karen talks about Memphis, Tennessee,where Elon Musk built Colossus, the
supercomputer used to train Grok,powered partly by 35 methane gasturbines.The community living there, a working
class, reportedly wasn't formally toldthey'd be hosting this facility.According to Karen, residents first
realized something had changed when theysmelled what seemed like a gas leakinside their own homes.That community, she says, already has
ome of the highest rates of asthma andrespiratory illness in the area.Now add industrial-scale gas turbines
running next door, 24 hours a day, topower a machine most of those residentswill never directly benefit from.
And in a cruel twist, the same wave ofautomation this facility helps build isalso the thing most likely to replace
the jobs many of them do.I want to be fair here, because I thinkit matters. AI data centers also createconstruction jobs, local tax revenue,
and in some cases genuinely usefultechnology for medicine and science.This isn't a simple villain story.
Karen says these companies pick some ofthe most vulnerable communities forthese projects. And when you look at
where facilities like this actuallyland, it's hard to call that acoincidence, either.Now, here's the part where you might
expect me to just tell you to log offand boycott AI forever.That's not what Karen says. Her answeris more interesting and honestly more
useful.Karen's suggestion isn't delete every AIapp. It's smarter than that. She callsall of us data donors, meaning every
time we use these tools, we're feedingthe very systems these companies need tokeep growing. Her point, you have more
leverage than you think. She lists a fewconcrete things, and I want to walkthrough them simply. Withhold what you
can. Artists and writers suing thesecompanies over their work are, in herwords, trying to withhold the resource
these companies need most, originalhuman data. Get loud locally.>> And that's what we've seen with all ofthese people that are now literally
protesting the streets against datacenters and having an enormous effect,by the way, actually stalling data
center projects and also completelybanning data centers from beingdeveloped in their localities.>> She points out that data centers are
popping up in ordinary towns right now,and in several places, local communitieshave already succeeded in stalling or
outright banning new data centerprojects through public pressure. Pushat your school or workplace.If your company or university is
drafting an AI adoption policy, thatconversation is one small piece of amuch bigger puzzle, and your voice in
that room genuinely counts. Supportalternatives.Karen says there's research showing thesame useful AI capabilities can be built
with far more efficient methods and farless resource consumption, what shecalls the bicycles of AI as opposed to
the resource-hungry rockets.She also cites a striking number.>> 80% of Americans in the most recent pollthink that the AI industry need to be
regulated.>> Yeah, I see.>> When was the last time that 80% ofAmericans were on the same side of anissue?
>> A shift she says happened largelybecause of stories like the ones in herbook reaching the public. I want to end
this fairly because Karen herself does.Late in the conversation, Steven pushesback a little saying that as an
entrepreneur and investor, he genuinelyfinds AI incredible. Safer driving,tools that help him create things he
couldn't before. Real value for over abillion users. And Karen doesn't dismissthat. Her answer is basically, you can
hold both truths at once.AI can be genuinely useful and thecurrent way it's being built and rushedto market can be genuinely harmful.
Those aren't contradictions. They're twohonest observations about the sameindustry. That's actually the most
balanced moment in the whole two hours.And it's the note I want to end on, too.So, here's my question for you and I
genuinely want to know. Knowing what younow know about where the water for yourchatbot's training run might be coming
from, does it change how you'll usethese tools tomorrow? Not never. I'm not
asking you to swear off technology. Justpay attention. Ask questions.Support the version of AI that doesn't
need a small town in Tennessee to smellgas in their living room to make itwork. If this made you thinkdifferently, even a little, share it
with one person who uses AI every daywithout ever asking these questions.That's genuinely how change like this
tarts.