AI对就业市场的冲击与未来职业格局
Barat Chandra: 我们看到，暴露在AI影响下的工作岗位，年轻员工的就业增长速度放缓了16%。这相当显著。AI能力对劳动力市场的结构性改变，将不会是暂时的。如果我们真正解锁AI在帮助人们学习方面的能力，那么在不同职业之间转换将会容易得多。所以我真的希望，我们最终能更接近一个对劳动者更友好的“职业格子”体系，而不是“职业阶梯”，后者存在着更多的技术变革风险。
Original English
Barat Chandra: We're seeing that the jobs that are more
exposed to AI, the young workers in
those jobs are seeing 16% slower
employment growth. So that's pretty
large. The structural change in AI
capabilities that are impacting the
labor market, that's not going to be a
temporary change. If we really unlock
AI's capabilities for helping people
learn, it could be much easier to switch
between different professions. So I'm
really hopeful that we end up somewhere
closer to a career lattice that works
for workers as opposed to a career
ladder where there's much more risk
about this technological change.
Barat Chandra: 我是Barat Chandra，斯坦福数字经济实验室的经济学家，我研究AI如何影响工作。我想说，在过去一年半左右的时间里，我认为今天劳动力经济学中最重要的问题之一就是AI对劳动力市场的影响。
Original English
I'm
Barat Chandra. I'm an economist at the
Stanford Digital Economy Lab and I study
how AI is impacting work. I would say
over the past year and a half or so, I
do feel like one of the most important
questions in labor economics today is
about AI's impact on the labor market.
Barat Chandra: 一旦我真正开始更多地使用这些工具并理解了它们的能力，这便成为了我研究议程的焦点，因为它似乎是未来可能影响社会的、最重要的问题之一。
Original English
Once I really started using the tools
more and understood their capabilities,
that became the focus of my research
agenda because it felt like one of the
most important questions impacting
society potentially in the future.
Barat Chandra: 我与我的合作者Eric Bolson和Ryu Chen一起发布了一项研究，我们研究了暴露在AI影响下的工作与未暴露在AI影响下的工作，它们的工作方式是如何变化的。我们追踪了美国数百万工人，使用的是一家薪资公司ADP的数据。
Original English
I released a study with my collaborators
Eric Bolson and Ryu Chen. We studied how
jobs were changing in jobs that were
more exposed to AI versus less exposed
to AI. and we were tracking millions of
workers across the United States using
data from a payroll company called ADP.
Barat Chandra: 那里的一个关键发现是，总体而言，我们没有看到更多和更少暴露在AI下的工作在就业变化方面有 major 差异。然而，当我们聚焦于年轻工人时，我们确实看到了更多的分歧：暴露在AI下的工作，例如软件开发、客户服务、更多行政岗位，我们看到了就业下滑；而暴露在AI下的工作较少时，我们仍然看到一些持续的就业增长。而且，对于更有经验的工人来说，就业增长也基本处于正常趋势。
Original English
One of the key findings there is that
overall we were not seeing major
differences in employment changes for
jobs that were more and less exposed to
AI. However, when we focus on young
workers, we do see more of a divergence
there where the jobs that are more
exposed to AI, such as software
development, customer service, more
administrative roles, we were seeing
employment declines and jobs that were
less exposed to AI, we were still seeing
some continued growth and employment.
And for more experienced workers as
well, we were still seeing employment
growth that was pretty much on trend.
Barat Chandra: 我们看到，暴露在AI下的工作岗位，那些工作中的年轻员工的就业增长速度放缓了16%。很多人刚刚开始他们的职业生涯，却发现困难重重。我们之所以选择“Canaries in the coal mine”（煤矿里的金丝雀）这个标题，我认为与这种观点是一致的。我们希望追踪这些结果，因为我们认为它们可能预示着AI未来可能产生的变革性影响。
Original English
We're seeing that the jobs that are more
exposed to AI, the young workers in
those jobs are seeing 16% slower
employment growth. a lot of people just
starting off in their careers and
they're finding it a hard time in doing
that. And the reason we chose the
canaries and the coal mine title is I
think consistent with that view. We want
to be tracking these outcomes because we
think they could be indicative of
potentially future transformative
impacts of AI.
Barat Chandra: 这在多大程度上是由AI驱动的，以及它将如何改变？我们不能确定这只是经济中的暂时变化，还是AI驱动的结构性变化。现在，我们确实测试了一些我们能想到的最合理的替代方案。这包括利率变化。暴露在利率变化下的工作实际上受AI影响较小。一种思考方式是，交通和建筑业受利率变化影响很大，但它们受AI影响却不大。所以，这是一个关键点，这让我认为驱动我们结果的可能不是利率变化。我们测试的其他因素包括科技行业过度招聘。如果我们剔除科技行业，结果是相似的。剔除计算机工作。我们测试了这些不同的替代方案，结果仍然非常相似。所以，正如你所说，如果这是AI能力的一次结构性改变，那将不是暂时的变化。这可能是长期的变化。而且我们追踪的时间越长，如果这些趋势仍然成立，那么AI就有可能对工作产生影响。当然，我们没有一个实验可以比较一个有AI的世界和一个没有AI的世界，并进行清晰的比较。要真正区分AI的影响，确实还有很多工作要做。
Original English
How much of this is being
driven by AI and how is that going to
change going forward? We can't be sure
whether this is just temporary change in
the economy or if it's a structural
change being driven by AI. Now, we did
test some of the most plausible
alternatives that we could think of. So,
that includes interest rate changes.
Jobs that are more exposed to interest
rate changes are actually less exposed
to AI. One way to think about that is
things like transportation and
construction are very exposed to
interest rate changes, but they're
really not very exposed to AI. So,
that's one key thing and that makes me
think that it's probably not interest
rate changes that are driving our
results. Other things that we tested
include tech over hiring. So, we can
take out the tech sector, we get similar
results. Take out computer jobs. We
tested some of these different
alternatives and we were still getting
this very similar results. So, like
you're saying, if it's a structural
change in AI capabilities that are
impacting the labor market, that's not
going to be a temporary change. That's
potentially going to be a long run
change. And the longer that we can track
this and if those trends still seem to
hold up, that would be indicative of AI
potentially impacting work. Now, that
said, we don't have an experiment where
we can compare a world with AI to one
without AI and do a clean comparison.
There's definitely a lot more work to be
done here to really tease apart the
impact of AI.
Barat Chandra: 当你考虑年轻工人在进入劳动力市场时，他们所做的工作，很多是执行性的，依赖于他们在学校学到的书本知识。而他们不太有经验和能力去做的，是依赖于隐性知识，或者说只有通过实际工作才能获得的经验。还有更多的社交互动和更具战略性的思考。隐性知识，我认为是指那些依赖于高度本地化语境、战略性思考、社交互动，或者只能通过在职经验积累的方面。所以，这些是可能没有被写进书本里的东西。对于年轻工人来说，这与AI的能力直接重叠。而这些可能是经验更丰富的工人在面对AI时，以及与年轻工人相比时，可能拥有相对优势的情况。
Original English
If you think about what young workers
are doing when they're entering the
workforce, a lot of it is
implementation, doing things that rely
on the book knowledge that they learned
while they were at school. Whereas the
things that they don't have as much
experience with an ability to to do is
relying on the tacet knowledge or the
sort of experience that you can only get
by doing things on the job. also more
social interaction and more strategic
thinking. Tacid knowledge I think of as
things that rely on a lot of hyper local
context or strategic thinking or social
interaction or things that you only
build via experience on the job. So
those are the types of things that are
maybe not written down as much in a
book. For young workers, it's more
directly overlapping with the AI
capabilities. And those could be the
sort of situations where more
experienced workers might have a
relative advantage compared to AI and
also compared to young workers.
Barat Chandra: 在培训年轻工人方面，企业确实希望雇佣年轻人，如果他们希望未来有中层管理人员或更有经验的员工。现在的问题是，尽管他们有这样做的动力，以便未来有员工，但他们可能没有足够的动力。所以，他们可能不会像从社会角度看那样雇佣足够多的年轻人，也可能不会像他们应该的那样培训他们。原因在于，这些年轻人不必永远留在公司。他们可以去另一家公司。所以，确实他们仍然想雇佣其中一些人，但他们可能不想雇佣足够多对社会有益的人数。这就是个人私营公司的激励与整个社会的激励之间的一种错配。现在，我能给出的更乐观的看法是，如果AI真的能很好地帮助人们学习，并且作为一种教育工具，它可能会加速这一过程，这可能还需要我们组织教育系统的很多改变，可能在大学，甚至在更低的层级，以帮助人们更快、更好地学习。
Original English
When it
comes to training young workers, it's
totally right that firms will want to
hire young people if they want to have a
middle management or more experienced
staff going forward. Now the issue here
is even though that they have some
incentive to do that so that they have
workers in the future, they might not
have enough incentive to do that. So
they might not hire as much young people
as they should from a social perspective
and they might not train them as much as
they should. And the reason that's the
case is because those young people don't
have to stay at the company forever.
They can just go leave to another
company. So it's true that they will
still want to hire some of them, but
they might not want to hire as many as
would be beneficial to society. And it's
just kind of this mismatch between what
is the incentive of the individual
private company versus what is the
incentive of society as a whole. Now the
more optimistic take that I could give
here is that if AI really is as capable
of helping people learn uh and as a tool
for education maybe could speed up the
process at which that happens that could
also require a lot of changes in the way
that we organize our education system
potentially universities or even at a
lower level than that to help people
learn faster and better.
Barat Chandra: 我认为AI在短期到中期内，将不太擅长三件事：第一，体力劳动，除非我们在机器人领域有重大突破。第二，战略性思考和指导需要做什么。第三，社交互动。我认为战略性思考越来越重要，并且在未来可能会变得更加重要，因为未来的工作可能更多的是指导AI代理来执行任务，而你则指导它们应该做什么。所以，这种战略性思考，表达需要做什么，或者我想要什么被产出，我认为这将是一项相当关键的技能，这有点像公司里经理的角色。所以，这种管理工作和战略指导在未来可能会是一项相当重要的技能。当我想到年轻工人时，他们如何发展这些技能？尽可能多地构建和使用工具，并习惯于那种工作模式。越快发生，他们在适应劳动力市场动荡或这些技术变革方面可能就会越好。
Original English
There are three
things that I think AI is going to be
much less capable of doing certainly in
the short to medium term. One physical
tasks unless we see a big advance in
robotics. Number two is strategic
thinking and guiding what needs to be
done. And number three is social
interaction. I think the strategic
thinking is increasingly important and
it's going to be even more important
going forward potentially because it
does seem like in the future a lot of
work might look like guiding AI agents
to do implementation while you're
telling them and guiding them on what
needs to be done. And so that sort of
strategic thinking, expressing what it
is that needs to be done or what I want
to be produced, I think that's going to
be a pretty key skill and that's kind of
the role of what a manager does within a
company. So that sort of managerial work
and strategic guidance could potentially
be a quite important skill going
forward. When I think about young
workers, how can they develop those
sorts of skills? building and using the
tools as much as possible and getting
used to to that sort of mode of work.
The faster that that can happen, the
better that they might be uh in terms of
adjusting to labor market disruptions or
these technological changes.
Barat Chandra: 我确实认为，将AI与一些历史变革进行比较会很有帮助。例如，工业革命。我认为AI与那个时期的一个比较是，实际上是技能最熟练的工人面临着来自工业革命的更大风险。一个想到的例子是“Luddites”（卢德主义者），他们是那种熟练的纺织工人，而工业革命期间出现的新发明实际上导致了他们许多人失业，而他们是社会中技能更熟练的工人。你可能在这里看到一些相似之处，那就是知识工作者，在受教育程度更高的岗位上，可能面临更大的AI暴露风险。所以我认为这是一个有趣的比较。如果我们考虑电力或IT革命，那么在20世纪，情况恰恰相反，它更多的是中等技能或低技能工作更容易受到该技术的影响。而最熟练、受教育程度最高的人们则从这项新技术的发展中获益更多。所以，我们仍然需要看看未来，AI会更像第一种情况还是第二种情况？
Original English
I do think it's very helpful to compare
AI to some of these historical changes.
So for example, the industrial
revolution. I think one comparison
between AI and that period that was a
case where it was actually the most
skilled workers who faced more risk from
the industrial revolution. So one case
that comes to mind is the lites who were
these kind of skilled textile workers
and the new inventions that came about
during the industrial revolution
actually led a lot of them to lose their
work and those were kind of the more
skilled workers in society. Something
that you might be seeing that's kind of
similar here is that it's more of the
knowledge workers in more educated roles
that might be facing greater AI
exposure. So I think that's an
interesting comparison. If we think
about things like electricity or the IT
revolution, so basically over the course
of the 20th century, a lot of those were
actually kind of the opposite where it
was kind of this middle skill or
low-skilled work that tended to be more
exposed to that technology. Whereas the
most skilled, the highest educated
people benefited a lot more from the
development of this new technology. So
we still have to see going forward, is
AI going to look more like the first
case or the second case?
Barat Chandra: 我确实认为，这里有一个值得考虑的方面。AI可能与过去的历史事件不同的一个方式是，它的能力改进速度。即使是现在，它比三年前能够完成的任务要多得多，而且我认为存在这个问题：随着新工作的产生，对现有工作的需求增加等等，这些是由人类来完成，还是AI的能力会发展得足够快，以至于AI也会做那种工作？我认为这是我们可能认为AI可能不同于之前技术的一个领域。
Original English
I do think
there's something worth bearing in mind
here. So one way that AI might be
different than past historical episodes
is just the rate of capabilities
improvement. Even today it's much more
capable of doing different tasks than it
was 3 years ago and I do think there's
this question about as new work gets
created there's new demand for existing
work etc. Are those going to be done by
humans or are the AI capabilities going
to advance fast enough that AI is also
going to be doing that kind of work? And
I think that's the one area where we
could think that potentially AI could be
different than prior technologies.
Barat Chandra: 有很多讨论关于我们如何使用AI来增强工人，让他们过得更好，而不是潜在地仅仅用AI取代他们，自动化他们正在做的所有事情。我写这篇文章的目的是提出一个我个人认为可能在很大程度上增强工人的具体解决方案。那就是利用AI作为一种学习工具。我认为目前正在自我增强的例子，比如一个拥有精干团队的初创公司创始人，能够因为能接触到AI而完成更多任务。那些他们以前完全不知道如何做的事情，现在因为有了AI工具，他们自己就能做。我确实认为这是一个非常好的增强的例子。
Original English
There's been a lot of discussion about
how we can use AI to augment workers and
make them better off as opposed to
potentially just substituting them from
the workforce and automating all
everything that they're doing. Where I
was going with this essay is just trying
to suggest one concrete solution that I
think could potentially augment workers
quite a bit. It using AI as a tool for
helping people learn. I think an example
of a person who's augmenting themselves
with AI right now. An example of that
would be a startup founder with a really
lean team that's able to do a lot more
tasks because they have access to the
AI. All of the different functions that
previously they wouldn't have had any
idea how to do. Now they can do it
themselves because they have access to
these AI tools. I I think that's a very
good example in fact of augmentation.
Barat Chandra: 无论你更多的是被自动化还是被增强，这真的取决于你关注的任务是什么。你是增加了你可以做任务的范围，还是你的任务被这项技术引入所压缩了？我认为这件事可能很棒，在于当我们想到有益于工人的技术时，通常是增加了他们能做的任务范围。相比之下，那些自动化工作、替代工人的事情，是那些剥夺了工人一些需要做的工作，现在他们需要做的事情更少了。我认为目标是找到增强工人能力的方法，让他们能做更多事情。而历史上，我们知道最好的方法之一就是教育他们。通过教育，工人能够比以前做更多的事情。
Original English
Whether you're more automated or
augmented really depends on what are the
tasks that you're focusing on. Are you
increasing the scope of tasks that you
can do or are your tasks getting shrunk
by the introduction of this technology?
The reason that I think that this could
be wonderful in terms of augmentation is
that when we think about technology that
benefits workers, often it is increasing
the set of tasks that they're able to
do. In contrast, things that automate
work that substitute for workers, those
are things that take away some of the
tasks that workers have to do and now
they have to do fewer things. know I
think the goal is to try to find ways to
augment workers to make them more
capable of doing things. And one of the
best ways that we know historically for
doing that is by educating them. With
education, workers are able to do a lot
more than they could do before.
Barat Chandra: 我确实认为，这里有一个值得牢记的方面。AI可能与过去的历史事件不同的一个方式是，它的能力改进速度。而且我认为我们现在有一个机会，在学习能力方面迎来100年来甚至更长时间以来最大的变化之一。那就是使用AI工具进行个性化学习。对我来说，使用AI进行增强，有几个分支。我越来越多地使用它来做数学。在一些我可能需要写下模型或证明某事的地方，它非常非常擅长。它的增强方式是，检查某事是否正确比从头写出来更容易。所以我认为这是一种重要的增强我工作的方式。
Original English
I do
think there's something worth bearing in
mind here. So one way that AI might be
different than past historical episodes
is just the rate of capabilities
improvement. And I think we have an
opportunity right now for one of the
biggest changes in learning capabilities
that we've had in 100 years if not
longer. And that's in using the AI tools
for personalized learning. For me, using
AI for augmentation, there's a couple
branches to that. And something that
increasingly I'm using it for is
actually for math. There are areas where
I might need to write down a model or
prove something. And it's really, really
good at that. The way that that's
augmenting is that it's easier to check
if something is correct than it is to
necessarily write it from scratch. And
so I also potentially view that as a as
a significant way of augmenting my work.
Barat Chandra: 另一方面，我不用AI做的事情，我个人不怎么用它来写作。我不使用它写作的原因是，写作可以帮助我思考，并且当我自己写作时，我能很好地理解一个问题。并不是我不信任AI工具来写作。更多的是，如果我不自己动手并理解我在说什么，我将从写作中获得的价值会少得多。
Original English
Now, on the other hand, things that I
don't do with AI, I personally don't
really use it for writing. And the
reason I don't use it for writing is
that writing helps me think and it helps
me understand a problem really well when
I do it myself. It's not that I don't
trust the AI tools to do the writing.
It's more that I would get way less
value out of the writing if I didn't do
it myself and understood what it was
that I was talking about.
Barat Chandra: 我认为在决定我们要委托什么给AI，以及什么要保留给人来做时，我认为这很大程度上取决于人类想要什么，其中一部分是关于价值观，比如什么是对的，什么是错的。其中一部分也是表达我们的偏好。那么，我们想建造什么？什么能让我们过得更好？什么能让我们更快乐？我们会真正想用AI来做什么样的实施工作？那是我们需要向AI表达的。我认为这些任务，至少在短期到中期内，并不明显如何被自动化，因为其中一部分也取决于我们的反思。我们需要仔细考虑我们想要什么。有时我们会通过反思和更深入的思考来了解我们想要什么。所以，关于我们应该构建什么，我们应该实施什么的指导，我认为至少在短期到中期内，这更具有人类特质，而不是AI。而我把AI更多地看作是实施方面。
Original English
I think in
deciding what we want to delegate and
what we want to preserve as human, I
think a lot of that depends on what it
is that humans want and some of that is
about values like what is right, what is
wrong. Some of that is also just
expressing our preferences. So what do
we want to build? What would make us
better off? What would make us happier?
What are the things that we would
actually want to use AI for for
implementation? That's something that we
have to express to the AI. I think those
sorts of tasks, it's not obvious to me
how that's going to be automated, you
know, in the short to medium term at
least because some of that both it
depends on also our reflection. We need
to think through what it is that we
want. Sometimes we learn about what it
is that we want as we reflect on it and
as we think more about it. And so that
guidance about what it is that we should
build, what it is that we should
implement, that I view as at least in
the short to medium term being more
characteristically human than AI. And I
view the AI is more on the
implementation side.
Barat Chandra: 想象一下，如果AI真的降低了学习新东西的好处。有趣的是，在那个世界里，劳动力市场的不平等可能大大降低。如果进入一个领域的顶端，或者在一个给定职业中获得最高质量产出的障碍大大降低，因为AI可以完成很多最困难的任务，那么那实际上是一个不平等可能更低的世界，因为那些在学校里懂很多并且能力很强的人，可能与那些在学校里不那么努力的人之间，差别不会那么大。这有点有趣，因为在不平等和学习投资之间存在一种潜在的权衡。另一方面，如果AI真的增加了这种战略性思考，甚至社交技能等的益处，那么它实际上可以增加努力学习的好处，因为如果我能发展出战略性思考技能，那么我在劳动力市场上就会非常有价值。
Original English
Imagine that AI really reduces the
benefits of learning something new. An
interesting thing about this is that
that's a world where potentially
inequality is much lower in the labor
market. If the barriers to getting at
the top of a field or getting the
highest quality output in a given
occupation or something, if that barrier
becomes much lower because AI can do a
lot of the hardest tasks, then that's
actually a world where potentially
inequality is lower because the
difference between people who know a lot
in school and are very capable could be
not that different from people who don't
try that hard in school. It's kind of
interesting because there's this
potentially trade-off between inequality
and investments in learning. On the
other hand, if AI really increases the
benefits of this sort of strategic
thinking, even these social skills,
etc., that could actually increase the
benefits of trying really hard in school
because if I can develop the strategic
thinking skills, then I'll be really
valuable in the labor market.
Barat Chandra: 我会鼓励年轻人，学生们，尽可能多地使用AI工具，用它们来构建，并真正专注于发展那种战略性思考。你如何最好地利用这些工具？它们不太擅长的地方在哪里，而作为人类，你能在哪些方面增加很多价值？我认为有一些非常复杂的方式来思考AI未来可能如何影响思维。这里有一些新的干预措施，比如使用AI的教育模式，让人们专注于批判性思维技能，而不是仅仅卸载任务。所以，有不同的平台。我知道，例如，Khan Academy有一个工具，你可以使用AI工具，但它不会直接给你答案，它会帮助你思考如何找到答案，而不是直接给出。
Original English
I would encourage young people, students
to use the AI tools as much as they can
uh build with them and really focus on
developing that kind of strategic
thinking. How do you best make use of
these tools? Where are the areas where
they're not as good and what are areas
in which you as a human can add a lot of
value? I think there are some very
complicated ways of thinking about how
AI might affect thinking going forward.
There are some newer interventions that
are happening here uh education style
modes with AI usage to make people focus
on the critical thinking skills as
opposed to just offloading the task. So
there are different sort of platforms. I
know uh Khan Academy for example has one
where you can use the AI tool but it's
not going to give you the answer. It's
going to help you think through how to
get to the answer as opposed to just
giving it to you off the bat.
Barat Chandra: 我确实认为，我们可以想象一个未来世界，如果我们真正解锁了AI帮助人们学习的能力，那么根据需求随时间演变的情况，在不同职业之间转换将会容易得多。如果某个工作在经济中变得更加重要，如果我们能找到一种帮助人们更快过渡的方法，那将真正释放出巨大的潜力。所以我真的希望，我们最终能更接近一个对劳动者更友好的“职业格子”体系，而不是“职业阶梯”，后者存在着更多的技术变革风险。
Original English
I do think
that we could imagine a world in the
future where if we really unlock AI's
capabilities for helping people learn,
it could be much easier to switch
between different professions based on
how demand for those jobs is evolving
over time. And if some uh job becomes
much more important in the economy, if
we can find a way to help people
transition faster, that could really
unlock a lot of potential. So I'm really
hopeful that we end up somewhere closer
to a career lattice that works for
workers as opposed to a career ladder
where there's much more risk about this
technological change.
个人对AI的认知转变与教育的未来
Ken Ono: 有史以来第一次，我很难提出ChatGPT会出错的问题。我曾感到沮丧，想着我该如何保持在AI的前面？我实际上认为那是错误的问题。
Original English
For the first time I struggled to
assemble questions that chat GPT would
get wrong. I was devastated was thinking
how am I going to stay ahead of AI? I
actually think that's the wrong
question.
Ken Ono: 我是Ken Ono，一名数学家，我也在AI for Math领域工作。我是弗吉尼亚大学的教授（休假中），也是Axiom Math的创始数学家。我对智能的看法现在已经改变了很多。我们这个世界在教育孩子方面做得还不够好。我这么说不是批评教育工作者，我本人就是一名教育工作者。
Original English
My name is Ken Ono. I'm a
mathematician and I also work in the
space called AI for math. I'm a
professor at the University of Virginia
on leave and I'm the founding
mathematician at Axiom Math. My view on
intelligence now has changed quite a
bit. We in this world aren't doing the
best we can at educating our children.
And I don't say that to be critical of
educators. I am an educator.
Ken Ono: 参观幼儿园班级，在“家长带我上学日”总是很有趣，这样他们就可以谈论他们做什么了。哦，我认识所有的质数，或者我真的擅长加法。我希望保留这种好奇心和孩子们在一切事物都是新事物时的那种活力。想想看，我们今天会在哪里？
Original English
It's always
a treat to visit a kindergarten class, a
first grade class when it's bring your
parent to school day so they can talk
about what they do. Oh, I know all the
prime numbers or I'm really good at
adding that wonder and I want to just
bottle up this energy because if we
could maintain that wonder in the world
and the energy that children have when
everything around them is new. Think
about where we would be today.
Ken Ono: 成为像Romanagen那样的人，或者至少在富有成效的方式上富有创造力的能力和潜力，我认为它存在于我们所有人身上。你的身份由谁拥有？你拥有。
Original English
The ability and the potential to be someone
like Romanagen or at least creative in a
productive way. I think it resides in us
all. Who owns your identity? You do.
📌 文中提及的人物和组织
人物: Barat Chandra, Ken Ono
公司/组织: Stanford Digital Economy Lab, Axiom Math, ADP, Khan Academy
产品/模型: ChatGPT