This was one of the most read stories on Bloomberg in the last 24 hours.
There's no surprise about that. It has all of the facets of a story that
we didn't, you know, just engage our audience on Bloomberg Technology.
Let's get specifics. Why only 5% of jobs and which sectors
and industries. Are you basing your thesis on?
Well, thanks, Ed. It's great to be on the program.
I think, right now. There is a lot of potential.
Excitement, perhaps hype about A.I., but if you look at its current capabilities.
You know, we are very far from. I either generative AI or other types of
AI performing any of the tasks that involve a heavy level of interaction
with the physical world construction, work,
manufacturing, work, carpentry. Those perhaps one day will be much more
feasible. For example, if A.I.
becomes so much more advanced, so much more reliable, and can be integrated
with so much better robots, for instance.
But it's not something that's going to happen in the next five or ten years.
Now there's a lot of other. Potential for future A.I., perhaps to
perform some social topics. But those are not going to be possible
right now either. You know, you're not going to go to an
air psychiatrist anytime soon. So if you forget about all of these,
you're not going to be left with much more than 5% of the economy.
Professor, may I jump in and push back with a point raised by our audience when
I said you were coming on, which is that technology is exponential, much in the
way that the invention of electricity with time led to all sorts of
breakthroughs. Right now you're saying 5% of jobs, but
in two years or five years from now, would you need to rethink your thesis or
redo your calculations? I should have preface this by saying
there's a huge amount of uncertainty in any forecasts about I and apologies that
I didn't do that. I try to do that all the time.
I was very excited. I just jumped into it.
There's a huge amount of uncertainty and one source of uncertainty is exactly
what's going to happen with AI in the next several years.
I don't think that the most optimistic views in the industry, which sometimes
people refer to as scaling laws, actually will hold water.
When you look at it within the next five years or ten years, which say, you know,
just double the amount of data that will the amount of compute power.
And now you're going to get double the amount of capabilities because.
We to do that, we would actually need higher quality data.
So if you want I do the job of a carpenter, you really need a completely
different kettle of fish when it comes to the kinds of data and something like
that might be feasible with a different architecture of AI.
But right now all of the money is going into the sort of the basic dominant
architecture which has its limitations, both in terms of reliability, in terms
of high level reasoning. So that's the basis of my belief that of
course generative AI and other types of AI will improve, but we're not going to
see a qualitative jump within the next 5 to 10 years professing your belief.
What is exactly it based on what data, what historical norms are you looking
back on to drive and push forward on this 5% take?
Yeah, I think this is why there is so much uncertainty.
There's nothing that's identical to generative AI in the past, and that's
part of the reason why people can hold very different beliefs.
But what I'm basing that on is, first of all, other waves of digital technologies
that promised a lot of automation, sometimes a lot of productivity
improvements, sometimes a lot of changes in the way that we would organize our
offices and things like that. And at the end, all of those changes
have been very gradual. And also what we have seen over the last
two and a half years where, you know, there have been advances, but the
advances haven't really been sort of qualitative in nature.
They haven't really exceeded the sort of the basic capabilities of GPT 3.5 or
3.4. So there will be advances, but I don't
think any of those advances will very quickly change the way that we do
various tasks in the economy. So for example, I do not believe that in
five years time when we look at the labor market, we're going to see certain
occupations that will have completely disappeared.
But many would say that they would be augmented.
The idea is perhaps the optimist view is we will not lose lots of people from the
labor force, but that productivity will be scaled.
Well, I think that's a yes no. I think that's a very, very interesting
and important point. I am not an AI denier or an AI
pessimist. I actually believe A.I.
has a lot of potential. And in fact, the real potential is
exactly what you said, Caroline, which is that A.I.
becomes a tool for workers to boost their productivity.
And again, we're seeing some of that happening.
You know, Microsoft has a lot of co-pilots, you know, some of them work
and they give some productivity improvements.
There are a few areas where we're seeing really phenomenal improvements, like,
for example, if you want to write simple subroutines in one of the common
programming languages, you know, GPT four is great before and GitHub copilot
was pretty good. So there are some things in which that
sort of help to decision makers as possible.
But again, when you look at the whole economy, that means helping carpenters,
electricians, plumbers, blue collar workers, construction workers, transport
workers, people who are doing teaching, people who are doing journalism, those
are things that could be achieved perhaps at some point.
But the reliability and the reasoning of the models is not up to the task yet.
Do you see specific job creation in specific industries for me?
I. Well, there is one class of jobs where
the AI is leading a big boost, which is people who have AI fluency, either
people who are AI programmers, A.I. integrators or other AI related service
activities. But in my research, albeit with a a from
a previous way, will be AI. In the late 2010, we didn't see any
other job category get a boost in terms of hiring.
And there are some other jobs that I think there will be some retrenchment.
So if you're in IT security and you're doing the routine end of I.T.
security, there will be declines in job vacancies in that area because some of
these A.I. tools can actually perform that quite
well. When you see the headline that open air
is worth $157 billion, when you see that in video is now worth almost 3 trillion.
What do you make of that in terms of how truly the capital markets are analyzing
the growth here? Well, I think there's a difference
between Nvidia and Openai, and Vidya is riding a wave, which is based on the
belief that those chips are going to become more valuable because generative
AI and other types of AI are going to continue to boom.
But they are generating revenues. Openai, on the other hand, I think does
hasn't found a revenue model that could justify the types of valuations we are
seeing at the moment. Now, it may well be that in the future
suddenly their API is going to be so valuable and other firms are going to
start building on it. But it doesn't seem like there are the
kinds of applications that can have deep impact on the productivity of workers,
on automation, of firms that are going to be sold within the next five years,
ten years. So I'm a little bit skeptical.
But on the other hand, Openai is also emerging as the market leader in the
current ecosystem in the digital world is right.
Firms that take over the market and they can use all of the data, they can, you
know, interact with the consumers or the programmers directly.
Those have become very valuable because of venture capital or other deep
pocketed funders.