So, Azeem, great to see you here in Davos.
It's a little bit chilly.
It's chilly, but it's wonderful to be here.
Your company is warming me up.
That's great to hear.
But finally we meet in person tons of activity.
You're my go to AI guru.
Thank you.
What are you seeing out there in terms of '24?
Any big surprises?
Did anything change for you as you with incoming perceptions
versus what you're hearing and as you look at '24?
Well, the big surprise for me has been hearing directly from
company bosses about how they're using AI, both at a dinner that
you hosted, but also in the official annual meeting.
I'm surprised at how far large companies are in deploying that,
not just traditional AI but generative AI as well and also
the sense that they've only just begun to do it.
So that's big surprise number one.
I think the second thing that I was very pleased to see was that
the World Economic Forum has been able to bring
representatives from all of the key foundation model, makers,
and the key scientists and get them in a room together to start
to talk about your practical, tangible issues of what comes
next.
Love it and I love that the tech leaders are actually embracing
that conversation.
They're not shying away from it.
Is that same sentiment that you feel? Yeah, I think that they
are definitely embracing it.
We always have to be a bit careful with with technology
firms because they always have their own agenda and sometimes
that agenda is a simple commercial agenda that you can
look at and sometimes it's also about some really fundamental
beliefs.
And one of the points of distinction that is emerging is
around the extent to which models should sit behind APIs,
sit behind proprietary doors, the extent to which they should
be open source and fine tunable.
What is better for industry?
What is better for society at large> Because this is a
powerful technology and there is still I think a sort of enough
creative disagreement about those all types of issues.
OK then that's your role to keep us on our toes and make sure
that that it's the overall productivity right of the
workforce etcetera.
So how do you frame that conversation when you're talking
about it and is it real, is it not real?
Well, the technology is so general and it can be applied in
so many different ways.
Its powers is in its generality and in a way when you start to
pull out specific use cases, you actually weaken the promise of
of generative AI.
And what I I love to think about is the way in which my team has
started to use this.
We use it for desk research.
We use it for analytical thinking.
We use it for creative thinking.
We use it to automate our marketing analysis.
And where do you begin?
Where do you where do you start?
And when you talk to bosses of companies with fifty 100
thousand, 200 thousand employees, they're in a similar
situation because every employee has got four or five different
unique use cases that can come to bear.
I'm quite optimistic that over over the course of this year
where firms have been a little bit slower to roll things out so
they can make sense of the technology, they will widen
participation across their organizations.
And then the question really will be will that productivity,
those productivity gains result in real changes to the way
business is done or will it just create more clutter the way
e-mail has created more clutter in our inboxes?
Interesting, but on the topic:
Is it also fair to assume that what I love in your when you
talk about AI, you're not just theoretisizing, right?
You're actually doing it right?
Is it fair to say that you're using a lot of these tools,
right in your day-to-day?
You did not shrink your team, but it increased the
productivity and you could actually grow and scale faster?
Yeah.
So our team is small.
We have a team of a handful of researchers, and when we started
using ChatGPT, GPT4, Claude from Anthropic, we actually were able
to delay 2 hirings.
And that's just because the team themselves is so much more
productive.
The quality of their work is higher, they feel much more in
control and in some sense they also have more time on their
hands.
I mean it's worked very, very well for us, but we are really
canonical desk workers, knowledge workers who trade in
ideas and it happens that LLMS are really, really good for
that.
Of course, across a large business very few people are
normally involved in processes like that.
But I had a great example when I was in Germany just before
coming into to Davos which was of the phone company had created
a chatbot, a field service chatbot using an LLM for
technicians as they sat by street
side cabinets.
What do we need to do with this yellow cable and the green cable
and the red cable? And it's actually speed up the work.
It's meant that the field service agents are not sitting
in the cold in a call centre trying to get get through to
support.
And that for me was a really great example.
But can you apply that to a pharmaceutical company or an
accounting firm?
No, You have to have your own particular user.
It's very distinct. And it's not just productivity.
It's also allows people to have their jobs treated with respect
in a way, right, so that they are not sitting in the cold if
they don't have to, etcetera.
Yeah, I think it's a tremendously humanising
technology.
We in the UK are coming off the back of a tremendous IT scandal
called the Post Office Horizon IT scandal where a billing
system rolled out across the the post offices had bugs in it and
several 100 post office workers were sent to prison wrongly for
so-called fraud.
And the point when you look at the software, it was very, very
dehumanized.
It was the the old style screen with a terrible UI, easy to make
mistakes.
The beauty of generative AI is that we get to talk to this
thing in our natural language.
It talks back to us in our natural language.
It's the most natural thing in the world and we can express
politeness to it and it can joke back to us.
A couple of weeks ago I finished a session with ChatGPT, where I
was looking. At a session you were conversing with?
Oh yeah.
And I was doing some work on, you know, pharmaceutical
technology transitions and I got tired.
And at the end, I just whimsically said you're a very
clever little robot.
Thank you.
And I'll come back tomorrow to talk about the moisture of
apparatus.
Moisture of apparatus is a phrase from Star Wars.
Star Wars One.
Luke Skywalker has to fix them.
I had not mentioned Star Wars and ChatGPT response.
Thanks.
We had a productive set session and may the force be with you.
Love it.
And it figured that out and that is incredibly humanized.
I can't think of any other software to put a smile on my
face in that way, Love it.
But then, like, how do I, how do I evolve that into the
conversation on collective intelligence?
Like what?
Like that.
Is that a first step towards that?
How do you even think about collective intelligence?
Yeah, I think this is a really important point.
When science fiction writers and and computer scientists were
thinking about AI, they often imagined it as a singleton.
There would be a single AI that would almost be, you know, like
a God somewhere.
But I think what we're increasingly seeing is that the
way we'll move towards a society of AI is in the same way that
we've moved towards a society of databases.
Our world lives on lots of databases that interact with
each other for better or for worse.
And we are going to see a collective intelligence emerge
because every one of your clients and BCG itself will have
hundreds of different AI systems that are some of which are very
deterministic, some of which are much more stochastic like these
LLM.
And they'll be interacting with us, they'll be interacting with
each other and things will feel smarter.
And from that will come this sense of collective
intelligence.
It raises all sorts of really interesting questions about, you
know, the governance of a distributed set of technologies
that are, that his behaviour is emergent, and questions of
control as well and predictability, which I think we
will start to figure out over the coming years.
But my sense is that we're going to move to a syncretic
collective intelligence.
I call it the Society of AI.
OK.
So it's going to be collection of these things that are going
to have a perception of a collective intelligence.
But will be a lot of things.
There'll be a lot of different things.
I'll be working together.
And and in fact, what I've just described is how human society
works, right?
We all have different capabilities.
And then we sometimes cluster in groups that we call teams or
work groups or companies that also have their own identity at
a slightly higher, more meta level.
And I think that those parallels are important because they take
away some of the anxiety people might feel about technologies
like AI.
They help us understand that we have actually got tools to make
individual intelligences work together in healthy ways.
Well, Azeem, thank you.
Thank you for joining me today.
And even more importantly, thank you for being that collective
intelligence that is unpacking all of this for us continuously,
keeping us on our toes and also, you know, forcing our thinking
and making sure we stay sharp.
So thank you a lot.
Thank you so much, Vlad.
My pleasure.