- I think AI has tremendous potential
to think more constructively about it, however,
it's useful to have a clear view about
what precisely we're talking about
when we're talking about artificial intelligence.
Since 1956, the start of the AI as a field,
the objective all along has been
not just to automate specific tasks,
but to replicate the same full general form of intelligence
that make us humans smart and unique on this planet.
However for decades that original ambition
was radically out of reach, so we settled instead
for building special purpose systems
and so-called expert systems.
Expert systems would be big databases,
they would be constructed by having some human domain expert
and a software engineer sit down together,
and the software engineer would painstakingly
try to extract from the human, the principles that they used
to achieve their performance.
But these expert systems were very brittle,
they didn't scale well
and ultimately, you really got out only what you had put in.
Well, since the last eight or nine years,
the focus has shifted.
The action is no longer in creating expert systems.
The action now is in crafting learning algorithms.
Figure out ways of making AI systems
able to learn from experience
in much the same way as we humans do,
and this has led to revolutionary new capacities,
things that were completely impossible to do
with good old fashioned AI, is now routinely done.
You have these deep neural networks that can, for example,
look at the picture and see what is in it
or that can hear somebody talking and transcribe speech.
And with deep neural networks
and deep reinforcement learning, a wide frontier
of new capabilities are opening up
that seem to have much more
of the intuitive pattern recognition capability
that we humans take for granted,
but that had proved elusive today.
And progress now seems to be really rapid in this field
and there are just a ton of exciting research avenues
at the horizon with a lot of talent
and money rushing in to explore all of these.
Now, if as I think will be the case,
progress will continue to be rapid.
We then have to ask, what will this lead to?
And here I think there are two different contexts
that we need to recognize and distinguish.
There is a near-term context
and then a long-term context
and each of these forms the basis
for what I think should be a serious conversation,
they both should be taken seriously, but they are different
and if you mix them together, then you get
a lot of confusion.
I think you simultaneously get
an over hyping of what is possible now,
but also, I think an under hyping
of what will ultimately be possible.
But if you wanna have some view about how to feel about AI,
I think we need to recognize that there are these contexts
and that the near-term context at some point
will become the long-term context.
So in the near-term, I think AI is really
a general purpose technology
that will have vast benefits across all sectors of society.
It will make many processes more efficient,
if you're running a logistics center, let us say,
and you are better able to forecast future demand,
then you can adjust the stocking
so that you need less inventory and you can save money.
If you are a big social media company
and you can find better ways of serving up in the newsfeed,
things that people actually want to read,
you can increase user engagement.
We will have self-driving cars,
we will have medical diagnosis systems
that can look at, say, an X-ray and help the doctor decide
whether it is a cancer or not
and you can go through almost every sector of society
and you can see there is some way in which
these deep leaning systems can help us get better results.
But then there is the long-term context and there
I think AI is not just one more
cool technological advance, not just
one more interesting gadget.
What happens if AI one day succeeds at it's original goal,
which has been all along, as I said, to replicate
human intelligence in all domains,
then really what we have is the last invention
that humans will ever need to make.
If you think about what it means to mechanize intelligence
to full human level performance
and then shortly after, presumably,
superhuman levels of intelligence.
You soon realize that, that's not just
a technological advance like any other.
If you have machines that can do research,
that can do science better than we humans can do,
then from there on, really further progress
is driven by the machines.
And so this transition to the machine super intelligence era
will be, I think, the most important thing
that has ever happened in human history.
And it will unlock an enormous potential
for wonderful things to occur.
I think a whole post-human condition becomes possible.
Space colonization, cures for aging,
all these things that we tend to think of
as just science fiction, I think that actually
becomes a real possibility once you have
super-intelligent scientists and technologies.
But along with this enormous potential for good,
I think there is also gonna be very significant risks,
including existential risks, threats to the very survival
of our species and so what I think we should do,
is I don't think we should try to stop this,
I don't think it's possible to stop
progress in AI and even if we could,
I don't think it would be a good idea to do so.
But we should try to get our act together,
both doing technical research into scalable methods
for AI control so that even as the systems
become arbitrarily intelligent
and at some point super-intelligent,
we still know how to align them with human values.
And also progress so that we will have
the government structure that makes it possible
for us to handle these enormous powers responsibly
and for the benefit of all.