TED2018
Max Tegmark: How to get empowered, not overpowered, by AI
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Many artificial intelligence researchers expect AI to outsmart humans at all tasks and jobs within decades, enabling a future where we're restricted only by the laws of physics, not the limits of our intelligence. MIT physicist and AI researcher Max Tegmark separates the real opportunities and threats from the myths, describing the concrete steps we should take today to ensure that AI ends up being the best -- rather than worst -- thing to ever happen to humanity.
Max Tegmark - Scientist, author
Max Tegmark is driven by curiosity, both about how our universe works and about how we can use the science and technology we discover to help humanity flourish rather than flounder. Full bio
Max Tegmark is driven by curiosity, both about how our universe works and about how we can use the science and technology we discover to help humanity flourish rather than flounder. Full bio
Double-click the English transcript below to play the video.
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After 13.8 billion years
of cosmic history,
of cosmic history,
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our universe has woken up
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and become aware of itself.
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From a small blue planet,
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tiny, conscious parts of our universe
have begun gazing out into the cosmos
have begun gazing out into the cosmos
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with telescopes,
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discovering something humbling.
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We've discovered that our universe
is vastly grander
is vastly grander
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than our ancestors imagined
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and that life seems to be an almost
imperceptibly small perturbation
imperceptibly small perturbation
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on an otherwise dead universe.
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But we've also discovered
something inspiring,
something inspiring,
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which is that the technology
we're developing has the potential
we're developing has the potential
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to help life flourish like never before,
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not just for centuries
but for billions of years,
but for billions of years,
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and not just on earth but throughout
much of this amazing cosmos.
much of this amazing cosmos.
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I think of the earliest life as "Life 1.0"
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because it was really dumb,
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like bacteria, unable to learn
anything during its lifetime.
anything during its lifetime.
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I think of us humans as "Life 2.0"
because we can learn,
because we can learn,
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which we in nerdy, geek speak,
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might think of as installing
new software into our brains,
new software into our brains,
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like languages and job skills.
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"Life 3.0," which can design not only
its software but also its hardware
its software but also its hardware
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of course doesn't exist yet.
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But perhaps our technology
has already made us "Life 2.1,"
has already made us "Life 2.1,"
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with our artificial knees,
pacemakers and cochlear implants.
pacemakers and cochlear implants.
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So let's take a closer look
at our relationship with technology, OK?
at our relationship with technology, OK?
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As an example,
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the Apollo 11 moon mission
was both successful and inspiring,
was both successful and inspiring,
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showing that when we humans
use technology wisely,
use technology wisely,
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we can accomplish things
that our ancestors could only dream of.
that our ancestors could only dream of.
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But there's an even more inspiring journey
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propelled by something
more powerful than rocket engines,
more powerful than rocket engines,
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where the passengers
aren't just three astronauts
aren't just three astronauts
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but all of humanity.
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Let's talk about our collective
journey into the future
journey into the future
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with artificial intelligence.
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My friend Jaan Tallinn likes to point out
that just as with rocketry,
that just as with rocketry,
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it's not enough to make
our technology powerful.
our technology powerful.
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We also have to figure out,
if we're going to be really ambitious,
if we're going to be really ambitious,
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how to steer it
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and where we want to go with it.
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So let's talk about all three
for artificial intelligence:
for artificial intelligence:
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the power, the steering
and the destination.
and the destination.
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Let's start with the power.
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I define intelligence very inclusively --
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simply as our ability
to accomplish complex goals,
to accomplish complex goals,
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because I want to include both
biological and artificial intelligence.
biological and artificial intelligence.
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And I want to avoid
the silly carbon-chauvinism idea
the silly carbon-chauvinism idea
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that you can only be smart
if you're made of meat.
if you're made of meat.
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It's really amazing how the power
of AI has grown recently.
of AI has grown recently.
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Just think about it.
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Not long ago, robots couldn't walk.
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Now, they can do backflips.
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Not long ago,
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we didn't have self-driving cars.
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Now, we have self-flying rockets.
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Not long ago,
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AI couldn't do face recognition.
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Now, AI can generate fake faces
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and simulate your face
saying stuff that you never said.
saying stuff that you never said.
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Not long ago,
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AI couldn't beat us at the game of Go.
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Then, Google DeepMind's AlphaZero AI
took 3,000 years of human Go games
took 3,000 years of human Go games
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and Go wisdom,
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ignored it all and became the world's best
player by just playing against itself.
player by just playing against itself.
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And the most impressive feat here
wasn't that it crushed human gamers,
wasn't that it crushed human gamers,
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but that it crushed human AI researchers
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who had spent decades
handcrafting game-playing software.
handcrafting game-playing software.
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And AlphaZero crushed human AI researchers
not just in Go but even at chess,
not just in Go but even at chess,
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which we have been working on since 1950.
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So all this amazing recent progress in AI
really begs the question:
really begs the question:
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How far will it go?
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I like to think about this question
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in terms of this abstract
landscape of tasks,
landscape of tasks,
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where the elevation represents
how hard it is for AI to do each task
how hard it is for AI to do each task
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at human level,
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and the sea level represents
what AI can do today.
what AI can do today.
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The sea level is rising
as AI improves,
as AI improves,
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so there's a kind of global warming
going on here in the task landscape.
going on here in the task landscape.
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And the obvious takeaway
is to avoid careers at the waterfront --
is to avoid careers at the waterfront --
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(Laughter)
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which will soon be
automated and disrupted.
automated and disrupted.
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But there's a much
bigger question as well.
bigger question as well.
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How high will the water end up rising?
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Will it eventually rise
to flood everything,
to flood everything,
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matching human intelligence at all tasks.
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This is the definition
of artificial general intelligence --
of artificial general intelligence --
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AGI,
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which has been the holy grail
of AI research since its inception.
of AI research since its inception.
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By this definition, people who say,
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"Ah, there will always be jobs
that humans can do better than machines,"
that humans can do better than machines,"
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are simply saying
that we'll never get AGI.
that we'll never get AGI.
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Sure, we might still choose
to have some human jobs
to have some human jobs
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or to give humans income
and purpose with our jobs,
and purpose with our jobs,
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but AGI will in any case
transform life as we know it
transform life as we know it
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with humans no longer being
the most intelligent.
the most intelligent.
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Now, if the water level does reach AGI,
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then further AI progress will be driven
mainly not by humans but by AI,
mainly not by humans but by AI,
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which means that there's a possibility
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that further AI progress
could be way faster
could be way faster
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than the typical human research
and development timescale of years,
and development timescale of years,
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raising the controversial possibility
of an intelligence explosion
of an intelligence explosion
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where recursively self-improving AI
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rapidly leaves human
intelligence far behind,
intelligence far behind,
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creating what's known
as superintelligence.
as superintelligence.
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Alright, reality check:
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Are we going to get AGI any time soon?
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Some famous AI researchers,
like Rodney Brooks,
like Rodney Brooks,
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think it won't happen
for hundreds of years.
for hundreds of years.
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But others, like Google DeepMind
founder Demis Hassabis,
founder Demis Hassabis,
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are more optimistic
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and are working to try to make
it happen much sooner.
it happen much sooner.
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And recent surveys have shown
that most AI researchers
that most AI researchers
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actually share Demis's optimism,
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expecting that we will
get AGI within decades,
get AGI within decades,
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so within the lifetime of many of us,
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which begs the question -- and then what?
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What do we want the role of humans to be
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if machines can do everything better
and cheaper than us?
and cheaper than us?
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The way I see it, we face a choice.
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One option is to be complacent.
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We can say, "Oh, let's just build machines
that can do everything we can do
that can do everything we can do
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and not worry about the consequences.
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Come on, if we build technology
that makes all humans obsolete,
that makes all humans obsolete,
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what could possibly go wrong?"
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(Laughter)
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But I think that would be
embarrassingly lame.
embarrassingly lame.
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I think we should be more ambitious --
in the spirit of TED.
in the spirit of TED.
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Let's envision a truly inspiring
high-tech future
high-tech future
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and try to steer towards it.
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This brings us to the second part
of our rocket metaphor: the steering.
of our rocket metaphor: the steering.
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We're making AI more powerful,
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but how can we steer towards a future
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where AI helps humanity flourish
rather than flounder?
rather than flounder?
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To help with this,
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I cofounded the Future of Life Institute.
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It's a small nonprofit promoting
beneficial technology use,
beneficial technology use,
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and our goal is simply
for the future of life to exist
for the future of life to exist
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and to be as inspiring as possible.
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You know, I love technology.
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Technology is why today
is better than the Stone Age.
is better than the Stone Age.
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And I'm optimistic that we can create
a really inspiring high-tech future ...
a really inspiring high-tech future ...
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if -- and this is a big if --
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if we win the wisdom race --
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the race between the growing
power of our technology
power of our technology
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and the growing wisdom
with which we manage it.
with which we manage it.
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But this is going to require
a change of strategy
a change of strategy
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because our old strategy
has been learning from mistakes.
has been learning from mistakes.
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We invented fire,
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screwed up a bunch of times --
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invented the fire extinguisher.
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(Laughter)
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We invented the car,
screwed up a bunch of times --
screwed up a bunch of times --
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invented the traffic light,
the seat belt and the airbag,
the seat belt and the airbag,
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but with more powerful technology
like nuclear weapons and AGI,
like nuclear weapons and AGI,
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learning from mistakes
is a lousy strategy,
is a lousy strategy,
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don't you think?
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(Laughter)
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It's much better to be proactive
rather than reactive;
rather than reactive;
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plan ahead and get things
right the first time
right the first time
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because that might be
the only time we'll get.
the only time we'll get.
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But it is funny because
sometimes people tell me,
sometimes people tell me,
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"Max, shhh, don't talk like that.
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That's Luddite scaremongering."
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But it's not scaremongering.
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It's what we at MIT
call safety engineering.
call safety engineering.
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Think about it:
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before NASA launched
the Apollo 11 mission,
the Apollo 11 mission,
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they systematically thought through
everything that could go wrong
everything that could go wrong
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when you put people
on top of explosive fuel tanks
on top of explosive fuel tanks
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and launch them somewhere
where no one could help them.
where no one could help them.
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And there was a lot that could go wrong.
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Was that scaremongering?
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No.
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That's was precisely
the safety engineering
the safety engineering
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that ensured the success of the mission,
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and that is precisely the strategy
I think we should take with AGI.
I think we should take with AGI.
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Think through what can go wrong
to make sure it goes right.
to make sure it goes right.
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So in this spirit,
we've organized conferences,
we've organized conferences,
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bringing together leading
AI researchers and other thinkers
AI researchers and other thinkers
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to discuss how to grow this wisdom
we need to keep AI beneficial.
we need to keep AI beneficial.
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Our last conference
was in Asilomar, California last year
was in Asilomar, California last year
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and produced this list of 23 principles
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which have since been signed
by over 1,000 AI researchers
by over 1,000 AI researchers
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and key industry leaders,
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and I want to tell you
about three of these principles.
about three of these principles.
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One is that we should avoid an arms race
and lethal autonomous weapons.
and lethal autonomous weapons.
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The idea here is that any science
can be used for new ways of helping people
can be used for new ways of helping people
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or new ways of harming people.
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For example, biology and chemistry
are much more likely to be used
are much more likely to be used
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for new medicines or new cures
than for new ways of killing people,
than for new ways of killing people,
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because biologists
and chemists pushed hard --
and chemists pushed hard --
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and successfully --
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for bans on biological
and chemical weapons.
and chemical weapons.
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And in the same spirit,
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most AI researchers want to stigmatize
and ban lethal autonomous weapons.
and ban lethal autonomous weapons.
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Another Asilomar AI principle
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is that we should mitigate
AI-fueled income inequality.
AI-fueled income inequality.
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I think that if we can grow
the economic pie dramatically with AI
the economic pie dramatically with AI
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and we still can't figure out
how to divide this pie
how to divide this pie
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so that everyone is better off,
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then shame on us.
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(Applause)
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Alright, now raise your hand
if your computer has ever crashed.
if your computer has ever crashed.
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(Laughter)
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Wow, that's a lot of hands.
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Well, then you'll appreciate
this principle
this principle
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that we should invest much more
in AI safety research,
in AI safety research,
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because as we put AI in charge
of even more decisions and infrastructure,
of even more decisions and infrastructure,
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we need to figure out how to transform
today's buggy and hackable computers
today's buggy and hackable computers
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into robust AI systems
that we can really trust,
that we can really trust,
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because otherwise,
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all this awesome new technology
can malfunction and harm us,
can malfunction and harm us,
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or get hacked and be turned against us.
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And this AI safety work
has to include work on AI value alignment,
has to include work on AI value alignment,
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because the real threat
from AGI isn't malice,
from AGI isn't malice,
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like in silly Hollywood movies,
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but competence --
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AGI accomplishing goals
that just aren't aligned with ours.
that just aren't aligned with ours.
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For example, when we humans drove
the West African black rhino extinct,
the West African black rhino extinct,
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we didn't do it because we were a bunch
of evil rhinoceros haters, did we?
of evil rhinoceros haters, did we?
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We did it because
we were smarter than them
we were smarter than them
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and our goals weren't aligned with theirs.
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But AGI is by definition smarter than us,
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so to make sure that we don't put
ourselves in the position of those rhinos
ourselves in the position of those rhinos
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if we create AGI,
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we need to figure out how
to make machines understand our goals,
to make machines understand our goals,
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adopt our goals and retain our goals.
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And whose goals should these be, anyway?
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Which goals should they be?
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This brings us to the third part
of our rocket metaphor: the destination.
of our rocket metaphor: the destination.
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We're making AI more powerful,
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trying to figure out how to steer it,
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but where do we want to go with it?
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This is the elephant in the room
that almost nobody talks about --
that almost nobody talks about --
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not even here at TED --
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because we're so fixated
on short-term AI challenges.
on short-term AI challenges.
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Look, our species is trying to build AGI,
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motivated by curiosity and economics,
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but what sort of future society
are we hoping for if we succeed?
are we hoping for if we succeed?
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We did an opinion poll on this recently,
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and I was struck to see
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that most people actually
want us to build superintelligence:
want us to build superintelligence:
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AI that's vastly smarter
than us in all ways.
than us in all ways.
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What there was the greatest agreement on
was that we should be ambitious
was that we should be ambitious
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and help life spread into the cosmos,
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but there was much less agreement
about who or what should be in charge.
about who or what should be in charge.
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And I was actually quite amused
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to see that there's some some people
who want it to be just machines.
who want it to be just machines.
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(Laughter)
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And there was total disagreement
about what the role of humans should be,
about what the role of humans should be,
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even at the most basic level,
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so let's take a closer look
at possible futures
at possible futures
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that we might choose
to steer toward, alright?
to steer toward, alright?
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So don't get be wrong here.
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I'm not talking about space travel,
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merely about humanity's
metaphorical journey into the future.
metaphorical journey into the future.
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So one option that some
of my AI colleagues like
of my AI colleagues like
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is to build superintelligence
and keep it under human control,
and keep it under human control,
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like an enslaved god,
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disconnected from the internet
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and used to create unimaginable
technology and wealth
technology and wealth
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for whoever controls it.
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But Lord Acton warned us
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that power corrupts,
and absolute power corrupts absolutely,
and absolute power corrupts absolutely,
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so you might worry that maybe
we humans just aren't smart enough,
we humans just aren't smart enough,
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or wise enough rather,
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to handle this much power.
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Also, aside from any
moral qualms you might have
moral qualms you might have
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about enslaving superior minds,
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you might worry that maybe
the superintelligence could outsmart us,
the superintelligence could outsmart us,
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break out and take over.
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But I also have colleagues
who are fine with AI taking over
who are fine with AI taking over
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and even causing human extinction,
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as long as we feel the the AIs
are our worthy descendants,
are our worthy descendants,
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like our children.
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But how would we know that the AIs
have adopted our best values
have adopted our best values
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and aren't just unconscious zombies
tricking us into anthropomorphizing them?
tricking us into anthropomorphizing them?
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Also, shouldn't those people
who don't want human extinction
who don't want human extinction
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have a say in the matter, too?
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Now, if you didn't like either
of those two high-tech options,
of those two high-tech options,
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it's important to remember
that low-tech is suicide
that low-tech is suicide
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from a cosmic perspective,
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because if we don't go far
beyond today's technology,
beyond today's technology,
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the question isn't whether humanity
is going to go extinct,
is going to go extinct,
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merely whether
we're going to get taken out
we're going to get taken out
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by the next killer asteroid, supervolcano
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or some other problem
that better technology could have solved.
that better technology could have solved.
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So, how about having
our cake and eating it ...
our cake and eating it ...
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with AGI that's not enslaved
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but treats us well because its values
are aligned with ours?
are aligned with ours?
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This is the gist of what Eliezer Yudkowsky
has called "friendly AI,"
has called "friendly AI,"
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and if we can do this,
it could be awesome.
it could be awesome.
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It could not only eliminate negative
experiences like disease, poverty,
experiences like disease, poverty,
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crime and other suffering,
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14:54
but it could also give us
the freedom to choose
the freedom to choose
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from a fantastic new diversity
of positive experiences --
of positive experiences --
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basically making us
the masters of our own destiny.
the masters of our own destiny.
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So in summary,
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our situation with technology
is complicated,
is complicated,
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but the big picture is rather simple.
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Most AI researchers
expect AGI within decades,
expect AGI within decades,
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and if we just bumble
into this unprepared,
into this unprepared,
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it will probably be
the biggest mistake in human history --
the biggest mistake in human history --
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let's face it.
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It could enable brutal,
global dictatorship
global dictatorship
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with unprecedented inequality,
surveillance and suffering,
surveillance and suffering,
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and maybe even human extinction.
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15:32
But if we steer carefully,
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we could end up in a fantastic future
where everybody's better off:
where everybody's better off:
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the poor are richer, the rich are richer,
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everybody is healthy
and free to live out their dreams.
and free to live out their dreams.
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Now, hang on.
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Do you folks want the future
that's politically right or left?
that's politically right or left?
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Do you want the pious society
with strict moral rules,
with strict moral rules,
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or do you an hedonistic free-for-all,
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more like Burning Man 24/7?
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Do you want beautiful beaches,
forests and lakes,
forests and lakes,
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or would you prefer to rearrange
some of those atoms with the computers,
some of those atoms with the computers,
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enabling virtual experiences?
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With friendly AI, we could simply
build all of these societies
build all of these societies
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and give people the freedom
to choose which one they want to live in
to choose which one they want to live in
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because we would no longer
be limited by our intelligence,
be limited by our intelligence,
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merely by the laws of physics.
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So the resources and space
for this would be astronomical --
for this would be astronomical --
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literally.
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So here's our choice.
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We can either be complacent
about our future,
about our future,
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taking as an article of blind faith
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that any new technology
is guaranteed to be beneficial,
is guaranteed to be beneficial,
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and just repeat that to ourselves
as a mantra over and over and over again
as a mantra over and over and over again
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as we drift like a rudderless ship
towards our own obsolescence.
towards our own obsolescence.
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Or we can be ambitious --
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thinking hard about how
to steer our technology
to steer our technology
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and where we want to go with it
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to create the age of amazement.
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We're all here to celebrate
the age of amazement,
the age of amazement,
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and I feel that its essence should lie
in becoming not overpowered
in becoming not overpowered
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but empowered by our technology.
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Thank you.
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(Applause)
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ABOUT THE SPEAKER
Max Tegmark - Scientist, authorMax Tegmark is driven by curiosity, both about how our universe works and about how we can use the science and technology we discover to help humanity flourish rather than flounder.
Why you should listen
Max Tegmark is an MIT professor who loves thinking about life's big questions. He's written two popular books, Our Mathematical Universe: My Quest for the Ultimate Nature of Reality and the recently published Life 3.0: Being Human in the Age of Artificial Intelligence, as well as more than 200 nerdy technical papers on topics from cosmology to AI.
He writes: "In my spare time, I'm president of the Future of Life Institute, which aims to ensure that we develop not only technology but also the wisdom required to use it beneficially."
Max Tegmark | Speaker | TED.com