< Return to Video

How to get empowered, not overpowered, by AI

  • 0:01 - 0:05
    After 13.8 billion years
    of cosmic history,
  • 0:05 - 0:07
    our universe has woken up
  • 0:07 - 0:09
    and become aware of itself.
  • 0:09 - 0:11
    From a small blue planet,
  • 0:11 - 0:16
    tiny, conscious parts of our universe
    have begun gazing out into the cosmos
  • 0:16 - 0:17
    with telescopes,
  • 0:17 - 0:18
    discovering something humbling.
  • 0:19 - 0:22
    We've discovered that our universe
    is vastly grander
  • 0:22 - 0:24
    than our ancestors imagined
  • 0:24 - 0:28
    and that life seems to be an almost
    imperceptibly small perturbation
  • 0:28 - 0:30
    on an otherwise dead universe.
  • 0:30 - 0:33
    But we've also discovered
    something inspiring,
  • 0:33 - 0:36
    which is that the technology
    we're developing has the potential
  • 0:36 - 0:39
    to help life flourish like never before,
  • 0:39 - 0:42
    not just for centuries
    but for billions of years,
  • 0:42 - 0:46
    and not just on earth but throughout
    much of this amazing cosmos.
  • 0:48 - 0:51
    I think of the earliest life as "Life 1.0"
  • 0:51 - 0:52
    because it was really dumb,
  • 0:52 - 0:57
    like bacteria, unable to learn
    anything during its lifetime.
  • 0:57 - 1:00
    I think of us humans as "Life 2.0"
    because we can learn,
  • 1:00 - 1:02
    which we in nerdy, geek speak,
  • 1:02 - 1:05
    might think of as installing
    new software into our brains,
  • 1:05 - 1:07
    like languages and job skills.
  • 1:08 - 1:12
    "Life 3.0," which can design not only
    its software but also its hardware
  • 1:12 - 1:14
    of course doesn't exist yet.
  • 1:14 - 1:17
    But perhaps our technology
    has already made us "Life 2.1,"
  • 1:17 - 1:22
    with our artificial knees,
    pacemakers and cochlear implants.
  • 1:22 - 1:26
    So let's take a closer look
    at our relationship with technology, OK?
  • 1:27 - 1:28
    As an example,
  • 1:28 - 1:33
    the Apollo 11 moon mission
    was both successful and inspiring,
  • 1:33 - 1:36
    showing that when we humans
    use technology wisely,
  • 1:36 - 1:40
    we can accomplish things
    that our ancestors could only dream of.
  • 1:40 - 1:43
    But there's an even more inspiring journey
  • 1:43 - 1:46
    propelled by something
    more powerful than rocket engines,
  • 1:47 - 1:50
    where the passengers
    aren't just three astronauts
  • 1:50 - 1:51
    but all of humanity.
  • 1:51 - 1:54
    Let's talk about our collective
    journey into the future
  • 1:54 - 1:56
    with artificial intelligence.
  • 1:57 - 2:01
    My friend Jaan Tallinn likes to point out
    that just as with rocketry,
  • 2:02 - 2:05
    it's not enough to make
    our technology powerful.
  • 2:06 - 2:09
    We also have to figure out,
    if we're going to be really ambitious,
  • 2:09 - 2:10
    how to steer it
  • 2:10 - 2:12
    and where we want to go with it.
  • 2:13 - 2:16
    So let's talk about all three
    for artificial intelligence:
  • 2:16 - 2:19
    the power, the steering
    and the destination.
  • 2:20 - 2:21
    Let's start with the power.
  • 2:22 - 2:25
    I define intelligence very inclusively --
  • 2:25 - 2:29
    simply as our ability
    to accomplish complex goals,
  • 2:29 - 2:33
    because I want to include both
    biological and artificial intelligence.
  • 2:33 - 2:37
    And I want to avoid
    the silly carbon-chauvinism idea
  • 2:37 - 2:39
    that you can only be smart
    if you're made of meat.
  • 2:41 - 2:45
    It's really amazing how the power
    of AI has grown recently.
  • 2:45 - 2:46
    Just think about it.
  • 2:46 - 2:50
    Not long ago, robots couldn't walk.
  • 2:51 - 2:53
    Now, they can do backflips.
  • 2:54 - 2:56
    Not long ago,
  • 2:56 - 2:58
    we didn't have self-driving cars.
  • 2:59 - 3:01
    Now, we have self-flying rockets.
  • 3:04 - 3:05
    Not long ago,
  • 3:05 - 3:08
    AI couldn't do face recognition.
  • 3:08 - 3:11
    Now, AI can generate fake faces
  • 3:11 - 3:15
    and simulate your face
    saying stuff that you never said.
  • 3:16 - 3:18
    Not long ago,
  • 3:18 - 3:20
    AI couldn't beat us at the game of Go.
  • 3:20 - 3:25
    Then, Google DeepMind's AlphaZero AI
    took 3,000 years of human Go games
  • 3:26 - 3:27
    and Go wisdom,
  • 3:27 - 3:32
    ignored it all and became the world's best
    player by just playing against itself.
  • 3:32 - 3:35
    And the most impressive feat here
    wasn't that it crushed human gamers,
  • 3:36 - 3:38
    but that it crushed human AI researchers
  • 3:38 - 3:42
    who had spent decades
    handcrafting game-playing software.
  • 3:42 - 3:47
    And AlphaZero crushed human AI researchers
    not just in Go but even at chess,
  • 3:47 - 3:49
    which we have been working on since 1950.
  • 3:50 - 3:54
    So all this amazing recent progress in AI
    really begs the question:
  • 3:55 - 3:57
    How far will it go?
  • 3:58 - 3:59
    I like to think about this question
  • 4:00 - 4:02
    in terms of this abstract
    landscape of tasks,
  • 4:03 - 4:06
    where the elevation represents
    how hard it is for AI to do each task
  • 4:06 - 4:07
    at human level,
  • 4:07 - 4:10
    and the sea level represents
    what AI can do today.
  • 4:11 - 4:13
    The sea level is rising
    as AI improves,
  • 4:13 - 4:17
    so there's a kind of global warming
    going on here in the task landscape.
  • 4:18 - 4:21
    And the obvious takeaway
    is to avoid careers at the waterfront --
  • 4:21 - 4:23
    (Laughter)
  • 4:23 - 4:26
    which will soon be
    automated and disrupted.
  • 4:26 - 4:29
    But there's a much
    bigger question as well.
  • 4:29 - 4:30
    How high will the water end up rising?
  • 4:31 - 4:35
    Will it eventually rise
    to flood everything,
  • 4:36 - 4:38
    matching human intelligence at all tasks.
  • 4:38 - 4:42
    This is the definition
    of artificial general intelligence --
  • 4:42 - 4:43
    AGI,
  • 4:43 - 4:47
    which has been the holy grail
    of AI research since its inception.
  • 4:47 - 4:49
    By this definition, people who say,
  • 4:49 - 4:52
    "Ah, there will always be jobs
    that humans can do better than machines,"
  • 4:52 - 4:55
    are simply saying
    that we'll never get AGI.
  • 4:56 - 4:59
    Sure, we might still choose
    to have some human jobs
  • 4:59 - 5:02
    or to give humans income
    and purpose with our jobs,
  • 5:02 - 5:06
    but AGI will in any case
    transform life as we know it
  • 5:06 - 5:09
    with humans no longer being
    the most intelligent.
  • 5:09 - 5:13
    Now, if the water level does reach AGI,
  • 5:13 - 5:18
    then further AI progress will be driven
    mainly not by humans but by AI,
  • 5:18 - 5:20
    which means that there's a possibility
  • 5:20 - 5:22
    that further AI progress
    could be way faster
  • 5:22 - 5:26
    than the typical human research
    and development timescale of years,
  • 5:26 - 5:30
    raising the controversial possibility
    of an intelligence explosion
  • 5:30 - 5:32
    where recursively self-improving AI
  • 5:32 - 5:35
    rapidly leaves human
    intelligence far behind,
  • 5:35 - 5:38
    creating what's known
    as superintelligence.
  • 5:40 - 5:42
    Alright, reality check:
  • 5:43 - 5:46
    Are we going to get AGI any time soon?
  • 5:46 - 5:49
    Some famous AI researchers,
    like Rodney Brooks,
  • 5:49 - 5:52
    think it won't happen
    for hundreds of years.
  • 5:52 - 5:55
    But others, like Google DeepMind
    founder Demis Hassabis,
  • 5:56 - 5:57
    are more optimistic
  • 5:57 - 5:59
    and are working to try to make
    it happen much sooner.
  • 5:59 - 6:03
    And recent surveys have shown
    that most AI researchers
  • 6:03 - 6:06
    actually share Demis's optimism,
  • 6:06 - 6:09
    expecting that we will
    get AGI within decades,
  • 6:10 - 6:12
    so within the lifetime of many of us,
  • 6:12 - 6:14
    which begs the question -- and then what?
  • 6:15 - 6:17
    What do we want the role of humans to be
  • 6:17 - 6:20
    if machines can do everything better
    and cheaper than us?
  • 6:23 - 6:25
    The way I see it, we face a choice.
  • 6:26 - 6:28
    One option is to be complacent.
  • 6:28 - 6:31
    We can say, "Oh, let's just build machines
    that can do everything we can do
  • 6:31 - 6:33
    and not worry about the consequences.
  • 6:33 - 6:36
    Come on, if we build technology
    that makes all humans obsolete,
  • 6:37 - 6:39
    what could possibly go wrong?"
  • 6:39 - 6:40
    (Laughter)
  • 6:40 - 6:43
    But I think that would be
    embarrassingly lame.
  • 6:44 - 6:48
    I think we should be more ambitious --
    in the spirit of TED.
  • 6:48 - 6:51
    Let's envision a truly inspiring
    high-tech future
  • 6:51 - 6:53
    and try to steer towards it.
  • 6:54 - 6:57
    This brings us to the second part
    of our rocket metaphor: the steering.
  • 6:57 - 6:59
    We're making AI more powerful,
  • 6:59 - 7:03
    but how can we steer towards a future
  • 7:03 - 7:06
    where AI helps humanity flourish
    rather than flounder?
  • 7:07 - 7:08
    To help with this,
  • 7:08 - 7:10
    I cofounded the Future of Life Institute.
  • 7:10 - 7:13
    It's a small nonprofit promoting
    beneficial technology use,
  • 7:13 - 7:16
    and our goal is simply
    for the future of life to exist
  • 7:16 - 7:18
    and to be as inspiring as possible.
  • 7:18 - 7:21
    You know, I love technology.
  • 7:21 - 7:24
    Technology is why today
    is better than the Stone Age.
  • 7:25 - 7:29
    And I'm optimistic that we can create
    a really inspiring high-tech future ...
  • 7:30 - 7:31
    if -- and this is a big if --
  • 7:31 - 7:34
    if we win the wisdom race --
  • 7:34 - 7:36
    the race between the growing
    power of our technology
  • 7:37 - 7:39
    and the growing wisdom
    with which we manage it.
  • 7:39 - 7:42
    But this is going to require
    a change of strategy
  • 7:42 - 7:45
    because our old strategy
    has been learning from mistakes.
  • 7:45 - 7:47
    We invented fire,
  • 7:47 - 7:48
    screwed up a bunch of times --
  • 7:48 - 7:50
    invented the fire extinguisher.
  • 7:50 - 7:52
    (Laughter)
  • 7:52 - 7:54
    We invented the car,
    screwed up a bunch of times --
  • 7:54 - 7:57
    invented the traffic light,
    the seat belt and the airbag,
  • 7:57 - 8:01
    but with more powerful technology
    like nuclear weapons and AGI,
  • 8:01 - 8:04
    learning from mistakes
    is a lousy strategy,
  • 8:04 - 8:05
    don't you think?
  • 8:05 - 8:06
    (Laughter)
  • 8:06 - 8:09
    It's much better to be proactive
    rather than reactive;
  • 8:09 - 8:11
    plan ahead and get things
    right the first time
  • 8:11 - 8:14
    because that might be
    the only time we'll get.
  • 8:14 - 8:16
    But it is funny because
    sometimes people tell me,
  • 8:16 - 8:19
    "Max, shhh, don't talk like that.
  • 8:19 - 8:21
    That's Luddite scaremongering."
  • 8:22 - 8:24
    But it's not scaremongering.
  • 8:24 - 8:26
    It's what we at MIT
    call safety engineering.
  • 8:27 - 8:28
    Think about it:
  • 8:28 - 8:31
    before NASA launched
    the Apollo 11 mission,
  • 8:31 - 8:34
    they systematically thought through
    everything that could go wrong
  • 8:34 - 8:36
    when you put people
    on top of explosive fuel tanks
  • 8:36 - 8:39
    and launch them somewhere
    where no one could help them.
  • 8:39 - 8:41
    And there was a lot that could go wrong.
  • 8:41 - 8:42
    Was that scaremongering?
  • 8:43 - 8:44
    No.
  • 8:44 - 8:46
    That's was precisely
    the safety engineering
  • 8:46 - 8:48
    that ensured the success of the mission,
  • 8:48 - 8:53
    and that is precisely the strategy
    I think we should take with AGI.
  • 8:53 - 8:57
    Think through what can go wrong
    to make sure it goes right.
  • 8:57 - 8:59
    So in this spirit,
    we've organized conferences,
  • 8:59 - 9:02
    bringing together leading
    AI researchers and other thinkers
  • 9:02 - 9:06
    to discuss how to grow this wisdom
    we need to keep AI beneficial.
  • 9:06 - 9:09
    Our last conference
    was in Asilomar, California last year
  • 9:09 - 9:12
    and produced this list of 23 principles
  • 9:12 - 9:15
    which have since been signed
    by over 1,000 AI researchers
  • 9:15 - 9:16
    and key industry leaders,
  • 9:16 - 9:20
    and I want to tell you
    about three of these principles.
  • 9:20 - 9:25
    One is that we should avoid an arms race
    and lethal autonomous weapons.
  • 9:25 - 9:29
    The idea here is that any science
    can be used for new ways of helping people
  • 9:29 - 9:31
    or new ways of harming people.
  • 9:31 - 9:35
    For example, biology and chemistry
    are much more likely to be used
  • 9:35 - 9:39
    for new medicines or new cures
    than for new ways of killing people,
  • 9:40 - 9:42
    because biologists
    and chemists pushed hard --
  • 9:42 - 9:43
    and successfully --
  • 9:43 - 9:45
    for bans on biological
    and chemical weapons.
  • 9:45 - 9:46
    And in the same spirit,
  • 9:46 - 9:51
    most AI researchers want to stigmatize
    and ban lethal autonomous weapons.
  • 9:52 - 9:53
    Another Asilomar AI principle
  • 9:53 - 9:57
    is that we should mitigate
    AI-fueled income inequality.
  • 9:57 - 10:02
    I think that if we can grow
    the economic pie dramatically with AI
  • 10:02 - 10:04
    and we still can't figure out
    how to divide this pie
  • 10:04 - 10:06
    so that everyone is better off,
  • 10:06 - 10:07
    then shame on us.
  • 10:07 - 10:11
    (Applause)
  • 10:11 - 10:15
    Alright, now raise your hand
    if your computer has ever crashed.
  • 10:15 - 10:17
    (Laughter)
  • 10:17 - 10:18
    Wow, that's a lot of hands.
  • 10:18 - 10:21
    Well, then you'll appreciate
    this principle
  • 10:21 - 10:24
    that we should invest much more
    in AI safety research,
  • 10:24 - 10:27
    because as we put AI in charge
    of even more decisions and infrastructure,
  • 10:27 - 10:31
    we need to figure out how to transform
    today's buggy and hackable computers
  • 10:31 - 10:34
    into robust AI systems
    that we can really trust,
  • 10:34 - 10:35
    because otherwise,
  • 10:35 - 10:38
    all this awesome new technology
    can malfunction and harm us,
  • 10:38 - 10:40
    or get hacked and be turned against us.
  • 10:40 - 10:45
    And this AI safety work
    has to include work on AI value alignment,
  • 10:45 - 10:48
    because the real threat
    from AGI isn't malice,
  • 10:48 - 10:50
    like in silly Hollywood movies,
  • 10:50 - 10:52
    but competence --
  • 10:52 - 10:55
    AGI accomplishing goals
    that just aren't aligned with ours.
  • 10:55 - 11:00
    For example, when we humans drove
    the West African black rhino extinct,
  • 11:00 - 11:04
    we didn't do it because we were a bunch
    of evil rhinoceros haters, did we?
  • 11:04 - 11:06
    We did it because
    we were smarter than them
  • 11:06 - 11:08
    and our goals weren't aligned with theirs.
  • 11:08 - 11:11
    But AGI is by definition smarter than us,
  • 11:11 - 11:15
    so to make sure that we don't put
    ourselves in the position of those rhinos
  • 11:15 - 11:17
    if we create AGI,
  • 11:17 - 11:21
    we need to figure out how
    to make machines understand our goals,
  • 11:21 - 11:24
    adopt our goals and retain our goals.
  • 11:25 - 11:28
    And whose goals should these be, anyway?
  • 11:28 - 11:30
    Which goals should they be?
  • 11:30 - 11:34
    This brings us to the third part
    of our rocket metaphor: the destination.
  • 11:35 - 11:37
    We're making AI more powerful,
  • 11:37 - 11:39
    trying to figure out how to steer it,
  • 11:39 - 11:41
    but where do we want to go with it?
  • 11:42 - 11:45
    This is the elephant in the room
    that almost nobody talks about --
  • 11:45 - 11:47
    not even here at TED --
  • 11:47 - 11:51
    because we're so fixated
    on short-term AI challenges.
  • 11:52 - 11:57
    Look, our species is trying to build AGI,
  • 11:57 - 12:00
    motivated by curiosity and economics,
  • 12:00 - 12:04
    but what sort of future society
    are we hoping for if we succeed?
  • 12:05 - 12:07
    We did an opinion poll on this recently,
  • 12:07 - 12:08
    and I was struck to see
  • 12:08 - 12:11
    that most people actually
    want us to build superintelligence:
  • 12:11 - 12:14
    AI that's vastly smarter
    than us in all ways.
  • 12:15 - 12:19
    What there was the greatest agreement on
    was that we should be ambitious
  • 12:19 - 12:21
    and help life spread into the cosmos,
  • 12:21 - 12:25
    but there was much less agreement
    about who or what should be in charge.
  • 12:25 - 12:27
    And I was actually quite amused
  • 12:27 - 12:30
    to see that there's some some people
    who want it to be just machines.
  • 12:30 - 12:32
    (Laughter)
  • 12:32 - 12:36
    And there was total disagreement
    about what the role of humans should be,
  • 12:36 - 12:38
    even at the most basic level,
  • 12:38 - 12:41
    so let's take a closer look
    at possible futures
  • 12:41 - 12:44
    that we might choose
    to steer toward, alright?
  • 12:44 - 12:45
    So don't get me wrong here.
  • 12:45 - 12:47
    I'm not talking about space travel,
  • 12:47 - 12:50
    merely about humanity's
    metaphorical journey into the future.
  • 12:51 - 12:54
    So one option that some
    of my AI colleagues like
  • 12:54 - 12:58
    is to build superintelligence
    and keep it under human control,
  • 12:58 - 13:00
    like an enslaved god,
  • 13:00 - 13:01
    disconnected from the internet
  • 13:01 - 13:05
    and used to create unimaginable
    technology and wealth
  • 13:05 - 13:06
    for whoever controls it.
  • 13:07 - 13:08
    But Lord Acton warned us
  • 13:08 - 13:12
    that power corrupts,
    and absolute power corrupts absolutely,
  • 13:12 - 13:16
    so you might worry that maybe
    we humans just aren't smart enough,
  • 13:16 - 13:18
    or wise enough rather,
  • 13:18 - 13:19
    to handle this much power.
  • 13:20 - 13:22
    Also, aside from any
    moral qualms you might have
  • 13:22 - 13:24
    about enslaving superior minds,
  • 13:25 - 13:28
    you might worry that maybe
    the superintelligence could outsmart us,
  • 13:29 - 13:31
    break out and take over.
  • 13:32 - 13:35
    But I also have colleagues
    who are fine with AI taking over
  • 13:35 - 13:37
    and even causing human extinction,
  • 13:37 - 13:41
    as long as we feel the the AIs
    are our worthy descendants,
  • 13:41 - 13:43
    like our children.
  • 13:43 - 13:48
    But how would we know that the AIs
    have adopted our best values
  • 13:48 - 13:53
    and aren't just unconscious zombies
    tricking us into anthropomorphizing them?
  • 13:53 - 13:56
    Also, shouldn't those people
    who don't want human extinction
  • 13:56 - 13:57
    have a say in the matter, too?
  • 13:58 - 14:02
    Now, if you didn't like either
    of those two high-tech options,
  • 14:02 - 14:05
    it's important to remember
    that low-tech is suicide
  • 14:05 - 14:06
    from a cosmic perspective,
  • 14:06 - 14:09
    because if we don't go far
    beyond today's technology,
  • 14:09 - 14:11
    the question isn't whether humanity
    is going to go extinct,
  • 14:11 - 14:13
    merely whether
    we're going to get taken out
  • 14:13 - 14:16
    by the next killer asteroid, supervolcano
  • 14:16 - 14:19
    or some other problem
    that better technology could have solved.
  • 14:19 - 14:22
    So, how about having
    our cake and eating it ...
  • 14:22 - 14:24
    with AGI that's not enslaved
  • 14:25 - 14:28
    but treats us well because its values
    are aligned with ours?
  • 14:28 - 14:32
    This is the gist of what Eliezer Yudkowsky
    has called "friendly AI,"
  • 14:33 - 14:35
    and if we can do this,
    it could be awesome.
  • 14:36 - 14:41
    It could not only eliminate negative
    experiences like disease, poverty,
  • 14:41 - 14:42
    crime and other suffering,
  • 14:42 - 14:45
    but it could also give us
    the freedom to choose
  • 14:45 - 14:49
    from a fantastic new diversity
    of positive experiences --
  • 14:49 - 14:52
    basically making us
    the masters of our own destiny.
  • 14:54 - 14:56
    So in summary,
  • 14:56 - 14:59
    our situation with technology
    is complicated,
  • 14:59 - 15:01
    but the big picture is rather simple.
  • 15:01 - 15:05
    Most AI researchers
    expect AGI within decades,
  • 15:05 - 15:08
    and if we just bumble
    into this unprepared,
  • 15:08 - 15:11
    it will probably be
    the biggest mistake in human history --
  • 15:11 - 15:13
    let's face it.
  • 15:13 - 15:15
    It could enable brutal,
    global dictatorship
  • 15:15 - 15:19
    with unprecedented inequality,
    surveillance and suffering,
  • 15:19 - 15:21
    and maybe even human extinction.
  • 15:21 - 15:23
    But if we steer carefully,
  • 15:24 - 15:28
    we could end up in a fantastic future
    where everybody's better off:
  • 15:28 - 15:30
    the poor are richer, the rich are richer,
  • 15:30 - 15:34
    everybody is healthy
    and free to live out their dreams.
  • 15:35 - 15:37
    Now, hang on.
  • 15:37 - 15:41
    Do you folks want the future
    that's politically right or left?
  • 15:41 - 15:44
    Do you want the pious society
    with strict moral rules,
  • 15:44 - 15:46
    or do you an hedonistic free-for-all,
  • 15:46 - 15:48
    more like Burning Man 24/7?
  • 15:48 - 15:51
    Do you want beautiful beaches,
    forests and lakes,
  • 15:51 - 15:54
    or would you prefer to rearrange
    some of those atoms with the computers,
  • 15:54 - 15:56
    enabling virtual experiences?
  • 15:56 - 15:59
    With friendly AI, we could simply
    build all of these societies
  • 15:59 - 16:02
    and give people the freedom
    to choose which one they want to live in
  • 16:02 - 16:05
    because we would no longer
    be limited by our intelligence,
  • 16:05 - 16:07
    merely by the laws of physics.
  • 16:07 - 16:11
    So the resources and space
    for this would be astronomical --
  • 16:11 - 16:13
    literally.
  • 16:13 - 16:15
    So here's our choice.
  • 16:16 - 16:18
    We can either be complacent
    about our future,
  • 16:19 - 16:22
    taking as an article of blind faith
  • 16:22 - 16:26
    that any new technology
    is guaranteed to be beneficial,
  • 16:26 - 16:30
    and just repeat that to ourselves
    as a mantra over and over and over again
  • 16:30 - 16:34
    as we drift like a rudderless ship
    towards our own obsolescence.
  • 16:35 - 16:37
    Or we can be ambitious --
  • 16:38 - 16:40
    thinking hard about how
    to steer our technology
  • 16:40 - 16:42
    and where we want to go with it
  • 16:42 - 16:44
    to create the age of amazement.
  • 16:45 - 16:48
    We're all here to celebrate
    the age of amazement,
  • 16:48 - 16:52
    and I feel that its essence should lie
    in becoming not overpowered
  • 16:53 - 16:56
    but empowered by our technology.
  • 16:56 - 16:57
    Thank you.
  • 16:57 - 17:00
    (Applause)
Title:
How to get empowered, not overpowered, by AI
Speaker:
Max Tegmark
Description:

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.

more » « less
Video Language:
English
Team:
closed TED
Project:
TEDTalks
Duration:
17:15

English subtitles

Revisions Compare revisions