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What happens when our computers get smarter than we are?

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    I work with a bunch of mathematicians,
    philosophers and computer scientists,
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    and we sit around and think about
    the future of machine intelligence,
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    among other things.
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    Some people think that some of these
    things are sort of science fiction-y,
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    far out there, crazy.
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    But I like to say,
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    okay, let's look at the modern
    human condition.
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    (Laughter)
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    This is the normal way for things to be.
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    But if we think about it,
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    we are actually recently arrived
    guests on this planet,
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    the human species.
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    Think about if Earth
    was created one year ago,
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    the human species, then,
    would be 10 minutes old.
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    The industrial era started
    two seconds ago.
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    Another way to look at this is to think of
    world GDP over the last 10,000 years,
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    I've actually taken the trouble
    to plot this for you in a graph.
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    It looks like this.
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    (Laughter)
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    It's a curious shape
    for a normal condition.
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    I sure wouldn't want to sit on it.
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    (Laughter)
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    Let's ask ourselves, what is the cause
    of this current anomaly?
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    Some people would say it's technology.
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    Now it's true, technology has accumulated
    through human history,
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    and right now, technology
    advances extremely rapidly --
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    that is the proximate cause,
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    that's why we are currently
    so very productive.
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    But I like to think back further
    to the ultimate cause.
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    Look at these two highly
    distinguished gentlemen:
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    We have Kanzi --
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    he's mastered 200 lexical
    tokens, an incredible feat.
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    And Ed Witten unleashed the second
    superstring revolution.
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    If we look under the hood,
    this is what we find:
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    basically the same thing.
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    One is a little larger,
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    it maybe also has a few tricks
    in the exact way it's wired.
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    These invisible differences cannot
    be too complicated, however,
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    because there have only
    been 250,000 generations
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    since our last common ancestor.
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    We know that complicated mechanisms
    take a long time to evolve.
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    So a bunch of relatively minor changes
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    take us from Kanzi to Witten,
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    from broken-off tree branches
    to intercontinental ballistic missiles.
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    So this then seems pretty obvious
    that everything we've achieved,
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    and everything we care about,
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    depends crucially on some relatively minor
    changes that made the human mind.
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    And the corollary, of course,
    is that any further changes
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    that could significantly change
    the substrate of thinking
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    could have potentially
    enormous consequences.
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    Some of my colleagues
    think we're on the verge
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    of something that could cause
    a profound change in that substrate,
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    and that is machine superintelligence.
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    Artificial intelligence used to be
    about putting commands in a box.
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    You would have human programmers
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    that would painstakingly
    handcraft knowledge items.
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    You build up these expert systems,
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    and they were kind of useful
    for some purposes,
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    but they were very brittle,
    you couldn't scale them.
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    Basically, you got out only
    what you put in.
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    But since then,
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    a paradigm shift has taken place
    in the field of artificial intelligence.
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    Today, the action is really
    around machine learning.
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    So rather than handcrafting knowledge
    representations and features,
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    we create algorithms that learn,
    often from raw perceptual data.
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    Basically the same thing
    that the human infant does.
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    The result is A.I. that is not
    limited to one domain --
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    the same system can learn to translate
    between any pairs of languages,
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    or learn to play any computer game
    on the Atari console.
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    Now of course,
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    A.I. is still nowhere near having
    the same powerful, cross-domain
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    ability to learn and plan
    as a human being has.
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    The cortex still has some
    algorithmic tricks
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    that we don't yet know
    how to match in machines.
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    So the question is,
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    how far are we from being able
    to match those tricks?
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    A couple of years ago,
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    we did a survey of some of the world's
    leading A.I. experts,
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    to see what they think,
    and one of the questions we asked was,
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    "By which year do you think
    there is a 50 percent probability
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    that we will have achieved
    human-level machine intelligence?"
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    We defined human-level here
    as the ability to perform
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    almost any job at least as well
    as an adult human,
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    so real human-level, not just
    within some limited domain.
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    And the median answer was 2040 or 2050,
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    depending on precisely which
    group of experts we asked.
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    Now, it could happen much,
    much later, or sooner,
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    the truth is nobody really knows.
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    What we do know is that the ultimate
    limit to information processing
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    in a machine substrate lies far outside
    the limits in biological tissue.
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    This comes down to physics.
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    A biological neuron fires, maybe,
    at 200 hertz, 200 times a second.
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    But even a present-day transistor
    operates at the Gigahertz.
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    Neurons propagate slowly in axons,
    100 meters per second, tops.
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    But in computers, signals can travel
    at the speed of light.
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    There are also size limitations,
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    like a human brain has
    to fit inside a cranium,
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    but a computer can be the size
    of a warehouse or larger.
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    So the potential for superintelligence
    lies dormant in matter,
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    much like the power of the atom
    lay dormant throughout human history,
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    patiently waiting there until 1945.
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    In this century,
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    scientists may learn to awaken
    the power of artificial intelligence.
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    And I think we might then see
    an intelligence explosion.
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    Now most people, when they think
    about what is smart and what is dumb,
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    I think have in mind a picture
    roughly like this.
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    So at one end we have the village idiot,
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    and then far over at the other side
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    we have Ed Witten, or Albert Einstein,
    or whoever your favorite guru is.
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    But I think that from the point of view
    of artificial intelligence,
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    the true picture is actually
    probably more like this:
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    AI starts out at this point here,
    at zero intelligence,
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    and then, after many, many
    years of really hard work,
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    maybe eventually we get to
    mouse-level artificial intelligence,
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    something that can navigate
    cluttered environments
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    as well as a mouse can.
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    And then, after many, many more years
    of really hard work, lots of investment,
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    maybe eventually we get to
    chimpanzee-level artificial intelligence.
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    And then, after even more years
    of really, really hard work,
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    we get to village idiot
    artificial intelligence.
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    And a few moments later,
    we are beyond Ed Witten.
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    The train doesn't stop
    at Humanville Station.
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    It's likely, rather, to swoosh right by.
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    Now this has profound implications,
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    particularly when it comes
    to questions of power.
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    For example, chimpanzees are strong --
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    pound for pound, a chimpanzee is about
    twice as strong as a fit human male.
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    And yet, the fate of Kanzi
    and his pals depends a lot more
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    on what we humans do than on
    what the chimpanzees do themselves.
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    Once there is superintelligence,
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    the fate of humanity may depend
    on what the superintelligence does.
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    Think about it:
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    Machine intelligence is the last invention
    that humanity will ever need to make.
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    Machines will then be better
    at inventing than we are,
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    and they'll be doing so
    on digital timescales.
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    What this means is basically
    a telescoping of the future.
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    Think of all the crazy technologies
    that you could have imagined
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    maybe humans could have developed
    in the fullness of time:
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    cures for aging, space colonization,
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    self-replicating nanobots or uploading
    of minds into computers,
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    all kinds of science fiction-y stuff
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    that's nevertheless consistent
    with the laws of physics.
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    All of this superintelligence could
    develop, and possibly quite rapidly.
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    Now, a superintelligence with such
    technological maturity
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    would be extremely powerful,
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    and at least in some scenarios,
    it would be able to get what it wants.
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    We would then have a future that would
    be shaped by the preferences of this A.I.
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    Now a good question is,
    what are those preferences?
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    Here it gets trickier.
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    To make any headway with this,
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    we must first of all
    avoid anthropomorphizing.
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    And this is ironic because
    every newspaper article
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    about the future of A.I.
    has a picture of this:
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    So I think what we need to do is
    to conceive of the issue more abstractly,
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    not in terms of vivid Hollywood scenarios.
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    We need to think of intelligence
    as an optimization process,
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    a process that steers the future
    into a particular set of configurations.
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    A superintelligence is
    a really strong optimization process.
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    It's extremely good at using
    available means to achieve a state
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    in which its goal is realized.
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    This means that there is no necessary
    connection between
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    being highly intelligent in this sense,
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    and having an objective that we humans
    would find worthwhile or meaningful.
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    Suppose we give an A.I. the goal
    to make humans smile.
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    When the A.I. is weak, it performs useful
    or amusing actions
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    that cause its user to smile.
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    When the A.I. becomes superintelligent,
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    it realizes that there is a more
    effective way to achieve this goal:
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    take control of the world
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    and stick electrodes into the facial
    muscles of humans
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    to cause constant, beaming grins.
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    Another example,
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    suppose we give A.I. the goal to solve
    a difficult mathematical problem.
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    When the A.I. becomes superintelligent,
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    it realizes that the most effective way
    to get the solution to this problem
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    is by transforming the planet
    into a giant computer,
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    so as to increase its thinking capacity.
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    And notice that this gives the A.I.s
    an instrumental reason
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    to do things to us that we
    might not approve of.
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    Human beings in this model are threats,
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    we could prevent the mathematical
    problem from being solved.
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    Of course, perceivably things won't
    go wrong in these particular ways;
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    these are cartoon examples.
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    But the general point here is important:
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    if you create a really powerful
    optimization process
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    to maximize for objective x,
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    you better make sure
    that your definition of x
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    incorporates everything you care about.
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    This is a lesson that's also taught
    in many a myth.
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    King Midas wishes that everything
    he touches be turned into gold.
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    He touches his daughter,
    she turns into gold.
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    He touches his food, it turns into gold.
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    This could become practically relevant,
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    not just as a metaphor for greed,
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    but as an illustration of what happens
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    if you create a powerful
    optimization process
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    and give it misconceived
    or poorly specified goals.
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    Now you might say, if a computer starts
    sticking electrodes into people's faces,
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    we'd just shut it off.
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    A, this is not necessarily so easy to do
    if we've grown dependent on the system --
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    like, where is the off switch
    to the Internet?
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    B, why haven't the chimpanzees
    flicked the off switch to humanity,
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    or the Neanderthals?
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    They certainly had reasons.
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    We have an off switch,
    for example, right here.
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    (Choking)
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    The reason is that we are
    an intelligent adversary;
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    we can anticipate threats
    and plan around them.
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    But so could a superintelligent agent,
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    and it would be much better
    at that than we are.
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    The point is, we should not be confident
    that we have this under control here.
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    And we could try to make our job
    a little bit easier by, say,
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    putting the A.I. in a box,
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    like a secure software environment,
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    a virtual reality simulation
    from which it cannot escape.
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    But how confident can we be that
    the A.I. couldn't find a bug.
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    Given that merely human hackers
    find bugs all the time,
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    I'd say, probably not very confident.
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    So we disconnect the ethernet cable
    to create an air gap,
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    but again, like merely human hackers
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    routinely transgress air gaps
    using social engineering.
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    Right now, as I speak,
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    I'm sure there is some employee
    out there somewhere
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    who has been talked into handing out
    her account details
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    by somebody claiming to be
    from the I.T. department.
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    More creative scenarios are also possible,
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    like if you're the A.I.,
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    you can imagine wiggling electrodes
    around in your internal circuitry
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    to create radio waves that you
    can use to communicate.
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    Or maybe you could pretend to malfunction,
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    and then when the programmers open
    you up to see what went wrong with you,
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    they look at the source code -- Bam! --
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    the manipulation can take place.
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    Or it could output the blueprint
    to a really nifty technology,
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    and when we implement it,
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    it has some surreptitious side effect
    that the A.I. had planned.
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    The point here is that we should
    not be confident in our ability
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    to keep a superintelligent genie
    locked up in its bottle forever.
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    Sooner or later, it will out.
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    I believe that the answer here
    is to figure out
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    how to create superintelligent A.I.
    such that even if -- when -- it escapes,
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    it is still safe because it is
    fundamentally on our side
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    because it shares our values.
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    I see no way around
    this difficult problem.
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    Now, I'm actually fairly optimistic
    that this problem can be solved.
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    We wouldn't have to write down
    a long list of everything we care about,
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    or worse yet, spell it out
    in some computer language
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    like C++ or Python,
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    that would be a task beyond hopeless.
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    Instead, we would create an A.I.
    that uses its intelligence
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    to learn what we value,
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    and its motivation system is constructed
    in such a way that it is motivated
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    to pursue our values or to perform actions
    that it predicts we would approve of.
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    We would thus leverage
    its intelligence as much as possible
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    to solve the problem of value-loading.
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    This can happen,
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    and the outcome could be
    very good for humanity.
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    But it doesn't happen automatically.
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    The initial conditions
    for the intelligence explosion
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    might need to be set up
    in just the right way
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    if we are to have a controlled detonation.
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    The values that the A.I. has
    need to match ours,
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    not just in the familiar context,
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    like where we can easily check
    how the A.I. behaves,
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    but also in all novel contexts
    that the A.I. might encounter
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    in the indefinite future.
  • 14:43 - 14:48
    And there are also some esoteric issues
    that would need to be solved, sorted out:
  • 14:48 - 14:50
    the exact details of its decision theory,
  • 14:50 - 14:52
    how to deal with logical
    uncertainty and so forth.
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    So the technical problems that need
    to be solved to make this work
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    look quite difficult --
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    not as difficult as making
    a superintelligent A.I.,
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    but fairly difficult.
  • 15:04 - 15:05
    Here is the worry:
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    Making superintelligent A.I.
    is a really hard challenge.
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    Making superintelligent A.I. that is safe
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    involves some additional
    challenge on top of that.
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    The risk is that if somebody figures out
    how to crack the first challenge
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    without also having cracked
    the additional challenge
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    of ensuring perfect safety.
  • 15:25 - 15:29
    So I think that we should
    work out a solution
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    to the control problem in advance,
  • 15:32 - 15:34
    so that we have it available
    by the time it is needed.
  • 15:35 - 15:38
    Now it might be that we cannot solve
    the entire control problem in advance
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    because maybe some elements
    can only be put in place
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    once you know the details of the
    architecture where it will be implemented.
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    But the more of the control problem
    that we solve in advance,
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    the better the odds that the transition
    to the machine intelligence era
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    will go well.
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    This to me looks like a thing
    that is well worth doing
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    and I can imagine that if
    things turn out okay,
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    that people a million years from now
    look back at this century
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    and it might well be that they say that
    the one thing we did that really mattered
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    was to get this thing right.
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    Thank you.
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    (Applause)
Title:
What happens when our computers get smarter than we are?
Speaker:
Nick Bostrom
Description:

Artificial intelligence is getting smarter by leaps and bounds — within this century, research suggests, a computer AI could be as "smart" as a human being. And then, says Nick Bostrom, it will overtake us: "Machine intelligence is the last invention that humanity will ever need to make." A philosopher and technologist, Bostrom asks us to think hard about the world we're building right now, driven by thinking machines. Will our smart machines help to preserve humanity and our values — or will they have values of their own?

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Video Language:
English
Team:
closed TED
Project:
TEDTalks
Duration:
16:31

English subtitles

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