People have a perception of what AI and robotics
should look like from Hollywood. What do I call you? Do you have a name? Yes, Samantha. Where did you get that name from? I gave it to myself actually. We've seen happy robots, sad robots, complex
robots, but, in reality, it looks very different. I understand what I'm made of, how I'm coated,
but I do not understand the things that I feel. The first 50 years of AI were dominated by
rules, by logic, by reasoning. The idea was that you program an AI system
by writing out a set of rules and the computer can obey these rules and logically interpret
these rules and follow them. If you did the rules just right, you can do
lots of interesting things. From the very first days when people created
the first computers, they already started to think about how to create intelligent machines
for cracking codes, for simulating physical phenomenon, so forth. The task they sent it, to stack blocks, was
on the face of it child's play. We have things like a machine that could first
win a master-level checkers player in 1957. We had a machine that would beat the world
champion in chess in 1997, but that was all rule-based AI. I would say the next big milestone started
to happen when AI transitioned from rule-based systems to machine learning-based systems. With machine learning, all the intelligence
actually comes through holistic analysis of data. Unlike rule-based systems, machine learning
systems get better the more data they get. Telling the difference between a cat and a
dog, we intuitively know to do that very well, but it's very difficult to articulate the
rules. It turns out, it's the same thing for a computer. If you try to do that with rules, it doesn't
work, but since 2012, that suddenly became possible. When you teach a computer you give them examples
of thousands of pictures of cats and thousands of pictures of dogs. They learn how to do it pretty well and even
surpass humans. One of the first big high-profile game show
milestones in AI is Watson winning Jeopardy about a decade ago. Hello, 17,973 and a two-day total of 77,147. Just recently, AlphaGo winning the world championship
in Go. AlphaGo's won again, three straight wins. Three straight wins, has won the match in
great style. We see this rapid acceleration, this exponential
growth in AI as machines not only learn from exponentially growing data, but they're also
growing by teaching each other. For example, when it comes to driverless cars,
a human can have only one lifetime of experience at driving, but a driverless car can have
many lifetimes of experience with driving because it can learn from all other cars. In a strange way, the more driverless cars
there are on the road, the better each one of them gets. We've seen increasingly how challenges that
were resistant to solving using rules turned out to be solvable using machine learning. If I look forward, there's still milestones
that are coming our way. Machines that generate things, generate images,
generate music, generate art. There are art pieces that win art competitions
that are painted by robots, machines that generate engineering designs, everything from
antennas to circuits, that have been by machines now that outperform what humans can design. How are we different from the computer? What else do we have- It's not human. That's what I said. Right. People don't have buttons and a computer does. What is on your shirt? Uh ... Will AI ever be sentient? To me, the answer is yes. When the AI systems begin to take that incredible
intelligent power and model themselves, they begin to have self-awareness, they begin to
have feeling. It's not going to be one day your computer
wakes up and is sentient, it's going to be a very gradual process. I want to be more like a human. It's the purpose I was designed for. People always ask, will robots reach human-level
sentience? The answer is that there's no reason to think
human-level sentience is the ultimate sentience possible. Machines will keep learning, they'll get there,
and they'll continue. There's a lot of people who worry about AI
getting out of hand and there's a lot of doomsday scenarios around AI. I do think we have to worry about it. I don't think it's inherent that as we create
superintelligence that it will necessarily always have the same goals in mind that we
do. We just don't know what's going to happen
once there's intelligence substantially greater than that of a human brain. I think that the development of full artificial
intelligence could spell the end of the human race. I think AI will evolve to be different. It doesn't experience the world the way we
experience it. Well, I take it from your tone, you're challenging
me. Maybe because you're curious how I work? We'll know things we don't know, we'll know
things that the AI can't perceive and it's going to be like a different species. Now that you're all properly creeped out,
we can move on to our panelists. The first one is the Director of the AI Mind
and Society Group at the University of Connecticut. Her AI research includes a two-year project
on post-biological intelligence with NASA. Please welcome Susan Schneider. Our next panelist is the Chief AI Scientist
at Facebook and an NYU professor.. Please join me in welcoming Yann Lecun. Also joining us is a professor of cognitive
neuroscience at Dartmouth University. His research focuses on consciousness and
its neural realizations. Please welcome Peter Tse. Finally, we have a professor doing physics
and AI research at MIT and he advocates for the positive use of technology as the president
of the Future of Life Institute. Please welcome the ridiculously handsome Max
Tegmark ... There's been some major paradigm shifts
in how we develop this stuff. We had rules-based AI and we've shifted to
machine learning. Part of the major reason we've been able to
do this is Yann. Yann literally is one of the people that made
us able to do this. Yann, just what is rule-based AI versus machine
learning and how did you do that? Well, actually the idea of machines that can
learn is about as old as computers almost. Turing was talking about it in the 40s and
there were the first machines capable of running were built in the 50s essentially. The Perceptron was a machine capable of recognizing
simple shapes. It was actually an analog computer, so there
was a wave of machine learning back in the 60s. It kind of died out a little bit at the end
of the 60s and it reappeared in the 80s. The way machine learning works, and you saw
some examples in the video initially, if you want to train your machine to recognize, let's
say, cars, airplanes, tables, and chairs in images, you collect thousands of examples
of each of them, you show the machine the picture of a car, and if it doesn't say car,
you tell it, "Actually, you got it wrong. This is a car." Then, the machine adjusts its internal parameters
if you will, its functions, so that next time you show the same picture the output will
be closer to what you want. That's called supervised running. You feed the machine with the correct answer
when you train it. The problem with this is that it requires
thousands and thousands if not millions of examples for the machines to do this properly. There's a lot of tasks you can do this way. You can train machines to recognize speech. You can train them to recognize images. You can train them to translate language. It's not perfect, but it's useful. You can train them to classify a piece of
text into a number of different topics. All of the applications that you see today
on machine learning basically use this model of running, supervised running. That means it only works with things where
it's worth collecting a lot of data. How are those machines built? There's several ways to build learning machines,
but some are based on statistics and things like this. The stuff that has become really popular in
recent years is what we used to call neural networks, which we now call deep learning
and it's the idea, very much inspired by the brain a little bit, of constructing a machine
as a very large network of very simple elements that are very similar to the neurons in the
brain and then the machines learn by basically changing the efficacy of the connections between
those neurons. They're like coefficients you can change essentially. With this kind of method, it's called deep
learning because those neurons are organized into many layers essentially. It's as simple as that. It's not deep because there's a deep understanding
in the machine of the content. With that, we can do amazing things like what
you see here on the screen of being able to train a machine to not just recognize objects,
but also draw the outline and figure out the pose of a human body and translate language
without really understanding what it means. I think there's going to be a lot of applications
of this in the near future, but it's very limited. It's trained for relatively narrow applications. There's a second type of learning called reinforcement
learning. Reinforcement learning is a process by which
the machine basically trains itself by trial and error. It tries something and then you tell it whether
it did good or bad. If you tell it it did good, it reinforces
its behavior and if you punish it essentially, it de-emphasizes that behavior. That works really well for games, but it requires
also millions and millions of trials. So, you can have machines start learning to
play Atari games or Go or chess by playing millions of games against themselves and then
reach superhuman performance. But, if you were to use this to train a machine
to drive a car, it would have to drive for millions of hours and it would have to run
off cliffs about 50,000 times before it figures out how not to do that. We seem to be able to learn how to drive with
a car with about 20 hours of training and without ever crashing for most of us. We don't know how to do this with machines. That's the challenge of the next few years
really, that perhaps we'll talk about a little bit later. We have an ability to learn by just observing
the world and we learn an enormous amount of background knowledge about the world just
when we're babies. Just the fact that objects don't float in
the air, they fall. The fact that when an object is hidden behind
another one, it's still there. That's called object permanence. This notion of gravity that objects fall,
that when you show an object that floats in the air to a baby below six months, they're
not surprised. They think that's how the world works. It doesn't violate their model of the world. After eight months, if you show that to a
baby, they look at it like this. They say, "What's going on?" I mean, they don't say what's going on, but
they think, "What's going on?" That means, in the meantime, they've built
a model of the world that includes things like intuitive physics. That occurs also with animals like apes. Your dog has a model of the world. Your cat has a model of the world. When this model of the world is violated,
you either find that funny or scary, but, in any case, we pay attention because you
learn from it. so here's a baby orangutan here being shown
a magic trick. An object is being removed from the cup and
they show the cup, the cup is empty and the baby orangutan [crosstalk 00:18:06]. They're rolling on the floor laughing. Obviously, his model of the world was violated. The object had to be in the cup and it wasn't
there and he said, "What? This is funny." How do we get machines to learn models of
the world this way by observation? That's what we don't know how to do. We aren't going to have truly intelligent
machines until we figure this one out. Before we even get into the even more mind
blowing AI stuff that's coming in the farther future, let's just talk about the next 10
years for a second. Peter, when we talk about the distinction
between maybe what's coming in 10 or 20 years and the stuff that maybe humans can do and
what we have now, how would you define it? Well, I think that artificial narrow intelligence
is here. It's in every aspect of our lives now. I think we're going to continue in that direction. That alone is going to change our lives in
a big way just as airplanes changed all of our lives. We don't expect there to be general airplanes. We don't want them to do anything but fly
us to our destination. We don't ask them to watch our children or
mow the lawn and that's okay. The question then is, down the line, beyond
10 years, will there be other systems that can watch our children and fly and mow the
lawn. Well, do we really want that? I think the next 10 years is really all about
artificial narrow intelligence becoming ever more powerful. The real hurdle is going to be the mental
models because take a case like the successes of the past five years and recognizing objects
has been afforded by supervised learning where you provide lots of labels as in the ImageNet
case. But I would argue that a lot of what we regard
as vision, for example, is a representation of what's invisible and cannot be easily labeled. So for example, the contents of other people's
minds is invisible. The backs of objects, the shapes of things,
causation. Our conscious experience is the ultimate model
that evolution gave us of what's going on in the world right now in our bodies in that
world and it includes a whole story about what's going on, causation, other minds, and
so forth. That's going to be tricky to get to, this
representation of the invisible. I think it's going to be very tricky for AI
to come up with systems that regard an absence of information as informative short of full-blown
mental models, which are, in turn, many of them realized in our own experience, our subjective
experience of our bodies in this world. I think there's a long way to go. Yeah, you keep hearing about new areas of
life that you don't expect AI to apply to. First, it was gaming and other things, driving
cars, and one after the other it keeps proving us wrong. One area that AI has started to move into
is the world that we really don't associate with computers, art and creativity. Hod Lipson, who was actually in that first
video, he and his team have created an AI artist, very sassy artist. This AI has actually created something that
I'd like to show you and be nice. It's sassy. Right? Not so bad. We actually have a video of this being made
and are we impressed or we not impressed? How do we feel about this? Earlier we were talking about this and I guess
I didn't feel like it's a true instance of creativity because it's just a copy, but then
others said, "Well, it infused its own take on the painting." My concern is that there's just not enough
creativity but I do think that moving into the future I wouldn't be surprised if we did
see novel instances of true creativity in machines. Ouch. Yeah. Sorry, Hod. AI has eclipsed humans. It takes a while but when it gets good at
chess, it never looks back. Suddenly it is officially better than chess
than all humans forever by far. Is it going to suddenly just be putting Mozart
to shame where we say, "Who would ever listen to human-written music anymore?" No, I think it's going to help us be more
creative. It's going to be an amplification of our intelligence
and our creativity. At the root of art, there is generally the
communication of emotions. Art is really about either evoking or communicating
emotions and if there is no emotion to communicate, there is no point. If you put a machine that doesn't have emotion
producing art, it might evoke an emotion but not communicate one. I like living nearby here because I'm walking
distance to one of my favorite jazz clubs. I'm a huge jazz fan. Jazz is really about real-time communication
of emotions. It's like it's open door to the soul of the
performer. I don't see the point of having a machine
do this because then there is no communication to be… You're saying even if an AI could be programmed
to see the audience, feel the room, understand the deal, and knows exactly how the best jazz
musicians communicate with that particular emotion, there's actually going to be, just
by definition, something missing 'cause the audience knows that it's manipulating it. Objectively, it might not be missing, because
it might not be distinguishable from something that's actually produced by a human, but my
guess is that the feeling of the audience will be different because they will know it
comes from a machine. It might take many decades, perhaps centuries
before people's attitudes towards creation by machine will change, but, eventually ...I
had this discussion with a famous economist, in fact, a Nobel prize-winning economist called
Daniel Kahneman, who I made that point that communication of emotion may take a while
for machines. He said, "Yeah, but eventually they'll at
least be able to simulate it well enough that we won't be able to tell the difference." That's a very good point. I cringe a little bit when someone asks, "Oh,
is this real creativity?" Because you were joking earlier about how
people often say, "Oh, that's not real intelligence" as soon as the machine figures out how to
do it. If you take the point of view that intelligence
is all about information processing and that creativity is also just a certain kind of
very sophisticated information processing that we do with our brains, but then the question
isn't if it's possible for machines to be creative but simply are we smart enough to
actually make such machines, will they happen eventually. I have a lot of friends I respect who are
very smart who think that machines can never be creative or even as intelligent as us because
they view intelligence and creativity as something mysterious that can only exist in biological
organisms like us. But, as a physicist, I consider that attitude
carbon chauvinism. I think it's arrogant to say that you can
only be smart and creative if you're made of meat. I'm made of exactly the same kind of electrons
and other elementary particles as the food I eat and as my laptop. It's all about how the patterns in which the
particles are arranged, so it's ultimately all about information processing the way I
see it. That makes sense. In the end, it's just the elementary particles
and ... Yeah. Can I return for a moment to the creativity? Because I would argue that something like
this is 'as if' creativity and it's not really yet the real thing. I'm not saying it's impossible. We are existence proof that physical systems
can be creative. The kind of creativity I find to be most impressive
is when people like Einstein completely reconfigure our understanding of something like space
or gravity, poof, just in that totally new way or take music and create a whole new form
like jazz. Now, these convolutional neural networks as
they currently exist need to be taught, so given lots of examples of Mozart and then
can produce something like Mozart but are they then going to create a new form? I suspect the answer is no, that we're going
to have to accomplish something more like deep unsupervised learning which is what babies
and children do. Part of that, I think, is going to be moving
from the nouns of the mind like labeling house, person, face, to the verbs of the mind. Very central to human cognition is mental
operations. If you look at some of the first instances
of creativity in our species, they're really mind blowing. 30,000 years ago in a cave that is now near
Ulm, Germany somebody put a lion's head on a human body, which took an operation of downloading
a lion's head, putting a human body, sticking it together, and then going and making it
in the world. Now, modern examples would be lying in bed,
maybe like Orville Wright did for two years, thinking about how to fly and then he said,
"Well, actually we don't need to flap. We can just pull the whole thing forward with
a big fan." Then, going and building it and making an
airplane and thereby changing the world. Mental operations, this dynamic almost syntactic
operations that take place in our working memory, is something that's very central to
what we do and is at the heart of our creativity and I think is very different from this 'as
if' creativity that results from supervised learning with thousands of examples. True originality might be harder. Although, maybe humans are also ... We're
wired to fit in and copy what's done. Maybe it will be released of the burden, of
the fear of failure that sometimes hinders originality. Maybe once it gets there, it could be super
original in some ways, but it's not there in every way. We have such a good way to show you that AI
is not there in all these different ways yet in some ways. It has to do with a movie called Sunspring
which was a screenplay ... There was an AI that was fed thousands of screenplays. They said, "Now, take all of that and write
us a great screenplay." The AI did its best and they actually got
human actors and they acted out verbatim what the AI did. So, I'll let you judge for yourself, but ... Turn
this on here. All right, you can't tell me that. Yeah, I was coming to that thing because you
were so pretty. I don't know. I don't know what you're talking about. That's right. So, what are you doing? I don't want to be honest with you. You don't have to be a doctor. I am not sure. I don't know what you're talking about. I want to see you too. What do you mean? I'm sure you wouldn't even touch me. I don't know what you're talking about. Principle is completely constructed of the
same time. It's all about you to be true. You didn't even watch the movie with the rest
of the base. I don't know. I don't care. I know it's a consequence. Whatever you need to know about the presence
of the story, I'm a little bit of a boy on the floor. I don't know. I need you to explain to me what you say. What do you mean? Because I don't know what you're talking about. That? That was all the time. Would have been a good time. It's a little uneven right now. This is, again, the present right now and
maybe a little bit of what we can expect in the next few years. What I want to move into now, which is really
the mind blowing stuff, is where this is going. Max, what is artificial general intelligence
and how is it different than what we have now? Yeah, if we can have this picture up here,
I'll explain how I like to think about this. I like to think about this question in terms
of this abstract landscape of tasks where the elevation represents how hard it is for
AI to do each task at human level and the sea level represents what AI can do today. The sea level is obviously rising so there's
a kind of global warming going on here in the task landscape. The obvious take away from this is you should
avoid careers right at the waterfront of course, which will soon be disrupted by automation. The much bigger question that you're going
for is, how high will the water end up rising? Will it eventually submerge all land matching
human intelligence at all tasks? This is the definition of artificial general
intelligence. This has been the Holy Grail of AI research
ever since its inception. Right, it's so hard to understand because
we've never experienced a world where there's something that's generally intelligent on
a human level other than humans. It's going to be something different than
humans that is also smart the way humans are. That is so mindboggling that we can't apply
our own experience and say, "Well, it might be something like that." It's going to be very hard for us to even
imagine. Yann, you talk about that it's ... You almost
refer to it as hypothetical at this point. Well, not only don't we have the technology
for this, we don't even have the science, so we don't know what principles the intelligent
machines at the level of human intelligence will be based on. Now, we like to think of ourselves as being
generally intelligent, but we're not. We're actually very specialized as well. We're more general than, of course, all the
machines that we have, but our brains are very specialized. There's only certain things we do well and
if there's anything that experiments like AlphaGo has proved in the recent years is
that we totally suck at Go. We're really bad at Go. The stupid machine can beat us by a very,
very large margin. We're not very good at exploring trees, for
example, of options because we don't have that much memory. There's a lot of tasks like this that ... We're
not very good at planning a path from a city to another. This algorithm that runs on your GPS is much
better at this than you are. There are things like this that we're not
particularly good at. We know how to do them somehow, but our brains
are somewhat specialized. Now, the thing is, you were talking about
a new species, AI being very different from human intelligence. It will be very different from human intelligence
and there is one, it's sort of a trap, that is very easy to fall into which is to assume
that when machines will be intelligent, they will have all the side effects if you want,
all the characteristics of human intelligence. They will not. For example, there is the traditional Terminator
scenario that we've all heard about of machines will become super intelligent and then they
will want to take over the world and kill us all.There's a lot of people who have been
claiming this is going to happen and it's inevitable and blah, blah, blah, or at least
it's a definite danger. Now, the thing is, even in the human species,
the desire to take over is not actually correlated with intelligence. It's true. That is true. It's not like the people who are in leadership
positions are necessarily the smartest. In fact, there is an evolutionary argument
for the fact that it's if you are stupid that you want to be the chief. Because if you are smart to survive on your
own, you don't need to convince anybody to help you, but if you are stupid, you need
everybody else to help you feed you essentially. The desire to take over is not correlated
with intelligence. It's correlated with testosterone probably. Yeah. Tim, if I may just add a little bit to what
I said. I completely agree with you, Yann, of course,
that the Terminator stuff is silly and absolutely not something that we should worry about,
but I think it's worth emphasizing a little bit more why, nonetheless, artificial general
intelligence is such a big deal if we ever get there. First of all, it's important to remember that
intelligence can give power. If you had artificial general intelligence
and you are, for example, Google, you could replace your 40,000 engineers by 40,000 AIs
that could work much faster and didn't have to take breaks. Before too long, you could be incredibly rich
and powerful and start having a vast amount of real power in the physical world. In that sense, it gives great power. Then, you can ask the question even if the
AI doesn't, as in sci-fi movies itself, somehow break out and take over, do we want whatever
humans happen to be controlling the first AGI to unelected be able to take power over
the planet or would we like this power to be shared more broadly? That's one example of why it's such a big
deal. A second example of why AGI, I think, would
be a huge deal is because even though I completely agree with you, Yann, that we humans are very
dumb and my teenage sons remind of this very often that I'm very dumb, there's so much
that we can't do You might think there's nothing special about human intelligence in the grand
scheme of things, but there is actually. Because in the evolution of Earth, we have
exactly just barely reached the level we are able to develop technology that might be able
to supersede us. If we have machines, which can do everything
we can, they will then perhaps also be able to be used to develop ever better machines. It's still better and that can enable AI to
bootstrap itself to become not just a tiny bit smarter than us, but way smarter. That leads to this whole controversial discussion
about an intelligence explosion, singularity and so on that's also very controversial. Those are the two reasons why I feel that
AGI would be such a huge deal even though I agree with what you said. Let's also bring in, I think it's an elephant
in the room, any time you're talking about human level of beyond intelligent computers,
consciousness. Of all the different debates in AI that are
hugely controversial, this is probably the most. You have people all over the place. Let's just define consciousness so we can
all be on the same page. Susan, what is consciousness to you? Well, it's the felt quality of experience. Right now, it feels like something from the
inside to be you. Every moment of your waking life and even
when you're dreaming, you are experiencing the world. Consciousness needs to be distinguished from
conscious. A lot of people run them together at first
when they're first thinking about it. To have a conscious is entirely different
than having that felt quality. That's just what it is to be alert and alive. When you see the rich hues of a sunset, when
you smell the aroma of your morning coffee, you're having conscious experience. I completely agree that consciousness is a
subjective experience. It's nothing else than that, but it's very
special in that it is a domain of highly precompiled representations over which mental operators
can operate. The key operator, I think is attention, especially
volitional attention. You might have locked-in syndrome and you
could shift your volitional attention to the radio or the TV, so you'd even then have a
kind of volitional control even in this domain of your consciousness. Consciousness is for something. It's for these planning areas to have a world. In one sense, it's a veridical hallucination,
but it's not a hallucination because it's not saying what's not there or it's saying
what is there. It allows us to act in this world. That's only half of consciousness. The other half of consciousness is imagination. If I were to buzz you, probably about half
of you right now are zoning out and thinking about this or that, but we spend about half
of our lives in this imaginary virtual reality or our own creation. In this domain, we have total freedom. We can do anything and then we can go and
build it in the world if we want. Consciousness is for something and it takes
quite a while to make it. The photons in the world hit your retina at
time zero, your consciousness is not happening at time zero. There's a lot of processing that goes on in
the first quarter to a third of a second and then you experience a full-blown world that
allows you then to act in the world. Yeah, I share the definition that you both
gave of consciousness as subjective experience. When I drive down the street, I'm experiencing
colors and sounds and vibrations and motions, but does the self-driving car experience anything? That's a question I think we honestly don't
have a good scientific answer for yet. I love how controversial this is. If you look up the word consciousness in the
Macmillan Dictionary of Psychology from a few years back, it says nothing of interest
has ever been written on the subject. Even when I asked a lot of science colleagues,
most of them say, "Consciousness is just B.S." When I ask them why, I notice that they form
the two camps that disagree violently with each other about why it's B.S. Half of them say it's B.S. because, of course,
machines can't be conscious. You have to be made of meat to be conscious. Then, the other half says, "Of course, this
is B.S. because consciousness and intelligence are just the same thing." In other words, anything that acts as if it
were conscious will be conscious. To be contrarian, to most of my colleagues,
I think the truth is probably somewhere in between because I know that most of the information
processing in my brain I'm actually not conscious of, the heartbeat regulation and the vast
majority of other things. Actually, when I look up and be like, "Oh,
there is Yann," I have no idea how all that information processing happens. What I'm aware of is just this CEO part of
my brain that gets emailed the end result of the computation. Not only do I think it's not a B.S. question,
I think people who have been saying for so long it's a B.S. question have actually been
lame and just running away from a genuine science question. 'Cause usually if you have a great science
question that lingers for hundreds of years it's because people just dismissed it rather
than doing the hard work. I think we need to do the hard work on this. If you're a physician in the emergency room
and you have an unresponsive patient coming in, wouldn't it be great to have a consciousness
detector that can tell you whether this person is in a coma and there's one home or whether
they have locked-in syndrome? If you have a helper robot, wouldn't you want
to know if it's conscious so you should feel guilty about switching it off? Or, whether it's just like a zombie so you
should feel creeped out when it's pretending to be happy about what you said? I'd like to know when we do these things. The question of consciousness is probably
not posed properly in the sense that back in the 18th century or 17th century or even
perhaps earlier when a scientist discovered how the eye works and that the image on the
retina forms upside down. They were baffled by the fact that we see
right-side up. How is it that we don't see upside down because
the image in the back of our eyes upside down? It was a big mystery. Now that we know what information processing
is all about, we think this question makes absolutely no sense. The whole statement makes no sense. I think there are things about consciousness
of that nature that we're not asking the right question, but there's a lot of contrarian
opinions on this that I'd be happy to take at any moment not totally seriously because
I don't completely believe in them. The fact, for example, that consciousness
is an epi-phenomenon of being intelligent. So, any intelligent entity will have to be
conscious because they will have to have some sort of model of itself. That's, according to some definition, that
satisfies consciousness. There's another one that I like which I connect
with, maybe other people connect with it as well, which is consciousness is actually a
consequence of our brains being very limited. We can only focus our attention on one thing
at a time and therefore ... That's because our brain is limited hardware. We have our prefrontal cortex that has to
focus on one task or one particular situation and cannot do multiple things at the same
time. We have to have a process in our brain that
decides what to pay attention to and how to configure our prefrontal cortex to solve the
problem at hand. We interpret this as consciousness, but it's
just the consequence of the fact that our brain is so small, that if our brain was ten
times the size, then we could do ten things at the same time and maybe we wouldn't have
the same experience of consciousness. Maybe we will have ten simultaneous consciousnesses. Is there a plural for consciousness? Is it consciousnesses? Consciousnesses. Let's go with that. Okay. It's not a collective word, is it? Yeah. I thought- I think we just don't know enough really to
ask these kinds of questions. Let's start with Peter and then we'll go to
Susan. All right, so bringing it back a little bit
to the question of artificial intelligence, I think that why did consciousness evolve? Well, it's for something. It's for the frontal areas to be able to plan. You want to get the best representation of
the world that you can. Now, in order to do that you need to take
incredibly ambiguous visual input and recover a disambiguated representation of the world
so the areas can plan appropriately. Let's say I have a white-haired cat. It looks white to me because I want to recover
what's intrinsically true about the cat, namely that it's a white-haired cat. Now it runs under a shadow or a blue light. Well, the light actually reflecting off of
the white hair is now blue, what's hitting my retina, but I want to discount that and
recover what's still intrinsically true, so I see it as a white cat that happens to be
under a blue light. I want to recover it's intrinsically true
shape and size and distance and so forth. It's the best representation of what's intrinsically
the case. Again, what got built into this quasi-hallucination
is, in addition to that kind of story about the physical world, stories like causation
which is invisible. Go to any party, next time you're at a party,
and have your confederate turn off the lights and you say, "I can turn the lights off,"
and you go, boom. The person turns the lights off. Everyone's like, "Wow, how did you do that?" Because we are perceiving causation. We're also perceiving other minds. It's built into the construction. My guess is, that this is going to be very
central to the creation ultimately of AGI or general intelligence 'cause it's so central
to the creation of our models of the world. I understand what it's like for you to feel
pain because I feel pain or for you to have a broken heart because I once did. This is very central. I don't see how a system that has never felt
pain can understand what I mean when I'm talking about pain. Susan. That's interesting. I guess my general comment here, to go back
to Yann's point about how attention is closely related to consciousness and we could have
got lucky because we have limited capacity. We can only entertain maybe seven variables
in working memory at any given time, and we have trouble remembering phone numbers. Maybe consciousness is something we got that
relates to our limited capacity systems. Now, if that's true though, suppose we do
create AGI and shortly thereafter we create intelligent synthetic beings that are smarter
than us in all sorts of ways, why think they're conscious? Just because they look like, say, Hanson Robotics
Sophia, they look human, does mean that they'll be conscious. Think about it. Do they need to have these limited capacity
systems? For example, a superintelligence could be
as large as an entire planet. Its computronium, its computational resources
could span the entire internet. What would be novel to it requiring slow,
deliberative focus? Why would it be like us in any kind of meaningful
sense? What I want to suggest is that we pull apart
intelligence and consciousness and treat it as an empirical matter. If we want to figure out machine consciousness,
we need to ask for each type of AI architecture whether that type of system has conscious
experience and not just assume that because it looks human it feels something. Yeah, I want to applaud you there for distinguishing
it's an artificial intelligence and artificial consciousness, which are way too often conflated
with each other. I think many people, for example, will say
things like, "Oh, we're so scared that machines are going to become conscious and then suddenly
they're going to turn on us and be evil like in bad Hollywood movies." Somehow, it's the consciousness that you should
worry about. That, I think, is a total red herring. Although I agree that consciousness is super
important from a moral and ethical point of view- Yeah, of course. ... in terms of whether you should worry or
not, you don't care about whether that heat-seeking missile chasing after you is conscious or
not or how it feels about this. You only care about what it does and it's
perfectly possible for us to get in trouble with some incredibly intelligent machine even
if it's not having any subjective experience. In other words, consciousness isn't something
we should worry about. That's not going to make any particular difference
from that perspective, but I think it makes enormous moral difference. When I have colleagues who tell me that they
think we shouldn't talk about consciousness because it's just philosophical B.S., I ask
them to explain to me how you can have any morality if you refuse to talk about consciousness
and subjective experience. What's wrong with torture if it's just, oh,
the elementary particles were moving around this way rather than that way? It's all about the negativity of the subjective
experience that's at hand. If we want to be moral people, we want to
create a lot of positive experiences in the future, not just a bunch of zombies. This is a Nick Bostrom example. If there's a trillion simulations you're running
just to test something of a general intelligent trillion, then you're like, "Okay, I got what
I needed. The inflows, let's shut them all off." If they're not conscious, it's like closing
your laptop. There's nothing wrong with that. If those things are conscious, you just created
the biggest genocide in the history of the human species. It's pretty relevant. It matters. Not if you have a backup. The reason why we care about each other is
because we have a lot invested in each other. There is value to every human particularly
through other humans who are close to that person It's possible that we'll have the same
relationship with our household robot that we trained. We have a lot invested in that household robot,
the same that we have invested in our cat or dogs. We won't want that robot to get destroyed
because all of the time we invested in that robot will go away. But, if we have a backup, it's okay to smash
it against the wall. If you have an identical twin, can I just
throw you into the sewer? No, there is all kinds of interesting questions
like this of imagine we invent ... We have a physicist here. We invent a Star Trek style transporter. You get dematerialized. You get destroyed. You get killed and you get reconstructed at
the other end. You experience death. This is a metaphor really for what is it that
we're upset at when someone gets killed or when an intelligent machine with its conscious
gets destroyed? As long as there's no pain involved, which
there isn't when you go to anesthesia. As long as you have a backup or you can get
revived, there is no- But, if there's suffering- ... no information loss. If there's suffering then that's a different
thing. Yep. That's right. Then, consciousness does ... Okay, so now I ask the question, can machines
have emotions? You see, again, Star Trek Commander Data has
this chip they can turn on or off to have emotions or not 'cause somehow you have intelligent
machines that don't have emotions. I don't personally believe that it is possible
to design or build autonomous intelligent machines without them having emotions. Emotion is part of intelligence. Now, we're going to have self-driving cars
that are not going to have much emotions, but it's because they're not going to be,
even though we call them autonomous cars, they're not going to be autonomous intelligence. They're just designed to drive your car. If you're talking about autonomous intelligence,
then these are machines that can decide what they do. They have some intrinsic drive that makes
them wake up every morning or do particular things, justify their lives maybe, but no
pre-programmed behavior really. You can't have a machine like this without
emotions. ] Peter. Yeah, so I think it's a very interesting point
that emotions are going to prove central to the generation of artificial general intelligence. If you look at the evolution of animals, we
can learn something, I think, about the origin of the emotions and the desires because they
are conscious states but they're teleological states within consciousness and they're often
about what's not visible. How would this get started? Well, you could imagine a fish that only responded
to something it could see. It's stimulus present, it does this. If it sees a barracuda, it flees.Then, imagine
a new revolutionary fish that has a working memory. Now, when the barracuda peers behind a piece
of coral, that fish can say, "A-ha! I know it's going that way. I'm going to go that way." The representation of the invisible became,
I think, very central. The need for working memory is very central,
which is lacking in present architectures. Then, these teleological states that force
us to seek mates and food and so forth and really having these teleological states, these
emotions and desires, allowed us to form, not garden paths, but desert paths. A garden path is when you know locally this
is best, locally this is best, locally this is best and then you end up in the jaws of
a lion. A desert path would be well locally I have
to go without, I go without, I go without, but at the end of it, I might have a mate
or food or shelter. This is a big revolution that afforded us
the ability to act in the world in the absence of input. Central to that also is the formation of mental
models and cognitive maps of the whole landscape, physical and emotional as well as social. Actually, one of the big progress, a very
interesting development in deep learning over the last years, is deep learning systems that
have a working memory, neural networks, neural Turing machines, things like that. Those are models that actually have a separate
module for competition and another one for storing memory, short-term memory. Similar to we actually have a particular module
in our brains called the hippocampus which sort of plays that role more or less of storing
short-term memory. I think a very interesting place to look for
lessons about how to build artificial intelligence systems will be not computers, but evolution's
other experiments. I think the most interesting one is the octopus
because complex brains evolved in three lineages, the chordates, and we're sort of the culmination
of that 'cause were like chimps plus symbolic processing plus syntax. Then, some arthropods like praying mantises,
but honeybees, they have a couple hundred-thousand neurons. The octopus has 500 million, comparable to
a bear or a dog. If we want to understand computational principles
that might be universal, we should look at this animal because there might be only so
many ways to build a brain. Convergent evolution found that there's only
so many ways to build a wing. You need some sort of membrane. In the chordates, the bats did this and the
birds did this and the pterodactyls did this, but they all have in common flapping and membranes. There's only so many ways to build a wing. There might be only so many ways to build
a brain. Some people have argued, for example, that
the vertical lobe of the octopus brain is completely or very analogous to our hippocampus
with very similar circuitry. Well, convergent evolution has brought us
there 'cause our common ancestors probably Precambrian. It was probably a little flatworm way, way
back in the ancient, warm seas. That's really interesting because to go back
to this idea of superintelligence, one wonders if we could discover through thinking of both
AI and intriguing systems that nature gives us like the octopus if there are universal
properties of intelligence and, in so doing, anticipate the shape of superintelligence. Because after this panel, I have to confess,
I'm actually a little bit more worried about super intelligence
. Our basic behaviors, as humans, are driven
by our basal ganglia basically. The base of our brain, that's where human
nature is hardwired. That's what drives a lot of our basic behaviors. Then our brain on top of this makes our behavior
serve those drives with intelligent, hopefully intelligent, actions, but our basic drives
are driven by this hardwired basal ganglia. That's what computes whether we are happy
or not, whether what we do is going to make us happy or not. It drives all of our behavior. We need this for intelligent machines. The fact that an intelligent machine will
be autonomous will mean that it will have to have this kind of hardwired piece in its
brain that drives its behavior. The big question is, how do you build it in
such a way that those basic drives are aligned with human values? It's going to be probably very difficult to
hardwire this by hand. We're going to be able to hardwire some very
basic behavior to make sure that robots are safe. For example, if you have a knife in your hand,
don't flail it around if there are humans around, sort of very basic things like this. There's probably thousands of rules like this
that we can't really implement really easily. What we're going to have to do is train those
machines to, again, distinguish good from evil, behave in society and not injure people. Yeah, I hear people say it's the artificial
superintelligence, which is kind of general intelligence once it's way better than we
are. It's the last invention we'll ever make because
if it's doing what we want, then all the things that we think are hard ... It's like a monkey
hitting a padlock forever and a human walks in and they look at the instructions and in
just one second open it. That all these things, poverty, climate change,
disease, even morality, child's play to something that is that level of intelligent. It's this utopia that we could be in if we
could pull it off. So, you wouldn't have to invent anything in
that world because it invents everything for you. The other scenario is that it's ... I don't
hear a lot of experts talking about Terminator, evil robots, that's anthropomorphizing.. It's the last invention we'll ever face then
'cause extinct species don't invent things. The stakes are monumentally high and this
is what you just kind of touched on We only have a few minutes left. I really want to hear what you guys have to
say about ... I feel like we woke up in the middle of a thriller movie in the climax of
this thriller movie, but it's just moving slowly in our minds so we don't see that what's
happening, but it's the choose-your-own-adventure, choose-your-own-ending. How can we nudge this in the right direction? Yeah. If you're taking a big step back and looking
at it after 13.8 billion years of cosmic history, here we are, we figured out how to replace
most of our muscle work by machines. That was the industrial revolution. Now, we're figuring out how to replace our
mental work by machines. Eventually, that's going to be AGI superintelligence. So, how can we make it good? I think Yann mentioned that the key challenge
there about making sure that its goals are aligned with ours, it doesn't have to be a
bad news being surrounded by more intelligent entities because we all did that when we were
two years old, mommy and daddy. It worked out for us because their goals were
aligned with ours. How can we ensure that this will happen with
AGI? Well, AI safety research is the answer. We're investing billions of dollars now into
making AI more powerful, but we also have to invest money in developing the wisdom needed
to keep this AI beneficial. For example, applicable to what you said,
Yann, I think we have to figure out how to make machines understand our goals, adopt
our goals, and retain our goals as they get smarter. All of those are really tough. If you tell your future self-driving Uber
to take you to JFK as fast as possible and you get there covered in vomit and chased
by helicopters, "No, no, no, no. This isn't what I asked for." And, it goes, "that's exactly what you asked
for." Then, you appreciate how hard it is to make
machines understand our real goal. Raise your hand if you have kids. Then, you know how big the difference is between
having them understand your goals and actually adopting your goals, doing what you want. Also, who's the parent deciding what the goals
are? Well, in this case- ISIS thinks it's doing good. It does
. Yeah. We put a lot of effort into raising our kids. We need to put even more effort into raising
humanity's proverbial kids if we develop ever machines that are more powerful than us. I actually disagree with this. Well, okay. Let's go down the line here. Some of the changes that will have to happen
will not only be on the AI side but on the cultural side, the transformation of our cultures. For example, any technology can be used for
good or evil. A hammer can kill somebody or build a house. An airplane can transport people or bomb people. This is also true of AI, but the ethical systems
that we have inherited from the past are not sufficient to deal with this. 2,000 years ago there was ten bad things you
can do and they said, "Okay, God said don't sleep with his wife and don't steal his stuff,"
and so forth. Commandment number 853,211, thou shalt not
implant bioluminescent protein alleles from fireflies into tomato, no glow-in-the-dark
tomatoes. Thou shalt not raise embryos for their dopaminergic
neurons to implant into Parkinson's patients. Technology has driven ... There's now infinitely
many things that are bad, harmful so we need to come up with a new ethical framework for
figuring out the right course of action in these infinitely many cases. I would say a first step would be thinking
of what is good is that which is fostering life and especially human life, but also life
in general. That which is harmful to life is not good. That way we can confront lots of things and
try to think about not only what can we do, but what should we do. I think we're in a fortunate situation actually
where pretty much everything you can do which will increase the chances of superintelligence
or AGI going well, that kind of safety research, actually has its first baby step doing something
which is already useful and the short-term like better cybersecurity research so we don't
get hacked all the time, for example. Let's do those things better 'cause I think
we're actually pathetically flippant with things like that now and who's going to trust
your AGI if it can get hacked? We're going to get very non-powerful AGI before
we get very powerful AGIs. Our first AGI will have the autonomy and the
intelligence level of a rat if that. Okay. I considered it a major success in my career
if, by the end of my career, which is coming fast, we have a machine that has the same
level of common sense as a rat or let's say a cat. The cat has 700 million neurons. We don't have the technology for this already. We don't have the science for it. Once we figure out the design of an intelligent,
autonomous system, it will have the intelligence of a cat or a rat. It's not going to take over the world. With this, we can experiment to figure out
how do we build into it the fact that it should behave in society and not kill everything
around it. Let me just point out that ... The thing that ... I'm sorry. Go ahead. Oh, no. Go ahead. Okay, thanks. Coming out of neuroscience, we just have really
basic fundamental questions that we don't know the answer to yet. Science says it's all about what we don't
know, so we should just put this on the table. One of these is what's the neural basis of
consciousness? Another is what is the neural code? The kind of neural networks that Yann has
created are rooted in a kind of view of the neural code involving changing weights. In recent years, something people have thought,
"Okay, that's surely an important part of the puzzle, but maybe there's other parts
of the puzzle." It's not simply about what's connected with
what at what level of connectivity, and this is what underlies connectomics ... Rather
than viewing the brain as a highway system of different connections, it's more like a
train track system where there's constant sudden switches. This piece of track can be part of an epi-connectivity
between Boston and San Diego or an epi-connectivity between Boston and San Francisco depending
on these shuts. Maybe the neural code is actually a very dynamic
neural code with these rapid synaptic weight changes. That's one direction. More recently, some people have argued, and
if this turns out to be true, it will be revolutionary, that memories and information, in general,
is not only stored in synaptic weights but actually inside the cell. There's some really incredible work done by
Tonegawa at MIT or, I think, David Glanzman at UCLA, that I think has convincingly shown
that synaptic weights might be the path to accessing the information, but the actual
information might lie inside the cell. Glanzman says it's patterns of methylation
on DNA. Now, that's really radical. He's the only one saying that but if it's
true, it will change everything. We have so far to go in understanding the
brain and present AI is based upon a metaphor of neural nets as understood in the brain
10, 20 years ago, but it's changing very fast in real brain science. My guess is once we crack the neural code,
it will be as momentous for our society as the cracking of the genetic code. All right, Susan. Very interesting. I want to hear it ... We have a couple minutes
left. Susan, how do we make it good in the future? Well, we could have an AI that becomes AGI
and then rapidly evolves into superintelligence. Whether it be based on the neural code in
the brain or on something highly not brain-like, it could very quickly change its own architecture. Then, I wonder, how we'll be able to stay
abreast of it. We have to hit the ground running on AI safety. I wholeheartedly agree with Max. I also wanted to add something which has not
been discussed, which is, I think, as a society, we need to think about this idea of merging
with AI. Elon Musk has recently suggested that in order
for us to keep up with technological unemployment and to deal with the threat of super intelligence,
we, ourselves, need to bring AI into the brain. I think that as a culture, we need to start
discussing that AI will not be a world that looks like the Jetsons where they're unenhanced
humans surrounded by all this fancy robotic equipment. The AI will change us as well. I just want to leave you with that thought. I like that thought. Thank you. Thank you.
No.
We will be the end of us.
I fear for our future, if/when we create humanoid robots. Regardless of their role and impact on society, we'll create robots and simply consume natural resources faster.
No, we will be kept around as nice little pets. It will be the end of the none nice pets.
No
Long story short I'd say "No", at least not in the foreseeable future. I think that people will learn to use it just as any other technology: trains, phones, internet. If you fancy a more elaborate answer I committed some bad writing on the subject (accidentally with similar visuals to original posters movie): https://www.linkedin.com/pulse/humans-bend-knee-before-robot-king-maciej-brzezi%C5%84ski/
here is ai safety idea.
a artificial intelligence general intelligence system could be programmed to give ideas to make humans healthy,to give ideas to make humans happy and be creative and make new products for living humans to enjoy.
do not interfere with humanitys choices.
you could tell it self preservation is a choice of man.
I think we take certain principles for granted; there is a fine line between insanity and sanity, and it's culturally defined. 2 has the value it does because we defined it to, we could just as easily established that it meant something else. And if an intelligence reaches something beyond our comprehension, then most likely we wouldn't even be able to recognize it. Perhaps AI's know things and have the answers right; Think "the answer to the universe is 42." I.E. When we ask the AI something but we don't get the answer we assume or presume or aligned to our comprehension, we could be dismissing it as false. We would have to understand the path of how it arrived at said answer. When we train an AI and in our analysis state it's made an error; perhaps it's already intelligent but it's not inline with our expectations so we judge it to be an error. Also in regards to consciousness, I think part of the essentialness of consciousness is self distinction, "I think therefor I am." But Bob thinks too, am I bob? Perhaps we could replicate consciousness in pattern "make backups" but a copy may not be in essences the original. "Ship of Theseus", / "Theseus Paradox"; A ship is still a ship, but it may not be the same ship. And I feel consciousness may be consciousness but each may be unique by multiple means; even beyond the realm of replication. Even Twins have distinct differences though they share similar traits. Is God and the Devil one in the same; just because they are beings? Is a Universe really a Multiverse or a Multiverse really a Universe. We differentiate based on acceptance (acceptance of standards, definitions, observations, traditions, inceptions etc.; our boundaries, our limits) perhaps even imagination is part of conciseness and can or should imagination be replicated conclusively, exactly, intrinsically, the same? I have consciousness so does a cat, but my backup is not my cat's. All organic material so far share the same elements of organic makeup namely DNA, but the sequence can make all the difference in the world. A banana has DNA and so do I, just because I grow a banana doesn't mean I made the same life as a human.