I think there's a valid concern that maybe we're giving machines too much power. Maybe
we don't want machines to be self-aware. In my opinion, everybody should understand that
this technology is around the corner. Your children, your grandchildren are going to
be living in a world where there are machines that are on par and possibly exceed human
self-awareness and what does that mean? We’ll have to figure that out. Inside his Creative
Machines Lab at Columbia University, Hod Lipson and his students are taking the first steps
towards sentient machines. Scattered on shelves and tucked into cubicles, their robot menagerie
is probing the biggest philosophical questions that face robotics and AI today. As these
deceivingly simple machines squirm and babble, they’re crawling towards a future where
machines can autonomously adapt to and understand their surroundings, embarking on a quest to
unlock artificial consciousness. We’ve been making huge advances in robotics for decades,
but engineers investigating these philosophical questions, has not always been a widely supported
pursuit. For many years, this whole area of consciousness, self-awareness, sentience,
emotions, was taboo. Academia tended to stay away from these grand claims. But I think
now we're at a turning point in history of AI where we can suddenly do things that were
thought impossible just five years ago. We humans cannot babysit all these incredibly
sophisticated systems that we're creating. We need to gift them with this ability to
see themselves. To do that, Hod’s lab is taking a unique approach. Instead of trying
to understand and replicate something as complicated as human consciousness, they’re looking
into something a little simpler: the ability to imagine yourself– or self-simulate. So,
the big question is what is self awareness, right? We have a very simple definition, and
our definition is that self awareness is nothing but the ability to self simulate. A dog might
be able to simulate itself into the afternoon. If it can see itself into the future, it can
see itself having its next meal. Now if you can simulate yourself, you can imagine yourself
into the future, you're self-aware. With that definition, we can build it into machines. The
first idea to use the arm really came about because arms are one of the most common types
of robots. And they're also fairly simple. We have the robot start by flailing around.
We call this motor babbling. It just moves just like child in a crib. After moving for one
day it collected enough information about its body, to understand the dynamics of its
motion, how when it moves, what's going to happen to its position and its ability to
move in the future. The team fed all of that data into a deep learning model, allowing
the robot to predict its next position based on its previous one. Essentially, it’s using
the model it created to “imagine” its own motion. From there we were able to use
this model to plan how to effectively accomplish tasks. In this case the robot is sort of
going through a variety of different actions that it could attempt to make. Testing them
on the self model and then executing the one which will bring it closest to its goal state.
So in this case, the goal state is right where it is right now, on the ball. And then it
will move, as its next goal state, to the cup where it will then drop it. It's a little
bit tricky, because you look at this robotic arm and you'll see it doing its task and you'll
think, "Oh, I could probably program this arm to do this task by myself. It's not a
big deal," but you have to remember not only did the robot learn how to do this by itself,
but it's particularly important that it learned inside the simulation that it created. To
demonstrate the transferability, we made the arm write us a message. We told it to write
hi and it wrote hi with no additional training, no additional information needed. We just
used our self model and wrote up a new objective for it and it successfully executed. We call
that zero-shot learning. We humans are terrific at doing that thing. I can show you a tree
you've never climbed before. You look at it, you think a little bit and, bam, you climb
the tree. The same thing happens with the robot. The next steps for us are really working
towards bigger and more complicated robots. Walking robots are much more of a dynamic
and complex system and as such we're actually going to start developing on that robot over
there. It will do the motor babbling and we hope that we can learn a variety of tasks
on that the same way that we did on the arm robot. We believe that while this is a small,
simple start, by progressively improving the model and the bodies and the capacity of these
robots, we can push the border between robot and human to become smaller and smaller with
each additional iteration. Every automated system would benefit from being self-aware.
Everything from driverless cars to airplanes to smart cities to traffic lights. Imagine
that your factory is operating. It's creating, I don't know what, solar panels, and it understands
if things are working well. It can foresee a problem on the horizon and it's going to
take measures to compensate or recover from that. All of that is incredibly useful no
matter what you're doing. But regardless of the benefits, the idea of self-aware machines
will inevitably raise concerns. Experts from the likes of Stephen Hawking to Elon Musk
have warned about the dangers of advancing AI, cautioning against a future where it progresses
to a point beyond human control. To me, it's very similar to the discovery of fire. You
can do a lot of bad things with fire. But, there's no doubt that fire's an incredible
technology, changed our civilization forever. So we can try to quench it and say, "Okay,
we're not touching this," but I think a much smarter thing to do is to say, "How can we
try to use this technology for good and sort of understand its pitfalls. Discovering the
ability to build a self-aware machines will change our ability in big ways. It's going
to take 10 years, or 50 years, I don't know, but it's going to happen in our lifetimes.
And, we have to make sure we understand how to use it properly because the benefits far
outweigh the risks if we can handle it.