XRDS • WINTER 2016 • VOL. 23 • NO. 2
even though that may not be the best
way to solve the problem. You should
really love the problem that you’re
solving—not the specific tool—and
look at the simplest way to solve that.
Just keep on refining your thought
process until you find out which ones
are worth pursuing. Then you can
build prototypes, simulations.
What technical challenges did you
encounter when building things at Kiva?
Overall, what made Kiva successful was the fact that it worked. The
biggest challenge we had at Kiva was
taking existing technologies, subsystems, and combining them in just the
right away to make a robust, reliable
system. There is no single way to do it.
It’s the art and the design of systems.
What are your views on how automation
will impact the labor market?
I don’t defend automation from
claims of leading to job losses. I
freely admit that robots and auto-
mation replace human workers. If I
take a step back, and I look at eth-
ics and philosophy, what we should
be doing… we should shape our so-
ciety so that we don’t replace jobs
that people enjoy doing. What is the
purpose of life? Why do we live? It’s
not so that we can feed a big machin-
ery of consumerism. It’s so that we
can enjoy our lives. So we should be
striving to set up our society, our
rules, our incentives, so that people
do jobs that they enjoy doing. We
should strive to create the rules and
regulations that move our society to
where we want it to be. Currently,
do robots replace jobs? Yes they do.
Fortunately, they replace jobs that
for the most part are not very good
jobs. So that’s a good thing, right? If
somebody is sitting at a tollbooth,
handing out tickets to vehicles that
go through a toll road, to me that is
a job you want to automate. That’s
not a very good way for a person to
spend 30 years of their life. There’s a
second aspect here: Would a person
rather be doing that than being on
welfare? I think most people would
rather be working than being on
welfare. But then it’s a social issue.
When we get rid of these menial jobs
that are not rewarding, let’s make
to create things using technology.
I’m very good at math, physics, algo-
rithms, computer science, and ana-
lytical things. That’s the tool set; and I
like to create, so it’s only natural that I
use those tools to help me create.
Why did you choose to create
autonomous systems for
I just saw this as yet another way in
which I could express my creative freedom. Verity Studios is just a way for us
to have flying machines out there in
the real world, doing sophisticated
things. There are no killer apps for indoor flying machines yet, except for in
entertainment. So this is a great way
for us to get a head start on everyone,
and actually do flying things indoors.
When did you first start building
The first sophisticated autonomous thing I built was when I was an
undergraduate student. We built a
voice-controlled robotic arm as part
of our undergraduate projects back in
1988-1989. However, my Ph.D. was in
control systems. But, control systems,
robotics, and autonomous systems
are very tightly intertwined.
How did you graduate from building
simple, low-cost machines to state-of-the art, precise, expensive ones?
On the contrary, the reason Kiva
was successful as a company was because we figured out a way to make inexpensive robots. To have thousands
of them in warehouses and to have
them behave like they were expensive
robots was the magic of system architecture, algorithms, and the components that we used. The robots were
Can you elaborate on the differences
between autonomous systems and
The main distinction is that robots
are subsystems of autonomous systems and they tend to imply motion.
Whereas a thermostat that regulates
the temperature in your house is an
autonomous system, there is no motion so people wouldn’t call it a robot. Cruise control in your car, people
would call that an autonomous system,
but they probably won’t call it a robot
simply because the car is not changing
shape or doing manipulations.
How did you make that transition from
working on simpler forms of autonomous
systems to a more distributed network
I was working on distributed control when I was a professor at Cornell
University. I ran a RoboCup project
where we had mobile robots playing
soccer. So there was a transition from
things that you cannot do in a university environment, because you do not
have the resources. But if you have a
viable business model, then you can
raise money, hire engineers, scientists,
a sales force, and make it self sustaining. There are different challenges, but
they share a lot of similarities.
Let’s talk about your creative process.
How do you go from an idea to creating a
blueprint for something you can build?
I’ll answer something different
first. Coming up with ideas is easy.
The first part is figuring out which
idea is worth pursuing and then executing on it. Also, I just don’t want to
discount the fact that it’s really hard
to figure out what you should be doing. And once you’ve figured that out,
once you assume that you want to
solve the problem, then it really becomes about the problem. And this is
where you have to be very honest with
yourself and do something that engineers don’t like to do. Engineers like
to come up with solutions. And they
get enamored with those solutions
that the systems
better and better,
and could replace
more and more
of what people do.