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Colin Angle: iRobot

Episode 2019-09-192019-09-19English

Guests: Colin Angle

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Contents4 chapters§01Transcript · 00:00–10:49§02Transcript · 10:52–22:43§03Transcript · 22:48–33:56§04Transcript · 33:57–37:30

§01Transcript · 00:00–10:49

00:00The following is a conversation with Colin Angle.

00:02He's the CEO and co-founder of iRobot,

00:05a robotics company that for 29 years

00:08has been creating robots that operate successfully

00:11in the real world.

00:12Not as a demo or on a scale of dozens,

00:15but on a scale of thousands and millions.

00:18As of this year, iRobot has sold more than

00:2125 million robots to consumers,

00:25including the Roomba vacuum cleaning robot,

00:28the Bravo floor mopping robot,

00:30and soon the Terra lawn mowing robot.

00:3429 million robots successfully operating autonomously

00:37in real people's homes,

00:39to me is an incredible accomplishment

00:42of science, engineering, logistics,

00:45and all kinds of general entrepreneurial innovation.

00:48Most robotics companies fail.

00:51iRobot has survived and succeeded for 29 years.

00:56I spent all day at iRobot,

00:58including a long tour and conversation with Colin

01:01about the history of iRobot,

01:03and then sat down for this podcast conversation

01:06that would have been much longer

01:08if I didn't spend all day learning about

01:10and playing with the various robots

01:12and the company's history.

01:13I'll release the video of the tour separately.

01:17Colin, iRobot, its founding team,

01:20its current team, and its mission

01:23has been and continues to be an inspiration to me

01:26and thousands of engineers who are working hard

01:28to create AI systems that help real people.

01:33This is the Artificial Intelligence Podcast.

01:35If you enjoy it, subscribe on YouTube,

01:38give it five stars on iTunes,

01:39support it on Patreon,

01:41or simply connect with me on Twitter

01:43at Lex Friedman, spelled F-R-I-D-M-A-N.

01:47And now, here's my conversation with Colin Engel.

01:51In his 1942 short story, "Runaround,"

01:55from his iRobot collection,

01:56Asimov proposed the three laws of robotics

02:01in order, don't harm humans, obey orders, protect yourself.

02:06So two questions.

02:07First, does the Roomba follow these three laws?

02:11And also, more seriously,

02:14what role do you hope to see robots take in modern society

02:18and in the future world?

02:21- So the three laws are very thought-provoking

02:25and require such a profound understanding

02:30of the world a robot lives in,

02:36the ramifications of its action,

02:38and its own sense of self,

02:40that it's not a relevant bar,

02:44at least it won't be a relevant bar for decades to come.

02:50And so if Roomba follows the three laws,

02:54and I believe it does,

02:56it is designed to help humans, not hurt them,

03:00it's designed to be inherently safe,

03:03and we designed it to last a long time,

03:06it's not through any AI or intent on the robot's part.

03:11It's because following the three laws

03:15is aligned with being a good robot product.

03:19So I guess it does,

03:23but not by explicit design.

03:27- So then the bigger picture,

03:28what role do you hope to see robotics, robots take

03:33in what's currently mostly a world of humans?

03:37- We need robots to help us continue

03:42to improve our standard of living.

03:46We need robots because the average age of humanity

03:51is increasing very quickly,

03:55and simply the number of people young enough

03:59and spry enough to care for the older,

04:02growing demographic is inadequate.

04:08And so what is the role of robots?

04:11Today the role is to make our lives a little easier,

04:15a little cleaner, maybe a little healthier,

04:17but in time, robots are gonna be the difference

04:22between real gut-wrenching declines

04:25in our ability to live independently

04:28and maintain our standard of living,

04:30and a future that is the bright one

04:35where we have more control over our lives,

04:37can spend more of our time focused on activities we choose,

04:44and I'm so honored and excited

04:48to be playing a role in that journey.

04:50- So you give me a tour,

04:51you showed me some of the long histories,

04:54now 29 years that iRobot has been at it,

04:57creating some incredible robots.

04:59You showed me PackBot,

05:01you showed me a bunch of other stuff

05:03that led up to Roomba, that led to Bravo and Terra.

05:08So let's skip that incredible history

05:14in the interest of time,

05:15'cause we already talked about it,

05:16I'll show this incredible footage.

05:18You mentioned elderly, and robotics in society,

05:22I think the home is a fascinating place for robots to be.

05:26So where do you see robots in the home?

05:29Currently, I would say, once again,

05:31probably most homes in the world don't have a robot.

05:34So how do you see that changing?

05:36Where do you think is the big initial value add

05:39that robots can do?

05:41- So iRobot has sort of over the years,

05:45narrowed in on the home, the consumer's home,

05:49as the place where we want to innovate

05:53and deliver tools that will help a home

05:58be a more automatically maintained place,

06:04a healthier place, a safer place,

06:06and perhaps even a more efficient place to be.

06:11And today, vacuum, we mop, soon we'll be mowing your lawn,

06:16but where things are going is,

06:21when do we get to the point where the home,

06:27not just the robots that live in your home,

06:29but the home itself becomes part of a system

06:32that maintains itself and plays an active role

06:35in caring for and helping the people who live in that home.

06:40And I see everything that we're doing

06:43as steps along the path toward that future.

06:46- So what are the steps?

06:47So if we can summarize some of the history of Roomba,

06:51you've mentioned, and maybe you can elaborate on it,

06:55but you mentioned that the early days

06:57were really taking a robot from something that works

07:02either in the lab or something that works in the field

07:04that helps soldiers do the difficult work they do

07:10to actually be in the hands of consumers

07:12and tens of thousands, hundreds of thousands of robots

07:15that don't break down over how much people love them

07:18over months of very extensive use.

07:21So that was the big first step.

07:22And then the second big step was the ability

07:26to sense the environment, to build a map, to localize,

07:29to be able to build a picture of the home

07:32that the human can then attach labels to

07:34in terms of giving some semantic knowledge to the robot

07:39about its environment.

07:40Okay, so that's like a huge, two big, huge steps.

07:44Maybe you can comment on them,

07:47but also what is the next step

07:51of making a robot part of the home?

07:54- Sure.

07:55So the goal is to make a home that takes care of itself,

08:00takes care of the people in the home,

08:03and gives the user an experience of just living their life

08:07in the home is somehow doing the right thing,

08:10turning on and off lights when you leave,

08:14cleaning up the environment.

08:17And we went from robots that were great in the lab,

08:22but were both too expensive and not sufficiently capable

08:30to ever do an acceptable job of anything

08:33other than being a toy or a curio in your home

08:37to something that was both affordable

08:42and sufficiently effective to drive,

08:45be above threshold and drive purchase intent.

08:48Now we've disrupted the entire vacuuming industry.

08:54The number one selling vacuums, for example,

08:59in the US are Roombas, so not robot vacuums, but vacuums.

09:02And that's really crazy and weird.

09:04- Yes, we need to pause it.

09:06I mean, that's incredible.

09:08That's incredible that a robot is the number one selling

09:13thing that does something.

09:15- Yep.

09:16- Something as essential as vacuuming.

09:18- So we're--

09:19- Congratulations.

09:20- Thank you.

09:20It's still kind of fun to say,

09:22but just because this was a crazy idea

09:26that just started in a room here,

09:30we're like, do you think we can do this?

09:33So, hey, let's give it a try.

09:36But now the robots are starting

09:40to understand their environment.

09:42And if you think about the next step,

09:45there's two dimensions.

09:47I've been working so hard since the beginning of iRobot

09:53to make robots are autonomous,

09:55that they're smart enough and understand their task enough

09:59that they can just go do it without human involvement.

10:03Now what I'm really excited and working on

10:07is how do I make them less autonomous?

10:09Meaning that the robot is supposed to be your partner,

10:15not this automaton that just goes and does

10:18what a robot does.

10:20And so that if you tell it,

10:22hey, I just dropped some flour by the fridge in the kitchen.

10:27Can you deal with it?

10:28Wouldn't it be awesome if the right thing just happened

10:32based on that utterance?

10:35And to some extent that's less autonomous

10:37'cause it's actually listening to you,

10:40understanding the context and intent of the sentence,

10:44mapping it against its understanding of the home it lives in

10:49and knowing what to do.

§02Transcript · 10:52–22:43

10:52And so that's an area of research.

10:56It's an area where we're starting to roll out features.

10:59You can now tell your robot to clean up the kitchen

11:02and it knows what the kitchen is and can do that.

11:05And that's sort of 1.0 of where we're going.

11:09The other cool thing is that we're starting to know

11:13where stuff is and why is that important?

11:16Well, robots are supposed to have arms, right?

11:21Data had an arm, Rosie had an arm,

11:24Robbie the robot had an arm.

11:25I mean, robots are,

11:26they are physical things that move around

11:28in an environment and they're supposed to do work.

11:31And if you think about it,

11:34if a robot doesn't know where anything is,

11:37why should it have an arm?

11:38But with this new dawn of home understanding

11:43that we're starting to go enjoy,

11:47I know where the kitchen is.

11:49I might in the future know where the refrigerator is.

11:52I might, if I had an arm, be able to find the handle,

11:55open it and even get myself a beer.

11:58Obviously that's one of the true dreams of robotics

12:01is to have robots bringing us a beer

12:03while we watch television.

12:05But I think that that new category of tasks

12:10where physical manipulation, robot arms,

12:14is just a potpourri of new opportunity and excitement.

12:19- And you see humans as a crucial part of that.

12:23So you kind of mentioned that,

12:26and I personally find that a really compelling idea.

12:29I think full autonomy can only take us so far,

12:34especially in the home.

12:35So you see humans as helping the robot understand

12:38or give deeper meaning to this spatial information.

12:42- Right, it's a partnership.

12:45The robot is supposed to operate

12:48according to descriptors that you would use

12:53to describe your own home.

12:55The robot is supposed to, in lieu of better direction,

13:02kind of go about its routine,

13:03which ought to be basically right

13:07and lead to a home maintained

13:12in a way that it's learned you like,

13:14but also be perpetually ready to take direction

13:19that would activate a different set of behaviors or actions

13:26to meet a current need

13:29to the extent it could actually perform that task.

13:32- So I gotta ask you,

13:33I think this is a fundamental and a fascinating question,

13:37because iRobot has been a successful company

13:39and a rare successful robotics company.

13:42So Anki, Jibo, Mayfield Robotics with their Robot Curry,

13:46Sci-Fi Works, Rethink Robotics,

13:49these are robotics companies that were founded

13:51and run by brilliant people.

13:53But all, very unfortunately, at least for us roboticists,

13:59all went out of business recently.

14:02So why do you think they didn't last longer?

14:05Why do you think it is so hard

14:07to keep a robotics company alive?

14:10- You know, I say this only partially in jest

14:14that back in the day before Roomba,

14:16you know, I was a high-tech entrepreneur building robots,

14:22but it wasn't until I became a vacuum cleaner salesman

14:26that we had any success.

14:28So, I mean, the point is technology alone

14:34doesn't equal a successful business.

14:37We need to go and find the compelling need

14:42where the robot that we're creating

14:45can deliver clearly more value

14:52to the end user than it costs.

14:55And this is not a marginal thing

14:59where you're looking at the scale and you're like,

15:00"Eh, it's close, maybe we can hold our breath

15:03"and make it work."

15:04It's clearly more value than the cost of the robot

15:09to bring in the store.

15:13And I think that the challenge has been

15:15finding those businesses

15:20where that's true in a sustainable fashion.

15:26You know, when you get into entertainment style things,

15:34you could be the cat's meow one year,

15:38but 85% of toys, regardless of their merit,

15:42fail to make it to their second season.

15:45It's just super hard to do so.

15:47And so that's just a tough business.

15:53And there's been a lot of experimentation

15:57around what is the right type of social companion?

16:02What is the right robot in the home

16:05that is doing something other than tasks people do

16:10every week that they'd rather not do?

16:16And I'm not sure we've got it all figured out right.

16:20And so that you get brilliant roboticists

16:22with super interesting robots

16:25that ultimately don't quite have

16:29that magical user experience,

16:32and thus that value benefit equation remains ambiguous.

16:37- So you as somebody who dreams of robots

16:44changing the world, what's your estimate?

16:46How big is the space of applications

16:53that fit the criteria that you just described

16:55where you can really demonstrate

16:58an obvious significant value

17:00over the alternative non-robotic solution?

17:04- Well, I think that we're just about none of the way

17:08to achieving the potential of robotics at home.

17:13But we have to do it in a really eyes wide open,

17:18honest fashion.

17:22- Another way to put that is the potential is infinite

17:25because we did take a few steps,

17:27but you're saying those steps are just very initial steps.

17:29So the Roomba is a hugely successful product,

17:32but you're saying that's just the very, very beginning.

17:34- That's just the very, very beginning.

17:36It's the foot in the door.

17:37And I think I was lucky that in the early days of robotics,

17:42people would ask me, "When are you gonna clean my floor?"

17:48It was something that I grew up saying,

17:52"I got all these really good ideas,

17:54but everyone seems to want their floor clean.

17:58And so maybe we should do that."

18:02- Yeah, your good ideas--

18:03- Earn the right to do the next thing after that.

18:05- So the good ideas have to match

18:07with the desire of the people,

18:10and then the actual cost has to,

18:12like the financial aspect has to all match together.

18:16- Yeah, during our partnership back a number of years ago

18:21with Johnson Wax, they would explain to me

18:24that they would go into homes

18:29and just watch how people lived

18:32and try to figure out what were they doing

18:35that they really didn't really like to do,

18:39but they had to do it frequently enough

18:42that it was top of mind and understood as a burden.

18:51Hey, let's make a product or come up with a solution

18:55to make that pain point less challenging.

19:00- And sometimes we do certain burdens so often as a society

19:07that we actually don't even realize,

19:09like it's actually hard to see that that burden

19:11is something that could be removed.

19:13So it does require just going into the home and staring at,

19:17wait, how do I actually live life?

19:19What are the pain points?

19:21- Yeah, and getting those insights is a lot harder

19:26than it would seem it should be in retrospect.

19:29- So how hard on that point,

19:33I mean, one of the big challenges of robotics

19:37is driving the cost down to something

19:42that consumers, people would afford.

19:45So people would be less likely to buy a Roomba

19:48if it costs $500,000, right?

19:52Which is probably sort of what a Roomba would cost

19:55several decades ago.

19:58So how do you drive, which I mentioned is very difficult,

20:02how do you drive the cost of a Roomba or a robot down

20:05such that people would want to buy it?

20:07- When I started building robots,

20:09the cost of the robot had a lot to do

20:12with the amount of time it took to build it.

20:15And so that we would build our robots out of aluminum,

20:18I would go spend my time in the machine shop

20:21on the milling machine, cutting out the parts and so forth.

20:26And then when we got into the toy industry,

20:29I realized that if we were building at scale,

20:34I could determine the cost of the robot

20:36instead of adding up all the hours to mill out the parts,

20:38but by weighing it.

20:40And that's liberating.

20:44You can say, wow, the world has just changed

20:49as I think about construction in a different way.

20:53The 3D CAD tools that are available to us today,

20:56the operating at scale where I can do tooling

21:01and injection mold an arbitrarily complicated part

21:06and the cost is going to be basically the weight

21:10of the plastic in that part is incredibly exciting

21:15and liberating and opens up all sorts of opportunities.

21:18And for the sensing part of it,

21:22where we are today is instead of trying to build skin,

21:28which is like really hard for a long time,

21:31I spent creating strategies and ideas

21:38around how could we duplicate the skin on the human body

21:42because it's such an amazing sensor.

21:45Instead of going down that path,

21:49why don't we focus on vision?

21:53And how many of the problems that face a robot

21:59trying to do real work could be solved

22:04with a cheap camera and a big ass computer.

22:08- Yeah.

22:09- And Moore's law continues to work.

22:12The cell phone industry, the mobile industry

22:16is giving us better and better tools

22:18that can run on these embedded computers.

22:21And I think we passed an important moment,

22:26maybe two years ago,

22:29where you could put machine vision capable processors

22:35on robots at consumer price points.

22:39And I was waiting for it to happen.

22:43We avoided putting lasers on our robots to do navigation

§03Transcript · 22:48–33:56

22:48and instead spent years researching

22:51how to do vision based navigation

22:54because you could just see

22:58where these technology trends were going.

23:01And between injection molded plastic

23:05and a camera with a computer capable of running

23:09machine learning and visual object recognition,

23:12I could build an incredibly affordable,

23:15incredibly capable robot and that's gonna be the future.

23:20- So you know, on that point with a small tangent,

23:23but I think an important one,

23:24another industry in which I would say

23:27the only other industry in which

23:29there is automation actually touching people's lives today

23:34is autonomous vehicles.

23:36What the vision you just described of using computer vision

23:42and using cheap camera sensors,

23:44there's a debate on that of LIDAR versus computer vision.

23:48And sort of, Elon Musk famously said

23:53that LIDAR is a crutch that really in camera,

23:57in the longterm camera only is the right solution,

24:00which echoes some of the ideas you're expressing.

24:03Of course, the domain in terms of its safety criticality

24:06is different, but what do you think about that approach

24:10in the autonomous vehicle space?

24:13And in general, do you see a connection

24:15between the incredible real world challenges

24:18you have to solve in the home with Roomba?

24:20And I saw a demonstration of some of them,

24:22corner cases, literally, and autonomous vehicles.

24:27- So there's absolutely a tremendous overlap

24:31between both the problems, you know,

24:35a robot vacuum and autonomous vehicle are trying to solve,

24:38and the tools and the types of sensors

24:41that are being applied in the pursuit of the solutions.

24:48In my world, my environment is actually much harder

24:53than the environment in automobile travels.

24:57We don't have roads, we have t-shirts, we have steps,

25:02we have a near infinite number of patterns and colors

25:07and surface textures on the floor.

25:10- Especially from a visual perspective.

25:12- Yeah, visually it's really tough.

25:14It's infinitely variable.

25:18- On the other hand, safety is way easier on the inside.

25:22My robots, they're not very heavy, they're not very fast.

25:27If they bump into your foot, you think it's funny.

25:31And, you know, and autonomous vehicles

25:36kind of have the inverse problem.

25:39And so that for me saying vision is the future,

25:45I can say that without reservation.

25:47For autonomous vehicles, I think I believe what

25:52Elon's saying about the future

25:56is ultimately going to be vision.

25:59Maybe if we put a cheap lighter on there

26:01as a backup sensor,

26:02it might not be the worst idea in the world.

26:03- So the stakes are much higher.

26:05- The stakes are much higher.

26:05- You have to be much more careful thinking through

26:08how far away that future is, right?

26:10- Right, but I think that the primary

26:14environmental understanding sensor

26:19is going to be a visual system.

26:21- Visual system.

26:23So on that point, well, let me ask,

26:25do you hope there's an iRobot robot

26:28in every home in the world one day?

26:30- I expect there to be at least one iRobot robot

26:34in every home.

26:37You know, we've sold 25 million robots.

26:41So we're in about 10% of US homes,

26:44which is a great start.

26:45But I think that when we think about the numbers of things

26:52that robots can do,

26:54today I can vacuum your floor, mop your floor,

26:58cut your lawn, or soon we'll be able to cut your lawn.

27:01But there are more things that we could do in the home.

27:06And I hope that we continue using the techniques

27:11I described around exploiting computer vision

27:14and low-cost manufacturing that we'll be able

27:18to create these solutions at affordable price points.

27:22- So let me ask, on that point of a robot in every home,

27:25that's my dream as well.

27:26I'd love to see that.

27:28You know, I think the possibilities there

27:31are indeed infinite positive possibilities.

27:34But in our current culture,

27:36no thanks to science fiction and so on,

27:40there's a serious kind of hesitation,

27:44anxiety, concern about robots,

27:47and also a concern about privacy.

27:50And it's a fascinating question to me,

27:54why that concern is amongst a certain group of people

27:59is as intense as it is.

28:02So you have to think about it,

28:04'cause it's a serious concern,

28:05but I wonder how you address it best.

28:07So from a perspective of a vision sensor,

28:09so robots that move about the home and sense the world,

28:14how do you alleviate people's privacy concerns?

28:19How do you make sure that they can trust iRobot

28:22and the robots that they share their home with?

28:25- I think that's a great question.

28:28And we've really leaned way forward on this

28:33because given our vision as to the role the company

28:38intends to play in the home,

28:40really for us, make or break is,

28:45can our approach be trusted to protecting the data

28:50and the privacy of the people who have our robots?

28:53And so we've gone out publicly with a privacy manifesto

28:58stating we'll never sell your data.

29:00We've adopted GDPR, not just where GDPR is required,

29:05but globally.

29:07We have ensured that images don't leave the robot.

29:14So processing data from the visual sensors

29:22happens locally on the robot

29:23and only semantic knowledge of the home

29:29with the consumer's consent is sent up.

29:32We show you what we know and are trying to go

29:36use data as an enabler for the performance of the robots

29:43with the informed consent and understanding

29:49of the people who own those robots.

29:52And we take it very seriously.

29:56And ultimately we think that by showing a customer that,

30:01if you let us build a semantic map of your home

30:07and know where the rooms are,

30:08well then you can say, clean the kitchen.

30:11If you don't want the robot to do that,

30:13don't make the map, it'll do its best job

30:15cleaning your home, but it won't be able to do that.

30:18And if you ever want us to forget

30:20that we know that it's your kitchen,

30:22you can have confidence that we will do that for you.

30:26So we're trying to go and be a sort of a

30:30data 2.0 perspective company where we treat the data

30:37that the robots have of the consumer's home

30:40as if it were the consumer's data

30:43and that they have rights to it.

30:47So we think by being the good guys on this front,

30:50we can build the trust and thus be entrusted

30:55to enable robots to do more things that are thoughtful.

31:00- You think people's worries will diminish over time?

31:03As a society, broadly speaking,

31:06do you think you can win over trust,

31:09not just for the company,

31:10but just the comfort that people have

31:12with AI in their home, enriching their lives in some way?

31:17- I think we're in an interesting place today

31:19where it's less about winning them over

31:22and more about finding a way to talk about privacy

31:26in a way that more people can understand.

31:28I would tell you that today,

31:30when there's a privacy breach,

31:33people get very upset and then go to the store

31:37and buy the cheapest thing,

31:38paying no attention to whether or not the products

31:41that they're buying honor privacy standards or not.

31:44In fact, if I put on the package of my Roomba,

31:50the privacy commitments that we have,

31:53I would sell less than I would if I did nothing at all.

31:58And that needs to change.

32:00So it's not a question about earning trust.

32:02I think that's necessary but not sufficient.

32:05We need to figure out how to have a comfortable set

32:08of what is the grade A meat standard applied to privacy

32:13that customers can trust and understand

32:18and then use in their buying decisions.

32:20That will reward companies for good behavior

32:25and that will ultimately be how this moves forward.

32:29- And maybe be part of the conversation

32:32between regular people about what it means,

32:34what privacy means.

32:36If you have some standards, you can say,

32:38you can start talking about who's following them,

32:41who's not, have more.

32:42'Cause most people are actually quite clueless

32:45about all aspects of artificial intelligence

32:47or data collection and so on.

32:48It would be nice to change that for people to understand

32:51the good that AI can do and it's not some system

32:55that's trying to steal all the most sensitive data.

32:58- Yep.

32:59- Do you think, do you dream of a Roomba

33:02with human level intelligence one day?

33:05So you've mentioned a very successful localization

33:10and mapping of the environment,

33:11being able to do some basic communication

33:14to say go clean the kitchen.

33:16Do you see in your maybe more bored moments,

33:21once you get the beer, to sit back with that beer

33:27and have a chat on a Friday night with a Roomba

33:30about how your day went?

33:32- So to your latter question, absolutely.

33:37To your former question as to whether a robot

33:40can have human level intelligence, not in my lifetime.

33:45- You can have, you--

33:46- I think you can have a great conversation,

33:48a meaningful conversation with a robot

33:52without it having anything that resembles

33:56human level intelligence.

§04Transcript · 33:57–37:30

33:57And I think that as long as you realize

34:02that conversation is not about the robot

34:05and making the robot feel good.

34:08That conversation is about you learning interesting things

34:14that make you feel like the conversation

34:18that you had with the robot is

34:21a pretty awesome way of learning something.

34:27And it could be about what kind of day your pet had.

34:30It could be about how can I make my home

34:35more energy efficient?

34:36It could be about if I'm thinking about climbing Mount Everest

34:40what should I know?

34:44And that's a very doable thing.

34:46But if I think that that conversation

34:51I'm gonna have with a robot is I'm gonna be rewarded

34:54by making the robot happy,

34:56well I could just put a button on the robot

34:58that you could push and the robot would smile

35:00and that sort of thing.

35:02So I think you need to think about the question

35:04in the right way and robots can be awesomely effective

35:11at helping people feel less isolated,

35:14learn more about the home that they live in

35:17and fill some of those lonely gaps

35:21that we wish we were engaged learning cool stuff

35:24about our world.

35:25- Last question.

35:27If you could hang out for a day with a robot

35:32from science fiction, movies, books

35:35and safely pick its brain for that day,

35:40who would you pick?

35:42- Data.

35:43- Data.

35:44- From Star Trek.

35:45I think that A, data's really smart.

35:49Data's been through a lot trying to go and save the galaxy

35:53and I'm really interested actually in emotion and robotics

35:58and I think he'd have a lot to say about that

36:03'cause I believe actually that emotion plays

36:08an incredibly useful role in doing reasonable things

36:13in situations where we have imperfect understanding

36:16of what's going on.

36:18- In social situations when there's imperfect information.

36:20- In social situations, also in competitive

36:25or dangerous situations that we have emotion for a reason

36:30and so that ultimately my theory is that

36:37as robots get smarter and smarter,

36:38they're actually gonna get more emotional

36:40because you can't actually survive on pure logic

36:46because only a very tiny fraction of the situations

36:53we find ourselves in can be resolved reasonably with logic

36:57and so I think data would have a lot to say about that

36:59and so I could find out whether he agrees.

37:02- If you could ask data one question

37:04and you would get a deep honest answer to,

37:07what would you ask?

37:08- What's Captain Picard really like?

37:10(laughing)

37:12- Okay, I think that's the perfect way to end it.

37:14Colin, thank you so much for talking today.

37:16I really appreciate it.

37:16- My pleasure.

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— A LITTLE MORE TO THINK ABOUT. —