Rodney Brooks: Why we will rely on robots

Recorded atFebruary 26, 2013
Duration (min:sec)09:37
Video TypeTED Stage Talk
Words per minute214.62 very fast
Readability (FK)68.3 very easy
SpeakerRodney Brooks
Occupationengineer, roboticist
DescriptionAustralian Roboticist

Official TED page for this talk


Scaremongers play on the idea that robots will simply replace people on the job. In fact, they can become our essential collaborators, freeing us up to spend time on less mundane and mechanical challenges. Rodney Brooks points out how valuable this could be as the number of working-age adults drops and the number of retirees swells. He introduces us to Baxter, the robot with eyes that move and arms that react to touch, which could work alongside an aging population -- and learn to help them at home, too.

Text Highlight (experimental)
100:13 Well, Arthur C. Clarke, a famous science fiction writer from the 1950s, said that, "We overestimate technology in the short term, and we underestimate it in the long term."
200:24 And I think that's some of the fear that we see about jobs disappearing from artificial intelligence and robots.
300:31 That we're overestimating the technology in the short term.
400:34 But I am worried whether we're going to get the technology we need in the long term.
500:39 Because the demographics are really going to leave us with lots of jobs that need doing and that we, our society, is going to have to be built on the shoulders of steel of robots in the future.
600:50 So I'm scared we won't have enough robots.
700:53 But fear of losing jobs to technology has been around for a long time.
800:57 Back in 1957, there was a Spencer Tracy, Katharine Hepburn movie.
901:01 So you know how it ended up, Spencer Tracy brought a computer, a mainframe computer of 1957, in to help the librarians.
1001:09 The librarians in the company would do things like answer for the executives, "What are the names of Santa's reindeer?"
1101:16 And they would look that up.
1201:17 And this mainframe computer was going to help them with that job.
1301:20 Well of course a mainframe computer in 1957 wasn't much use for that job.
1401:24 The librarians were afraid their jobs were going to disappear.
1501:27 But that's not what happened in fact.
1601:29 The number of jobs for librarians increased for a long time after 1957.
1701:34 It wasn't until the Internet came into play, the web came into play and search engines came into play that the need for librarians went down.
1801:42 And I think everyone from 1957 totally underestimated the level of technology we would all carry around in our hands and in our pockets today.
1901:51 And we can just ask: "What are the names of Santa's reindeer?" and be told instantly -- or anything else we want to ask.
2001:59 By the way, the wages for librarians went up faster than the wages for other jobs in the U.S. over that same time period, because librarians became partners of computers.
2102:11 Computers became tools, and they got more tools that they could use and become more effective during that time.
2202:16 Same thing happened in offices.
2302:18 Back in the old days, people used spreadsheets.
2402:20 Spreadsheets were spread sheets of paper, and they calculated by hand.
2502:25 But here was an interesting thing that came along.
2602:27 With the revolution around 1980 of P.C.'s, the spreadsheet programs were tuned for office workers, not to replace office workers, but it respected office workers as being capable of being programmers.
2702:40 So office workers became programmers of spreadsheets.
2802:43 It increased their capabilities.
2902:45 They no longer had to do the mundane computations, but they could do something much more.
3002:51 Now today, we're starting to see robots in our lives.
3102:54 On the left there is the PackBot from iRobot.
3202:57 When soldiers came across roadside bombs in Iraq and Afghanistan, instead of putting on a bomb suit and going out and poking with a stick, as they used to do up until about 2002, they now send the robot out.
3303:08 So the robot takes over the dangerous jobs.
3403:10 On the right are some TUGs from a company called Aethon in Pittsburgh.
3503:15 These are in hundreds of hospitals across the U.S.
3603:17 And they take the dirty sheets down to the laundry.
3703:20 They take the dirty dishes back to the kitchen.
3803:21 They bring the medicines up from the pharmacy.
3903:24 And it frees up the nurses and the nurse's aides from doing that mundane work of just mechanically pushing stuff around to spend more time with patients.
4003:32 In fact, robots have become sort of ubiquitous in our lives in many ways.
4103:37 But I think when it comes to factory robots, people are sort of afraid, because factory robots are dangerous to be around.
4203:46 In order to program them, you have to understand six-dimensional vectors and quaternions.
4303:51 And ordinary people can't interact with them.
4403:54 And I think it's the sort of technology that's gone wrong.
4503:57 It's displaced the worker from the technology.
4604:00 And I think we really have to look at technologies that ordinary workers can interact with.
4704:06 And so I want to tell you today about Baxter, which we've been talking about.
4804:09 And Baxter, I see, as a way -- a first wave of robot that ordinary people can interact with in an industrial setting.
4904:18 So Baxter is up here.
5004:19 This is Chris Harbert from Rethink Robotics.
5104:22 We've got a conveyor there.
5204:24 And if the lighting isn't too extreme --
5304:27 Ah, ah! There it is. It's picked up the object off the conveyor.
5404:31 It's going to come bring it over here and put it down.
5504:34 And then it'll go back, reach for another object.
5604:37 The interesting thing is Baxter has some basic common sense.
5704:41 By the way, what's going on with the eyes?
5804:43 The eyes are on the screen there.
5904:45 The eyes look ahead where the robot's going to move.
6004:47 So a person that's interacting with the robot understands where it's going to reach and isn't surprised by its motions.
6104:53 Here Chris took the object out of its hand, and Baxter didn't go and try to put it down; it went back and realized it had to get another one.
6205:00 It's got a little bit of basic common sense, goes and picks the objects.
6305:03 And Baxter's safe to interact with.
6405:05 You wouldn't want to do this with a current industrial robot.
6505:08 But with Baxter it doesn't hurt.
6605:10 It feels the force, understands that Chris is there and doesn't push through him and hurt him.
6705:17 But I think the most interesting thing about Baxter is the user interface.
6805:20 And so Chris is going to come and grab the other arm now.
6905:23 And when he grabs an arm, it goes into zero-force gravity-compensated mode and graphics come up on the screen.
7005:31 You can see some icons on the left of the screen there for what was about its right arm.
7105:35 He's going to put something in its hand, he's going to bring it over here, press a button and let go of that thing in the hand.
7205:43 And the robot figures out, ah, he must mean I want to put stuff down.
7305:48 It puts a little icon there.
7405:49 He comes over here, and he gets the fingers to grasp together, and the robot infers, ah, you want an object for me to pick up.
7505:59 That puts the green icon there.
7606:01 He's going to map out an area of where the robot should pick up the object from.
7706:06 It just moves it around, and the robot figures out that was an area search.
7806:11 He didn't have to select that from a menu.
7906:13 And now he's going to go off and train the visual appearance of that object while we continue talking.
8006:18 So as we continue here, I want to tell you about what this is like in factories.
8106:22 These robots we're shipping every day.
8206:23 They go to factories around the country.
8306:25 This is Mildred.
8406:26 Mildred's a factory worker in Connecticut.
8506:28 She's worked on the line for over 20 years.
8606:31 One hour after she saw her first industrial robot, she had programmed it to do some tasks in the factory.
8706:37 She decided she really liked robots.
8806:39 And it was doing the simple repetitive tasks that she had had to do beforehand.
8906:44 Now she's got the robot doing it.
9006:45 When we first went out to talk to people in factories about how we could get robots to interact with them better, one of the questions we asked them was, "Do you want your children to work in a factory?"
9106:55 The universal answer was "No, I want a better job than that for my children."
9206:59 And as a result of that, Mildred is very typical of today's factory workers in the U.S.
9307:04 They're older, and they're getting older and older.
9407:07 There aren't many young people coming into factory work.
9507:10 And as their tasks become more onerous on them, we need to give them tools that they can collaborate with, so that they can be part of the solution, so that they can continue to work and we can continue to produce in the U.S.
9607:22 And so our vision is that Mildred who's the line worker becomes Mildred the robot trainer.
9707:29 She lifts her game, like the office workers of the 1980s lifted their game of what they could do.
9807:35 We're not giving them tools that they have to go and study for years and years in order to use.
9907:40 They're tools that they can just learn how to operate in a few minutes.
10007:43 There's two great forces that are both volitional but inevitable.
10107:47 That's climate change and demographics.
10207:50 Demographics is really going to change our world.
10307:52 This is the percentage of adults who are working age.
10407:56 And it's gone down slightly over the last 40 years.
10507:59 But over the next 40 years, it's going to change dramatically, even in China.
10608:03 The percentage of adults who are working age drops dramatically.
10708:08 And turned up the other way, the people who are retirement age goes up very, very fast, as the baby boomers get to retirement age.
10808:17 That means there will be more people with fewer social security dollars competing for services.
10908:23 But more than that, as we get older we get more frail and we can't do all the tasks we used to do.
11008:29 If we look at the statistics on the ages of caregivers, before our eyes those caregivers are getting older and older.
11108:38 That's happening statistically right now.
11208:40 And as the number of people who are older, above retirement age and getting older, as they increase, there will be less people to take care of them.
11308:48 And I think we're really going to have to have robots to help us.
11408:51 And I don't mean robots in terms of companions.
11508:53 I mean robots doing the things that we normally do for ourselves but get harder as we get older.
11608:58 Getting the groceries in from the car, up the stairs, into the kitchen.
11709:02 Or even, as we get very much older, driving our cars to go visit people.
11809:07 And I think robotics gives people a chance to have dignity as they get older by having control of the robotic solution.
11909:17 So they don't have to rely on people that are getting scarcer to help them.
12009:20 And so I really think that we're going to be spending more time with robots like Baxter and working with robots like Baxter in our daily lives. And that we will -- Here, Baxter, it's good.
12109:38 And that we will all come to rely on robots over the next 40 years as part of our everyday lives.
12209:45 Thanks very much.
12309:46 (Applause)