every human used to have to hunt or gather to survive. but humans are smart...ly lazy so we made tools to make our work easier. from sticks, to plows, to tractors we’ve gone from everyone needing to make food to, modern agriculture with almost no one needing to make food — and yet, we still have abundance. of course, it’s not just farming, it’severything. we’ve spent the last several thousand years building tools to reduce physicallabor of all kinds. these are mechanical muscles. stronger, more reliable, and more tirelessthan human muscles ever could be. and that's a good thing. replacing human laborwith mechanical muscles frees people to specialize and that leaves everyone better off - even thosestill doing physical labor. this is how economies
grow and standards of living rise. some people have specialized to be programmersand engineers whose job is to build mechanical minds. just as mechanical muscles made humanlabor less in demand so are mechanical minds making human brain labor less in demand. this is an economic revolution. you may thinkwe've been here before, but we haven't. this time is different. ## physical labor when you think of automation, you probablythink of this: giant, custom-built, expensive, efficient, but really dumb robots blind tothe world and their own work. they were a
scary kind of automation but they haven'ttaken over the world because they're only cost effective in narrow situations. but they're the old kind of automation, thisis the new kind. meet baxter. unlike these things which require skilledoperators and technicians and millions of dollars, baxter has vision and can learn whatyou want him to do by watching you do it. and he costs less than the average annualsalary of a human worker. unlike his older brothers he isn't pre-programmed for one specificjob, he can do whatever work is within the reach of his arms. baxter is what might bethought of as a general purpose robot and
general purpose is a big deal. think computers, they too started out as highlycustom and highly expensive, but when cheap-ish general-purpose computers appeared they quicklybecame vital to everything. a general-purpose computer can just as easilycalculate change or assign seats on an airplane or play a game or do anything just by swappingits software. and this huge demand for computers of all kinds is what makes them both morepowerful and cheaper every year. baxter today is the computer of the 1980s.he’s not the apex but the beginning. even if baxter is slow his hourly cost is penniesworth of electricity while his meat-based competition costs minimum wage. a tenth thespeed is still cost effective when it's a
hundredth the price. and while baxter isn'tas smart as some of the other things we will talk about, he's smart enough to take overmany low-skill jobs. and we've already seen how dumber robots thanbaxter can replace jobs. in new supermarkets what used to be 30 humans is now one humanoverseeing 30 cashier robots. or take the hundreds of thousand baristas employedworld-wide? there’s a barista robot coming for them. sure maybe your guy makes the double-mocha-whateverjust perfect and you’d never trust anyone else -- but millions of people don’t careand just want a decent cup of coffee. oh, and by the way this robot is actually a giantnetwork of robots that remembers who you are and how you like your coffee no matter whereyou are. pretty convenient.
we think of technological change as the fancynew expensive stuff, but the real change comes from last decade's stuff getting cheaper andfaster. that's what's happening to robots now. and because their mechanical minds arecapable of decision making they are out-competing humans for jobs in a way no pure mechanicalmuscle ever could. ## luddite horses imagine a pair of horses in the early 1900stalking about technology. one worries all these new mechanical muscles will make horsesunnecessary. the other reminds him that everything so farhas made their lives easier -- remember all that farm work? remember running from coast-to-coastdelivering mail? remember riding into battle?
all terrible. these city jobs are pretty cushy, and with so many humans in the cities there will be more jobs for horses than ever. even if this car thingy takes off - he might say - there will be new jobs for horses we can't imagine. but you, dear viewer, from beyond 2000 knowwhat happened -- there are still working horses, but nothing like before. the horse populationpeaked in 1915 -- from that point on it was nothing but down. there isn’t a rule of economics that saysbetter technology makes more better jobs for horses. it sounds shockingly dumb to evensay that out loud, but swap horses for humans
and suddenly people think it sounds aboutright. as mechanical muscles pushed horses out ofthe economy, mechanical minds will do the same to humans. not immediately, not everywhere,but in large enough numbers and soon enough that it's going to be a huge problem if weare not prepared. and we are not prepared. you, like the second horse, may look at thestate of technology now and think it can’t possibly replace your job. but technologygets better, cheaper, and faster at a rate biology can’t match. just as the car was the beginning of the endfor the horse so now does the car show us the shape of things to come.
## automobiles self-driving cars aren't the future: they'rehere and they work. self-driving cars have travelled hundreds of thousands of miles upand down the california coast and through cities -- all without human intervention. the question is not if they'll replaces cars,but how quickly. they don’t need to be perfect, they just need to be better than us. humansdrivers, by the way, kill 40,000 people a year with cars just in the united states.given that self-driving cars don’t blink, don’t text while driving, don’t get sleepyor stupid, it's easy to see them being better than humans because they already are.
now to describe self-driving cars as carsat all is like calling the first cars mechanical horses. cars in all their forms are so muchmore than horses that using the name limits your thinking about what they can even do.lets call self-driving cars what they really are: autos: the solution to the transport-objects-from-point-a-to-point-bproblem. traditional cars happen to be human sized to transport humans but tiny autos canwork in warehouses and gigantic autos can work in pit mines. moving stuff around iswho knows how many jobs but the transportation industry in the united states employs aboutthree million people. extrapolating world-wide that’s something like 70 million jobs ata minimum.
these jobs are over. the usual argument is that unions will preventit. but history is filled with workers who fought technology that would replace themand the workers always lose. economics always wins and there are huge incentives acrosswildly diverse industries to adopt autos. for many transportation companies, humansare about a third their total costs. that's just the straight salary costs. humans sleepingin their long haul trucks costs time and money. accidents cost money. carelessness costs money.if you think insurance companies will be against it, guess what? their perfect driver is onewho pays their small premiums and never gets into an accident.
the autos are coming and they're the firstplace where most people will really see the robots changing society. but there are manyother places in the economy where the same thing is happening, just less visibly. so it goes with autos, so it goes for everything. ## the shape of things to come it's easy to look at autos and baxters andthink: technology has always gotten rid of low-skill jobs we don't want people doinganyway. they'll get more skilled and do better educated jobs -- like they've always done. even ignoring the problem of pushing a hundred-millionadditional people through higher education,
white-collar work is no safe haven either.if your job is sitting in front of a screen and typing and clicking -- like maybe you'resupposed to be doing right now -- the bots are coming for you too, buddy. software bots are both intangible and wayfaster and cheaper than physical robots. given that white collar workers are, from a company'sperspective, both more expensive and more numerous -- the incentive to automate theirwork is greater than low skilled work. and that's just what automation engineersare for. these are skilled programmers whose entire job is to replace your job with a softwarebot. you may think even the world's smartest automationengineer could never make a bot to do your
job -- and you may be right -- but the cuttingedge of programming isn't super-smart programmers writing bots, it's super-smart programmerswriting bots that teach themselves how to do things the programmer could never teachthem to do. how that works is well beyond the scope ofthis video, but the bottom line is there are limited ways to show a bot a bunch of stuffto do, show the bot a bunch of correctly done stuff, and it can figure out how to do thejob to be done. even with just a goal and no knowledge of howto do it the bots can still learn. take the stock market which, in many ways, is no longera human endeavor. it's mostly bots that taught themselves to trade stocks, trading stockswith other bots that taught themselves.
as a result, the floor of the new york stockexchange isn't filled with traders doing their day jobs anymore, it's largely a tv set. so bots have learned the market and bots havelearned to write. if you've picked up a newspaper lately you've probably already read a storywritten by a bot. there are companies that teach bots to write anything: sportsstories, tps reports, even say, those quarterly reports that you write at work. paper work, decision making, writing -- alot of human work falls into that category and the demand for human metal labor is theseareas is on the way down. but surely the professions are safe from bots? yes?
## professional bots when you think 'lawyer' it's easy to thinkof trials. but the bulk of lawyering is actually drafting legal documents, predicting the likelyoutcome and impact of lawsuits, and something called 'discovery' which is where boxes ofpaperwork gets dumped on the lawyers and they need to find the pattern or the one out-of-placetransaction among it all. this can be bot work. discovery, in particular,is already not a human job in many law firms. not because there isn't paperwork to go through,there's more of it than ever, but because clever research bots shift through millionsof emails and memos and accounts in hours not weeks -- crushing human researchers interms of not just cost and time but, most
importantly, accuracy. bots don't get sleepyreading through a million emails. but that's the simple stuff: ibm has a botnamed watson: you may have seen him on tv destroy humans at jeopardy — but that wasjust a fun side project for him. watson's day-job is to be the best doctorin the world: to understand what people say in their own words and give back accuratediagnoses. and he's already doing that at slone-kettering, giving guidance on lung cancertreatments. just as auto don’t need to be perfect -- theyjust need to make fewer mistakes than humans -- the same goes for doctor bots. human doctors are by no means perfect -- thefrequency and severity of misdiagnoses are
terrifying -- and human doctors are severelylimited in dealing with a human's complicated medical history. understanding every drugand every drug's interaction with every other drug is beyond the scope of human knowability. especially when there are research robotswhose whole job it is to test thousands of new drugs at a time. and human doctors can only improve through theirown experiences. doctor bots can learn from the experiences of every doctor bot. can readthe latest in medical research and keep track of everything that happens to all their patientsworld-wide and make correlations that would be impossible to find otherwise.
not all doctors will go away, but when the doctorbots are comparable to humans and they're only as far away as your phone -- the needfor general doctors will be less. so professionals, white-collar workers andlow-skill workers all have things to worry about from automation. but perhaps you are unfazed becauseyou're a special creative snowflake. well guess what? you're not that special. ## creative bots creativity may feel like magic, but it isn't.the brain is a complicated machine -- perhaps the most complicated machine in the wholeuniverse -- but that hasn't stopped us from trying to simulate it.
there is this notion that just as mechanicalmuscles allowed us to move into thinking jobs that mechanical minds will allow us tomove into creative work. but even if we assume the human mind is magically creative -- it'snot, but just for the sake of argument -- artistic creativity isn't what the majority of jobsdepend on. the number of writers and poets and directors and actors and artists who actuallymake a living doing their work is a tiny, tiny portion of the labor force. and giventhat these are professions dependent on popularity they'll always be a very smallportion of the population. there can't be such a thing as a poem and paintingbased economy. oh, by the way, this music in the backgroundthat you're listening to? it was written by a bot.
her name is emily howell and she canwrite an infinite amount of new music all day for free. and people can't tell the difference between her and human composers when put to a blind test. talking about artificial creativity gets weirdfast -- what does that even mean? but it's nonetheless a developing field. people used to think that playing chess wasa uniquely creative human skill that machines could never do right up until they beat thebest of us. and so it will go for all human talents. ## conclusion right: this may have been a lot to takein, and you might want to reject it -- it's
easy to be cynical of the endless and idioticpredictions of futures that never are. so that's why it's important to emphasize again thatthis stuff isn't science fiction. the robots are here right now. there is a terrifyingamount of working automation in labs and warehouses around the world. we have been through economic revolutionsbefore, but the robot revolution is different. horses aren't unemployed now because theygot lazy as a species, they’re unemployable. there's little work a horse can do that doto pay for its housing and hay. and many bright, perfectly capable humanswill find themselves the new horse: unemployable through no fault of their own.
but if you still think new jobs will saveus: here is one final point to consider. the us census in 1776 tracked only a few kindsof jobs. now there are hundreds of kinds of jobs, but the new ones are not a significantpart of the labor force. here's the list of jobs ranked by the numberof people who perform them - it's a sobering list with the transportation industry at thetop. continuing downward, all of this work existed in some form a hundred years ago and almostall of them are targets for automation. only when we get to number 33 on the list is therefinally something new. don't that every barista or white collar worker need lose their job before things are a problem. the unemployment rate during the great depressionwas 25%.
this list above is 45% of the workforce. justwhat we've talked about today, the stuff that already works, can push us over that numberpretty soon. and given that even in our modern technological wonderland new kinds of workaren't a significant portion of the economy, this is a big problem. this video isn't about how automation is bad-- rather that automation is inevitable. it's a tool to produce abundance for little effort.we need to start thinking now about what to do when large sections of the population areunemployable -- through no fault of their own. what to do in a future where, for mostjobs, humans need not apply.
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