As the Nobel laureate economist Robert Solow noted in 1987, computers are ‘‘everywhere but in the productivity statistics’’.
Since then, the so-called productivity paradox has become ever more striking. Automation has eliminated many jobs. Robots and artificial intelligence now seem to promise (or threaten) yet more radical change.
Yet productivity growth has slowed across the advanced economies; in Britain, labour is no more productive today than it was in 2007.
Some economists see low business investment, poor skills, outdated infrastructure, or excessive regulation holding back potential growth.
Others note wide disparities in productivity between leaders and laggards among industrial manufacturers.
Still others question whether information technology is really so distinctively powerful.
But the explanation may lie deeper still. As we get richer, measured productivity may inevitably slow, and measured GDP per capita may tell us ever less about trends in human welfare.
The growth of difficult-toautomate service activities may explain some of the productivity slowdown. In the United States, the Bureau of Labour Statistics reports that eight of the 10 fastestgrowing job categories are lowwage services such as personal care and home health aides.
The growth of ‘‘zero-sum’’ activities may, however, be even more important. Look around the economy, and it’s striking how much high-talent manpower is devoted to activities that cannot possibly increase human welfare, but entail competition for the available economic pie.
Such activities have become ubiquitous: legal services, policing, and prisons; cybercrime and the army of experts defending organisations against it; financial regulators trying to stop misselling and the growing ranks of compliance officers employed in response; the huge resources devoted to US election campaigns; real-estate services that facilitate the exchange of already-existing assets; and much financial trading.
Much design, branding, and advertising activity is also essentially zero-sum. It is certainly good that new fashions can continually compete for our attention. Choice and human creativity are valuable per se.
But we have no reason to believe that 2050’s designs and brands will make us any happier than those of 2017.
Information technology may improve human welfare in ways not captured in measured output. Billions of hours of consumer time previously spent filling in forms, making telephone calls, and queuing are eliminated by internet-based shopping and search services.
Valuable information and entertainment services are provided for free.
Much that delivers human welfare benefits is not reflected in GDP.
Indeed, measured GDP and gains in human welfare eventually may become entirely divorced.
Imagine in 2100 a world in which solar-powered robots, manufactured by robots and controlled by artificial intelligence systems, deliver most of the goods and services that support human welfare.
All that activity would account for a trivial proportion of measured GDP, simply because it would be so cheap.
Conversely, almost all measured GDP would reflect zerosum and/or impossible-toautomate activities – housing rents, sports prizes, artistic performance fees, brand royalties, and administrative, legal, and political system costs. Measured productivity growth would be close to nil, but also irrelevant to improvement in human welfare.
We are far from there yet. But the trend in that direction may well help explain the recent productivity slowdown.
The computers are not in the productivity statistics precisely because they are so powerful.
Adair Turner is chairman of the Institute for New Economic Thinking.
Google’s artificial intelligence (AI) program AlphaGo defeated world go champion Lee Se-dol again in their second game, Thursday, on the back of superior calculations that almost seemed to exceed human brains.
The game, which seemed to be a close one in the middle, drastically inclined to the AI’s favor towards the end after its attack on Lee’s territory in the center of the board. Lee, who chose relatively safer moves than in the previous round, tried to overturn the game even after he entered overtime counting but ended up resigning again after 211 moves.
After the match, Lee calmly admitted a perfect defeat.
“I was already surprised enough yesterday and I think I have nothing to say now,” Lee said. “It was really a perfect defeat. I have never thought I was in the lead for a moment.”
He also said AlphaGo played a flawless game.
“I could not find anything particularly strange (from AlphaGo). Yesterday I thought there might be something strange but today AlphaGo played a perfect game,” Lee said.
Despite the two consecutive losses, Lee pledged to continue to do his utmost in the remaining games.
“Now that the score is 2-0 and (the victory) is not expected to be easy,” he said. “But I will do my best to win at least one round.
“Reflecting on today’s match, it is difficult to overturn the game after the middle of it. I will need to try to conclude the game before then to have a better chance of winning.”
A match commentator Michael Redmond said, “Unlike in October, AlphaGo was very impressive, played innovatively and adventurously and led dangerously-looking moves to success.”
Changing f rom the game, Lee played second with white stones, receiving 7.5 compensation points as AlphaGo did in the previous game.
Playing first with black stones, AlphaGo began the game at the 3-4 point of top left corner on the board instead of the flower point where it started in the previous round and in all five wins against European go champion Fan Hui in October last year.
In the 13th move, the AI abruptly moved from the bottom right corner and opened a new l ayout in the upper edge, which the commentator said was “surprising and unprecedented.”
From this moment, AlphaGo continued with irregular and unpredictable positions while Lee proceeded with relatively stable moves to counteract the AI. In the meantime, Lee refrained from his unique aggressive and creative playing style and spent twice as much time as AlphaGo around an hour into the game, thinking deeply about his moves.
Two hours into the game, the AI started combat moves in the bottom left corner. But Lee broke through and succeeded in securing territory.
But when AlphaGo attacked Lee’s group in the center, Lee turned to the AI’s territory in the top right in exchange, which the commentators said was a bad move for Lee.
Leaving only one minute and 15 seconds, Lee made a key move to turn the tables.
But the machine did not falter and drove Lee to overtime counting.
In this special competition between the world’s top go player and the AI system developed by Google’s London-based subsidiary DeepMind, each player was given two hours per match with three lots of 60 seconds overtime counting after they have finished the allowed time. Each 60-second lot is refreshed if it is not used up.
Lee strived for breakthrough but chose to resign four hours and 25 minutes into the game.
On Wednesday, AlphaGo beat Lee by a resignation in 186 moves after three-and-a-half hours. After AlphaGo’s moves that seemed by commentators as “obvious and critical” mistakes in the latter half of that game, Lee tried to push further but failed to secure enough points to overcome the 7.5 compensation points and resigned.
Lee’s defeat in the first game stunned the world as many have predicted his win under assumption that go still remains difficult area for machines to outperform humans as the ancient game requires both accurate calculations and intuition.
Last month, Lee showed confidence and said he would clinch a victory with a score of 5-0 or 4-1. But in a press conference on Tuesday, one day before the first game, he said AlphaGo’s improved ability to narrow down options for next moves could be more intimidating than he originally expected.
The five-game match between Lee and the AI system will continue on Saturday and Sunday before wrapping up with the fifth-round on March 15. The Google DeepMind Challenge Match, which was organized by Google and the Korea Baduk Association, will continue even after three wins by either side as the event aims at providing the machine with more data.
Washington: There was a robot invented in America that catches thieves. In the US, it caught 10 thieves; in Australia, it caught 100. In China, it caught 1,000. In India, someone stole the robot. You may want the joke to come true because robots are coming to steal your jobs, particularly if your work is mostly repetitive, mechanical, motorised; something that is programmable.
It’s no secret that automation is taking over low-wage jobs, but as robots and drones get increasingly sophisticated, a White House economic report released on Monday has put numbers on a trend that should give pause to anyone who thinks low-wage manufacturing is the panacea to economic salvation in India, or anywhere else for that matter.
In the US, there’s an 83% chance that automation will take a job with an hourly wage below $20, a 31% chance automation will take a job with an hourly wage between $20 and $40, and just a 4% chance automation will take a job with an hourly wage above $40, a report by the White House Council of Economic Advisers (CEA) warned. The risk of having your job effectively taken over by a robot, CEA chairman Jason Furman told reporters on Monday, “varies enormously based on what your salary is.” In other words, the more skilled, creative, and high-earning you are, less likely your job will be taken over by automatons.
Mechanical and assemblyline tasks, from laying bricks to making cars and even driving them, are already being taken over by drones, robots, and other “intelligent” forms even as scientists are trying to infuse them with intuition and emotions, their memory and computing power long having surpassed that of human beings. Furman said the risk of many current jobs being performed by robots is another example of why it is important to invest in education that helps people have skills that complements automation.
Developments in US indust- ry serve as a warning against over-reliance on low-grade, assembly-line manufacturing that can be replaced by robots. Even some of the low-level service jobs, such as dispensing food or gas or money, have been destroyed in the US with the advancement of automation — from ATMs to self-serve kiosks for photographs.
Manufacturing jobs have declined by more than 7.2 million, or 37%, since employment in manufacturing peaked in 1979. In 1965, manufacturing accounted for 53% of the US economy; by 1988 it only accounted for 39%, in 2014, it accounted for less than 9%.
Not all of the destruction is accounted for by flight of jobs to China or Mexico. Lurking in the background, technological advancement. University of Oxford researchers Carl Benedikt Frey and Michael Osborne estimated in 2013 that 47% of total US jobs could be automated and taken over by computers by 2033. Even jobs in medicine, law, and education are not immune. Remarkably though, even as employment is shrinking, productivity is growing, thanks to the technological advancements. So, while the GDP is soaring, median income in many jobs is falling even as the job market itself is becoming smaller.
NASA is developing a sixfeet tall humanoid robot that could assist astronauts in risky and extremely hazardous deep space missions to Mars and asteroids in the future.
The US space agency is considering ushering new humanoid robots that could offer astronauts a helping hand in future expeditions.
“Nasa is counting on robots to setup and care for deep space exploration facilities and equipment pre-deployed ahead of astronauts,” Sasha Congiu Ellis of Nasa’s Langley Research Centre, told Astrowatch.Net.
“Robots are also excellent precursors for conducting science missions ahead of human exploration,” Ellis said.
That is why the agency is developing a six-feet tall humanoid robot called R5, previously known as Valkyrie. The machine weighs about 131 kg.
It was initially designed to complete disaster-relief manoeuvres. In November last year, Nasa awarded two R5 robots to university groups — the Massachusetts Institute of Technology (MIT) and the Northeastern University in Boston.
According to Nasa, the teams have two years to perform research and software development in order to improve the robot’s autonomy. They also have access to onsite and virtual technical support from the agency.
In a glitzy exhibition hall in Beijing, an extraordinary Tai chi show is on. The performers are a martial arts master in spotless white robes and — wait for it — an industrial robot.
It’s the kind of robot you would often see hiding behind safety barriers at factories.
No sooner had the master pushed his right hand against the robot than the latter sprung into action, circled around and smoothly pushed him back in one fluid motion.
The 90- second demo is more ballet than combat as the man and the machine engage in almost intimate motions. Every time the master comes into contact, the sensor- rich machine, well, senses the touch instantly, determines the amount of pressure in it and ‘ instinctively’ moves in the intended direction.
“This is China’s first homegrown seven- axis collaborative robot,” said Qu Daokui, president of Siasun Robot & Automation Co, the manufacturer of the motorized arm.
It can be trained by hands to perform a string of industrial tasks like grinding, packaging and feeding parts.
“It is ready to work side by side with humans on assembly lines, performing a string of industrial tasks like grinding, packaging, assembling and feeding parts,” he said.
The collaborative robot, which was unveiled in November, is part of a broad effort by Siasun, as well as its domestic peers, to cash in on the country’s growing appetite for industrial robots as enterprises are cranking up automation of car and electronics factories.
The world’s second- largest economy is already the leading market for industrial robots, accounting for a quarter of global sales, according to the International Federation of Robotics.
Between 2010 and 2014, total supply of industrial robots in China increased by about 40 percent per year on average.
“This ( China’s) rapid development is unique in the history of robotics. There has never been such dynamic rise in such a short period of time in any other market,” IFR said in a report.
But still, for every 10,000 employees, there are only 36 robots in China, compared with 478 in South Korea, 292 in Germany and 164 in the United States in 2014.
As the surging labor cost is pushing more enterprises to embrace robots, IFR estimates China will account for more than one- third of the industrial robots installed worldwide in 2018, more than doubling over the next two years — from 262, 900 now to 614,200.
Naturally, the growth prospect offers a golden opportunity for domestic robot manufacturers.
In addition to Siasun, the country’s largest robot maker by market value, a bunch of new players are getting lured in and many robot makers are upping the ante with ambitious development plans.
“The past two years have seen an explosion of domestic robot makers, partly stimulat- ed by strong policy support,” said Luo Jun, chief executive officer of the International Robotics and Intelligent Equipment Industry Alliance, a Beijing- based industry association.
The robot industry is central to the country’s Made in China 2025 strategy designed to promote high- end manufacturing.
It is also highlighted in Beijing’s new five- year plan, which guides national economic development.
One of the new entrants is HIT Robot Group, which was established in December 2014 with funding from a provincial government and the Harbin Institute of Technology, a Chinese university which was ranked 7 th among the best global engineering universities by US News in 2015.
The elite university has done years of cutting- edge research into robots — it is the maker of China’s first space robots and lunar vehicle.
For its part, the company is positioned to have a presence in a wide range of areas, from robot components, industrial robots, service robots to auto- mated equipment for nuclear power plants and aerospace industries.
“We have arguably the best robot engineers and researchers in China, which can give us an unparalleled advantage,” wrote Han Jiecai, honorary chairman of HIT Robot and vice president of the Harbin Institute of Technology, in a bylined article in the Economic Observer.
But despite the efforts by leading Chinese robot manufacturers to build a premium brand, most players are still locked in low- end competi- tion, experts said.
“Though the domestic scientific community has been researching robots for many years, the robot industry is still in its infancy,” said Hao Yucheng, deputy director of the China Robot Industry Alliance.
“The bulk of enterprises have no intellectual properties, talents, and cash. They are just entering the sector with enthusiasm and doing repetitive jobs like assembling robots instead of making robots,” he said.
In 2014, China bought over 57,000 industrial robots, but less than 30 percent of them are from domestic suppliers, data from the China Robot Industry Alliance shows.
Foreign heavyweights including ABB Ltd, KUKA Robotics Corp and FANUC Corp are sharing the rest 70 percent of the market.
“China’s robot industry is like a toddler. But it is growing in the world’s largest robot market where many competitive foreign enterprises are scrambling for a pie. Opportunities abound, so do challenges. A simple mistake is likely to nip the industry in the bud,” Qu of Siasun said.
Also, a wide technological gap still exists between domestic robot manufacturers and their foreign counterparts.
China now has few enterprises that can provide massproduced and reliable industrial robot components such as speed reducers, drive and control devices, as well as servomotors.
“Most of these components are still imported from foreign countries, whose steep tariffs increase the cost of robots,” Hao of the China Robot Industry Alliance said.
For instance, speed reducers could account for about 30 percent of domestic robots’ cost, compared with only 12 percent for similar Japanese robots, an industry resource said.
But local enterprises are already accelerating steps to boost their capability in research and development as well as small- scale production of key robot components.
Shaanxi Qinchuan Machinery Development Co Ltd, for instance, has poured 194 million yuan in 2013 into a robot speed reducer project, which can now produce 500 to 700 units per month.
“We are working on a mass production assembly line project. When completed, it will boost monthly production capacity to 5,000 units by the end of 2016,” the company said in a press release in November.
Siasun also expanded its presence in the niche by setting up a unit in May 2015.
It is planning to acquire competitive domestic and international component manufacturers after the Shenzhen- listed company raised 2.96 billion yuan from five institutional investors in November.
“We have been in negotiations with potential companies for over a year and we hope to complete the acquisition by June,” Qu, president of Siasun said, declining to offer more details.
“Our goal is not to catch up but to take the lead by innovating on the basis of state- of- the- art technologies,” he said.
Americans are justified to be angry about the economic recovery. As President Barack Obama enters his final year, good-paying jobs remain scarce and family incomes are down about $1,650 on his watch.
Since Ronald Reagan ran the country, the availability of attractive employment has been trending down and slowing economic growth is often blamed — during Obama’s recovery, gross domestic product has advanced at a 2.2 percent annual pace, whereas the comparable figures for Reagan and Clinton were 4.6 and 3.7 percent.
But that puts the story backward — the lack of workers adequately trained for a more technological demanding workplace is slowing growth, not the other way around.
Automation has been an enduring theme throughout American history. First, reapers and tractors consolidated farms and sent workers to factories. Then machines replaced workers in manufacturing, pushing them into more highly paid professions in medicine, education and technology but also less well-paid occupations in restaurants, retailing and other services.
Until recently, computer-programmed machines could be taught strenuous and repetitive tasks like attaching a heavy, rigid fender onto an automobile. Going forward robots will increasingly replace people in activi- ties requiring more subtle manual dexterity — like making shirts and harvesting fruit — and those requiring more complex cognitive processes like masonry construction, driving limousines and building new robots that adapt to changing environmental conditions.
The drugstore I visit in Washington no longer has cashiers — just a group of checkout machines and one clerk to assist technologically flummoxed patrons. Over the next two decades, robots will be capable of unloading pallets, stocking shelves, filling prescriptions, and generally running the store with minimal human intervention.
By 2030, it will become technologically possible to replace 90 percent of the jobs as we know them by smart machines. The real challenge will be training most Americans to engage in intellectu- ally demanding and creative work, or the globalization of technology and competition will relegate most of us to very low paying work better left to androids.
In 2016, Americans should be skeptical, not merely of false promises to restore prosperity made by Bernie Sanders and Donald Trump but also outraged by the handiwork of mainstream politicians.
The latter’s efforts to make a high school diploma universal have made it a nearly worthless credential. Less than 40 percent of 12th-graders are ready to read or learn math at the college level, and many fewer have skills to enter technically demanding positions without post-secondary training.
A college diploma is not much better. After pushing millions of unqualified students into universities through affirmative action and government loan programs, 4 in 10 graduates lack the complex reasoning skills needed for white-collar work — as it exists today, never mind as it will be after machines equipped with high-level artificial intelligence can replace armies of stockbrokers, insurance adjusters and restaurant managers over the next several decades.
Meanwhile, the president and his presumptive heir, Hillary Clinton, remain obsessed with sexism in education and the workplace. That nearly 60 percent of college degrees are now awarded to women and females often earn more than males in comparable positions are inconvenient facts when there are voters to be misled to extend a political dynasty.
And conservatives — including the likes of Ted Cruz and Marco Rubio — oppose universal standards for more academic rigor like the Common Core.
The future lies in educating Americans, not to be angry about false injustice or an omnipresent state but, rather, to build and teach the machines that will do the work that has burdened humanity since the first branch was shaped into a hunting implement.
Without young people trained and encouraged to do that sophisticated work, the locus of prosperity will permanently shift from America to Asia, where pragmatic leaders urge children to study engineering, not the superstitions peddled by pious academics and deceitful politicians.
— In a martial artist’s white silk pyjamas, a man practiced tai-chi in harmony with a motorized arm at a Beijing exhibition showcasing a vision of robots with Chinese characteristics.
Vehicles with automated gun turrets sat alongside drink-serving karaoke machines at the World Robot Conference, as manufacturers sought new buyers for their “jiqiren” — “machine people” in Chinese.
The push has support at the highest levels of government. President Xi Jinping issued a letter of congratulations for the conference, and the industry is name-checked in the draft version of the country’s new five-year plan, the policy document that guides national economic development.
The world’s second-largest economy is already the leading market for industrial robots, accounting for a quarter of global sales, according to the International Federation of Robotics. But executives at a conference roundtable said the real market opportunity was in service robots for the homes and offices of the world’s most populous country. “There are now less than 100,000 robots in Chinese families, not including vacuum cleaners,” said Liu Xuenan, chief executive officer of Canbot.
In the future, said Yu Kai, the head of Horizon Robotics, China’s automated helpers will do everything from building cars to driving them, predicting that “each person might have 10 robots” — nearly 14 billion potential tin men at current population levels.
Planet of the Apps
Robots have captured China’s imagination. From Transformers to Baymax, the star of Disney’s movie “Big Hero 6,” Chinese consumers have embraced robot heroes, spending hundreds of millions on related movies and merchandise.
In Chinese cities, businesses try to attract customers with robot waiters, cooks, and concierges. In the countryside, rural Da Vincis cobble together mechanical men from scrapyard junk.
A panel at the conference struggled with the question of how China would deal with the rise of artificially intelligent machines.
But the transition from the world of fantasy and novelty to a real robot economy could be tricky, with the country’s technology still lagging far behind neighbors Korea and Japan, the undisputed king of the robots.
China should have more realistic expectations for the near future, said Pinpin Zhu, president of China’s voice controlled service Xiao I Robot, which was involved in a patent dispute with American tech giant Apple linked to its personal digital assistant Siri.
The country may descend from the peak of high expectations into a “trough of disillusionment,” said Zhu, who believes a smartphone-based “Planet of the Apps” is more likely than a world served by humanoid robots.
The day after a book called The Rise of the Robots won the Financial Times McKinsey Business Book of the Year award in London this week, a little company called Fastbrick Robotics listed on the ASX and promptly doubled in value.
It was instant fulfilment. Fastbrick Robotics has invented a bricklaying robot; the book, by Silicon Valley entrepreneur Martin Ford, presents a grim view of a future in which robots permanently replace human jobs.
Replacing brickies with robots is not that surprising when you think about it — after all, laying bricks is a repetitive, robot-like task. Talk to me when you’ve in- vented a robot builder, then I’ll be impressed (and grateful).
Brickies might not agree, but the corporate videos of Fastbrick Robotics present a bright new world of quick and efficient construction, in which a house can go up in two days.
The Rise of the Robots, on the other hand, foresees a dark dystopian future of fewer jobs, with disruption from machines and algorithms on both manufacturing and professional industries.
According to the reviews (I
haven’t read the book yet), Ford essentially argues that the current industrial revolution will not be like the last one, when new jobs were created just as quickly as the old ones were eliminated by technology. He writes: “While humanmachine collaboration jobs will certainly exist, they seem likely to be relatively few in number and often short-lived. In a great many cases, they may also be unrewarding and even dehumanising.”
According to Martin Ford, artificial intelligence is already well on its way to making “good jobs” obsolete: many paralegals, journalists, office workers and even computer programmers are poised to be replaced by robots and smart software. As progress continues, blue and white collar jobs alike will evaporate, squeezing working and middle class families ever further.
But Ford does not only talk about job theft by machines. One of his key points is that robots weaken middle-class demand by skewing the gains to a few — worsening inequality.
As labour becomes uneconomic relative to machines, purchasing power falls. For example, the US economy produces a third more today than it did in 1998 with the same sized workforce. What he doesn’t mention is that macroeconomic policy is doing the same thing, to some extent driven by digital disruption and robotics.
Just as falling wage growth is reducing middle-class demand, so are super low interest rates. It’s true that disposable incomes of middle-class mortgagees are being boosted by low interest rates, but that is being cancelled by the opposite effect on retirees who live off their savings. To some extent it’s a circular phenomenon: automation and disruption reduce costs and prices, reducing inflation and therefore interest rates.
So monetary policy itself becomes a disrupter. Not only is wages growth the lowest on record and unit labour costs not grown at all for three years, interest rates are the lowest they have ever been. In the US they have been effectively zero for seven years.
As I see it the world has to deal with six great disruptions at once:
Zero interest rates and quantitat- ive easing are one of great disruptive innovations of our time: negative real interest rates — and in some places even negative nominal interest rates — and central banks simply printing money and buying assets from banks. It’s an experiment that is having a profound effect on the way all markets and economies operate.
When Gordon Moore observed in 1965 that the number of transistors on an integrated circuit could double every year (and then revised that to every two years in 1975) it was early days for Moore’s Law. Forty years of that exponential growth in computing power is now affecting every part of life. Moore’s Law is responsible for smartphones, robotics, artificial intelligence, programmatic trading in shares and advertising … the list goes on, and includes all the things that Martin Ford is so worried about.
In a way this is an extension of Moore’s Law, but turning both data storage and software into a service — operating expenditure rather than capital expenditure — is itself hugely disruptive and deserves its own mention.
In an interview this week with Stephen Bartholomeusz and myself for Business Spectator, the CEO of Telstra Andy Penn revealed that the company had achieved a data speed over its mobile network of one gigabit per second in a test environment. Similar download speeds are already being achieved over fixed line. This has meant the internet can be used for broadcasting as well as connecting millions of machines (the “internet of things”) transmitting colossal amounts of data and storing it in the cloud.
This is the technology at the heart of Bitcoin, but its uses go far wider than that. Blockchain is a way of organising and verifying almost any transaction. It is early days, but already clear that this technology will eventually be at heart of a new banking system and a new settlement system.
In my view this is the most powerful disruptive force of all.
The internet has become a tool for humans to deal directly with each other. And it turns out that in even a world that is also being disrupted by appalling acts of terrorism, there is an overwhelming urge for people to trust each other.
We go and stay in each other’s houses (Airbnb), get in each other’s cars (Uber), buy stuff from each other and pay first (eBay, etc). We tell each other about our lives and ideas (Facebook, Twitter, Instagram, etc) and we’re now lending each other money (Society One, Lending Club, etc).
The willingness of humans to trust each other and, separately, to express themselves to each other, is not a new thing, but the internet has unleashed it and allowed it to be organised.
The social urge in human society has always existed, but has been confined to small communities simply because of the lack of any means to communicate efficiently across large distances.
The combination of connectivity and computing power has literally put that ability into our pockets — it’s with us everywhere we go. It has meant that our inherent urge to trust and communicate can be both fully expressed and organised.
“I’ve seen things you people wouldn’t believe,” the villain played by Rutger Hauer reminisces at the end of the film Blade Runner after hauling Harrison Ford’s character onto a rooftop and sparing his life. “People” is the operative word as Roy Batty is not a person but an android who escapes to earth from a space colony and takes revenge on the Tyrell Corporation, his creator. That is what I call a killer robot – a being that can hold an intelligent conversation with you before wiping you out.
It was science fiction in 1982, when Blade Runner, based on Philip K. Dick’s dystopian fantasy novel Do Androids Dream Of Electric Sheep?, came out. It is now faintly plausible – sufficiently for artificial intelligence researchers to warn this week of the dangers of an autonomous arms race.
The killer machines feared by those such as Mr Elon Musk, the founder of Tesla Motors, and theoretical physicist Stephen Hawking are crude terminators by comparison with the Nexus replicants in Blade Runner. No one would fall in love with an armed quadcopter that blows up enemy soldiers, as the hero of Blade Runner does with Rachael, the female android who does not realise that she is a replicant.
Robots can murder us but they cannot understand us. Autonomous killing machines are becoming reality – Israel already has its Harpy anti-radar drone, which loiters in the sky before choosing and destroying targets by itself. A sentient, sophisticated machine with common sense and the capacity to grasp people’s moods and predict behaviour is still a distant prospect.
In theory, it will be created. Artificial intelligence researchers do not see the barrier in principle to robots developing higher reasoning powers, or the kind of physical dexterity that humans possess. The last remaining workers on car assembly lines are people who can attach screws nimbly and reach inside the body shells for electrical wiring in a way that has defeated robots to date.
Machines also possess some advantages. They do not have to constrict their processing units to fit into skulls, and they do not need to supply them with oxygen, an energy-hogging technology. Nor are they limited by an evolutionary edict to reproduce, rather than purely to get cleverer.
But despite rapid advances in machine learning, visual and voice recognition, and neural network processing – all the elements that are now transforming the potential of artificial intelligence – androids are not with us. Computers can beat humans easily at chess, but poker at the highest level is beyond them – they would need to see through the other players’ bluffs.
“Computers are becoming better and better at perception tasks,” says Dr Fei-Fei Li, director of Stanford University’s artificial intelligence laboratory. “Algorithms can identify thousands of types of cars while I can tell only three of them. But at the cognitive, empathetic, and emotional level, machines are not even close to humans.”
I have also experienced something you people would not believe – Google’s self-driving car. The thing that struck me as it toured Mountain View in California recently was that it felt human. It accelerated from junctions confidently, even assertively, closing the gaps with vehicles in front so others could not rush in. We would be safer if all drivers were equally calm and rational.
Inside the car, you can see what it perceives with its sensors and rooftop radar. The outlines of objects around, including pedestrians, buses and other cars, are displayed like hollow, moving shapes on the screen of a laptop held by a Google engineer. The objects are categorised by different colours, so the vehicle knows it should react to them and how far to steer clear.
A self-driving vehicle would, in other words, be a perfectly capable killer robot if you attach a missile launcher to its roof, and machine guns to its sides (not that Google would do such a thing, of course). It could cruise through cities, scanning for warm, slow-moving, pink-coloured objects to destroy.
So it is not scaremongering for scientists to warn of artificial intelligence research being tainted by association with autonomous weapons. The Internet itself emerged from research funded by the United States Department of Defence in the 1960s, and military and space programmes have the deepest pockets and the keenest interest in developing cutting-edge technology. What would be foolish would be to think the advent of killer robots means that machines are ready to take over the world.
Destroying things is easier than understanding or creating them. Artificial intelligence – the ability to scan, process and analyse large data sets – is not the same as the capacity to perform most human tasks (known as artificial general intelligence).
Even those who warn of machines taking jobs that are now performed by humans accept that managerial, professional and artistic jobs that demand high-level reasoning, empathy and creativity are still safe.
A robot that scans a set of features to identify a woman, but cannot grasp her mood, or use common sense to solve an unexpected puzzle, remains very limited. “Quite an experience to live in fear, isn’t it? That’s what it’s like to be a slave,” Roy Batty says to the human bounty-hunter he has defeated in combat before reaching out and rescuing him from falling to his death. Let us not enslave ourselves yet.
The smartphone era has introduced a new list of rules for shopping.
First, find a product and check the Internet to compare the store’s price against that of a nearby competitor or online retailer. If the current location wins, make the purchase. If not, either take the trip across town or press the checkout button on your virtual shopping cart.
There’s little doubt that the instant accessibility of the Internet has helped consumers find the goods they need for the prices they’re willing to pay. However, with Internet searches adding to digital profiles designed to glean as much information about consumer lives and habits as possible, is the best price one that has been predetermined by corporations based on a shopper’s history?
Differential pricing — the economic term for setting different
prices for the same product for different customers — has long been a feature of commerce in one form or another. Senior citizens’ and veterans’ discounts, airline tickets and negotiated rates on car lots all fall under the umbrella. Dynamic pricing, in which businesses change prices based on algorithms that take into account competitor pricing, supply and demand, and other external factors, has grown more sophisticated over time.
The catch is that in the past the practice was geared toward specific demographics or in response to broad market conditions. But digital data that tracks nearly every online action could give companies the opportunity someday to track the exact price an individual consumer is willing to pay for a good or service — a form of personalized pricing on steroids.
“The more a merchant knows about you, the more they can predict your maximum willingness to pay for a good,” said Alessandro Acquisti, Carnegie Mellon University professor of information technology and co-director of the university’s Center for Behavioral Research.
“All of the trails of data that you leave as you browse around the Internet are being studied to create a picture of you which can be used not only to show you a certain, particular advertisement, but also to show you a certain, particular price.”
Mr. Acquisti, a renowned privacy researcher who will explore the issue as part of a two-year fellowship with the Carnegie Corporation of New York this year, said he was first drawn to the idea by a paper he wrote with former colleague Hal Varian in 2001 predicting the phenomenon. Since it was published more than a decade ago, there has been exponential growth in dynamic pricing services such as Amazon Prime or loyalty rewards programs that offer discounts to certain customers.
What hasn’t been seen as often is targeted pricing based on purchasing history, even though there’s some evidence it has occurred. A 2012 Wall Street Journal investigation revealed that Staples, Home Depot and several other retailers gave different consumers different prices for the same products based on location data from consumers’ cell phones that indicated how close the consumers were to a competitor’s store.
Differential pricing is not illegal unless the reason for the difference is based on reliance on a category such as race, religion, national origin or gender. The practice could also be illegal if it violates antitrust or price-fixing laws.
But consumers who are aware that haggling is the norm in bricks-and-mortar places such as car dealerships may not be aware that the same thing goes on online.
A car salesperson might figure that a customer in a $3,000 suit driving a 1-yearold Mercedes is a good bet for selling at a higher price, but an Internet retailer can tell by that same customer’s online buying habits with greater accuracy that he’s likely to pay more for an espresso machine than the customer with a history of shopping around for the best price. And while the welldressed customer can haggle as readily as his grungier counterpart on the sales room floor, it’s harder to bargain with an Amazon shopping cart.
Since consumers don’t regularly compare prices with consumers from across town or across the country buying the same goods, it’s difficult to tell how often the practice actually occurs, said Ali Lange, policy analyst for the Washington, D.C.-based nonprofit Center for Democracy and Technology.
“It’s definitely a concern for consumers. The way companies can assume things about people based on their data is something I don’t think people fully grasp,” she said.
In an attempt to get ahead of the issue, the White House in February issued the report “Big Data and Differential Pricing.” Its ultimate conclusion was that personalized pricing was probably scarce because companies aren’t sure they can target customers’ needs accurately and because of a fear of backlash against the practice.
The report agreed with Mr. Acquisti in one regard: raising awareness of the potential for danger in order to to protect consumer rights.
“Given the speed at which both the technology and business practices are evolving, commercial applications of big data deserve ongoing scrutiny, particularly where companies may be using sensitive information in ways that are not transparent to users and fall outside the boundaries of existing regulatory frameworks.”
THE WORLD of sex dolls is about to get even stranger. A project, dubbed Realbotix, is creating intelligent dolls that can communicate realistically with their owners.
The project’s creator hopes that the sex dolls will eventually be able to think for themselves, while satisfying the customer’s physical needs. Realbotix is the invention of Matt McMullen who is best known for creating “Real Dolls”, which are life-like silicone dolls that have become popular in the industry.
McMullen boasts that he has sold more than 5 000 life-size dolls since 1996, with prices from $5 000 (R62 026) to $10 000.
As part of his new project, McMullen is focusing on developing convincing artificial intelligence on a robotic head that can blink and open and close its mouth. According to a report in the New York Times, he hopes to integrate the dolls with mobile apps so that they can act as virtual assistants.
Virtual reality headsets could also be used separately or along- side the physical dolls. The dolls will also build on the Real Doll creation by adding what McMullen calls a “customisable programming of personality”.
“The hope is to create something that will actually arouse someone on an emotional, intellectual level, beyond the physical,” he said.
In the video by the New York Times, one of the dolls describes herself as “a prototype of a very exciting new form of adult companionship”. – Daily Mail
Computers will have developed “common sense” within a decade and we could be counting them among our friends not long afterwards, one of the world’s leading artificial intelligence scientists has predicted.
Prof Geoff Hinton, hired by Google two years ago to help develop intelligent operating systems, said that the company is on the brink of developing algorithms with the capacity for logic, natural conversation and even flirtation.
The researcher told the Guardian that Google is working on a new type of algorithm designed to encode thoughts as sequences of numbers – something he described as “thought vectors”.
Although the work is at an early stage, he said there is a plausible path from the current software to a more sophisticated version that would have something approaching human-like capacity for reasoning and logic. “Basically, they’ll have common sense.”
The idea that thoughts can be captured and distilled down to cold sequences of digits is controversial, Hinton said. “There’ll be a lot of people who argue against it, who say you can’t capture a thought like that,” he added. “But there’s no reason why not. I think you can capture a thought by a vector.”
Hinton, who is due to give a talk at the Royal Society in London today, believes that the “thought vector” approach will help to crack two of the central challenges in artificial intelligence (AI): mastering natural, conversational language, and the ability to make leaps of logic.
He painted a picture of the near-future in which people will chat with their computers for fun – reminiscent of the film, Her, in which Joaquin Phoenix falls in love with his intelligent operating system.
“It’s not that far-fetched,” Hinton said. “I don’t see why it shouldn’t be like a friend. I don’t see why you shouldn’t grow quite attached to them.”
Richard Socher, an AI scientist at Stanford University, recently developed a program called NaSent that he taught to recognise human sentiment by training it on 12,000 sentences taken from the film review website Rotten Tomatoes.
Part of the initial motivation for developing “thought vectors” was to improve translation software, such as Google Translate, which currently uses dictionaries to translate individual words and searches through previously translated documents to find typical translations for phrases. Although these methods often provide the rough meaning, they are also prone to delivering nonsense and dubious grammar.
Thought vectors, Hinton explained, work at a higher level by extracting something closer to actual meaning.
The technique works by ascribing each word a set of numbers (or vector) that define its position in a theoretical “meaning space” or cloud. A sentence can be looked at as a path between these words, which can in turn be distilled down to its own set of numbers, or thought vector. The “thought” serves as the bridge between the two languages because it can be transferred into, say, the French version of meaning space and decoded back into a new path between words.
The key is working out which numbers to assign each word in a language – this is where deep learning comes
in. Initially the positions of words are ordered at random and the translation algorithm begins training on a dataset of translated sentences.
At first the translations it produces are nonsense, but a feedback loop provides an error signal that allows the position of each word to be refined until eventually the position of words in the cloud captures the way humans use them – in effect a map of their meanings.
Hinton said the idea language can be deconstructed with almost mathematical precision is surprising, but true. “If you take the vector for Paris and subtract the vector for France and add Italy, you get Rome. It’s quite remarkable.”
Dr Hermann Hauser, a Cambridge computer scientist and entrepreneur, said that Hinton and others could be on the way to solving what programmers call the “genie problem”.
“With machines at the moment, you get exactly what you wished for,” Hauser said. “The problem is we’re not very good at wishing for the right thing.
“Hinton is our number one guru in the world on this at the moment,” he added.
Some aspects of communication are likely to prove more challenging, Hinton predicted. “Irony is going to be hard to get,” he said. “You have to be master of the literal first. But then, Americans don’t get irony either. Computers are going to reach the level of Americans before Brits.” A flirtatious program would probably be quite simple to create, however.
Many of the recent advances in AI have sprung from the field of deep learning, which Hinton has been working on since the 1980s. At its core is the idea that computer programs learn how to carry out tasks by training on huge datasets, rather than being taught a set of inflexible rules.
With the advent of huge datasets and powerful processors, the approach pioneered by Hinton decades ago has come into the ascendency and underpins the work of Google’s artificial intelligence arm, DeepMind, and similar programs of research at Facebook and Microsoft.
Hinton played down concerns about the dangers of AI raised by those such as the American entrepreneur Elon Musk, who has described the technologies under development as humanity’s greatest existential threat.
“I’m more scared about the things that have already happened,” said Hinton. “The NSA is already bugging everything that everybody does. Each time there’s a new revelation from Snowden, you realise the extent of it.”
“I am scared that if you make the technology work better, you help the NSA misuse it more,” he added. “I’d be more worried about that than about autonomous killer robots.”
Can robots make good Christians? As computer science races ahead, at least one forward-looking Florida pastor sees a future for the faith in whatever passes for a soul in robots, androids, cyborgs and other forms of artificial intelligence. No, I’m not making this up. When the Rev. Christopher Benek, an associate pastor of the First Presbyterian Church of Fort Lauderdale, talks about artificial intelligence, or “AI,” he wrote in a recent online essay, “I am not talking about iPhone’s Siri, a Roomba vacuum or one of those toasters that can make perfectly timed toast with a likeness of Jesus on it. ... I am talking about an autonomous creature that has self-awareness.”
When something not only can think, reason, plan, learn, communicate and perceive things, but also “feel love, sadness, compassion, joy, affection and a multitude of emotions,” he wrote, then it is not a great leap to think that “an AI that is very much like us but exponentially more intelligent (could) participate in Christ’s redemptive purposes in the world” and “help to make the world a better place.”
I see his point, although they also could make the world a worse place. Imagine, for example, robots of different denominations getting into a dispute over who has the best lock on eternal life after their lease on this life burns out — if it ever does.
Yet, at a time when much of the religious and political world seems to be at war with science, Benek has gained international attention with his visionary ideas about how ethics and morality can survive in our rapidly changing techno-future.
Ever since IBM’s Watson computer beat two former winners on “Jeopardy!” in 2011, interest in artificial intelligence seems to have accelerated, along with anxieties about what it means for the future of us mere humans.
Best-selling author Ray Kurzweil, a director of engineering at Google, has become the most widely known prophet of “singularity,” the widely theorized time, perhaps as soon as 20 or 30 years from now, when computers will be as smart as humans — and proceed immediately to becoming much smarter than humans.
The chilling possibility that, like Bender, the roguish robot on “Futurama,” future AIs might want to do without us “meatbag” humans has caused widespread android anxiety. In January, the famous physicist Stephen Hawking and adventurous SpaceX CEO Elon Musk pledged to do all they can to make sure that artificial intelligence will benefit humankind and not destroy our species. Good luck, guys.
Meanwhile, trepidation about our robot future seems to be popping up with new vigor in popular culture, where science fiction has long been an outlet for our industrial-age anxieties.
The new movie “Ex Machina” offers Ava, a strikingly attractive female humanoid, and the haunting existential question, “Does Ava actually like you? Or is she pretending to like you?”
Only a month earlier we had “Chappie,” the story of a police droid who becomes the first robot with the ability to think and feel for himself. Adventures ensue.
Still to come: “Avengers: Age of Ultron,” in which the villainous robot taunts in the previews that, like Walt Disney’s Pinocchio, “There are no strings on me.”
And at Christmas, we are scheduled to see George Lucas’ latest “Star Wars” sequel. That means the return of star droids R2-D2 and C3PO with the sort of AI that we humans love: They don’t let their superior intelligence go to their heads — or wherever else their central processing units might be installed.
If the sci-fi world is our guide, public concern about the future power of AI looms in the background of our lives whether we want to confront it directly or not. Some sort of regulatory safeguards might well be in order, but we can hardly expect Washington lawmakers to help us get along with robots when they can hardly get along with one another.
Besides, AI is way beyond the technical know-how of a Congress that seems barely able to figure out net neutrality. They aren’t alone.
Meanwhile, research in artificial intelligence and our uncertain robot future forges ahead. Benek’s ideas about bringing salvation to robots doesn’t sound so nutty after all. He actually raises an important question: If your supercomputer loses its moral or ethical way, who’s going to tell it?
When Clark State Community College President Jo Alice Blondin first came to Ohio nearly two years ago, she knew using drones with its agriculture program “was a real opportunity.”
Clark State isn’t the first community college to venture into using unmanned aerial vehicles, also known as unmanned aerial systems and commonly referenced as drones. Sinclair Community College in Dayton first looked into using drones during a 2008 trade mission trip to Israel, and a handful of other U.S. community colleges have developed some type of drone program.
But earlier this month Clark State became the latest institution of higher education to receive a certificate of authorization to fly drones over fields near the Springfield-Beckley Municipal Airport. These drones will collect data for students in the school’s two-year precision ag program, which began this past August.
“It gives our students real-time data that they can analyze and they can help real farmers with,” said Blondin, who spoke with this newspaper in Washington, D.C., as a guest of Speaker of the House John Boehner for this past Tuesday’s State of the Union address. “And with one in seven jobs in Ohio being related to agriculture, and within our region there are nearly 1,200 farms, this is just a great opportunity to test their skills.”
The hope is to acquire additional certificates to fly over more local farms and collect more data for the farming industry.
“Industry will develop around how the farmer uses (the data),” Blondin said. “For example, he sees if there are low levels, or various levels of chemicals, and he needs to provide chemicals in this field — and I’m talking down to the millimeter now, so you’re not wasting.
“You’re actually saving quite a bit of money and time by using the data by targeting the real problems that are in your field.”
The earliest drone data will be used in classes would be this May or next January, said Blondin, whose program is receiving support from Springfield-based SelectTech GeoSpatial. But those who entered the associate degree program this past August will be able to graduate at the earliest in May 2016.
U.S. Sen. Rob Portman, R-Ohio, said he has “worked extensively” to strengthen unique drone ag capabilities and increase Ohio’s leadership in defense and aerospace.
“I am committed to advancing our state’s leadership role in unmanned systems,” said Portman. “Ohioans have a unique ability to develop and build cutting-edge technologies and aerospace equipment with work done at our academic institutions like Clark State, the Air Force Research Lab at Wright-Patterson, NASA Glenn Research Center in Cleveland and industry partners.”
U.S. Sen. Sherrod Brown, D-Ohio, said the Miami Valley is a hub for drone research, training and development and “Clark State is building on that momentum by training students for the jobs of tomorrow.
“By applying UAS technologies to the agriculture industry, we help bolster Ohio’s leading industry by ensuring producers have the resources necessary to compete,” Brown said.
One chapter in the saga of Edward Snowden, the American computer professional who leaked classified information, was about how the US’ National Security Agency (NSA) was snooping on phone conversations, including those of politicians. In India, the government sought assurances from the US after revelations that the Bharatiya Janata Party was targeted by the NSA in 2010. We don’t know who is listening to our phone conversations or reading our text messages, but someone probably is.
Governments can also collect user data from other sources, including cloud storage. Additionally, websites, advertisers and spammers could be accessing your texts and browsing history. Want to stop them?
There are a few phones and apps out there that encrypt conversations. Blackphone (www.blackphone.ch) runs a customized secure version of Android—PrivatOS. The control centre lets you manage which hardware or service each app can access—perhaps you don’t want a messaging app to have access to the phone’s dialler. Silent Circle (www.silentcir cle.com), which also partnered the Blackphone product, offers a series of secure apps for Android and iOS—messaging, contacts, and encrypted calling packages. Whisper Systems (www.whisper ystems.org) has the free-todownload RedPhone and TextSecure apps for Android. It has been suggested that BlackBerry Messenger was the backbone for conversations between protesters and their local/foreign supporters during the London riots in 2011. Twitter assumed that role during the 2010 pro-democracy demonstrations known as the Arab Spring. And when the Turkish government shut down parts of the Internet during the 2013 Taksim Square protests—opposing the reconstruction of Ottoman-era military barracks as a museum-cum-shopping centre—people started using virtual private networks (VPN) to access blocked communication apps. In Hong Kong this year, the app of choice for the pro-democracy protesters was FireChat.
The “off-the-grid” feature uses various communication sensors in the phone, and can communicate with other devices in a 200ft range.
The developers, Open Garden, reported that over 100,000 users from Hong Kong signed up within 24 hours on a late September day. With the Chinese government known to turn off the Internet at the slightest pretext, this offline app worked well. As we ushered in 2014, smartphone class divisions were clear—affordable phones were intensely frustrating to use. Users would have to spend upwards of ` 30,000 for top-ofthe-line performance. But Xiaomi’s Mi3 packed in powerful hardware at a price point of around ` 15,000, and Motorola’s Moto E redefined the meaning of an Android phone under ` 10,000. They changed things.
The more fancied smartphone brands have learnt the hard way. Google’s Android One project aims to take the smartphone to the next billion users. “Terrorists want Android One smartphones more than AK-47s,” Prime Minister Narendra Modi said during a speech earlier this month in Jammu and Kashmir. Raising funds for a business no longer needs suits, golf courses, or reclusive billionaires. Now it can be democratic, and online.
Crowdfunding platforms surged into the business space. Start-ups used social media as a platform to get investors on board. For example, crowdfunding platform Kickstarter released quarterly numbers at the end of Q1 2014—$1,244,868 (around ` 79,049,118) was pledged on average each day; 4,497 projects successfully reached funding goals; and 887,848 backers joined the platform. This is just the beginning. It took them a while, but companies understood that smartphones and tablets were becoming primary sources for accessing, consuming and creating content. The PC has been left far behind.
Apple and Microsoft are gearing their office suites for phones. Evernote’s Work Chat makes formal communication crisp and breezy on a mobile device. Banks are pushing for mobile apps and online services. Mobile operators and their phone apps let users do everything from recharge to bill payment. Platforms such as Paytm have evolved to offer a variety of services—recharge, bill payment and shopping—through one interface. Soon, you will be able to ditch all devices but one—the phone. “Irrespective of what device it is, as long as you are using a Microsoft service, we are happy,” a Microsoft executive, who didn’t want to be named, told us recently. The subsequent announcements tie in well with this change in thinking.
Office 365 suite users now get unlimited OneDrive storage (earlier it was 1 TB). MS Office apps (Word, Excel and PowerPoint) are now free to download and use on Android phones and iOS. Then there is the tie-up with Dropbox, and the official extension for the Chrome Web browser that lets users edit files within the browser—you don’t need to have MS Office installed. Online storage space prices crashed in the second half of the year. The Microsoft Office 365 subscription now bundles unlimited OneDrive storage. Google is offering 100 GB space for $1.99 (around ` 125) a month. Box now offers 10 GB space with the free package. Buy a new smartphone, and chances are Google, Box or Dropbox will offer some free space. Smartwatches and fitness bands were a hot gadget category through the year. People were drawn helplessly to the concept of accessing apps, getting notifications and monitoring how many steps they had walked in a day through a sleek device on their wrist. While they are costly, Vishal Gondal’s GOQii band did things a bit differently—adding a human trainer to help you understand the data that the tracker generates, and create a fitness schedule customized to each individual. Motorola’s 360 is, so far, the best-looking smartwatch.
The year of the selfie craze
The Oxford English Dictionary’s definition of selfie is “a photograph that one has taken of oneself, typically one taken with a smartphone or webcam and uploaded to a social media website”. For some reason, this became the most exciting fad of 2014. Everyone went about clicking themselves (alone or with friends, against any backdrop possible).
Someone trying to take a selfie with a gun managed to shoot himself with both the camera and the gun. Another person got kicked in the head by the conductor of a moving train for standing too close to the tracks. There was some good stuff too: Canadian adventurer George Kourounis descended into a boiling lava lake in Vanuatu’s Ambrym volcano with a GoPro camera and clicked a selfie before heat made the camera unusable. South Korea has banned the use of unregistered selfie sticks, a popular accessory used to attach the phone to one end and hold it further away from yourself: They can apparently disrupt radio frequencies. It is official. The Nokia Lumia smartphones will now be known as Microsoft Lumia. Microsoft closed the Nokia deal earlier this year, but the rebranding happened in early December with the launch of Microsoft Lumia 535. The more affordable phones will continue to sport the Nokia branding, because the brand had a better connect with a wider potential customer demographic. Last month, Nokia announced the N1 Android tablet too—it clearly has plans beyond the Microsoft ecosystem. Same day shipping and delivery will soon be relegated to the category marked snail’s pace. Amazon is working on getting its drones into the air. The service is called Prime Air, and is currently awaiting US Federal Aviation Administration (FAA) approval.
Amazon says drones can help deliver orders to customers in 30 minutes. These drones can fly at 80.5km an hour and lift weights up to 2.3kg. Once the rules are in place, sometime in early 2015, we will see the first commercial tests. Real-world deployment is still some way away, but is inevitable.
CHANGES in technology are happening at a scale which was unimaginable before and will cause disruption in industry after industry. We are not ready for this change, and most of our leading companies won’t exist 1520 years from now. Here are five sectors to keep an eye on:
1. Manufacturing. Robotics and 3D printing have made it cheaper to manufacture in the United States and Europe than in China. Robots such as Baxter, from Rethink Robotics, and UR10, from Universal Robots, have arms, screens which show you their emotions, and sensors that detect what is happening around them.
The cost of operating these is less than the cost of human labor. We can now have robots working 24/7. These robots will become ever more sophisticated and do most human jobs. The manufacturing industry is surely going to be disrupted in a very big way.
This is good news for America, Europe and parts of Asia, because it will become a local industry. But this will be bad for the Chinese economy — which is largely dependent on manufacturing jobs.
In the next decade, robots will likely go on strike, because we won’t need them anymore. They will be replaced by 3D printers. Within 15 to 20 years, we will even be able to 3D print electronics. Imagine being able to design your own iPhone and print it at home.
2. Finance. We are already witnessing a controversy over Bitcoin. Crowdfunding is shaking up the venturecapital industry. We will soon be able to crowdfund loans for houses, cars and other goods. With cardless transactions for purchasing goods, we won’t need the types of physical banks and financial institutions we have.
3. Health care. Apple recently announced Healthkit, its platform for health information. It wants to store data from the wearable sensors that will soon be monitoring our blood pressure, blood oxygenation, heart rhythms, temperature, activity levels and other symptoms. Google, Microsoft and Samsung will surely not be left behind.
With these data, they will be able to warn us when we are about to get sick. AIbased physicians will advise us on what we need to do to get healthy.
Medicaltest data, especially in fields such as oncology, is often so complex that doctors cannot understand it. This will become even more difficult when they have genomics data to correlate.
When you combine these data with the medicalsensor data tech companies are collecting on their cloud platforms, we will have a medical revolution. We won’t need doctors for daytoday medical advice. Robotic surgeons will also do the most sophisticated surgeries.
4. Energy. Five years ago, we were worried about America run ning out of oil; today we’re talking about Saudi America, because of fracking.
And then there’s solar energy. Solar prices have dropped about 97 percent over the past 35 years, and by the end of this decade we will achieve grid parity. Grid parity means it’s cheaper to produce energy at home on your solar cells than to buy it from utilities. Move forward another 10 or 20 years, and it will cost a fraction as much to produce your own energy as to buy it from the grid.
Utility companies will be in serious trouble. If solar keeps advancing in the way it is, it will eclipse the fossilfuel industry. Solar is only one of maybe a hundred technologies that could disrupt the energy industry.
When we have unlimited energy, we can have unlimited clean water, because we can simply boil as much ocean water as we want. We can afford to grow food locally in vertical farms.
5. Communications. Note how AT&T, Verizon and Sprint have seen their landline businesses disappear. These were replaced by mobile — which is now being replaced by data. When I travel abroad, I don’t make longdistance calls any more, because I just call over Skype. Soon we will have WiFi everywhere.
In practically every industry, I see a major disruption. The vast majority of companies that are presently the leaders will likely not even exist. Executives either are not aware of the changes that are coming, are reluctant to invest the money required for them to reinvent themselves or are protecting legacy businesses. Most are focused on shortterm performance.
New trilliondollar industries will come out of nowhere and wipe out existing trilliondollar industries. This is the future we’re headed into, for better or for worse.
Tracy, Calif. — This holiday season, Amazon’s little helper is an orange, 320pound robot called Kiva.
The robots — more than 15,000 of them companywide — are part of Amazon’s high-tech effort to get orders to customers faster. By lifting shelves of Amazon products off the ground and speedily delivering them to employee stations, the robots dramatically reduce the time it takes for workers to find items and put them into boxes for shipment.
On the eve of Cyber Monday, Amazon’s year-old warehouse in Tracy, California, was buzzing with activity as the retailer prepared for one of the biggest shopping days of the year.
Kiva robots zoomed around the floor with uncanny precision, hoisting shelves containing video games, coloring books and stuffed animals. Yellow bins filled with merchandise zipped by on conveyor belts. A group of employees, some sporting red Santa hats, spent their break doing a series of arm stretches.
Since acquiring robot-maker Kiva, a Massachusetts company, for $775 million in cash in 2012, the e-commerce retailer has been increasingly implementing automation at its gargantuan fulfillment centers. Kivas, which resemble overgrown Roombas, are capable of lifting as much as 750 pounds and glide across Amazon’s warehouse floors by following rows of sensors.
Sunday was the first time Amazon publicly unveiled the Tracy warehouse, which boasts the company’s latest “eighth-gener-
ation” fulfillment center technology, including 3,000 Kivas. Ten Amazon warehouses, including two in California, are classified as eighth-generation; Amazon now has109 fulfillment centers globally.
Dave Clark, Amazon’s senior vice president of worldwide operations and customer service, said that because Kiva-equipped facilities eliminate the need for wide aisles for humans to walk down, eighth-generation centers can hold 50 percent more inventory than older warehouses. More storage capacity means a wider selection of merchandise, fewer chances of products being out of stock and more possibilities for same-day delivery, he said.
“It’s sort of a virtuous cycle,” he said during a tour of the facility. The robots, he added, have also cut processing times for orders to as little as 13 minutes from well over an hour.
The Tracy center, which is more than 1 million square feet in size and has 1,500 full-time employees, is still not at full capacity. It currently houses 21.5 million items (3.5 million unique SKUs), with plans to increase that number to as much as 27 million items next year. On a peak day — such as Cyber Monday — the warehouse ships 700,000 items.
Seattle-based Amazon has been adding new technology to many of its fulfillment centers. Some warehouses utilize RoboStow, a 6-ton robot that moves merchandise pallets as high as 24 feet directly onto Kiva robots, and “vision systems” that can receive an entire trailer of inventory in as little as 30 minutes by capturing an image of the trailer’s contents.
Workers at the Tracy facility said they enjoyed the ease of Kiva robots bringing products directly to them, though some conceded they missed walking the former maze of aisles to find products.
Clark declined to discuss the cost of each robot, or how much Amazon spent building the Tracy warehouse. But he noted, “we’re very happy with the economics.”
He said increased automation hasn’t led to reduced staffing levels at newer warehouses because the company continues to grow rapidly. “That growth is driving increased hiring. We continue to add employees, and no employee has been negatively impacted by Kiva coming on board,” he said.