Instead of worrying so much about robots taking away jobs, maybe we should worry more about wages being too low for robots to even get a chance. Seasonal labor for harvesting agricultural products, particularly fruits and vegetables, is dependent on human labor from a diminishing universe of willing workers.

Robots that can supplement or replace human workers in the harvesting process are being developed and tested in startups and academia, but almost all are not yet ready for prime time.

In a NY Times article written by Neil Irwin entitled Rethinking Low Productivity, productivity growth has been on a downward path since the Financial Crisis. Irwin, who writes about economic trends, asks whether the downward trend is the cause of low growth, or the result, a troubling question in the dynamics of the agriculture industry.

“Inventors and business innovators are always developing better ways to do things, but it takes a labor shortage and high wages to coax firms to deploy the investment it takes to actually put those innovations into widespread use.”

Those two phenomena are happening today in the U.S. agricultural industry. Labor rates are rising while willing laborers are diminishing — yet farmers are not yet investing in robotics. In fact, they are accommodating to the labor crisis by planting less and changing the crops they grow to be less labor intensive.

J.W. Mason, the author of a paper by the Roosevelt Institute cited as the basis for the thesis of Irwin’s article, says:

“If the labor market tightens and wages rise, that will be the impetus to get companies to consider more big-ticket innovations that generate productivity growth so that we don’t perpetuate the present conundrum in which both arguments cannot be true:

“On Mondays and Wednesdays, economists argue that wages are low because robots are taking people’s jobs.

On Tuesdays and Thursdays, it’s that we can’t have wages rise because productivity growth is low.”

This situation cannot continue without radical changes else we will become buyers of foreign fruits and vegetables paying prices set by foreign providers and dependent on them for availability and quality.

A number of factors are causing a reset in the ag industry in addition to the declining availability of farm workers: the challenges and complexities of employing and retaining farm labor; the rising cost of farm workers; changing farmlands; climate change; the growth of indoor farming; and the broader automation of the agriculture industry. All are propelling farmers to make changes in how they farm (or change downward the product mix they farm (which is often a path toward failure)). Market challenges for the sector include unclear value propositions, limited awareness of robotic systems among growers, insufficient robotic solutions, the difficulty of matching human-like dexterity with machines, fragmented technology development, and weak support.

Tractica, in their report on agricultural robotics, forecast an optimistic resolution to this temporary conundrum in the very near term and that that shipments of agricultural robots will increase significantly in the years ahead, rising from 32,000 units in 2016 to 594,000 units annually by 2024, by which time the market is expected to reach $74 billion in annual revenue. Certainly the time is ripe and, like Mason said, “Both arguments can’t be true.”

By Jeff Morgan, Trinity College Dublin

Robots have been taking our jobs since the 1960s. So why are politicians and business leaders only now becoming so worried about robots causing mass unemployment?

It comes down to the question of what a robot really is. While science fiction has often portrayed robots as androids carrying out tasks in the much the same way as humans, the reality is that robots take much more specialised forms. Traditional 20th century robots were automated machines and robotic arms building cars in factories. Commercial 21st century robots are supermarket self-checkouts, automated guided warehouse vehicles, and even burger-flipping machines in fast-food restaurants.

Ultimately, humans haven’t become completely redundant because these robots may be very efficient but they’re also kind of dumb. They do not think, they just act, in very accurate but very limited ways. Humans are still needed to work around robots, doing the jobs the machines can’t and fixing them when they get stuck. But this is all set to change thanks to a new wave of smarter, better value machines that can adapt to multiple tasks. This change will be so significant that it will create a new industrial revolution.

Industry 4.0

This era of “Industry 4.0” is being driven by the same technological advances that enable the capabilities of the smartphones in our pockets. It is a mix of low-cost and high-power computers, high-speed communication and artificial intelligence. This will produce smarter robots with better sensing and communication abilities that can adapt to different tasks, and even coordinate their work to meet demand without the input of humans.

In the manufacturing industry, where robots have arguably made the most headway of any sector, this will mean a dramatic shift from centralised to decentralised collaborative production. Traditional robots focused on single, fixed, high-speed operations and required a highly skilled human workforce to operate and maintain them. Industry 4.0 machines are flexible, collaborative and can operate more independently, which ultimately removes the need for a highly skilled workforce.

For large-scale manufacturers, Industry 4.0 means their robots will be able to sense their environment and communicate in an industrial network that can be run and monitored remotely. Each machine will produce large amounts of data that can be collectively studied using what is known as “big data” analysis. This will help identify ways to improve operating performance and production quality across the whole plant, for example by better predicting when maintenance is needed and automatically scheduling it.

For small-to-medium manufacturing businesses, Industry 4.0 will make it cheaper and easier to use robots. It will create machines that can be reconfigured to perform multiple jobs and adjusted to work on a more diverse product range and different production volumes. This sector is already beginning to benefit from reconfigurable robots designed to collaborate with human workers and analyse their own work to look for improvements, such as BAXTER, SR-TEX and CareSelect.

While these machines are getting smarter, they are still not as smart as us. Today’s industrial artificial intelligence operates at a narrow level, which gives the appearance of human intelligence exhibited by machines, but designed by humans.

What’s coming next is known as “deep learning”. Similar to big data analysis, it involves processing large quantities of data in real time to make decisions about what is the best action to take. The difference is that the machine learns from the data so it can improve its decision making. A perfect example of deep learning was demonstrated by Google’s AlphaGo software, which taught itself to beat the world’s greatest Go players.

The turning point in applying artificial intelligence to manufacturing could come with the application of special microchips called graphical processing units (GPUs). These enable deep learning to be applied to extremely large data sets at extremely fast speeds. But there is still some way to go and big industrial companies are recruiting vast numbers of scientists to further develop the technology.

Impact on industry

As Industry 4.0 technology becomes smarter and more widely available, manufacturers of any size will be able to deploy cost-effective, multipurpose and collaborative machines as standard. This will lead to industrial growth and market competitiveness, with a greater understanding of production processes leading to new high-quality products and digital services.

Exactly what impact a smarter robotic workforce with the potential to operate on its own will have on the manufacturing industry, is still widely disputed. Artificial intelligence as we know it from science fiction is still in its infancy. It could well be the 22nd century before robots really have the potential to make human labour obsolete by developing not just deep learning but true artificial understanding that mimics human thinking.

Ideally, Industry 4.0 will enable human workers to achieve more in their jobs by removing repetitive tasks and giving them better robotic tools. In theory, this would allow us humans to focus more on business development, creativity and science, which it would be much harder for any robot to do. Technology that has made humans redundant in the past has forced us to adapt, generally with more education.

But because Industry 4.0 robots will be able to operate largely on their own, we might see much greater human redundancy from manufacturing jobs without other sectors being able to create enough new work. Then we might see more political moves to protect human labour, such as taxing robots.

Again, in an ideal scenario, humans may be able to focus on doing the things that make us human, perhaps fuelled by a basic income generated from robotic work. Ultimately, it will be up to us to define whether the robotic workforce will work for us, with us, or against us.

This article was originally published on The Conversation. Read the original article.

University students experiment with human-robot interaction and autonomous manipulation, two elements of manufacturing’s future. Nikolaus Correll, CC BY-ND

America’s manufacturing heyday is gone, and so are millions of jobs, lost to modernization. Despite what Treasury Secretary Steven Mnuchin might think, the National Bureau of Economic Research and Silicon Valley executives, among many others, know it’s already happening. And a new report from PwC estimates that 38 percent of American jobs are at “high risk” of being replaced by technology within the next 15 years. But how soon automation will replace workers is not the real problem. The real threat to American jobs will come if China does it first.

Since the year 2000, the U.S. has lost five million manufacturing jobs. An estimated 2.4 million jobs went to low-wage workers in China and elsewhere between 1999 and 2011. The remainder fell victim to gains in efficiency of production and automation, making many traditional manufacturing jobs obsolete.

Though more than a million jobs have returned since the 2008 recession, the net loss has devastated the lives of millions of people and their families. Some blame robotics, others globalization. It turns out that those forces work together, and have been equally hurtful to manufacturing jobs. The car industry, for example, imports more and more parts from abroad, while automating their assembly in the U.S.

As a robotics researcher and educator, I strongly advocate that the best way to get those jobs back is to build on our existing strengths, remaining a leader in manufacturing efficiency and doing the hard work to further improve our educational and social systems to cope with a changing workforce. Particularly when looking at what’s happening in China, it’s clear we need to maintain America’s international competitiveness, as we have done since the beginning of industrialization.

Chinese competition

In 2014, China exported more, and more valuable, products than the U.S. for the first time. Many of these were made by the low-wage laborers China has become famous for.

Yet China has also emerged as the largest growth market for robotics. Chinese companies bought more than twice as many industrial robots (68,000) in 2015 than American companies did (27,000). China’s Midea – an appliance manufacturer – just purchased the German robotic powerhouse Kuka.

China has understood that its competitive advantage of cheap labor will not last forever. Instead, labor costs will rise as its economy develops. Look at FoxConn, for example, the Taiwanese manufacturing contractor of the iPhone known for the high-pressure work environment at its plants in China. The company already uses more than 60,000 robots, and has said it wants to use as many as a million robots by 2020.

That’s a bold goal, especially given the current state of robotics. At present, robots are good only at highly repetitive tasks in structured environments. They are still far inferior to humans in simple tasks like picking items from a shelf. But FoxConn’s goal of transforming its streamlined manufacturing line is definitely achievable. Many of the tasks now done by humans thousands of times a day can be easily automated – such as applying a puddle of glue, placing double-sided tape, positioning a piece of plastic, tightening screws or loading products onto a pallet.

The lesson here is simple: Some occupations will simply disappear, like those of weavers in the textile industry displaced by the power loom. We need to embrace this disruption if we want to avoid being taken out of the game altogether. Imagine if China is able to replace our low-wage jobs with its workers, and then can automate those jobs: Work Americans now do will be done here, or anywhere – but not by humans. FoxConn is planning its first plant in the U.S.; soon, Chinese robots will be working in America.

Seeing opportunity, not loss

The good news is that while many types of jobs will cease to exist, robots will create other jobs – and not only in the industry of designing new robots.

This is already beginning to happen. In 2014, there were more than 350,000 manufacturing companies with only one employee, up 17 percent from 2004. These companies combine globalization and automation, embracing outsourcing and technological tools to make craft foods, artisanal goods and even high-tech engineered products.

Many American entrepreneurs use digitally equipped manufacturing equipment like 3-D printers, laser cutters and computer-controlled CNC mills, combined with market places to outsource small manufacturing jobs like mfg.com to run small businesses. I’m one of them, manufacturing custom robotic grippers from my basement. Automation enables these sole proprietors to create and innovate in small batches, without large costs.

Returning to manufacturing dominance

This sort of solo entrepreneurship is just getting going. Were robots more available and cheaper, people would make jewelry and leather goods at home, and even create custom-made items like clothing or sneakers, directly competing with mass-produced items from China. As with the iPhone, even seemingly complex manufacturing tasks can be automated significantly; it’s not even necessary to incorporate artificial intelligence into the process.

Three trends are emerging that, with industry buy-in and careful government support, could help revitalize the U.S. manufacturing sector.

First, robots are getting cheaper. Today’s US$100,000 industrial robotic arms are not what the future needs. Automating iPhone assembly lines will require cheap robotic arms, simple conveyor belts, 3-D-printed fixtures and software to manage the entire process. As we saw in the 3-D printing industry, the maker movement is setting the pace, creating low-cost fabrication robots. The government is involved, too: The Pentagon’s research arm, DARPA, has backed the OtherMill, a low-cost computer-controlled mill.

In addition, more people are programming robots. Getting a robot to accomplish repetitive tasks in industry – for example, using Universal Robot’s interface – is as simple as programming LEGO Mindstorms. Many people think it’s much harder than that, confusing robotic automation with artificial intelligence systems playing chess or Go. In fact, building and programming robots is very similar both physically and intellectually to doing your own plumbing, electrical wiring and car maintenance, which many Americans enjoy and are capable of learning. “Maker spaces” for learning and practicing these skills and using the necessary equipment are sprouting across the country. It is these spaces that might develop the skill sets that enable Americans to take automation into their own hands at their workplaces.

Lastly, cutting-edge research is improving the hardware needed to grasp and manipulate manufacturing components, and the software to sense and plan movements for assembling complex items. Industrial robot technology is upgradeable and new robots are designed to complement human workers, allowing industry to make gradual changes, rather than complete factory retooling.

A path forward

To fully take advantage of these trends and other developments, we need to improve connections between researchers and businesses. Government effort, in the form of the Defense Department’s new Advanced Robotics Manufacturing Institute, is already working toward this goal. Funded by US$80 million in federal dollars, the institute has drawn an additional $173 million in cash, personnel, equipment and facilities from the academic and private sectors, aiming to create half a million manufacturing jobs in the next 10 years.

Those numbers might sound high, but China is way ahead: Just two provinces, Guangdong and Zhejiang, plan to spend a combined $270 billion over the next five years to equip factories with industrial robots.

The stakes are high: If the U.S. government ignores or avoids globalization and automation, it will stifle innovation. Americans can figure out how to strengthen society while integrating robotics into the workforce, or we can leave the job to China. Should it come to that, Chinese companies will be able to export their highly efficient manufacturing and logistics operations back to the U.S., putting America’s manufacturing workforce out of business forever.

This article was originally published on The Conversation. Read the original article here: http://theconversation.com/to-really-help-us-workers-we-should-invest-in-robots-71125.

RoboJobs is a new dedicated jobs board for the global robotics community that connects both seasoned robotics experts and recent top graduates with entrepreneurs and established businesses seeking the brightest minds to fill their ranks. We’ve just launched our beta site in collaboration with Silicon Valley Robotics in an effort to connect our readers with the top jobs in robotics. Roboticists can post their resumes and view ads for free. Prospective employers can publish job postings at competitive rates, and at the same time know that the dollars they are spending will help support Robohub’s non-profit efforts to bring you the latest in robotics news. 

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Posting on the Slate blog Future Tense, James Bessen takes issue with the notion that technology causes unemployment, illustrating his point by debunking a pair of frequently cited examples, textile workers in the early nineteenth century and telephone operators during the mid-twentieth century.

In a response titled “Luddites Are Almost Always Wrong: Technology Rarely Destroys Jobs” on TechDirt’s Innovation blog, Bessen’s thesis is roundly applauded, but he is taken to task for failure to make the connection between the process which prevents net job destruction (the creation of new jobs) and reasonable access to intellectual property, currently endangered by nonpracticing patent owners (a.k.a. “patent trolls”).

This post is part of Robohub’s Jobs Focus.

We’re in the midst of National Robotics Week, and roboticists all over the US are celebrating robotics research, development and education through hundreds of events and demonstrations at local libraries, universities, Block Parties and FIRST competitions. The point of National Robotics week is to celebrate, educate and inspire a new generation to pursue careers in robotics. But another key goal of the week is to advocate.

Advocating for cash is one part of the job, because R&D requires lots of it. And if you’re going to acquire cash from granting bodies or investors, you have to convince them that the work you are doing is important, that it’s going to solve a problem, and (if you’re a start-up) that it has commercial potential. And as robotic technologies move from research into commercial viability, advocating for robotics-friendly legislation becomes just as important: if laws and regulations prevent your product from reaching the market, it doesn’t matter how much cash you have.

Nymann Teknik arm, from Universal Robots.

So what does advocacy have to do with jobs? Plenty. The jobs issue is a visceral one. It hits us where it counts: how we earn, how we feed ourselves and our families, how we put a roof over our heads. It’s why employment is always a key issue in election politics – it’s a topic that impacts almost every voter of working age. ‘Robots and jobs’ has become a contentious issue that, like it or not, will determine the success or failure of many new robotics technologies, so it’s no great surprise that there are plenty of people who have something to say about it.

Here are the main points of view that have been entrenched and promoted:

1. Robot replace human workers, and that is a bad thing; they are a ‘disruptive force’ that will cause irrevocable harm to our entire socioeconomic system. See 60 Minutes’ Are robots hurting job growth? and CNN World’s The jobless economy, and the Economists’ Robots don’t complain or die.
2. Robots replace human workers, and that is a good thing; they will take over dull, dirty and dangerous jobs and leave us humans with more time to do interesting/productive work. See Andrew McAfee’s TED Talk, and Wired’s Better than human: Why robots will – and must – take our jobs.
3. Robots don’t steal jobs, they create them; whether through ‘re-shoring’ or through the emergence of new robotics industries, there is tremendous job growth potential for economies that support robotic technologies. See Time’s Can robots bring back manufacturing jobs to the US? and Kuka’s infographic Robots and automation bring jobs back to the US.

To help us tease out the issues we are featuring a week’s worth of coverage on the topic from top experts in the field, including fact finding, analysis and opinion. Here’s a quick teaser of what to expect over the next week or so …

A look at the numbers:

• Frank Tobe gives us a critical walk-through of IFR’s latest Metra Martech report.
• Armed with data from the recently released Economic Impact of Unmanned Aircraft Systems Integration in the US,  Chris Mailey from AUVSI suggests that a multibillion dollar market will quickly emerge to create over 100,000 jobs in the US by 2025 once current FAA restrictions to unmanned aerial systems are lifted, as they are schedule to do in 2015.
• Plus, a fact-finding post with all the latest economic reports on the robotics industry.

A look at influencing factors:

• John Dulchinos, Executive Board Member of the International Federation of Robotics, takes us through some of the latest jobs stats and suggest that robotics is eliminating the advantage and influence that low-cost labour has had on manufacturing.
• Rich Mahoney, Director of Robotics at SRI, says that it’s too early to make any grand predictions about how robots will affect the jobs economy in the future, but that the success of robotics companies’ management teams will surely play a critical role.
• In response to the Robotics by Invitation question “Do robots kill jobs?“, Raffaello D’Andrea, co-founder of Kiva Systems, talks about how low interest rates are fuelling the jobs debate; and Mark Tilden argues that robots are just scapegoats, and that corporate ethics are to be blamed for poor employment numbers.
• Regular Robohub contributor and agribot expert John Payne echoes the many voices in the agricultural sector, which point out that agricultural robots will be replacing job vacancies, not people.

Outlook:

• Martin Ford, author of The Lights in the Tunnel: Automation, Accelerating Technology and the Economy of the Future argues that as robots and other forms of automation progress, machines will take over an ever-increasing fraction of those routine jobs and significant unemployment will become inevitable.
• Federico Pistono, author of “Robots Will Steal Your Job, But That’s OK: How to Survive the Economic Collapse and Be Happy” suggests that technological unemployment is already a reality today and argues that we should use this opportunity to rethink what the purpose of society should be.
• Matt Beane, from MIT’s Sloan School of Management asks if we are on the cusp of a robotics revolution or whether robots are distracting us from the forces profoundly affecting our economy. Matt Beane’s short answer: yes.

And don’t forget:

• Coverage of this week’s Silicon Valley Robot Block Party and Xconomy Forum: Robots Remake the Workplace by Robohub correspondents Frank Tobe and Andra Keay.
• Live streaming of Stanford’s We Robot conference on robotics and the law.
• Sabine Hauert‘s report on Jobs for Roboticists.
• Frank Tobe’s post from January 2013 on how the definition of robots affects how they are perceived in the jobs debate
• And on a lighter note, Jim Haas‘ Nate the Robot – the Dilbert of robotics. Look for Nate in the sidebar!

Managing the ‘issue’ of robots and jobs is important to the success of businesses, research institutions and politicians alike, whether they are ‘for’ robots or ‘against’, so there is no doubt that you will continue to see headlines about robots and jobs for the foreseeable future, both in the mainstream media and here on Robohub. We hope you enjoy this focus series … feedback is welcome, so send us your comments!

See all the posts in Robohub’s Jobs Focus.

This post is part of Robohub’s Jobs Focus.

“People hate me because they say robots steal jobs.”
“What jobs?”
“Low paid, extremely dangerous, repetitive, physically demanding…”
*boggle*
“I know, right?”

See all the posts in Robohub’s Jobs Focus.

This post is part of Robohub’s Jobs Focus.

A strong argument can be made that a very large percentage of jobs are, on some level, essentially routine and repetitive in nature. In other words, the job can be broken down into a discrete set of tasks that tend to get repeated on a regular basis and can be predicated based on historical data. It seems likely that, as both computer hardware and software continue to progress, a large fraction of these job types are ultimately going to be susceptible to robotic or software automation, and in particular to machine learning technology.

Recent innovations like IBM’s Watson computer suggest that machine learning algorithms may soon be able to take on a number of cognitive tasks. As technology accelerates, I think there is little doubt that these systems will begin to match or exceed the capability of human workers in many routine job categories — and this includes a lot of workers with college degrees or other significant training.

As robots and smart algorithms increasingly take on the more routine, predictable jobs, this will leave much of our workforce with an unprecedented challenge. Historically, most workers have been able to move from routine occupations in one area to similarly routine jobs in a new emerging area, perhaps acquiring some new skills as part of the transition. However, as technology impacts virtually all routine work across the board, workers will have to find work in areas that are genuinely non-routine or creative in order to remain relevant. There are good reasons to be concerned that a significant fraction of our workforce will have great difficulty with such a transition: after all, if we assume a normal distribution or capability, then by definition, 50% of workers are average or below average.

None of this is intended to argue against continuing progress in areas like robotics, big data and AI. However, as these technologies continue to accelerate, the impact on employment and income inequality is likely to become more and more visible to the general public. Ultimately, I think that in order to solve the distributional problems that will be created by automation — and to ensure continued, broad-based prosperity — we will need to reform our economic systems. If we fail to do this, it seems very likely that a public backlash against automation technologies, as well as significant social and economic upheaval could well result.

This post is part of Robohub’s Jobs Focus.

Recently, many of these explanations, predictions and proposed solutions focus on robots. Robots seem to have found their way into an increasing number of titles, photos and articles about our economic future, whether from economists like Paul Krugman, journalists like John Markoff, roboticists like Rod Brooks or futurists like Ray Kurzweil.

Disagreement about robots and our future is flying fast and furious. Are we on the edge of a robotics revolution, analogous to the PC revolution of the 70s? If so, will we see similar patterns of economic activity – automation of a great deal of work, death of some occupations, birth of others? Are current-day robots a harbinger of times to come, just as canaries were for coal miners until the early 20^th century? Or are we experiencing a “robot revolution” in name only? Are cutting-edge robots like Baxter a red herring – do they misdirect our hopes and fears about our future?

If you’re looking for the punch line of this piece, here it is: we have evidence that robots are both red herrings and canaries in a coalmine. We are arguing about this issue as if it’s either/or when both views can be usefully seen as true.

Robots as Red Herrings
Imagine a robot that costs almost nothing to produce (as in less than a cent), costs almost nothing to ship, that runs on almost no power, that could be customized for a wide variety of applications and that could execute billions of tasks every second. Obviously this robot would be software. We’d be excused for assuming it would sell pretty well, and for assuming software might play some role in the economy.

Because it already has. According to the BES, there was an installed base of 1.85 trillion dollars of software and related hardware in the US in 2011, which has grown an average of about 3.3%/year since 2004. Though there is ongoing disagreement about the role of IT in our economy, recent analysis lends strong support for the view that IT is mostly being used as a substitute for human labor on routine, non-physical tasks. Many economists point to IT as a key contributor to the “hollowing out” of the global economy – otherwise known as the “death of the middle class”. As Erik Brynjolfsson of MIT is fond of saying, it’s hard for a tax preparer to compete with TurboTax – especially when this software is actually free these days to new users, and integrates seamlessly with Mint.com, a free, online tool for personal finance.

From this angle, software has had a truly massive impact on the kinds of tasks humans can do and get paid for. On a global scale, we’re talking hundreds of millions of jobs and livelihoods, broad changes to the structure of work and occupations, and dramatic shifts in the way we encounter each other and the working world.

Yet when we talk about change associated with technology in the economy these days, we talk mostly about robots.

This seems a little strange, given that the IFR (a global authority on the robotics industry) estimates that there is an installed base of just 9 billion dollars of robotic systems in US and Canadian industry put together. That’s less than half a percent of the installed IT base. While recent growth numbers are large (38% in 2011), the IFR projects the global annual growth rate at about 6% through 2015. At quadruple this rate, it would take robotics 23 years to catch up with IT, assuming IT stood still. So if we want to investigate the technologically-related automation of jobs, work and the economy, maybe we should be focusing more (maybe a lot more) on Watson, Google and Robo-Traders on Wall Street. Maybe robotics is a red herring.

Robots as Canaries
But then again, maybe not. Many roboticists, economists, and journalists are claiming that we are on the cusp of a period of discontinuous progress in robotics technology. If this is true, then maybe we’ll soon see exponential – not linear – growth rates in robotics. Then again, maybe we already have.

How could we tell? One promising first step is to judge robotics based on performance per unit of time. While Moore’s law predicts the number of transistors on a chip as a function of the passage of time, its progress is almost perfectly correlated with performance-oriented metrics in other domains, such as processing speed, memory capacity and sensor quality. From this perspective, it is reasonable to assume that robots’ performance of basic tasks would correlate well with progress in underlying technical domains. If it hasn’t, then a revolution seems less likely.

Given that we all seem concerned with robots that may replace non-routine physical labor, Rod Brooks has suggested in a few talks that we should look at performance in autonomous robotic navigation as an indicator of progress. This does seem like a reasonable proxy: autonomous navigation requires a system to sense its environment, plan next steps and enact those steps through actuated movement, more or less without human input. The greater the performance of such a system, the more sophisticated each of the component technologies (sensors, AI and actuation). These requirements and related technological progress seem likely to generalize to other physical tasks in a dynamic environment.

So where do we stand on this front? Hans Moravec’s (Stanford) lab robot could navigate 20 meters in six hours in 1979. Ian Horswell’s (MIT) robot could navigate 2000 meters in six hours in 1992. The best car in the second (2005) Darpa Grand Challenge navigated 212 kilometers in 6.52 hours (about 194,500 meters in six hours). The winning car in the 2007 Darpa Urban Challenge navigated 96 kilometers of dynamic urban environment in 4 hours and 10 minutes (about 23,000 meters in six hours). By 2010, the Google Car was capable of autonomous navigation for six (or more) hours straight in normal traffic. If we presume it obeyed the speed limit and did this driving on a highway (at 65 mph), the car could travel 390 miles during that time (or roughly 627,000 meters). Here is a plot of these achievements (on a logarithmic scale) over time:

If anything, this approach may underestimate the rate of change; the task has gotten more difficult. The 2005 Darpa Grand Challenge cars would have made much better time if they had to traverse 212km in a straight line, indoors, with no obstacles. Incidentally, the cost of just the camera on Moravec’s 1979 robot was $159,000 (in 2012 dollars); a far superior camera can be purchased today for less than $1.

Put together, this indicates the cost of robotic systems is dropping rapidly just as performance is increasing exponentially. While it is all the rage to predict the future based on exponential technological trends, this “back of the envelope” exploration should put us on notice: stories of linear progress in robotics should be justified, not taken for granted.

Robots as Red Herrings and Canaries in a Coal Mine
Work is scarce and wealth is increasingly in the hands of a few. This leads many of us to be scared, angry and curious about the future. Robots are a lightning rod for these emotions and questions – they move with apparent intention, they do tasks that sit at the core of what most of us define as “good, honest work”, and they’re rapidly getting cheaper and more capable. If we want to point a finger at technologies that are “responsible” for the inequities and challenges in our economy, however, it seems pretty clear that we should be pointing to IT. The vast majority of tasks that are being handed off to technology are still going to software and computers, and the evidence indicates that this will be true in the short and medium term. Robots are a red herring from this perspective.

But from another perspective, they are also canaries. We have seen apparently exponential progress in robotic capacity over the last 30 years. How many of us think that, in a hundred years, we won’t have highly autonomous, mobile, dexterous robots that can adapt to a wide range of tasks in a wide range of environments – for less than the cost of human labor? Are we willing to bet our national education and job training investments on the assumption that this is a hundred years away? Fifty years? Thirty? If this transition is going to happen on a mass scale, at best we probably have seventy years to prepare for it. That’s only two generations away, and that means we should be planning for it now.

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Before responding to that question, let me turn it around. Why, given that there are no laws preventing them from doing so, are so few people in the ‘modern world’ engaged in by-hand cultivation, or even cultivation using draft animals?

One big reason is that land isn’t free, and the cheapest land is located far from city markets, as well as from the amenities cities provide. And, even if there were still land for homesteading, there’s the matter of potable water, housing, tools, seed, food enough to last until the first crops come in, canning supplies and equipment if part of that crop has to last through the winter, and some means of transporting a portion of the crop to market. If you’re growing one of the local commodity crops, you can almost leave off the transportation part, since there will already be a network in place for that purpose, and you’ll only need to move your crop as far as the nearest node in that network, but you’ll also be competing with other producers benefitting from economies of scale for the thin margins they’re accustomed to. If, on the other hand, you’re growing watermelons in wheat country, you’ll have to provide your own transportation.

Okay, back to the original question, why robots, given that there are people in need of work?

People are slow. One person can just about manage five acres by hand, if they work at it full time. Depending on the climate and what’s being grown, that might be enough to feed as many as twenty, or at least provide them with vegetables, which isn’t such a bad consumer/producer ratio, but it’s far lower than the average for conventional agriculture. One person using the sort of equipment you see everywhere in rural America, can work between 600 and 1,000 acres, planted to crops like wheat or soybeans that lend themselves to bulk handling.

People are expensive. Who’s going to pay the unemployed to produce by hand a small fraction of what is already being produced far more cheaply by means of machines under direct human control? Even if the current cost of production were to rise several fold, current practice would still result in cheaper food than what workers earning minimum wage could produce by hand. Granted that the economics are better for crops that don’t lend themselves to linear mechanization (performing field operations while/by moving over the surface), and that a diet limited to those that do would be significantly impoverished.

People are lazy have other priorities. And well they should! (Personally, I’m a fan of Bucky Fuller’s idea of paying people, modestly, to go to school. They benefit by becoming more marketable, and society benefits through an increase in the skill-level of its workforce.)

People would [still] be needed. A conversion from tractors to small, autonomous machines [applying horticultural techniques] almost certainly would not result in a net displacement of workers, rather the reverse, and you’re more likely to find enough people (4..8, at a guess) willing to maintain (and augment*) the machines that manage a square mile of land than you are to find enough people (about 100) willing to work that land by hand.

*(Especially at first, it’s unlikely that robots would be able to do everything that needed to be done, and the gaps in their capabilities would have to be supplied otherwise, most likely by people.)

Reposted from Cultibotics.