At the 2011 Google I/O developer's conference, Google announced a new initiative called "cloud robotics" in conjunction with robot manufacturer Willow Garage. Google has developed an open source (free) operating system for robots, with the unsurprising name "ROS" -- or Robot Operating System. In other words, Google is trying to create the MS-DOS (or MS Windows) of robotics.
With ROS, software developers will be able to write code in the Java programming language and control robots in a standardized way -- much in the same way that programmers writing applications for Windows or the Mac can access and control computer hardware.
Google's approach also offers compatibility with Android. Robots will be able to take advantage of the "cloud-based" (in other words, online) features used in Android phones, as well as new cloud-based capabilities specifically for robots. In essence this means that much of the intelligence that powers the robots of the future may reside on huge server farms, rather than in the robot itself. While that may sound a little "Skynet-esque," it's a strategy that could offer huge benefits for building advanced robots.
One of the most important cloud-based robotic capabilities is certain to be object recognition. In my book, The Lights in the Tunnel, I have a section where I talk about the difficulty of building a general-purpose housekeeping robot largely because of the object recognition challenge:
A housekeeping robot would need to be able to recognize hundreds or even thousands of objects that belong in the average home and know where they belong. In addition, it would need to figure out what to do with an almost infinite variety of new objects that might be brought in from outside.
Designing computer software capable of recognizing objects in a very complex and variable field of view and then controlling a robot arm to correctly manipulate those objects is extraordinarily difficult. The task is made even more challenging by the fact that the objects could be in many possible orientations or configurations. Consider the simple case of a pair of sunglasses sitting on a table. The sunglasses might be closed with the lenses facing down, or with the lenses up. Or perhaps the glasses are open with the lenses oriented vertically. Or maybe one side of the glasses is open and the other closed. And, of course, the glasses could be rotated in any direction. And perhaps they are touching or somehow entangled with other objects.
Building and programming a robot that is able to recognize the sunglasses in any possible configuration and then pick them up, fold them and put them back in their case is so difficult that we can probably conclude that the housekeeper's job is relatively safe for the time being.
Cloud robotics is likely to be a powerful tool in ultimately solving that challenge. Android phones already have a feature called "Google Goggles" that allows users to take photos of an object and then have the system identify it. As this feature gets better and faster, it's easy to see how it could have a dramatic impact on advances in robotics. A robot in your home or in a commercial setting could take advantage of a database comprising the visual information entered by tens of millions of mobile device users all over the world. That will go a long way toward ultimately making object recognition and manipulation practical and affordable.
In general, there are some important advantages to the cloud-based approach:
The last point cannot be emphasized enough. I think that many economists and others who dismiss the potential for robots and automation to dramatically impact the job market have not fully assimilated the implications of machine learning. Human workers need to be trained individually, and that is a very expensive, time-consuming and error-prone process. Machines are different: train just one and all the others acquire the knowledge. And as each machine improves, all the others benefit immediately.
Imagine that a company like FedEx or UPS could train ONE worker and then have its entire workforce instantly acquire those skills with perfect proficiency and consistency. That is the promise of machine learning when "workers" are no longer human. And, of course, machine learning will not be limited to just robots performing manipulative tasks -- software applications employed in knowledge-based tasks are also going to get much smarter.
The bottom line is that nearly any type of work that is on some level routine in nature -- regardless of the skill level or educational requirements -- is likely to someday be impacted by these technologies. The only real question is how soon it will happen.
Martin Ford is the author of The Lights in the Tunnel: Automation, Accelerating Technology and the Economy of the Future (available from Amazon or as a PDF download). The book argues that accelerating information technology, and in particular robotics and artificial intelligence, is likely to have a disruptive impact on the future job market and economy. He also has a blog at econfuture.wordpress.com.
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A job is a focus on what is done to earn a living but it is also a placement within a set of social relationships that share resources and rewards. When robots do more of the former, rewards will still be determined by the latter. Don't fear the machine; fear the people who won't share.
It seems to me that overcommitment to work is the only way to make a living these days, and as robots take away more of the simple tasks humans can do less well than robots, the social relationships which those of us who are making a living need to survive will depend on those with all the wealth sharing, or having it taken from them. Do you see it that way? Is that what you are saying?
People, singly or grouped, can become wealthy through use of the resources. Wealth is a positive thing. When distributed fairly, it creates societies like Canada where hunger, shelter, and medical care are far beyond adequate.Especially individuals who through their own efforts create value deserve the rewards they get. (For example, I find Bill Gates to be a very deserving rich man.)However. most wealth is used to buy up more resources without any additional effort. That seems inefficient use of eminent domain. Returning excess resources to the general population "raises all boats", overtime, while allowing it to pile up in the hands of a few will sink all but a few in the end. Societies that are structure to share the rewards earned from community resources will grow economically for rich and poor alike though inequally.
If I take more of the resources then I can possibly use, you may be left with more work just to survive. That seems to be happening now.
Look at many types of farming, fishing, mining, lumbering, manufacturing.
The bulk work is accomplished by machine and if the machines are smart and independent enough, we call them robots.
War is now beginning to be outsourced to machines via drones and other semi or autonomous war machines.
As traditional costs rise various Medical and Doctor services will also be automated, even surgery.
Even most banking and wealth management functions (at least the legal ones) are or can be largely performed by automation.
We are reaching the point where there will be few high value Necessary activities for people to do.
We all really have to rethink the way we approach education, the economy, work and life.
If the increasing proportion of of jobs continues to shift to the cheapest possible labor or automation, what are most people supposed to do to earn a reasonable living? Or can they?
Human labor will be one of the biggest issues to Globally resolve if we survive the others threats of : large scale war, increasing scarcity of resources, climate change and environmental decay.
These all require majority Global action to address.
Meanwhile our corporate and ideologically directed "leaders" and "media" bombard us all with largely irrelevant or harmful crap, instead of dealing with the very real and pressing problems humanity faces.
Maybe that's a one sided view. Maybe it doesn't really work. But I share your concerns and am looking for answers.
Willow Garage, not Google, developed ROS (and PCL and maintains OpenCV) http://www.willowgarage.com/pages/software/overview
Google has a small group experimenting with cloud robotics.
Before all this, we need to have effective robots. Even the "jobs" part of our premise is completely wrong. Former blind-dumb manufacturing displaced human jobs (even is it created others in supporting industry) because the robots were blind and dumb and so too dangerous for people to be around. The next wave of robotics is smart+sensing and so able to work with humans around. These will likely increase employment since manufactures want the people for flexibility and the robots for repeatability.
In any case, not doing this means losing more manufacturing to the lowest cost labor overseas. Doing this brings manufacturing and it's associated innovation and support industries back here. Definitely a net gain in employment.
Please try again with a few facts.
I don't see robots as a solution to outsourcing. Rather, I see them as an additional strain on a poorly educated public looking to make a living.
So, students of today should be learning how to program and learning engineering rather than heading into the direction of easily automated physical labor.
Besides, I have two for this energy-intensive vision of the future: peak-oil.
http://econfuture.wordpress.com/2012/01/02/googles-cloud-robotics-strategy-could-accelerate-progress-toward-truly-advanced-robots/
Not sure if HuffPost will update this version as editing is locked once published...
What if we make 50% unemployment a GOAL for 2032 - 20 years from now, instead of trying to fight this trend, or worse, trying to ignore it? Even thinking it requires a quantum leap in many concepts, from work ethic concepts to income distribution concepts. But, we're human, we can do that. We've done it before.
In the late '60s the Longshoremen looked forward and saw millions of stevedore jobs being eliminated by containerized mechanization. They negotiated a contract where replaced journeymen went home, with full pay for life, if they were replaced. With that backdrop Nixon proposed a negative income tax guaranteeing a minimum income.Congress instead gave him the earned-income credit.
Today, 46% of households own stock, many in the companies they work for. There are numerous ways to spread the wealth created from "increases in productivity". And finding useful ones to use is probably not an option.