The robots are on the move. Based on advancements in hardware, self learning algorithms and artificial intelligence, robotics is moving towards the centre of our technological future. Google is doing some heavy investing; acquiring over eight robotics companies—including Boston Dynamics, maker of BigDog, WildCat and a stable of other astonishing Pentagon-funded bots. Robots of varying shape and design, all controlled remotely and challenging the current limits of artificial sensing, manipulation, and agility.
To get you in the mood, here a few clips of robots build by Boston Dynamics:
Big Dog was one of the first machines they build. Powered by a go-kart engine it used 69 sensors to monitor the movement of its legs, the forces exerted on those limbs, and factors including temperature and hydraulic pressure. Using dynamic balance, it could walk across sand, snow, and even ice. Later they developed Cheetah, a robot that can run at 47 kilometers per hour on a treadmill while attached to a stabilizing bar. Check out this great piece by MIT on Boston Dynamics.
However, as is emphasized by Gill Pratt, the DARPA program manager in charge of the robotics challenge: “If you watch someone dancing or climbing or doing parkour, we are incredibly far [away from] a robot that can do that.”. But it’s not all about moving around of course. Robots are already building our cars and are inside our ATM machines. Although these are more repetitive tasks, robots will soon be able to tackle an array of more complex, varied tasks with greater degrees of autonomy and intelligence. For what the possible impact of all this might be, here’s a interesting analogy by Dmitry Grishin, founder of the consumer robotics venture firm Grishin Robotics:
Indeed, trying to predict where the robotics industry is headed feels like holding your first iPhone in 2007 and imagining how it would become part of our lives—it’s exciting to ponder what the future holds, but impossible to know. When it introduced the first iPhone, Apple had created an extraordinary piece of technology. But more important, it had produced an affordable product. We can now do the same with robots, and the possible applications are endless.
But before we move on from the best known household robot of all, the roomba, we need to realize that algorithms rely on patterns and the patterns of human life are notoriously difficult to discern. But like us humans, robots are also learning by sharing knowledge online. With the basic framework of the Internet—networked information-sharing— robots can learn from each others experiences.
Like this MIT research focused on a method for crowdsourcing the learned facts of several robots in order to achieve a collective intelligence among them. One example of this method is to send in multiple robots to investigate the same building and classify each room based on what’s in it. Each robot might have learned different things about the building, but if they’re able to constantly be comparing data, the can achieve more accurate models. Translating this to consumer service robots, this means that you can have robots communicate their learnings—navigating a supermarket to get your groceries—to each other. And as research has shown, robots can learn a lot when fed enough data.
Should we trust robots and can we handle them?
As robots insinuate themselves ever more deeply into our lives, understanding their limitations will be as crucial as knowing their capabilities. The trick to this might be to design machines that acknowledge their own weaknesses. Research has shown that we tend to trust things that are honest in showing a little uncertainty or weakness.
Law professor Ryan Calo believes that we should have new laws and new regulators who specialize in the field of expertise. Calo argues that robots aren’t now unregulated, they just fall under the purview of various agencies that lack the expertise to make sound, timely decisions, and who, fearing the unknown, often say “no” to desirable innovations as a result. Here’s the abstract of his paper that can be found here:
Two decades of analysis have produced a rich set of insights as to how the law should apply to the Internet’s peculiar characteristics. But, in the meantime, technology has not stood still. The same public and private institutions that developed the Internet, from the armed forces to search engines, have initiated a significant shift toward robotics and artificial intelligence.
This article is the first to examine what the introduction of a new, equally transformative technology means for cyberlaw (and law in general). Robotics has a different set of essential qualities than the Internet and, accordingly, will raise distinct issues of law and policy. Robotics combines, for the first time, the promiscuity of data with the capacity to do physical harm; robotic systems accomplish tasks in ways that cannot be anticipated in advance; and robots increasingly blur the line between person and instrument.
Others, like Missy Cummings (professor of engineering at Duke), say that the (US) government has virtually no experts on the inside that understand autonomous robotic systems. Here’s more on that perspective.
Are robots the future of work?
The book The Second Machine Age argues that humanity is entering a second machine age. During the first, driven by the industrial revolution, machines took over all the muscle jobs. In their place though, technology created huge numbers of jobs where you had to use your brain. But machines, in the shape of robots and computers, are about to take over most of these white collar jobs as well, with profound impacts on our society and economy.
A study from Oxford University last year found that 47% of U.S. jobs are potentially at risk, including including unsuspected ones like police officers. This graphic by Bloomberg, is a representation of that analysis (Click on the image to enlarge).
So, now what?
Has the time come to welcome our robotic overlords? Not quite yet. At present, traditional industrial robots are evolving into assistants to humans. In accordance with the vision of the Fourth Industrial Revolution, humans and intelligent machines will jointly perform production and cognitive tasks in the future. Sensors, cameras and self-learning software will be indispensable to this process. Key to this process is the idea that robots will have to adapt to humans, and not vice versa.