Tag Archives: experience

#432891 This Week’s Awesome Stories From ...

Elon Musk Presents His Tunnel Vision to the People of LA
Jack Stewart and Aarian Marshall | Wired
“Now, Musk wants to build this new, 2.1-mile tunnel, near LA’s Sepulveda pass. It’s all part of his broader vision of a sprawling network that could take riders from Sherman Oaks in the north to Long Beach Airport in the south, Santa Monica in the west to Dodger Stadium in the east—without all that troublesome traffic.”

Feel What This Robot Feels Through Tactile Expressions
Evan Ackerman | IEEE Spectrum
“Guy Hoffman’s Human-Robot Collaboration & Companionship (HRC2) Lab at Cornell University is working on a new robot that’s designed to investigate this concept of textural communication, which really hasn’t been explored in robotics all that much. The robot uses a pneumatically powered elastomer skin that can be dynamically textured with either goosebumps or spikes, which should help it communicate more effectively, especially if what it’s trying to communicate is, ‘Don’t touch me!’”

In Virtual Reality, How Much Body Do You Need?
Steph Yin | The New York Times
“In a paper published Tuesday in Scientific Reports, they showed that animating virtual hands and feet alone is enough to make people feel their sense of body drift toward an invisible avatar. Their work fits into a corpus of research on illusory body ownership, which has challenged understandings of perception and contributed to therapies like treating pain for amputees who experience phantom limb.”

How Graphene and Gold Could Help Us Test Drugs and Monitor Cancer
Angela Chen | The Verge
“In today’s study, scientists learned to precisely control the amount of electricity graphene generates by changing how much light they shine on the material. When they grew heart cells on the graphene, they could manipulate the cells too, says study co-author Alex Savtchenko, a physicist at the University of California, San Diego. They could make it beat 1.5 times faster, three times faster, 10 times faster, or whatever they needed.”

Robotic Noses Could Be the Future of Disaster Rescue—If They Can Outsniff Search Dogs
Eleanor Cummins | Popular Science
“While canine units are a tried and fairly true method for identifying people trapped in the wreckage of a disaster, analytical chemists have for years been working in the lab to create a robotic alternative. A synthetic sniffer, they argue, could potentially prove to be just as or even more reliable than a dog, more resilient in the face of external pressures like heat and humidity, and infinitely more portable.”

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#432880 Google’s Duplex Raises the Question: ...

By now, you’ve probably seen Google’s new Duplex software, which promises to call people on your behalf to book appointments for haircuts and the like. As yet, it only exists in demo form, but already it seems like Google has made a big stride towards capturing a market that plenty of companies have had their eye on for quite some time. This software is impressive, but it raises questions.

Many of you will be familiar with the stilted, robotic conversations you can have with early chatbots that are, essentially, glorified menus. Instead of pressing 1 to confirm or 2 to re-enter, some of these bots would allow for simple commands like “Yes” or “No,” replacing the buttons with limited ability to recognize a few words. Using them was often a far more frustrating experience than attempting to use a menu—there are few things more irritating than a robot saying, “Sorry, your response was not recognized.”

Google Duplex scheduling a hair salon appointment:

Google Duplex calling a restaurant:

Even getting the response recognized is hard enough. After all, there are countless different nuances and accents to baffle voice recognition software, and endless turns of phrase that amount to saying the same thing that can confound natural language processing (NLP), especially if you like your phrasing quirky.

You may think that standard customer-service type conversations all travel the same route, using similar words and phrasing. But when there are over 80,000 ways to order coffee, and making a mistake is frowned upon, even simple tasks require high accuracy over a huge dataset.

Advances in audio processing, neural networks, and NLP, as well as raw computing power, have meant that basic recognition of what someone is trying to say is less of an issue. Soundhound’s virtual assistant prides itself on being able to process complicated requests (perhaps needlessly complicated).

The deeper issue, as with all attempts to develop conversational machines, is one of understanding context. There are so many ways a conversation can go that attempting to construct a conversation two or three layers deep quickly runs into problems. Multiply the thousands of things people might say by the thousands they might say next, and the combinatorics of the challenge runs away from most chatbots, leaving them as either glorified menus, gimmicks, or rather bizarre to talk to.

Yet Google, who surely remembers from Glass the risk of premature debuts for technology, especially the kind that ask you to rethink how you interact with or trust in software, must have faith in Duplex to show it on the world stage. We know that startups like Semantic Machines and x.ai have received serious funding to perform very similar functions, using natural-language conversations to perform computing tasks, schedule meetings, book hotels, or purchase items.

It’s no great leap to imagine Google will soon do the same, bringing us closer to a world of onboard computing, where Lens labels the world around us and their assistant arranges it for us (all the while gathering more and more data it can convert into personalized ads). The early demos showed some clever tricks for keeping the conversation within a fairly narrow realm where the AI should be comfortable and competent, and the blog post that accompanied the release shows just how much effort has gone into the technology.

Yet given the privacy and ethics funk the tech industry finds itself in, and people’s general unease about AI, the main reaction to Duplex’s impressive demo was concern. The voice sounded too natural, bringing to mind Lyrebird and their warnings of deepfakes. You might trust “Do the Right Thing” Google with this technology, but it could usher in an era when automated robo-callers are far more convincing.

A more human-like voice may sound like a perfectly innocuous improvement, but the fact that the assistant interjects naturalistic “umm” and “mm-hm” responses to more perfectly mimic a human rubbed a lot of people the wrong way. This wasn’t just a voice assistant trying to sound less grinding and robotic; it was actively trying to deceive people into thinking they were talking to a human.

Google is running the risk of trying to get to conversational AI by going straight through the uncanny valley.

“Google’s experiments do appear to have been designed to deceive,” said Dr. Thomas King of the Oxford Internet Institute’s Digital Ethics Lab, according to Techcrunch. “Their main hypothesis was ‘can you distinguish this from a real person?’ In this case it’s unclear why their hypothesis was about deception and not the user experience… there should be some kind of mechanism there to let people know what it is they are speaking to.”

From Google’s perspective, being able to say “90 percent of callers can’t tell the difference between this and a human personal assistant” is an excellent marketing ploy, even though statistics about how many interactions are successful might be more relevant.

In fact, Duplex runs contrary to pretty much every major recommendation about ethics for the use of robotics or artificial intelligence, not to mention certain eavesdropping laws. Transparency is key to holding machines (and the people who design them) accountable, especially when it comes to decision-making.

Then there are the more subtle social issues. One prominent effect social media has had is to allow people to silo themselves; in echo chambers of like-minded individuals, it’s hard to see how other opinions exist. Technology exacerbates this by removing the evolutionary cues that go along with face-to-face interaction. Confronted with a pair of human eyes, people are more generous. Confronted with a Twitter avatar or a Facebook interface, people hurl abuse and criticism they’d never dream of using in a public setting.

Now that we can use technology to interact with ever fewer people, will it change us? Is it fair to offload the burden of dealing with a robot onto the poor human at the other end of the line, who might have to deal with dozens of such calls a day? Google has said that if the AI is in trouble, it will put you through to a human, which might help save receptionists from the hell of trying to explain a concept to dozens of dumbfounded AI assistants all day. But there’s always the risk that failures will be blamed on the person and not the machine.

As AI advances, could we end up treating the dwindling number of people in these “customer-facing” roles as the buggiest part of a fully automatic service? Will people start accusing each other of being robots on the phone, as well as on Twitter?

Google has provided plenty of reassurances about how the system will be used. They have said they will ensure that the system is identified, and it’s hardly difficult to resolve this problem; a slight change in the script from their demo would do it. For now, consumers will likely appreciate moves that make it clear whether the “intelligent agents” that make major decisions for us, that we interact with daily, and that hide behind social media avatars or phone numbers are real or artificial.

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#432640 Artificial Intelligence And Education

Today, we frequently hear the term artificial intelligence. Furthermore, we experience its benefits in our everyday life, but how does it influence the educational system? Can AI improve its quality and boost the productivity of college or university students? Several years ago, its impact wasn’t as noticeable as it is today. Nevertheless, it shows a …

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#432563 This Week’s Awesome Stories From ...

Pedro Domingos on the Arms Race in Artificial Intelligence
Christoph Scheuermann and Bernhard Zand | Spiegel Online
“AI lowers the cost of knowledge by orders of magnitude. One good, effective machine learning system can do the work of a million people, whether it’s for commercial purposes or for cyberespionage. Imagine a country that produces a thousand times more knowledge than another. This is the challenge we are facing.”

Gene Therapy Could Free Some People From a Lifetime of Blood Transfusions
Emily Mullin | MIT Technology Review
“A one-time, experimental treatment for an inherited blood disorder has shown dramatic results in a small study. …[Lead author Alexis Thompson] says the effect on patients has been remarkable. ‘They have been tied to this ongoing medical therapy that is burdensome and expensive for their whole lives,’ she says. ‘Gene therapy has allowed people to have aspirations and really pursue them.’ ”

The Revolutionary Giant Ocean Cleanup Machine Is About to Set Sail
Adele Peters | Fast Company
“By the end of 2018, the nonprofit says it will bring back its first harvest of ocean plastic from the North Pacific Gyre, along with concrete proof that the design works. The organization expects to bring 5,000 kilograms of plastic ashore per month with its first system. With a full fleet of systems deployed, it believes that it can collect half of the plastic trash in the Great Pacific Garbage Patch—around 40,000 metric tons—within five years.”

Autonomous Boats Will Be on the Market Sooner Than Self-Driving Cars
Tracey Lindeman | Motherboard
“Some unmanned watercraft…may be at sea commercially before 2020. That’s partly because automating all ships could generate a ridiculous amount of revenue. According to the United Nations, 90 percent of the world’s trade is carried by sea and 10.3 billion tons of products were shipped in 2016.”

Style Is an Algorithm
Kyle Chayka | Racked
“Confronting the Echo Look’s opaque statements on my fashion sense, I realize that all of these algorithmic experiences are matters of taste: the question of what we like and why we like it, and what it means that taste is increasingly dictated by black-box robots like the camera on my shelf.”

How Apple Will Use AR to Reinvent the Human-Computer Interface
Tim Bajarin | Fast Company
“It’s in Apple’s DNA to continually deliver the ‘next’ major advancement to the personal computing experience. Its innovation in man-machine interfaces started with the Mac and then extended to the iPod, the iPhone, the iPad, and most recently, the Apple Watch. Now, get ready for the next chapter, as Apple tackles augmented reality, in a way that could fundamentally transform the human-computer interface.”

Advanced Microscope Shows Cells at Work in Incredible Detail
Steve Dent | Engadget
“For the first time, scientists have peered into living cells and created videos showing how they function with unprecedented 3D detail. Using a special microscope and new lighting techniques, a team from Harvard and the Howard Hughes Medical Institute captured zebrafish immune cell interactions with unheard-of 3D detail and resolution.”

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#432549 Your Next Pilot Could Be Drone Software

Would you get on a plane that didn’t have a human pilot in the cockpit? Half of air travelers surveyed in 2017 said they would not, even if the ticket was cheaper. Modern pilots do such a good job that almost any air accident is big news, such as the Southwest engine disintegration on April 17.

But stories of pilot drunkenness, rants, fights and distraction, however rare, are reminders that pilots are only human. Not every plane can be flown by a disaster-averting pilot, like Southwest Capt. Tammie Jo Shults or Capt. Chesley “Sully” Sullenberger. But software could change that, equipping every plane with an extremely experienced guidance system that is always learning more.

In fact, on many flights, autopilot systems already control the plane for basically all of the flight. And software handles the most harrowing landings—when there is no visibility and the pilot can’t see anything to even know where he or she is. But human pilots are still on hand as backups.

A new generation of software pilots, developed for self-flying vehicles, or drones, will soon have logged more flying hours than all humans have—ever. By combining their enormous amounts of flight data and experience, drone-control software applications are poised to quickly become the world’s most experienced pilots.

Drones That Fly Themselves
Drones come in many forms, from tiny quad-rotor copter toys to missile-firing winged planes, or even 7-ton aircraft that can stay aloft for 34 hours at a stretch.

When drones were first introduced, they were flown remotely by human operators. However, this merely substitutes a pilot on the ground for one aloft. And it requires significant communications bandwidth between the drone and control center, to carry real-time video from the drone and to transmit the operator’s commands.

Many newer drones no longer need pilots; some drones for hobbyists and photographers can now fly themselves along human-defined routes, leaving the human free to sightsee—or control the camera to get the best view.

University researchers, businesses, and military agencies are now testing larger and more capable drones that will operate autonomously. Swarms of drones can fly without needing tens or hundreds of humans to control them. And they can perform coordinated maneuvers that human controllers could never handle.

Could humans control these 1,218 drones all together?

Whether flying in swarms or alone, the software that controls these drones is rapidly gaining flight experience.

Importance of Pilot Experience
Experience is the main qualification for pilots. Even a person who wants to fly a small plane for personal and noncommercial use needs 40 hours of flying instruction before getting a private pilot’s license. Commercial airline pilots must have at least 1,000 hours before even serving as a co-pilot.

On-the-ground training and in-flight experience prepare pilots for unusual and emergency scenarios, ideally to help save lives in situations like the “Miracle on the Hudson.” But many pilots are less experienced than “Sully” Sullenberger, who saved his planeload of people with quick and creative thinking. With software, though, every plane can have on board a pilot with as much experience—if not more. A popular software pilot system, in use in many aircraft at once, could gain more flight time each day than a single human might accumulate in a year.

As someone who studies technology policy as well as the use of artificial intelligence for drones, cars, robots, and other uses, I don’t lightly suggest handing over the controls for those additional tasks. But giving software pilots more control would maximize computers’ advantages over humans in training, testing, and reliability.

Training and Testing Software Pilots
Unlike people, computers will follow sets of instructions in software the same way every time. That lets developers create instructions, test reactions, and refine aircraft responses. Testing could make it far less likely, for example, that a computer would mistake the planet Venus for an oncoming jet and throw the plane into a steep dive to avoid it.

The most significant advantage is scale: Rather than teaching thousands of individual pilots new skills, updating thousands of aircraft would require only downloading updated software.

These systems would also need to be thoroughly tested—in both real-life situations and in simulations—to handle a wide range of aviation situations and to withstand cyberattacks. But once they’re working well, software pilots are not susceptible to distraction, disorientation, fatigue, or other human impairments that can create problems or cause errors even in common situations.

Rapid Response and Adaptation
Already, aircraft regulators are concerned that human pilots are forgetting how to fly on their own and may have trouble taking over from an autopilot in an emergency.

In the “Miracle on the Hudson” event, for example, a key factor in what happened was how long it took for the human pilots to figure out what had happened—that the plane had flown through a flock of birds, which had damaged both engines—and how to respond. Rather than the approximately one minute it took the humans, a computer could have assessed the situation in seconds, potentially saving enough time that the plane could have landed on a runway instead of a river.

Aircraft damage can pose another particularly difficult challenge for human pilots: It can change what effects the controls have on its flight. In cases where damage renders a plane uncontrollable, the result is often tragedy. A sufficiently advanced automated system could make minute changes to the aircraft’s steering and use its sensors to quickly evaluate the effects of those movements—essentially learning how to fly all over again with a damaged plane.

Boosting Public Confidence
The biggest barrier to fully automated flight is psychological, not technical. Many people may not want to trust their lives to computer systems. But they might come around when reassured that the software pilot has tens, hundreds, or thousands more hours of flight experience than any human pilot.

Other autonomous technologies, too, are progressing despite public concerns. Regulators and lawmakers are allowing self-driving cars on the roads in many states. But more than half of Americans don’t want to ride in one, largely because they don’t trust the technology. And only 17 percent of travelers around the world are willing to board a plane without a pilot. However, as more people experience self-driving cars on the road and have drones deliver them packages, it is likely that software pilots will gain in acceptance.

The airline industry will certainly be pushing people to trust the new systems: Automating pilots could save tens of billions of dollars a year. And the current pilot shortage means software pilots may be the key to having any airline service to smaller destinations.

Both Boeing and Airbus have made significant investments in automated flight technology, which would remove or reduce the need for human pilots. Boeing has actually bought a drone manufacturer and is looking to add software pilot capabilities to the next generation of its passenger aircraft. (Other tests have tried to retrofit existing aircraft with robotic pilots.)

One way to help regular passengers become comfortable with software pilots—while also helping to both train and test the systems—could be to introduce them as co-pilots working alongside human pilots. Planes would be operated by software from gate to gate, with the pilots instructed to touch the controls only if the system fails. Eventually pilots could be removed from the aircraft altogether, just like they eventually were from the driverless trains that we routinely ride in airports around the world.

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

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