Tag Archives: interact
#433634 This Robotic Skin Makes Inanimate ...
In Goethe’s poem “The Sorcerer’s Apprentice,” made world-famous by its adaptation in Disney’s Fantasia, a lazy apprentice, left to fetch water, uses magic to bewitch a broom into performing his chores for him. Now, new research from Yale has opened up the possibility of being able to animate—and automate—household objects by fitting them with a robotic skin.
Yale’s Soft Robotics lab, the Faboratory, is led by Professor Rebecca Kramer-Bottiglio, and has long investigated the possibilities associated with new kinds of manufacturing. While the typical image of a robot is hard, cold steel and rigid movements, soft robotics aims to create something more flexible and versatile. After all, the human body is made up of soft, flexible surfaces, and the world is designed for us. Soft, deformable robots could change shape to adapt to different tasks.
When designing a robot, key components are the robot’s sensors, which allow it to perceive its environment, and its actuators, the electrical or pneumatic motors that allow the robot to move and interact with its environment.
Consider your hand, which has temperature and pressure sensors, but also muscles as actuators. The omni-skins, as the Science Robotics paper dubs them, combine sensors and actuators, embedding them into an elastic sheet. The robotic skins are moved by pneumatic actuators or memory alloy that can bounce back into shape. If this is then wrapped around a soft, deformable object, moving the skin with the actuators can allow the object to crawl along a surface.
The key to the design here is flexibility: rather than adding chips, sensors, and motors into every household object to turn them into individual automatons, the same skin can be used for many purposes. “We can take the skins and wrap them around one object to perform a task—locomotion, for example—and then take them off and put them on a different object to perform a different task, such as grasping and moving an object,” said Kramer-Bottiglio. “We can then take those same skins off that object and put them on a shirt to make an active wearable device.”
The task is then to dream up applications for the omni-skins. Initially, you might imagine demanding a stuffed toy to fetch the remote control for you, or animating a sponge to wipe down kitchen surfaces—but this is just the beginning. The scientists attached the skins to a soft tube and camera, creating a worm-like robot that could compress itself and crawl into small spaces for rescue missions. The same skins could then be worn by a person to sense their posture. One could easily imagine this being adapted into a soft exoskeleton for medical or industrial purposes: for example, helping with rehabilitation after an accident or injury.
The initial motivating factor for creating the robots was in an environment where space and weight are at a premium, and humans are forced to improvise with whatever’s at hand: outer space. Kramer-Bottoglio originally began the work after NASA called out for soft robotics systems for use by astronauts. Instead of wasting valuable rocket payload by sending up a heavy metal droid like ATLAS to fetch items or perform repairs, soft robotic skins with modular sensors could be adapted for a range of different uses spontaneously.
By reassembling components in the soft robotic skin, a crumpled ball of paper could provide the chassis for a robot that performs repairs on the spaceship, or explores the lunar surface. The dynamic compression provided by the robotic skin could be used for g-suits to protect astronauts when they rapidly accelerate or decelerate.
“One of the main things I considered was the importance of multi-functionality, especially for deep space exploration where the environment is unpredictable. The question is: How do you prepare for the unknown unknowns? … Given the design-on-the-fly nature of this approach, it’s unlikely that a robot created using robotic skins will perform any one task optimally,” Kramer-Bottiglio said. “However, the goal is not optimization, but rather diversity of applications.”
There are still problems to resolve. Many of the videos of the skins indicate that they can rely on an external power supply. Creating new, smaller batteries that can power wearable devices has been a focus of cutting-edge materials science research for some time. Much of the lab’s expertise is in creating flexible, stretchable electronics that can be deformed by the actuators without breaking the circuitry. In the future, the team hopes to work on streamlining the production process; if the components could be 3D printed, then the skins could be created when needed.
In addition, robotic hardware that’s capable of performing an impressive range of precise motions is quite an advanced technology. The software to control those robots, and enable them to perform a variety of tasks, is quite another challenge. With soft robots, it can become even more complex to design that control software, because the body itself can change shape and deform as the robot moves. The same set of programmed motions, then, can produce different results depending on the environment.
“Let’s say I have a soft robot with four legs that crawls along the ground, and I make it walk up a hard slope,” Dr. David Howard, who works on robotics at CSIRO in Australia, explained to ABC.
“If I make that slope out of gravel and I give it the same control commands, the actual body is going to deform in a different way, and I’m not necessarily going to know what that is.”
Despite these and other challenges, research like that at the Faboratory still hopes to redefine how we think of robots and robotics. Instead of a robot that imitates a human and manipulates objects, the objects themselves will become programmable matter, capable of moving autonomously and carrying out a range of tasks. Futurists speculate about a world where most objects are automated to some degree and can assemble and repair themselves, or are even built entirely of tiny robots.
The tale of the Sorcerer’s Apprentice was first written in 1797, at the dawn of the industrial revolution, over a century before the word “robot” was even coined. Yet more and more roboticists aim to prove Arthur C Clarke’s maxim: any sufficiently advanced technology is indistinguishable from magic.
Image Credit: Joran Booth, The Faboratory Continue reading
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#433545 Six Degrees of Torque-controlled ...
ALMA (“Articulated Locomotion and Manipulation”), a quadrupedal robotic framework, allows a cool robotic arm six degrees of dynamic locomotion (“movement”) while doing something else. Possible motions include walking, trotting, pacing and torso-posturing, simultaneously with other complex tasks, as well as … Continue reading
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#433386 What We Have to Gain From Making ...
The borders between the real world and the digital world keep crumbling, and the latter’s importance in both our personal and professional lives keeps growing. Some describe the melding of virtual and real worlds as part of the fourth industrial revolution. Said revolution’s full impact on us as individuals, our companies, communities, and societies is still unknown.
Greg Cross, chief business officer of New Zealand-based AI company Soul Machines, thinks one inescapable consequence of these crumbling borders is people spending more and more time interacting with technology. In a presentation at Singularity University’s Global Summit in San Francisco last month, Cross unveiled Soul Machines’ latest work and shared his views on the current state of human-like AI and where the technology may go in the near future.
Humanizing Technology Interaction
Cross started by introducing Rachel, one of Soul Machines’ “emotionally responsive digital humans.” The company has built 15 different digital humans of various sexes, groups, and ethnicities. Rachel, along with her “sisters” and “brothers,” has a virtual nervous system based on neural networks and biological models of different paths in the human brain. The system is controlled by virtual neurotransmitters and hormones akin to dopamine, serotonin, and oxytocin, which influence learning and behavior.
As a result, each digital human can have its own unique set of “feelings” and responses to interactions. People interact with them via visual and audio sensors, and the machines respond in real time.
“Over the last 20 or 30 years, the way we think about machines and the way we interact with machines has changed,” Cross said. “We’ve always had this view that they should actually be more human-like.”
The realism of the digital humans’ graphic representations comes thanks to the work of Soul Machines’ other co-founder, Dr. Mark Sager, who has won two Academy Awards for his work on some computer-generated movies, including James Cameron’s Avatar.
Cross pointed out, for example, that rather than being unrealistically flawless and clear, Rachel’s skin has blemishes and sun spots, just like real human skin would.
The Next Human-Machine Frontier
When people interact with each other face to face, emotional and intellectual engagement both heavily influence the interaction. What would it look like for machines to bring those same emotional and intellectual capacities to our interactions with them, and how would this type of interaction affect the way we use, relate to, and feel about AI?
Cross and his colleagues believe that humanizing artificial intelligence will make the technology more useful to humanity, and prompt people to use AI in more beneficial ways.
“What we think is a very important view as we move forward is that these machines can be more helpful to us. They can be more useful to us. They can be more interesting to us if they’re actually more like us,” Cross said.
It is an approach that seems to resonate with companies and organizations. For example, in the UK, where NatWest Bank is testing out Cora as a digital employee to help answer customer queries. In Germany, Daimler Financial Group plans to employ Sarah as something “similar to a personal concierge” for its customers. According to Cross, Daimler is looking at other ways it could deploy digital humans across the organization, from building digital service people, digital sales people, and maybe in the future, digital chauffeurs.
Soul Machines’ latest creation is Will, a digital teacher that can interact with children through a desktop, tablet, or mobile device and help them learn about renewable energy. Cross sees other social uses for digital humans, including potentially serving as doctors to rural communities.
Our Digital Friends—and Twins
Soul Machines is not alone in its quest to humanize technology. It is a direction many technology companies, including the likes of Amazon, also seem to be pursuing. Amazon is working on building a home robot that, according to Bloomberg, “could be a sort of mobile Alexa.”
Finding a more human form for technology seems like a particularly pervasive pursuit in Japan. Not just when it comes to its many, many robots, but also virtual assistants like Gatebox.
The Japanese approach was perhaps best summed up by famous android researcher Dr. Hiroshi Ishiguro, who I interviewed last year: “The human brain is set up to recognize and interact with humans. So, it makes sense to focus on developing the body for the AI mind, as well as the AI. I believe that the final goal for both Japanese and other companies and scientists is to create human-like interaction.”
During Cross’s presentation, Rob Nail, CEO and associate founder of Singularity University, joined him on the stage, extending an invitation to Rachel to be SU’s first fully digital faculty member. Rachel accepted, and though she’s the only digital faculty right now, she predicted this won’t be the case for long.
“In 10 years, all of you will have digital versions of yourself, just like me, to take on specific tasks and make your life a whole lot easier,” she said. “This is great news for me. I’ll have millions of digital friends.”
Image Credit: Soul Machines Continue reading
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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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