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#435196 Avatar Love? New ‘Black Mirror’ ...

This week, the widely-anticipated fifth season of the dystopian series Black Mirror was released on Netflix. The storylines this season are less focused on far-out scenarios and increasingly aligned with current issues. With only three episodes, this season raises more questions than it answers, often leaving audiences bewildered.

The episode Smithereens explores our society’s crippling addiction to social media platforms and the monopoly they hold over our data. In Rachel, Jack and Ashley Too, we see the disruptive impact of technologies on the music and entertainment industry, and the price of fame for artists in the digital world. Like most Black Mirror episodes, these explore the sometimes disturbing implications of tech advancements on humanity.

But once again, in the midst of all the doom and gloom, the creators of the series leave us with a glimmer of hope. Aligned with Pride month, the episode Striking Vipers explores the impact of virtual reality on love, relationships, and sexual fluidity.

*The review contains a few spoilers.*

Striking Vipers
The first episode of the season, Striking Vipers may be one of the most thought-provoking episodes in Black Mirror history. Reminiscent of previous episodes San Junipero and Hang the DJ, the writers explore the potential for technology to transform human intimacy.

The episode tells the story of two old friends, Danny and Karl, whose friendship is reignited in an unconventional way. Karl unexpectedly appears at Danny’s 38th birthday and reintroduces him to the VR version of a game they used to play years before. In the game Striking Vipers X, each of the players is represented by an avatar of their choice in an uncanny digital reality. Following old tradition, Karl chooses to become the female fighter, Roxanne, and Danny takes on the role of the male fighter, Lance. The state-of-the-art VR headsets appear to use an advanced form of brain-machine interface to allow each player to be fully immersed in the virtual world, emulating all physical sensations.

To their surprise (and confusion), Danny and Karl find themselves transitioning from fist-fighting to kissing. Over the course of many games, they continue to explore a sexual and romantic relationship in the virtual world, leaving them confused and distant in the real world. The virtual and physical realities begin to blur, and so do the identities of the players with their avatars. Danny, who is married (in a heterosexual relationship) and is a father, begins to carry guilt and confusion in the real world. They both wonder if there would be any spark between them in real life.

The brain-machine interface (BMI) depicted in the episode is still science fiction, but that hasn’t stopped innovators from pushing the technology forward. Experts today are designing more intricate BMI systems while programming better algorithms to interpret the neural signals they capture. Scientists have already succeeded in enabling paralyzed patients to type with their minds, and are even allowing people to communicate with one another purely through brainwaves.

The convergence of BMIs with virtual reality and artificial intelligence could make the experience of such immersive digital realities possible. Virtual reality, too, is decreasing exponentially in cost and increasing in quality.

The narrative provides meaningful commentary on another tech area—gaming. It highlights video games not necessarily as addictive distractions, but rather as a platform for connecting with others in a deeper way. This is already very relevant. Video games like Final Fantasy are often a tool for meaningful digital connections for their players.

The Implications of Virtual Reality on Love and Relationships
The narrative of Striking Vipers raises many novel questions about the implications of immersive technologies on relationships: could the virtual world allow us a safe space to explore suppressed desires? Can virtual avatars make it easier for us to show affection to those we care about? Can a sexual or romantic encounter in the digital world be considered infidelity?

Above all, the episode explores the therapeutic possibilities of such technologies. While many fears about virtual reality had been raised in previous seasons of Black Mirror, this episode was focused on its potential. This includes the potential of immersive technology to be a source of liberation, meaningful connections, and self-exploration, as well as a tool for realizing our true identities and desires.

Once again, this is aligned with emerging trends in VR. We are seeing the rise of social VR applications and platforms that allow you to hang out with your friends and family as avatars in the virtual space. The technology is allowing for animation movies, such as Coco VR, to become an increasingly social and interactive experience. Considering that meaningful social interaction can alleviate depression and anxiety, such applications could contribute to well-being.

Techno-philosopher and National Geographic host Jason Silva points out that immersive media technologies can be “engines of empathy.” VR allows us to enter virtual spaces that mimic someone else’s state of mind, allowing us to empathize with the way they view the world. Silva said, “Imagine the intimacy that becomes possible when people meet and they say, ‘Hey, do you want to come visit my world? Do you want to see what it’s like to be inside my head?’”

What is most fascinating about Striking Vipers is that it explores how we may redefine love with virtual reality; we are introduced to love between virtual avatars. While this kind of love may seem confusing to audiences, it may be one of the complex implications of virtual reality on human relationships.

In many ways, the title Black Mirror couldn’t be more appropriate, as each episode serves as a mirror to the most disturbing aspects of our psyches as they get amplified through technology. However, what we see in uplifting and thought-provoking plots like Striking Vipers, San Junipero, and Hang The DJ is that technology could also amplify the most positive aspects of our humanity. This includes our powerful capacity to love.

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Posted in Human Robots

#435161 Less Like Us: An Alternate Theory of ...

The question of whether an artificial general intelligence will be developed in the future—and, if so, when it might arrive—is controversial. One (very uncertain) estimate suggests 2070 might be the earliest we could expect to see such technology.

Some futurists point to Moore’s Law and the increasing capacity of machine learning algorithms to suggest that a more general breakthrough is just around the corner. Others suggest that extrapolating exponential improvements in hardware is unwise, and that creating narrow algorithms that can beat humans at specialized tasks brings us no closer to a “general intelligence.”

But evolution has produced minds like the human mind at least once. Surely we could create artificial intelligence simply by copying nature, either by guided evolution of simple algorithms or wholesale emulation of the human brain.

Both of these ideas are far easier to conceive of than they are to achieve. The 302 neurons of the nematode worm’s brain are still an extremely difficult engineering challenge, let alone the 86 billion in a human brain.

Leaving aside these caveats, though, many people are worried about artificial general intelligence. Nick Bostrom’s influential book on superintelligence imagines it will be an agent—an intelligence with a specific goal. Once such an agent reaches a human level of intelligence, it will improve itself—increasingly rapidly as it gets smarter—in pursuit of whatever goal it has, and this “recursive self-improvement” will lead it to become superintelligent.

This “intelligence explosion” could catch humans off guard. If the initial goal is poorly specified or malicious, or if improper safety features are in place, or if the AI decides it would prefer to do something else instead, humans may be unable to control our own creation. Bostrom gives examples of how a seemingly innocuous goal, such as “Make everyone happy,” could be misinterpreted; perhaps the AI decides to drug humanity into a happy stupor, or convert most of the world into computing infrastructure to pursue its goal.

Drexler and Comprehensive AI Services
These are increasingly familiar concerns for an AI that behaves like an agent, seeking to achieve its goal. There are dissenters to this picture of how artificial general intelligence might arise. One notable alternative point of view comes from Eric Drexler, famous for his work on molecular nanotechnology and Engines of Creation, the book that popularized it.

With respect to AI, Drexler believes our view of an artificial intelligence as a single “agent” that acts to maximize a specific goal is too narrow, almost anthropomorphizing AI, or modeling it as a more realistic route towards general intelligence. Instead, he proposes “Comprehensive AI Services” (CAIS) as an alternative route to artificial general intelligence.

What does this mean? Drexler’s argument is that we should look more closely at how machine learning and AI algorithms are actually being developed in the real world. The optimization effort is going into producing algorithms that can provide services and perform tasks like translation, music recommendations, classification, medical diagnoses, and so forth.

AI-driven improvements in technology, argues Drexler, will lead to a proliferation of different algorithms: technology and software improvement, which can automate increasingly more complicated tasks. Recursive improvement in this regime is already occurring—take the newer versions of AlphaGo, which can learn to improve themselves by playing against previous versions.

Many Smart Arms, No Smart Brain
Instead of relying on some unforeseen breakthrough, the CAIS model of AI just assumes that specialized, narrow AI will continue to improve at performing each of its tasks, and the range of tasks that machine learning algorithms will be able to perform will become wider. Ultimately, once a sufficient number of tasks have been automated, the services that an AI will provide will be so comprehensive that they will resemble a general intelligence.

One could then imagine a “general” intelligence as simply an algorithm that is extremely good at matching the task you ask it to perform to the specialized service algorithm that can perform that task. Rather than acting like a single brain that strives to achieve a particular goal, the central AI would be more like a search engine, looking through the tasks it can perform to find the closest match and calling upon a series of subroutines to achieve the goal.

For Drexler, this is inherently a safety feature. Rather than Bostrom’s single, impenetrable, conscious and superintelligent brain (which we must try to psychoanalyze in advance without really knowing what it will look like), we have a network of capabilities. If you don’t want your system to perform certain tasks, you can simply cut it off from access to those services. There is no superintelligent consciousness to outwit or “trap”: more like an extremely high-level programming language that can respond to complicated commands by calling upon one of the myriad specialized algorithms that have been developed by different groups.

This skirts the complex problem of consciousness and all of the sticky moral quandaries that arise in making minds that might be like ours. After all, if you could simulate a human mind, you could simulate it experiencing unimaginable pain. Black Mirror-esque dystopias where emulated minds have no rights and are regularly “erased” or forced to labor in dull and repetitive tasks, hove into view.

Drexler argues that, in this world, there is no need to ever build a conscious algorithm. Yet it seems likely that, at some point, humans will attempt to simulate our own brains, if only in the vain attempt to pursue immortality. This model cannot hold forever. Yet its proponents argue that any world in which we could develop general AI would probably also have developed superintelligent capabilities in a huge range of different tasks, such as computer programming, natural language understanding, and so on. In other words, CAIS arrives first.

The Future In Our Hands?
Drexler argues that his model already incorporates many of the ideas from general AI development. In the marketplace, algorithms compete all the time to perform these services: they undergo the same evolutionary pressures that lead to “higher intelligence,” but the behavior that’s considered superior is chosen by humans, and the nature of the “general intelligence” is far more shaped by human decision-making and human programmers. Development in AI services could still be rapid and disruptive.

But in Drexler’s case, the research and development capacity comes from humans and organizations driven by the desire to improve algorithms that are performing individualized and useful tasks, rather than from a conscious AI recursively reprogramming and improving itself.

In other words, this vision does not absolve us of the responsibility of making our AI safe; if anything, it gives us a greater degree of responsibility. As more and more complex “services” are automated, performing what used to be human jobs at superhuman speed, the economic disruption will be severe.

Equally, as machine learning is trusted to carry out more complex decisions, avoiding algorithmic bias becomes crucial. Shaping each of these individual decision-makers—and trying to predict the complex ways they might interact with each other—is no less daunting a task than specifying the goal for a hypothetical, superintelligent, God-like AI. Arguably, the consequences of the “misalignment” of these services algorithms are already multiplying around us.

The CAIS model bridges the gap between real-world AI, machine learning developments, and real-world safety considerations, as well as the speculative world of superintelligent agents and the safety considerations involved with controlling their behavior. We should keep our minds open as to what form AI and machine learning will take, and how it will influence our societies—and we must take care to ensure that the systems we create don’t end up forcing us all to live in a world of unintended consequences.

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#435080 12 Ways Big Tech Can Take Big Action on ...

Bill Gates and Mark Zuckerberg have invested $1 billion in Breakthrough Energy to fund next-generation solutions to tackle climate. But there is a huge risk that any successful innovation will only reach the market as the world approaches 2030 at the earliest.

We now know that reducing the risk of dangerous climate change means halving global greenhouse gas emissions by that date—in just 11 years. Perhaps Gates, Zuckerberg, and all the tech giants should invest equally in innovations to do with how their own platforms —search, social media, eCommerce—can support societal behavior changes to drive down emissions.

After all, the tech giants influence the decisions of four billion consumers every day. It is time for a social contract between tech and society.

Recently myself and collaborator Johan Falk published a report during the World Economic Forum in Davos outlining 12 ways the tech sector can contribute to supporting societal goals to stabilize Earth’s climate.

Become genuine climate guardians

Tech giants go to great lengths to show how serious they are about reducing their emissions. But I smell cognitive dissonance. Google and Microsoft are working in partnership with oil companies to develop AI tools to help maximize oil recovery. This is not the behavior of companies working flat-out to stabilize Earth’s climate. Indeed, few major tech firms have visions that indicate a stable and resilient planet might be a good goal, yet AI alone has the potential to slash greenhouse gas emissions by four percent by 2030—equivalent to the emissions of Australia, Canada, and Japan combined.

We are now developing a playbook, which we plan to publish later this year at the UN climate summit, about making it as simple as possible for a CEO to become a climate guardian.

Hey Alexa, do you care about the stability of Earth’s climate?

Increasingly, consumers are delegating their decisions to narrow artificial intelligence like Alexa and Siri. Welcome to a world of zero-click purchases.

Should algorithms and information architecture be designed to nudge consumer behavior towards low-carbon choices, for example by making these options the default? We think so. People don’t mind being nudged; in fact, they welcome efforts to make their lives better. For instance, if I want to lose weight, I know I will need all the help I can get. Let’s ‘nudge for good’ and experiment with supporting societal goals.

Use social media for good

Facebook’s goal is to bring the world closer together. With 2.2 billion users on the platform, CEO Mark Zuckerberg can reasonably claim this goal is possible. But social media has changed the flow of information in the world, creating a lucrative industry around a toxic brown-cloud of confusion and anger, with frankly terrifying implications for democracy. This has been linked to the rise of nationalism and populism, and to the election of leaders who shun international cooperation, dismiss scientific knowledge, and reverse climate action at a moment when we need it more than ever.

Social media tools need re-engineering to help people make sense of the world, support democratic processes, and build communities around societal goals. Make this your mission.

Design for a future on Earth

Almost everything is designed with computer software, from buildings to mobile phones to consumer packaging. It is time to make zero-carbon design the new default and design products for sharing, re-use and disassembly.

The future is circular

Halving emissions in a decade will require all companies to adopt circular business models to reduce material use. Some tech companies are leading the charge. Apple has committed to becoming 100 percent circular as soon as possible. Great.

While big tech companies strive to be market leaders here, many other companies lack essential knowledge. Tech companies can support rapid adoption in different economic sectors, not least because they have the know-how to scale innovations exponentially. It makes business sense. If economies of scale drive the price of recycled steel and aluminium down, everyone wins.

Reward low-carbon consumption

eCommerce platforms can create incentives for low-carbon consumption. The world’s largest experiment in greening consumer behavior is Ant Forest, set up by Chinese fintech giant Ant Financial.

An estimated 300 million customers—similar to the population of the United States—gain points for making low-carbon choices such as walking to work, using public transport, or paying bills online. Virtual points are eventually converted into real trees. Sure, big questions remain about its true influence on emissions, but this is a space for rapid experimentation for big impact.

Make information more useful

Science is our tool for defining reality. Scientific consensus is how we attain reliable knowledge. Even after the information revolution, reliable knowledge about the world remains fragmented and unstructured. Build the next generation of search engines to genuinely make the world’s knowledge useful for supporting societal goals.

We need to put these tools towards supporting shared world views of the state of the planet based on the best science. New AI tools being developed by startups like Iris.ai can help see through the fog. From Alexa to Google Home and Siri, the future is “Voice”, but who chooses the information source? The highest bidder? Again, the implications for climate are huge.

Create new standards for digital advertising and marketing

Half of global ad revenue will soon be online, and largely going to a small handful of companies. How about creating a novel ethical standard on what is advertised and where? Companies could consider promoting sustainable choices and healthy lifestyles and limiting advertising of high-emissions products such as cheap flights.

We are what we eat

It is no secret that tech is about to disrupt grocery. The supermarkets of the future will be built on personal consumer data. With about two billion people either obese or overweight, revolutions in choice architecture could support positive diet choices, reduce meat consumption, halve food waste and, into the bargain, slash greenhouse gas emissions.

The future of transport is not cars, it’s data

The 2020s look set to be the biggest disruption of the automobile industry since Henry Ford unveiled the Model T. Two seismic shifts are on their way.

First, electric cars now compete favorably with petrol engines on range. Growth will reach an inflection point within a year or two once prices reach parity. The death of the internal combustion engine in Europe and Asia is assured with end dates announced by China, India, France, the UK, and most of Scandinavia. Dates range from 2025 (Norway) to 2040 (UK and China).

Tech giants can accelerate the demise. Uber recently announced a passenger surcharge to help London drivers save around $1,500 a year towards the cost of an electric car.

Second, driverless cars can shift the transport economic model from ownership to service and ride sharing. A complete shift away from privately-owned vehicles is around the corner, with large implications for emissions.

Clean-energy living and working

Most buildings are barely used and inefficiently heated and cooled. Digitization can slash this waste and its corresponding emissions through measurement, monitoring, and new business models to use office space. While, just a few unicorns are currently in this space, the potential is enormous. Buildings are one of the five biggest sources of emissions, yet have the potential to become clean energy producers in a distributed energy network.

Creating liveable cities

More cities are setting ambitious climate targets to halve emissions in a decade or even less. Tech companies can support this transition by driving demand for low-carbon services for their workforces and offices, but also by providing tools to help monitor emissions and act to reduce them. Google, for example, is collecting travel and other data from across cities to estimate emissions in real time. This is possible through technologies like artificial intelligence and the internet of things. But beware of smart cities that turn out to be not so smart. Efficiencies can reduce resilience when cities face crises.

It’s a Start
Of course, it will take more than tech to solve the climate crisis. But tech is a wildcard. The actions of the current tech giants and their acolytes could serve to destabilize the climate further or bring it under control.

We need a new social contract between tech companies and society to achieve societal goals. The alternative is unthinkable. Without drastic action now, climate chaos threatens to engulf us all. As this future approaches, regulators will be forced to take ever more draconian action to rein in the problem. Acting now will reduce that risk.

Note: A version of this article was originally published on World Economic Forum

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#435046 The Challenge of Abundance: Boredom, ...

As technology continues to progress, the possibility of an abundant future seems more likely. Artificial intelligence is expected to drive down the cost of labor, infrastructure, and transport. Alternative energy systems are reducing the cost of a wide variety of goods. Poverty rates are falling around the world as more people are able to make a living, and resources that were once inaccessible to millions are becoming widely available.

But such a life presents fuel for the most common complaint against abundance: if robots take all the jobs, basic income provides us livable welfare for doing nothing, and healthcare is a guarantee free of charge, then what is the point of our lives? What would motivate us to work and excel if there are no real risks or rewards? If everything is simply given to us, how would we feel like we’ve ever earned anything?

Time has proven that humans inherently yearn to overcome challenges—in fact, this very desire likely exists as the root of most technological innovation. And the idea that struggling makes us stronger isn’t just anecdotal, it’s scientifically validated.

For instance, kids who use anti-bacterial soaps and sanitizers too often tend to develop weak immune systems, causing them to get sick more frequently and more severely. People who work out purposely suffer through torn muscles so that after a few days of healing their muscles are stronger. And when patients visit a psychologist to handle a fear that is derailing their lives, one of the most common treatments is exposure therapy: a slow increase of exposure to the suffering so that the patient gets stronger and braver each time, able to take on an incrementally more potent manifestation of their fears.

Different Kinds of Struggle
It’s not hard to understand why people might fear an abundant future as a terribly mundane one. But there is one crucial mistake made in this assumption, and it was well summarized by Indian mystic and author Sadhguru, who said during a recent talk at Google:

Stomach empty, only one problem. Stomach full—one hundred problems; because what we refer to as human really begins only after survival is taken care of.

This idea is backed up by Maslow’s hierarchy of needs, which was first presented in his 1943 paper “A Theory of Human Motivation.” Maslow shows the steps required to build to higher and higher levels of the human experience. Not surprisingly, the first two levels deal with physiological needs and the need for safety—in other words, with the body. You need to have food, water, and sleep, or you die. After that, you need to be protected from threats, from the elements, from dangerous people, and from disease and pain.

Maslow’s Hierarchy of Needs. Photo by Wikimedia User:Factoryjoe / CC BY-SA 3.0
The beauty of these first two levels is that they’re clear-cut problems with clear-cut solutions: if you’re hungry, then you eat; if you’re thirsty, then you drink; if you’re tired, then you sleep.

But what about the next tiers of the hierarchy? What of love and belonging, of self-esteem and self-actualization? If we’re lonely, can we just summon up an authentic friend or lover? If we feel neglected by society, can we demand it validate us? If we feel discouraged and disappointed in ourselves, can we simply dial up some confidence and self-esteem?

Of course not, and that’s because these psychological needs are nebulous; they don’t contain clear problems with clear solutions. They involve the external world and other people, and are complicated by the infinite flavors of nuance and compromise that are required to navigate human relationships and personal meaning.

These psychological difficulties are where we grow our personalities, outlooks, and beliefs. The truly defining characteristics of a person are dictated not by the physical situations they were forced into—like birth, socioeconomic class, or physical ailment—but instead by the things they choose. So a future of abundance helps to free us from the physical limitations so that we can truly commit to a life of purpose and meaning, rather than just feel like survival is our purpose.

The Greatest Challenge
And that’s the plot twist. This challenge to come to grips with our own individuality and freedom could actually be the greatest challenge our species has ever faced. Can you imagine waking up every day with infinite possibility? Every choice you make says no to the rest of reality, and so every decision carries with it truly life-defining purpose and meaning. That sounds overwhelming. And that’s probably because in our current socio-economic systems, it is.

Studies have shown that people in wealthier nations tend to experience more anxiety and depression. Ron Kessler, professor of health care policy at Harvard and World Health Organization (WHO) researcher, summarized his findings of global mental health by saying, “When you’re literally trying to survive, who has time for depression? Americans, on the other hand, many of whom lead relatively comfortable lives, blow other nations away in the depression factor, leading some to suggest that depression is a ‘luxury disorder.’”

This might explain why America scores in the top rankings for the most depressed and anxious country on the planet. We surpassed our survival needs, and instead became depressed because our jobs and relationships don’t fulfill our expectations for the next three levels of Maslow’s hierarchy (belonging, esteem, and self-actualization).

But a future of abundance would mean we’d have to deal with these levels. This is the challenge for the future; this is what keeps things from being mundane.

As a society, we would be forced to come to grips with our emotional intelligence, to reckon with philosophy rather than simply contemplate it. Nearly every person you meet will be passionately on their own customized life journey, not following a routine simply because of financial limitations. Such a world seems far more vibrant and interesting than one where most wander sleep-deprived and numb while attempting to survive the rat race.

We can already see the forceful hand of this paradigm shift as self-driving cars become ubiquitous. For example, consider the famous psychological and philosophical “trolley problem.” In this thought experiment, a person sees a trolley car heading towards five people on the train tracks; they see a lever that will allow them to switch the trolley car to a track that instead only has one person on it. Do you switch the lever and have a hand in killing one person, or do you let fate continue and kill five people instead?

For the longest time, this was just an interesting quandary to consider. But now, massive corporations have to have an answer, so they can program their self-driving cars with the ability to choose between hitting a kid who runs into the road or swerving into an oncoming car carrying a family of five. When companies need philosophers to make business decisions, it’s a good sign of what’s to come.

Luckily, it’s possible this forceful reckoning with philosophy and our own consciousness may be exactly what humanity needs. Perhaps our great failure as a species has been a result of advanced cognition still trapped in the first two levels of Maslow’s hierarchy due to a long history of scarcity.

As suggested in the opening scenes in 2001: A Space Odyssey, our ape-like proclivity for violence has long stayed the same while the technology we fight with and live amongst has progressed. So while well-off Americans may have comfortable lives, they still know they live in a system where there is no safety net, where a single tragic failure could still mean hunger and homelessness. And because of this, that evolutionarily hard-wired neurotic part of our brain that fears for our survival has never been able to fully relax, and so that anxiety and depression that come with too much freedom but not enough security stays ever present.

Not only might this shift in consciousness help liberate humanity, but it may be vital if we’re to survive our future creations as well. Whatever values we hold dear as a species are the ones we will imbue into the sentient robots we create. If machine learning is going to take its guidance from humanity, we need to level up humanity’s emotional maturity.

While the physical struggles of the future may indeed fall to the wayside amongst abundance, it’s unlikely to become a mundane world; instead, it will become a vibrant culture where each individual is striving against the most important struggle that affects all of us: the challenge to find inner peace, to find fulfillment, to build meaningful relationships, and ultimately, the challenge to find ourselves.

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#435023 Inflatable Robot Astronauts and How to ...

The typical cultural image of a robot—as a steel, chrome, humanoid bucket of bolts—is often far from the reality of cutting-edge robotics research. There are difficulties, both social and technological, in realizing the image of a robot from science fiction—let alone one that can actually help around the house. Often, it’s simply the case that great expense in producing a humanoid robot that can perform dozens of tasks quite badly is less appropriate than producing some other design that’s optimized to a specific situation.

A team of scientists from Brigham Young University has received funding from NASA to investigate an inflatable robot called, improbably, King Louie. The robot was developed by Pneubotics, who have a long track record in the world of soft robotics.

In space, weight is at a premium. The world watched in awe and amusement when Commander Chris Hadfield sang “Space Oddity” from the International Space Station—but launching that guitar into space likely cost around $100,000. A good price for launching payload into outer space is on the order of $10,000 per pound ($22,000/kg).

For that price, it would cost a cool $1.7 million to launch Boston Dynamics’ famous ATLAS robot to the International Space Station, and its bulk would be inconvenient in the cramped living quarters available. By contrast, an inflatable robot like King Louie is substantially lighter and can simply be deflated and folded away when not in use. The robot can be manufactured from cheap, lightweight, and flexible materials, and minor damage is easy to repair.

Inflatable Robots Under Pressure
The concept of inflatable robots is not new: indeed, earlier prototypes of King Louie were exhibited back in 2013 at Google I/O’s After Hours, flailing away at each other in a boxing ring. Sparks might fly in fights between traditional robots, but the aim here was to demonstrate that the robots are passively safe: the soft, inflatable figures won’t accidentally smash delicate items when moving around.

Health and safety regulations form part of the reason why robots don’t work alongside humans more often, but soft robots would be far safer to use in healthcare or around children (whose first instinct, according to BYU’s promotional video, is either to hug or punch King Louie.) It’s also much harder to have nightmarish fantasies about robotic domination with these friendlier softbots: Terminator would’ve been a much shorter franchise if Skynet’s droids were inflatable.

Robotic exoskeletons are increasingly used for physical rehabilitation therapies, as well as for industrial purposes. As countries like Japan seek to care for their aging populations with robots and alleviate the burden on nurses, who suffer from some of the highest rates of back injuries of any profession, soft robots will become increasingly attractive for use in healthcare.

Precision and Proprioception
The main issue is one of control. Rigid, metallic robots may be more expensive and more dangerous, but the simple fact of their rigidity makes it easier to map out and control the precise motions of each of the robot’s limbs, digits, and actuators. Individual motors attached to these rigid robots can allow for a great many degrees of freedom—individual directions in which parts of the robot can move—and precision control.

For example, ATLAS has 28 degrees of freedom, while Shadow’s dexterous robot hand alone has 20. This is much harder to do with an inflatable robot, for precisely the same reasons that make it safer. Without hard and rigid bones, other methods of control must be used.

In the case of King Louie, the robot is made up of many expandable air chambers. An air-compressor changes the pressure levels in these air chambers, allowing them to expand and contract. This harks back to some of the earliest pneumatic automata. Pairs of chambers act antagonistically, like muscles, such that when one chamber “tenses,” another relaxes—allowing King Louie to have, for example, four degrees of freedom in each of its arms.

The robot is also surprisingly strong. Professor Killpack, who works at BYU on the project, estimates that its payload is comparable to other humanoid robots on the market, like Rethink Robotics’ Baxter (RIP).

Proprioception, that sixth sense that allows us to map out and control our own bodies and muscles in fine detail, is being enhanced for a wider range of soft, flexible robots with the use of machine learning algorithms connected to input from a whole host of sensors on the robot’s body.

Part of the reason this is so complicated with soft, flexible robots is that the shape and “map” of the robot’s body can change; that’s the whole point. But this means that every time King Louie is inflated, its body is a slightly different shape; when it becomes deformed, for example due to picking up objects, the shape changes again, and the complex ways in which the fabric can twist and bend are far more difficult to model and sense than the behavior of the rigid metal of King Louie’s hard counterparts. When you’re looking for precision, seemingly-small changes can be the difference between successfully holding an object or dropping it.

Learning to Move
Researchers at BYU are therefore spending a great deal of time on how to control the soft-bot enough to make it comparably useful. One method involves the commercial tracking technology used in the Vive VR system: by moving the game controller, which provides a constant feedback to the robot’s arm, you can control its position. Since the tracking software provides an estimate of the robot’s joint angles and continues to provide feedback until the arm is correctly aligned, this type of feedback method is likely to work regardless of small changes to the robot’s shape.

The other technologies the researchers are looking into for their softbot include arrays of flexible, tactile sensors to place on the softbot’s skin, and minimizing the complex cross-talk between these arrays to get coherent information about the robot’s environment. As with some of the new proprioception research, the project is looking into neural networks as a means of modeling the complicated dynamics—the motion and response to forces—of the softbot. This method relies on large amounts of observational data, mapping how the robot is inflated and how it moves, rather than explicitly understanding and solving the equations that govern its motion—which hopefully means the methods can work even as the robot changes.

There’s still a long way to go before soft and inflatable robots can be controlled sufficiently well to perform all the tasks they might be used for. Ultimately, no one robotic design is likely to be perfect for any situation.

Nevertheless, research like this gives us hope that one day, inflatable robots could be useful tools, or even companions, at which point the advertising slogans write themselves: Don’t let them down, and they won’t let you down!

Image Credit: Brigham Young University. Continue reading

Posted in Human Robots