Tag Archives: control

#432568 Tech Optimists See a Golden ...

Posted on April 22, 2018 by Android

Technology evangelists dream about a future where we’re all liberated from the more mundane aspects of our jobs by artificial intelligence. Other futurists go further, imagining AI will enable us to become superhuman, enhancing our intelligence, abandoning our mortal bodies, and uploading ourselves to the cloud.

Paradise is all very well, although your mileage may vary on whether these scenarios are realistic or desirable. The real question is, how do we get there?

Economist John Maynard Keynes notably argued in favor of active intervention when an economic crisis hits, rather than waiting for the markets to settle down to a more healthy equilibrium in the long run. His rebuttal to critics was, “In the long run, we are all dead.” After all, if it takes 50 years of upheaval and economic chaos for things to return to normality, there has been an immense amount of human suffering first.

Similar problems arise with the transition to a world where AI is intimately involved in our lives. In the long term, automation of labor might benefit the human species immensely. But in the short term, it has all kinds of potential pitfalls, especially in exacerbating inequality within societies where AI takes on a larger role. A new report from the Institute for Public Policy Research has deep concerns about the future of work.

Uneven Distribution
While the report doesn’t foresee the same gloom and doom of mass unemployment that other commentators have considered, the concern is that the gains in productivity and economic benefits from AI will be unevenly distributed. In the UK, jobs that account for £290 billion worth of wages in today’s economy could potentially be automated with current technology. But these are disproportionately jobs held by people who are already suffering from social inequality.

Low-wage jobs are five times more likely to be automated than high-wage jobs. A greater proportion of jobs held by women are likely to be automated. The solution that’s often suggested is that people should simply “retrain”; but if no funding or assistance is provided, this burden is too much to bear. You can’t expect people to seamlessly transition from driving taxis to writing self-driving car software without help. As we have already seen, inequality is exacerbated when jobs that don’t require advanced education (even if they require a great deal of technical skill) are the first to go.

No Room for Beginners
Optimists say algorithms won’t replace humans, but will instead liberate us from the dull parts of our jobs. Lawyers used to have to spend hours trawling through case law to find legal precedents; now AI can identify the most relevant documents for them. Doctors no longer need to look through endless scans and perform diagnostic tests; machines can do this, leaving the decision-making to humans. This boosts productivity and provides invaluable tools for workers.

But there are issues with this rosy picture. If humans need to do less work, the economic incentive is for the boss to reduce their hours. Some of these “dull, routine” parts of the job were traditionally how people getting into the field learned the ropes: paralegals used to look through case law, but AI may render them obsolete. Even in the field of journalism, there’s now software that will rewrite press releases for publication, traditionally something close to an entry-level task. If there are no entry-level jobs, or if entry-level now requires years of training, the result is to exacerbate inequality and reduce social mobility.

Automating Our Biases
The adoption of algorithms into employment has already had negative impacts on equality. Cathy O’Neil, mathematics PhD from Harvard, raises these concerns in her excellent book Weapons of Math Destruction. She notes that algorithms designed by humans often encode the biases of that society, whether they’re racial or based on gender and sexuality.

Google’s search engine advertises more executive-level jobs to users it thinks are male. AI programs predict that black offenders are more likely to re-offend than white offenders; they receive correspondingly longer sentences. It needn’t necessarily be that bias has been actively programmed; perhaps the algorithms just learn from historical data, but this means they will perpetuate historical inequalities.

Take candidate-screening software HireVue, used by many major corporations to assess new employees. It analyzes “verbal and non-verbal cues” of candidates, comparing them to employees that historically did well. Either way, according to Cathy O’Neil, they are “using people’s fear and trust of mathematics to prevent them from asking questions.” With no transparency or understanding of how the algorithm generates its results, and no consensus over who’s responsible for the results, discrimination can occur automatically, on a massive scale.

Combine this with other demographic trends. In rich countries, people are living longer. An increasing burden will be placed on a shrinking tax base to support that elderly population. A recent study said that due to the accumulation of wealth in older generations, millennials stand to inherit more than any previous generation, but it won’t happen until they’re in their 60s. Meanwhile, those with savings and capital will benefit as the economy shifts: the stock market and GDP will grow, but wages and equality will fall, a situation that favors people who are already wealthy.

Even in the most dramatic AI scenarios, inequality is exacerbated. If someone develops a general intelligence that’s near-human or super-human, and they manage to control and monopolize it, they instantly become immensely wealthy and powerful. If the glorious technological future that Silicon Valley enthusiasts dream about is only going to serve to make the growing gaps wider and strengthen existing unfair power structures, is it something worth striving for?

What Makes a Utopia?
We urgently need to redefine our notion of progress. Philosophers worry about an AI that is misaligned—the things it seeks to maximize are not the things we want maximized. At the same time, we measure the development of our countries by GDP, not the quality of life of workers or the equality of opportunity in the society. Growing wealth with increased inequality is not progress.

Some people will take the position that there are always winners and losers in society, and that any attempt to redress the inequalities of our society will stifle economic growth and leave everyone worse off. Some will see this as an argument for a new economic model, based around universal basic income. Any moves towards this will need to take care that it’s affordable, sustainable, and doesn’t lead towards an entrenched two-tier society.

Walter Schiedel’s book The Great Leveller is a huge survey of inequality across all of human history, from the 21st century to prehistoric cave-dwellers. He argues that only revolutions, wars, and other catastrophes have historically reduced inequality: a perfect example is the Black Death in Europe, which (by reducing the population and therefore the labor supply that was available) increased wages and reduced inequality. Meanwhile, our solution to the financial crisis of 2007-8 may have only made the problem worse.

But in a world of nuclear weapons, of biowarfare, of cyberwarfare—a world of unprecedented, complex, distributed threats—the consequences of these “safety valves” could be worse than ever before. Inequality increases the risk of global catastrophe, and global catastrophes could scupper any progress towards the techno-utopia that the utopians dream of. And a society with entrenched inequality is no utopia at all.

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Posted in Human Robots

#432549 Your Next Pilot Could Be Drone Software

Posted on April 20, 2018 by Android

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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Posted in Human Robots

#432539 10 Amazing Things You Can Learn From ...

Posted on April 18, 2018 by Android

Hardly a day goes by without a research study or article published talking sh*t—or more precisely, talking about the gut microbiome. When it comes to cutting-edge innovations in medicine, all signs point to the microbiome. Maybe we should have listened to Hippocrates: “All disease begins in the gut.”

Your microbiome is mostly located in your gut and contains trillions of little guys and gals called microbes. If you want to optimize your health, biohack your body, make progress against chronic disease, or know which foods are right for you—almost all of this information can be found in your microbiome.

My company, Viome, offers technology to measure your microscopic organisms and their behavior at a molecular level. Think of it as the Instagram of your inner world. A snapshot of what’s happening inside your body. New research about the microbiome is changing our understanding of who we are as humans and how the human body functions.

It turns out the microbiome may be mission control for your body and mind. Your healthy microbiome is part best friend, part power converter, part engine, and part pharmacist. At Viome, we’re working to analyze these microbial functions and recommend a list of personalized food and supplements to keep these internal complex machines in a finely tuned balance.

We now have more information than ever before about what your microbiome is doing, and it’s going to help you and the rest of the world do a whole lot better. The new insights emerging from microbiome research are changing our perception of what keeps us healthy and what makes us sick. This new understanding of the microbiome activities may put an end to conflicting food advice and make fad diets a thing of the past.

What are these new insights showing us? The information is nothing short of mind-blowing. The value of your poop just got an upgrade.

Here are some of the amazing things we’ve learned from our work at Viome.

1. Was Popeye wrong? Why “health food” isn’t necessarily healthy.
Each week there is a new fad diet released, discussed, and followed. The newest “research” shows that this is now the superfood to eat for everyone. But, too often, the fad diet is just a regurgitation of what worked for one person and shouldn’t be followed by everyone else.

For example, we’ve been told to eat our greens and that greens and nuts are “anti-inflammatory,” but this is actually not always true. Spinach, bran, rhubarb, beets, nuts, and nut butters all contain oxalate. We now know that oxalate-containing food can be harmful, unless you have the microbes present that can metabolize it into a non-harmful substance.

30% of Viome customers do not have the microbes to metabolize oxalates properly. In other words, “healthy foods” like spinach are actually not healthy for these people.

Looks like not everyone should follow Popeye’s food plan.

2. Aren’t foods containing “antioxidants” always good for everyone?
Just like oxalates, polyphenols in foods are usually considered very healthy, but unless you have microbes that utilize specific polyphenols, you may not get full benefit from them. One example is a substance found in these foods called ellagic acid. We can detect if your microbiome is metabolizing ellagic acid and converting it into urolithin A. It is only the urolithin A that has anti-inflammatory and antioxidant effects. Without the microbes to do this conversion you will not benefit from the ellagic acid in foods.

Examples: Walnuts, raspberries, pomegranate, blackberries, pecans, and cranberries all contain ellagic acid.

We have analyzed tens of thousands of people, and only about 50% of the people actually benefit from eating more foods containing ellagic acid.

3. You’re probably eating too much protein (and it may be causing inflammation).
When you think high-protein diet, you think paleo, keto, and high-performance diets.

Protein is considered good for you. It helps build muscle and provide energy—but if you eat too much, it can cause inflammation and decrease longevity.

We can analyze the activity of your microbiome to determine if you are eating too much protein that feeds protein-fermenting bacteria like Alistipes putredinis and Tannerella forsythia, and if these organisms are producing harmful substances such as ammonia, hydrogen sulfide, p-cresol, or putrescine. These substances can damage your gut lining and lead to things like leaky gut.

4. Something’s fishy. Are “healthy foods” causing heart disease?
Choline in certain foods can get converted by bacteria into a substance called trimethylamine (TMA) that is associated with heart disease when it gets absorbed into your body and converted to TMAO. However, TMA conversion doesn’t happen in individuals without these types of bacteria in their microbiome.

We can see the TMA production pathways and many of the gammaproteobacteria that do this conversion.

What foods contain choline? Liver, salmon, chickpeas, split peas, eggs, navy beans, peanuts, and many others.

Before you decide to go full-on pescatarian or paleo, you may want to check if your microbiome is producing TMA with that salmon or steak.

5. Hold up, Iron Man. We can see inflammation from too much iron.
Minerals like iron in your food can, in certain inflammatory microbial environments, promote growth of pathogens like Esherichia, Shigella, and Salmonella.

Maybe it wasn’t just that raw chicken that gave you food poisoning, but your toxic microbiome that made you sick.

On the other hand, when you don’t have enough iron, you could become anemic leading to weakness and shortness of breath.

So, just like Iron Man, it’s about finding your balance so that you can fly.

6. Are you anxious or stressed? Your poop will tell you.
Our gut and brain are connected via the vagus nerve. A large majority of neurotransmitters are either produced or consumed by our microbiome. In fact, some 90% of all serotonin (a feel-good neurotransmitter) is produced by your gut microbiome and not by your brain.

When you have a toxic microbiome that’s producing a large amount of toxins like hydrogen sulfide, the lining of your gut starts to deteriorate into what’s known as leaky gut. Think of leaky gut as your gut not having healthy borders or boundaries. And when this happens, all kinds of disease can emerge. When the barrier of the gut breaks down, it starts a chain reaction causing low-grade chronic inflammation—which has been identified as a potential source of depression and higher levels of anxiety, in addition to many other chronic diseases.

We’re not saying you shouldn’t meditate, but if you want to get the most out of your meditation and really reduce your stress levels, make sure you are eating the right food that promotes a healthy microbiome.

7. Your microbiome is better than Red Bull.
If you want more energy, get your microbiome back into balance.

No you don’t need three pots of coffee to keep you going, you just need a balanced microbiome.

Your microbiome is responsible for calorie extraction, or creating energy, through pathways such as the Tricarboxylic acid cycle. Our bodies depend on the energy that our microbiome produces.

How much energy we get from our food is dependent on how efficient our microbiome is at converting the food into energy. High-performing microbiomes are excellent at converting food into energy. This is great when you are an athlete and need the extra energy, but if you don’t use up the energy it may be the source of some of those unwanted pounds.

If the microbes can’t or won’t metabolize the glucose (sugar) that you eat, it will be stored as fat. If the microbes are extracting too many calories from your food or producing lipopolysaccharides (LPS) and causing metabolic endotoxemia leading to activation of toll-like receptors and insulin resistance you may end up storing what you eat as fat.

Think of your microbiome as Doc Brown’s car from the future—it can take pretty much anything and turn it into fuel if it’s strong and resilient enough.

8. We can see your joint pain in your poop.
Got joint pain? Your microbiome can tell you why.

Lipopolysaccharide (LPS) is a key pro-inflammatory molecule made by some of your microbes. If your microbes are making too much LPS, it can wreak havoc on your immune system by putting it into overdrive. When your immune system goes on the warpath there is often collateral damage to your joints and other body parts.

Perhaps balancing your microbiome is a better solution than reaching for the glucosamine. Think of your microbiome as the top general of your immune army. It puts your immune system through basic training and determines when it goes to war.

Ideally, your immune system wins the quick battle and gets some rest, but sometimes if your microbiome keeps it on constant high alert it becomes a long, drawn-out war resulting in chronic inflammation and chronic diseases.

Are you really “getting older” or is your microbiome just making you “feel” older because it keeps giving warnings to your immune system ultimately leading to chronic pain?

Before you throw in the towel on your favorite activities, check your microbiome. And, if you have anything with “itis” in it, it’s possible that when you balance your microbiome the inflammation from your “itis” will be reduced.

9. Your gut is doing the talking for your mouth.
When you have low stomach acid, your mouth bacteria makes it down to your GI tract.

Stomach acid is there to protect you from the bacteria in your mouth and the parasites and fungi that are in your food. If you don’t have enough of it, the bacteria in your mouth will invade your gut. This invasion is associated with and a risk factor for autoimmune disease and inflammation in the gut.

We are learning that low stomach acid is perhaps one of the major causes of chronic disease. This stomach acid is essential to kill mouth bacteria and help us digest our food.

What kinds of things cause low stomach acid? Stress and antacids like Nexium, Zantac, and Prilosec.

10. Carbs can be protein precursors.
Rejoice! Perhaps carbs aren’t as bad as we thought (as long as your microbiome is up to the task). We can see if some of the starches you eat can be made into amino acids by the microbiome.

Our microbiome makes 20% of our branched-chain amino acids (BCAAs) for us, and it will adapt to make these vital BCAAs for us in almost any way it can.

Essentially, your microbiome is hooking up carbons and hydrogens into different formulations of BCAAs, depending on what you feed it. The microbiome is excellent at adapting and pivoting based on the food you feed it and the environment that it’s in.

So, good news: Carbs are protein precursors, as long as you have the right microbiome.

Stop Talking Sh*t Now
Your microbiome is a world class entrepreneur that can take low-grade sources of food and turn them into valuable and useable energy.

You have a best friend and confidant within you that is working wonders to make sure you have energy and that all of your needs are met.

And, just like a best friend, if you take great care of your microbiome, it will take great care of you.

Given the research emerging daily about the microbiome and its importance on your quality of life, prioritizing the health of your microbiome is essential.

When you have a healthy microbiome, you’ll have a healthy life.

It’s now clear that some of the greatest insights for your health will come from your poop.

It’s time to stop talking sh*t and get your sh*t together. Your life may depend on it.

Viome can help you identify what your microbiome is actually doing. The combination of Viome’s metatranscriptomic technology and cutting-edge artificial intelligence is paving a brand new path forward for microbiome health.

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Posted in Human Robots

#432519 Robot Cities: Three Urban Prototypes for ...

Posted on April 14, 2018 by Android

Before I started working on real-world robots, I wrote about their fictional and historical ancestors. This isn’t so far removed from what I do now. In factories, labs, and of course science fiction, imaginary robots keep fueling our imagination about artificial humans and autonomous machines.

Real-world robots remain surprisingly dysfunctional, although they are steadily infiltrating urban areas across the globe. This fourth industrial revolution driven by robots is shaping urban spaces and urban life in response to opportunities and challenges in economic, social, political, and healthcare domains. Our cities are becoming too big for humans to manage.

Good city governance enables and maintains smooth flow of things, data, and people. These include public services, traffic, and delivery services. Long queues in hospitals and banks imply poor management. Traffic congestion demonstrates that roads and traffic systems are inadequate. Goods that we increasingly order online don’t arrive fast enough. And the WiFi often fails our 24/7 digital needs. In sum, urban life, characterized by environmental pollution, speedy life, traffic congestion, connectivity and increased consumption, needs robotic solutions—or so we are led to believe.

Is this what the future holds? Image Credit: Photobank gallery / Shutterstock.com
In the past five years, national governments have started to see automation as the key to (better) urban futures. Many cities are becoming test beds for national and local governments for experimenting with robots in social spaces, where robots have both practical purpose (to facilitate everyday life) and a very symbolic role (to demonstrate good city governance). Whether through autonomous cars, automated pharmacists, service robots in local stores, or autonomous drones delivering Amazon parcels, cities are being automated at a steady pace.

Many large cities (Seoul, Tokyo, Shenzhen, Singapore, Dubai, London, San Francisco) serve as test beds for autonomous vehicle trials in a competitive race to develop “self-driving” cars. Automated ports and warehouses are also increasingly automated and robotized. Testing of delivery robots and drones is gathering pace beyond the warehouse gates. Automated control systems are monitoring, regulating and optimizing traffic flows. Automated vertical farms are innovating production of food in “non-agricultural” urban areas around the world. New mobile health technologies carry promise of healthcare “beyond the hospital.” Social robots in many guises—from police officers to restaurant waiters—are appearing in urban public and commercial spaces.

Vertical indoor farm. Image Credit: Aisyaqilumaranas / Shutterstock.com
As these examples show, urban automation is taking place in fits and starts, ignoring some areas and racing ahead in others. But as yet, no one seems to be taking account of all of these various and interconnected developments. So, how are we to forecast our cities of the future? Only a broad view allows us to do this. To give a sense, here are three examples: Tokyo, Dubai, and Singapore.

Tokyo
Currently preparing to host the Olympics 2020, Japan’s government also plans to use the event to showcase many new robotic technologies. Tokyo is therefore becoming an urban living lab. The institution in charge is the Robot Revolution Realization Council, established in 2014 by the government of Japan.

Tokyo: city of the future. Image Credit: ESB Professional / Shutterstock.com
The main objectives of Japan’s robotization are economic reinvigoration, cultural branding, and international demonstration. In line with this, the Olympics will be used to introduce and influence global technology trajectories. In the government’s vision for the Olympics, robot taxis transport tourists across the city, smart wheelchairs greet Paralympians at the airport, ubiquitous service robots greet customers in 20-plus languages, and interactively augmented foreigners speak with the local population in Japanese.

Tokyo shows us what the process of state-controlled creation of a robotic city looks like.

Singapore
Singapore, on the other hand, is a “smart city.” Its government is experimenting with robots with a different objective: as physical extensions of existing systems to improve management and control of the city.

In Singapore, the techno-futuristic national narrative sees robots and automated systems as a “natural” extension of the existing smart urban ecosystem. This vision is unfolding through autonomous delivery robots (the Singapore Post’s delivery drone trials in partnership with AirBus helicopters) and driverless bus shuttles from Easymile, EZ10.

Meanwhile, Singapore hotels are employing state-subsidized service robots to clean rooms and deliver linen and supplies, and robots for early childhood education have been piloted to understand how robots can be used in pre-schools in the future. Health and social care is one of the fastest growing industries for robots and automation in Singapore and globally.

Dubai
Dubai is another emerging prototype of a state-controlled smart city. But rather than seeing robotization simply as a way to improve the running of systems, Dubai is intensively robotizing public services with the aim of creating the “happiest city on Earth.” Urban robot experimentation in Dubai reveals that authoritarian state regimes are finding innovative ways to use robots in public services, transportation, policing, and surveillance.

National governments are in competition to position themselves on the global politico-economic landscape through robotics, and they are also striving to position themselves as regional leaders. This was the thinking behind the city’s September 2017 test flight of a flying taxi developed by the German drone firm Volocopter—staged to “lead the Arab world in innovation.” Dubai’s objective is to automate 25% of its transport system by 2030.

It is currently also experimenting with Barcelona-based PAL Robotics’ humanoid police officer and Singapore-based vehicle OUTSAW. If the experiments are successful, the government has announced it will robotize 25% of the police force by 2030.

While imaginary robots are fueling our imagination more than ever—from Ghost in the Shell to Blade Runner 2049—real-world robots make us rethink our urban lives.

These three urban robotic living labs—Tokyo, Singapore, Dubai—help us gauge what kind of future is being created, and by whom. From hyper-robotized Tokyo to smartest Singapore and happy, crime-free Dubai, these three comparisons show that, no matter what the context, robots are perceived as a means to achieve global futures based on a specific national imagination. Just like the films, they demonstrate the role of the state in envisioning and creating that future.

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

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Posted in Human Robots

#432487 Can We Make a Musical Turing Test?

Posted on April 8, 2018 by Android

As artificial intelligence advances, we’re encountering the same old questions. How much of what we consider to be fundamentally human can be reduced to an algorithm? Can we create something sufficiently advanced that people can no longer distinguish between the two? This, after all, is the idea behind the Turing Test, which has yet to be passed.

At first glance, you might think music is beyond the realm of algorithms. Birds can sing, and people can compose symphonies. Music is evocative; it makes us feel. Very often, our intense personal and emotional attachments to music are because it reminds us of our shared humanity. We are told that creative jobs are the least likely to be automated. Creativity seems fundamentally human.

But I think above all, we view it as reductionist sacrilege: to dissect beautiful things. “If you try to strangle a skylark / to cut it up, see how it works / you will stop its heart from beating / you will stop its mouth from singing.” A human musician wrote that; a machine might be able to string words together that are happy or sad; it might even be able to conjure up a decent metaphor from the depths of some neural network—but could it understand humanity enough to produce art that speaks to humans?

Then, of course, there’s the other side of the debate. Music, after all, has a deeply mathematical structure; you can train a machine to produce harmonics. “In the teachings of Pythagoras and his followers, music was inseparable from numbers, which were thought to be the key to the whole spiritual and physical universe,” according to Grout in A History of Western Music. You might argue that the process of musical composition cannot be reduced to a simple algorithm, yet musicians have often done so. Mozart, with his “Dice Music,” used the roll of a dice to decide how to order musical fragments; creativity through an 18th-century random number generator. Algorithmic music goes back a very long way, with the first papers on the subject from the 1960s.

Then there’s the techno-enthusiast side of the argument. iTunes has 26 million songs, easily more than a century of music. A human could never listen to and learn from them all, but a machine could. It could also memorize every note of Beethoven. Music can be converted into MIDI files, a nice chewable data format that allows even a character-by-character neural net you can run on your computer to generate music. (Seriously, even I could get this thing working.)

Indeed, generating music in the style of Bach has long been a test for AI, and you can see neural networks gradually learn to imitate classical composers while trying to avoid overfitting. When an algorithm overfits, it essentially starts copying the existing music, rather than being inspired by it but creating something similar: a tightrope the best human artists learn to walk. Creativity doesn’t spring from nowhere; even maverick musical geniuses have their influences.

Does a machine have to be truly ‘creative’ to produce something that someone would find valuable? To what extent would listeners’ attitudes change if they thought they were hearing a human vs. an AI composition? This all suggests a musical Turing Test. Of course, it already exists. In fact, it’s run out of Dartmouth, the school that hosted that first, seminal AI summer conference. This year, the contest is bigger than ever: alongside the PoetiX, LimeriX and LyriX competitions for poetry and lyrics, there’s a DigiKidLit competition for children’s literature (although you may have reservations about exposing your children to neural-net generated content… it can get a bit surreal).

There’s also a pair of musical competitions, including one for original compositions in different genres. Key genres and styles are represented by Charlie Parker for Jazz and the Bach chorales for classical music. There’s also a free composition, and a contest where a human and an AI try to improvise together—the AI must respond to a human spontaneously, in real time, and in a musically pleasing way. Quite a challenge! In all cases, if any of the generated work is indistinguishable from human performers, the neural net has passed the Turing Test.

Did they? Here’s part of 2017’s winning sonnet from Charese Smiley and Hiroko Bretz:

The large cabin was in total darkness.
Come marching up the eastern hill afar.
When is the clock on the stairs dangerous?
Everything seemed so near and yet so far.
Behind the wall silence alone replied.
Was, then, even the staircase occupied?
Generating the rhymes is easy enough, the sentence structure a little trickier, but what’s impressive about this sonnet is that it sticks to a single topic and appears to be a more coherent whole. I’d guess they used associated “lexical fields” of similar words to help generate something coherent. In a similar way, most of the more famous examples of AI-generated music still involve some amount of human control, even if it’s editorial; a human will build a song around an AI-generated riff, or select the most convincing Bach chorale from amidst many different samples.

We are seeing strides forward in the ability of AI to generate human voices and human likenesses. As the latter example shows, in the fake news era people have focused on the dangers of this tech– but might it also be possible to create a virtual performer, trained on a dataset of their original music? Did you ever want to hear another Beatles album, or jam with Miles Davis? Of course, these things are impossible—but could we create a similar experience that people would genuinely value? Even, to the untrained eye, something indistinguishable from the real thing?

And if it did measure up to the real thing, what would this mean? Jaron Lanier is a fascinating technology writer, a critic of strong AI, and a believer in the power of virtual reality to change the world and provide truly meaningful experiences. He’s also a composer and a musical aficionado. He pointed out in a recent interview that translation algorithms, by reducing the amount of work translators are commissioned to do, have, in some sense, profited from stolen expertise. They were trained on huge datasets purloined from human linguists and translators. If you can train an AI on someone’s creative output and it produces new music, who “owns” it?

Although companies that offer AI music tools are starting to proliferate, and some groups will argue that the musical Turing test has been passed already, AI-generated music is hardly racing to the top of the pop charts just yet. Even as the line between human-composed and AI-generated music starts to blur, there’s still a gulf between the average human and musical genius. In the next few years, we’ll see how far the current techniques can take us. It may be the case that there’s something in the skylark’s song that can’t be generated by machines. But maybe not, and then this song might need an extra verse.

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