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#435167 A Closer Look at the Robots Helping Us ...

Buck Rogers had Twiki. Luke Skywalker palled around with C-3PO and R2-D2. And astronauts aboard the International Space Station (ISS) now have their own robotic companions in space—Astrobee.

A pair of the cube-shaped robots were launched to the ISS during an April re-supply mission and are currently being commissioned for use on the space station. The free-flying space robots, dubbed Bumble and Honey, are the latest generation of robotic machines to join the human crew on the ISS.

Exploration of the solar system and beyond will require autonomous machines that can assist humans with numerous tasks—or go where we cannot. NASA has said repeatedly that robots will be instrumental in future space missions to the moon, Mars, and even to the icy moon Europa.

The Astrobee robots will specifically test robotic capabilities in zero gravity, replacing the SPHERES (Synchronized Position Hold, Engage, Reorient, Experimental Satellite) robots that have been on the ISS for more than a decade to test various technologies ranging from communications to navigation.

The 18-sided robots, each about the size of a volleyball or an oversized Dungeons and Dragons die, use CO2-based cold-gas thrusters for movement and a series of ultrasonic beacons for orientation. The Astrobee robots, on the other hand, can propel themselves autonomously around the interior of the ISS using electric fans and six cameras.

The modular design of the Astrobee robots means they are highly plug-and-play, capable of being reconfigured with different hardware modules. The robots’ software is also open-source, encouraging scientists and programmers to develop and test new algorithms and features.

And, yes, the Astrobee robots will be busy as bees once they are fully commissioned this fall, with experiments planned to begin next year. Scientists hope to learn more about how robots can assist space crews and perform caretaking duties on spacecraft.

Robots Working Together
The Astrobee robots are expected to be joined by a familiar “face” on the ISS later this year—the humanoid robot Robonaut.

Robonaut, also known as R2, was the first US-built robot on the ISS. It joined the crew back in 2011 without legs, which were added in 2014. However, the installation never entirely worked, as R2 experienced power failures that eventually led to its return to Earth last year to fix the problem. If all goes as planned, the space station’s first humanoid robot will return to the ISS to lend a hand to the astronauts and the new robotic arrivals.

In particular, NASA is interested in how the two different robotic platforms can complement each other, with an eye toward outfitting the agency’s proposed lunar orbital space station with various robots that can supplement a human crew.

“We don’t have definite plans for what would happen on the Gateway yet, but there’s a general recognition that intra-vehicular robots are important for space stations,” Astrobee technical lead Trey Smith in the NASA Intelligent Robotics Group told IEEE Spectrum. “And so, it would not be surprising to see a mobile manipulator like Robonaut, and a free flyer like Astrobee, on the Gateway.”

While the focus on R2 has been to test its capabilities in zero gravity and to use it for mundane or dangerous tasks in space, the technology enabling the humanoid robot has proven to be equally useful on Earth.

For example, R2 has amazing dexterity for a robot, with sensors, actuators, and tendons comparable to the nerves, muscles, and tendons in a human hand. Based on that design, engineers are working on a robotic glove that can help factory workers, for instance, do their jobs better while reducing the risk of repetitive injuries. R2 has also inspired development of a robotic exoskeleton for both astronauts in space and paraplegics on Earth.

Working Hard on Soft Robotics
While innovative and technologically sophisticated, Astrobee and Robonaut are typical robots in that neither one would do well in a limbo contest. In other words, most robots are limited in their flexibility and agility based on current hardware and materials.

A subfield of robotics known as soft robotics involves developing robots with highly pliant materials that mimic biological organisms in how they move. Scientists at NASA’s Langley Research Center are investigating how soft robots could help with future space exploration.

Specifically, the researchers are looking at a series of properties to understand how actuators—components responsible for moving a robotic part, such as Robonaut’s hand—can be built and used in space.

The team first 3D prints a mold and then pours a flexible material like silicone into the mold. Air bladders or chambers in the actuator expand and compress using just air.

Some of the first applications of soft robotics sound more tool-like than R2-D2-like. For example, two soft robots could connect to produce a temporary shelter for astronauts on the moon or serve as an impromptu wind shield during one of Mars’ infamous dust storms.

The idea is to use soft robots in situations that are “dangerous, dirty, or dull,” according to Jack Fitzpatrick, a NASA intern working on the soft robotics project at Langley.

Working on Mars
Of course, space robots aren’t only designed to assist humans. In many instances, they are the only option to explore even relatively close celestial bodies like Mars. Four American-made robotic rovers have been used to investigate the fourth planet from the sun since 1997.

Opportunity is perhaps the most famous, covering about 25 miles of terrain across Mars over 15 years. A dust storm knocked it out of commission last year, with NASA officially ending the mission in February.

However, the biggest and baddest of the Mars rovers, Curiosity, is still crawling across the Martian surface, sending back valuable data since 2012. The car-size robot carries 17 cameras, a laser to vaporize rocks for study, and a drill to collect samples. It is on the hunt for signs of biological life.

The next year or two could see a virtual traffic jam of robots to Mars. NASA’s Mars 2020 Rover is next in line to visit the Red Planet, sporting scientific gadgets like an X-ray fluorescence spectrometer for chemical analyses and ground-penetrating radar to see below the Martian surface.

This diagram shows the instrument payload for the Mars 2020 mission. Image Credit: NASA.
Meanwhile, the Europeans have teamed with the Russians on a rover called Rosalind Franklin, named after a famed British chemist, that will drill down into the Martian ground for evidence of past or present life as soon as 2021.

The Chinese are also preparing to begin searching for life on Mars using robots as soon as next year, as part of the country’s Mars Global Remote Sensing Orbiter and Small Rover program. The mission is scheduled to be the first in a series of launches that would culminate with bringing samples back from Mars to Earth.

Perhaps there is no more famous utterance in the universe of science fiction as “to boldly go where no one has gone before.” However, the fact is that human exploration of the solar system and beyond will only be possible with robots of different sizes, shapes, and sophistication.

Image Credit: NASA. Continue reading

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#435127 Teaching AI the Concept of ‘Similar, ...

As a human you instinctively know that a leopard is closer to a cat than a motorbike, but the way we train most AI makes them oblivious to these kinds of relations. Building the concept of similarity into our algorithms could make them far more capable, writes the author of a new paper in Science Robotics.

Convolutional neural networks have revolutionized the field of computer vision to the point that machines are now outperforming humans on some of the most challenging visual tasks. But the way we train them to analyze images is very different from the way humans learn, says Atsuto Maki, an associate professor at KTH Royal Institute of Technology.

“Imagine that you are two years old and being quizzed on what you see in a photo of a leopard,” he writes. “You might answer ‘a cat’ and your parents might say, ‘yeah, not quite but similar’.”

In contrast, the way we train neural networks rarely gives that kind of partial credit. They are typically trained to have very high confidence in the correct label and consider all incorrect labels, whether ”cat” or “motorbike,” equally wrong. That’s a mistake, says Maki, because ignoring the fact that something can be “less wrong” means you’re not exploiting all of the information in the training data.

Even when models are trained this way, there will be small differences in the probabilities assigned to incorrect labels that can tell you a lot about how well the model can generalize what it has learned to unseen data.

If you show a model a picture of a leopard and it gives “cat” a probability of five percent and “motorbike” one percent, that suggests it picked up on the fact that a cat is closer to a leopard than a motorbike. In contrast, if the figures are the other way around it means the model hasn’t learned the broad features that make cats and leopards similar, something that could potentially be helpful when analyzing new data.

If we could boost this ability to identify similarities between classes we should be able to create more flexible models better able to generalize, says Maki. And recent research has demonstrated how variations of an approach called regularization might help us achieve that goal.

Neural networks are prone to a problem called “overfitting,” which refers to a tendency to pay too much attention to tiny details and noise specific to their training set. When that happens, models will perform excellently on their training data but poorly when applied to unseen test data without these particular quirks.

Regularization is used to circumvent this problem, typically by reducing the network’s capacity to learn all this unnecessary information and therefore boost its ability to generalize to new data. Techniques are varied, but generally involve modifying the network’s structure or the strength of the weights between artificial neurons.

More recently, though, researchers have suggested new regularization approaches that work by encouraging a broader spread of probabilities across all classes. This essentially helps them capture more of the class similarities, says Maki, and therefore boosts their ability to generalize.

One such approach was devised in 2017 by Google Brain researchers, led by deep learning pioneer Geoffrey Hinton. They introduced a penalty to their training process that directly punished overconfident predictions in the model’s outputs, and a technique called label smoothing that prevents the largest probability becoming much larger than all others. This meant the probabilities were lower for correct labels and higher for incorrect ones, which was found to boost performance of models on varied tasks from image classification to speech recognition.

Another came from Maki himself in 2017 and achieves the same goal, but by suppressing high values in the model’s feature vector—the mathematical construct that describes all of an object’s important characteristics. This has a knock-on effect on the spread of output probabilities and also helped boost performance on various image classification tasks.

While it’s still early days for the approach, the fact that humans are able to exploit these kinds of similarities to learn more efficiently suggests that models that incorporate them hold promise. Maki points out that it could be particularly useful in applications such as robotic grasping, where distinguishing various similar objects is important.

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#435119 Are These Robots Better Than You at ...

Robot technology is evolving at breakneck speed. SoftBank’s Pepper is found in companies across the globe and is rapidly improving its conversation skills. Telepresence robots open up new opportunities for remote working, while Boston Dynamics’ Handle robot could soon (literally) take a load off human colleagues in warehouses.

But warehouses and offices aren’t the only places where robots are lining up next to humans.

Toyota’s Cue 3 robot recently showed off its basketball skills, putting up better numbers than the NBA’s most accurate three-point shooter, the Golden State Warriors’ Steph Curry.

Cue 3 is still some way from being ready to take on Curry, or even amateur basketball players, in a real game. However, it is the latest member of a growing cast of robots challenging human dominance in sports.

As these robots continue to develop, they not only exemplify the speed of exponential technology development, but also how those technologies are improving human capabilities.

Meet the Contestants
The list of robots in sports is surprisingly long and diverse. There are robot skiers, tumblers, soccer players, sumos, and even robot game jockeys. Introductions to a few of them are in order.

Robot: Forpheus
Sport: Table tennis
Intro: Looks like something out of War of the Worlds equipped with a ping pong bat instead of a death ray.
Ability level: Capable of counteracting spin shots and good enough to beat many beginners.

Robot: Sumo bot
Sport: Sumo wrestling
Intro: Hyper-fast, hyper-aggressive. Think robot equivalent to an angry wasp on six cans of Red Bull crossed with a very small tank.
Ability level: Flies around the ring way faster than any human sumo. Tend to drive straight out of the ring at times.

Robot: Cue 3
Sport: Basketball
Intro: Stands at an imposing 6 foot and 10 inches, so pretty much built for the NBA. Looks a bit like something that belongs in a video game.
Ability level: A 62.5 percent three-pointer percentage, which is better than Steph Curry’s; is less mobile than Charles Barkley – in his current form.

Robot: Robo Cup Robots
Intro: The future of soccer. If everything goes to plan, a team of robots will take on the Lionel Messis and Cristiano Ronaldos of 2050 and beat them in a full 11 vs. 11 game.
Ability level: Currently plays soccer more like the six-year-olds I used to coach than Lionel Messi.

The Limiting Factor
The skill level of all the robots above is impressive, and they are doing things that no human contestant can. The sumo bots’ inhuman speed is self-evident. Forpheus’ ability to track the ball with two cameras while simultaneously tracking its opponent with two other cameras requires a look at the spec sheet, but is similarly beyond human capability. While Cue 3 can’t move, it makes shots from the mid-court logo look easy.

Robots are performing at a level that was confined to the realm of science fiction at the start of the millennium. The speed of development indicates that in the near future, my national team soccer coach would likely call up a robot instead of me (he must have lost my number since he hasn’t done so yet. It’s the only logical explanation), and he’d be right to do so.

It is also worth considering that many current sports robots have a humanoid form, which limits their ability. If engineers were to optimize robot design to outperform humans in specific categories, many world champions would likely already be metallic.

Swimming is perhaps one of the most obvious. Even Michael Phelps would struggle to keep up with a torpedo-shaped robot, and if you beefed up a sumo robot to human size, human sumos might impress you by running away from them with a 100-meter speed close to Usain Bolt’s.

In other areas, the playing field for humans and robots is rapidly leveling. One likely candidate for the first head-to-head competitions is racing, where self-driving cars from the Roborace League could perhaps soon be ready to race the likes of Lewis Hamilton.

Tech Pushing Humans
Perhaps one of the biggest reasons why it may still take some time for robots to surpass us is that they, along with other exponential technologies, are already making us better at sports.

In Japan, elite volleyball players use a robot to practice their attacks. Some American football players also practice against robot opponents and hone their skills using VR.

On the sidelines, AI is being used to analyze and improve athletes’ performance, and we may soon see the first AI coaches, not to mention referees.

We may even compete in games dreamt up by our electronic cousins. SpeedGate, a new game created by an AI by studying 400 different sports, is a prime example of that quickly becoming a possibility.

However, we will likely still need to make the final call on what constitutes a good game. The AI that created SpeedGate reportedly also suggested less suitable pastimes, like underwater parkour and a game that featured exploding frisbees. Both of these could be fun…but only if you’re as sturdy as a robot.

Image Credit: RoboCup Standard Platform League 2018, ©The Robocup Federation. Published with permission of reproduction granted by the RoboCup Federation. Continue reading

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#435110 5 Coming Breakthroughs in Energy and ...

The energy and transportation industries are being aggressively disrupted by converging exponential technologies.

In just five days, the sun provides Earth with an energy supply exceeding all proven reserves of oil, coal, and natural gas. Capturing just 1 part in 8,000 of this available solar energy would allow us to meet 100 percent of our energy needs.

As we leverage renewable energy supplied by the sun, wind, geothermal sources, and eventually fusion, we are rapidly heading towards a future where 100 percent of our energy needs will be met by clean tech in just 30 years.

During the past 40 years, solar prices have dropped 250-fold. And as these costs plummet, solar panel capacity continues to grow exponentially.

On the heels of energy abundance, we are additionally witnessing a new transportation revolution, which sets the stage for a future of seamlessly efficient travel at lower economic and environmental costs.

Top 5 Transportation Breakthroughs (2019-2024)
Entrepreneur and inventor Ramez Naam is my go-to expert on all things energy and environment. Currently serving as the Energy Co-Chair at Singularity University, Naam is the award-winning author of five books, including the Nexus series of science fiction novels. Having spent 13 years at Microsoft, his software has touched the lives of over a billion people. Naam holds over 20 patents, including several shared with co-inventor Bill Gates.

In the next five years, he forecasts five respective transportation and energy trends, each poised to disrupt major players and birth entirely new business models.

Let’s dive in.

Autonomous cars drive 1 billion miles on US roads. Then 10 billion

Alphabet’s Waymo alone has already reached 10 million miles driven in the US. The 600 Waymo vehicles on public roads drive a total of 25,000 miles each day, and computer simulations provide an additional 25,000 virtual cars driving constantly. Since its launch in December, the Waymo One service has transported over 1,000 pre-vetted riders in the Phoenix area.

With more training miles, the accuracy of these cars continues to improve. Since last year, GM Cruise has improved its disengagement rate by 321 percent since last year, trailing close behind with only one human intervention per 5,025 miles self-driven.

Autonomous taxis as a service in top 20 US metro areas

Along with its first quarterly earnings released last week, Lyft recently announced that it would expand its Waymo partnership with the upcoming deployment of 10 autonomous vehicles in the Phoenix area. While individuals previously had to partake in Waymo’s “early rider program” prior to trying Waymo One, the Lyft partnership will allow anyone to ride in a self-driving vehicle without a prior NDA.

Strategic partnerships will grow increasingly essential between automakers, self-driving tech companies, and rideshare services. Ford is currently working with Volkswagen, and Nvidia now collaborates with Daimler (Mercedes) and Toyota. Just last week, GM Cruise raised another $1.15 billion at a $19 billion valuation as the company aims to launch a ride-hailing service this year.

“They’re going to come to the Bay Area, Los Angeles, Houston, other cities with relatively good weather,” notes Naam. “In every major city within five years in the US and in some other parts of the world, you’re going to see the ability to hail an autonomous vehicle as a ride.”

Cambrian explosion of vehicle formats

Naam explains, “If you look today at the average ridership of a taxi, a Lyft, or an Uber, it’s about 1.1 passengers plus the driver. So, why do you need a large four-seater vehicle for that?”

Small electric, autonomous pods that seat as few as two people will begin to emerge, satisfying the majority of ride-hailing demands we see today. At the same time, larger communal vehicles will appear, such as Uber Express, that will undercut even the cheapest of transportation methods—buses, trams, and the like. Finally, last-mile scooter transit (or simply short-distance walks) might connect you to communal pick-up locations.

By 2024, an unimaginably diverse range of vehicles will arise to meet every possible need, regardless of distance or destination.

Drone delivery for lightweight packages in at least one US city

Wing, the Alphabet drone delivery startup, recently became the first company to gain approval from the Federal Aviation Administration (FAA) to make deliveries in the US. Having secured approval to deliver to 100 homes in Canberra, Australia, Wing additionally plans to begin delivering goods from local businesses in the suburbs of Virginia.

The current state of drone delivery is best suited for lightweight, urgent-demand payloads like pharmaceuticals, thumb drives, or connectors. And as Amazon continues to decrease its Prime delivery times—now as speedy as a one-day turnaround in many cities—the use of drones will become essential.

Robotic factories drive onshoring of US factories… but without new jobs

The supply chain will continue to shorten and become more agile with the re-onshoring of manufacturing jobs in the US and other countries. Naam reasons that new management and software jobs will drive this shift, as these roles develop the necessary robotics to manufacture goods. Equally as important, these robotic factories will provide a more humane setting than many of the current manufacturing practices overseas.

Top 5 Energy Breakthroughs (2019-2024)

First “1 cent per kWh” deals for solar and wind signed

Ten years ago, the lowest price of solar and wind power fell between 10 to 12 cents per kilowatt hour (kWh), over twice the price of wholesale power from coal or natural gas.

Today, the gap between solar/wind power and fossil fuel-generated electricity is nearly negligible in many parts of the world. In G20 countries, fossil fuel electricity costs between 5 to 17 cents per kWh, while the average cost per kWh of solar power in the US stands at under 10 cents.

Spanish firm Solarpack Corp Technological recently won a bid in Chile for a 120 MW solar power plant supplying energy at 2.91 cents per kWh. This deal will result in an estimated 25 percent drop in energy costs for Chilean businesses by 2021.

Naam indicates, “We will see the first unsubsidized 1.0 cent solar deals in places like Chile, Mexico, the Southwest US, the Middle East, and North Africa, and we’ll see similar prices for wind in places like Mexico, Brazil, and the US Great Plains.”

Solar and wind will reach >15 percent of US electricity, and begin to drive all growth

Just over eight percent of energy in the US comes from solar and wind sources. In total, 17 percent of American energy is derived from renewable sources, while a whopping 63 percent is sourced from fossil fuels, and 17 percent from nuclear.

Last year in the U.K., twice as much energy was generated from wind than from coal. For over a week in May, the U.K. went completely coal-free, using wind and solar to supply 35 percent and 21 percent of power, respectively. While fossil fuels remain the primary electricity source, this week-long experiment highlights the disruptive potential of solar and wind power that major countries like the U.K. are beginning to emphasize.

“Solar and wind are still a relatively small part of the worldwide power mix, only about six percent. Within five years, it’s going to be 15 percent in the US and more than close to that worldwide,” Naam predicts. “We are nearing the point where we are not building any new fossil fuel power plants.”

It will be cheaper to build new solar/wind/batteries than to run on existing coal

Last October, Northern Indiana utility company NIPSCO announced its transition from a 65 percent coal-powered state to projected coal-free status by 2028. Importantly, this decision was made purely on the basis of financials, with an estimated $4 billion in cost savings for customers. The company has already begun several initiatives in solar, wind, and batteries.

NextEra, the largest power generator in the US, has taken on a similar goal, making a deal last year to purchase roughly seven million solar panels from JinkoSolar over four years. Leading power generators across the globe have vocalized a similar economic case for renewable energy.

ICE car sales have now peaked. All car sales growth will be electric

While electric vehicles (EV) have historically been more expensive for consumers than internal combustion engine-powered (ICE) cars, EVs are cheaper to operate and maintain. The yearly cost of operating an EV in the US is about $485, less than half the $1,117 cost of operating a gas-powered vehicle.

And as battery prices continue to shrink, the upfront costs of EVs will decline until a long-term payoff calculation is no longer required to determine which type of car is the better investment. EVs will become the obvious choice.

Many experts including Naam believe that ICE-powered vehicles peaked worldwide in 2018 and will begin to decline over the next five years, as has already been demonstrated in the past five months. At the same time, EVs are expected to quadruple their market share to 1.6 percent this year.

New storage technologies will displace Li-ion batteries for tomorrow’s most demanding applications

Lithium ion batteries have dominated the battery market for decades, but Naam anticipates new storage technologies will take hold for different contexts. Flow batteries, which can collect and store solar and wind power at large scales, will supply city grids. Already, California’s Independent System Operator, the nonprofit that maintains the majority of the state’s power grid, recently installed a flow battery system in San Diego.

Solid-state batteries, which consist of entirely solid electrolytes, will supply mobile devices in cars. A growing body of competitors, including Toyota, BMW, Honda, Hyundai, and Nissan, are already working on developing solid-state battery technology. These types of batteries offer up to six times faster charging periods, three times the energy density, and eight years of added lifespan, compared to lithium ion batteries.

Final Thoughts
Major advancements in transportation and energy technologies will continue to converge over the next five years. A case in point, Tesla’s recent announcement of its “robotaxi” fleet exemplifies the growing trend towards joint priority of sustainability and autonomy.

On the connectivity front, 5G and next-generation mobile networks will continue to enable the growth of autonomous fleets, many of which will soon run on renewable energy sources. This growth demands important partnerships between energy storage manufacturers, automakers, self-driving tech companies, and ridesharing services.

In the eco-realm, increasingly obvious economic calculi will catalyze consumer adoption of autonomous electric vehicles. In just five years, Naam predicts that self-driving rideshare services will be cheaper than owning a private vehicle for urban residents. And by the same token, plummeting renewable energy costs will make these fuels far more attractive than fossil fuel-derived electricity.

As universally optimized AI systems cut down on traffic, aggregate time spent in vehicles will decimate, while hours in your (or not your) car will be applied to any number of activities as autonomous systems steer the way. All the while, sharing an electric vehicle will cut down not only on your carbon footprint but on the exorbitant costs swallowed by your previous SUV. How will you spend this extra time and money? What new natural resources will fuel your everyday life?

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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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