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#438749 Folding Drone Can Drop Into Inaccessible ...

Inspecting old mines is a dangerous business. For humans, mines can be lethal: prone to rockfalls and filled with noxious gases. Robots can go where humans might suffocate, but even robots can only do so much when mines are inaccessible from the surface.

Now, researchers in the UK, led by Headlight AI, have developed a drone that could cast a light in the darkness. Named Prometheus, this drone can enter a mine through a borehole not much larger than a football, before unfurling its arms and flying around the void. Once down there, it can use its payload of scanning equipment to map mines where neither humans nor robots can presently go. This, the researchers hope, could make mine inspection quicker and easier. The team behind Prometheus published its design in November in the journal Robotics.

Mine inspection might seem like a peculiarly specific task to fret about, but old mines can collapse, causing the ground to sink and damaging nearby buildings. It’s a far-reaching threat: the geotechnical engineering firm Geoinvestigate, based in Northeast England, estimates that around 8 percent of all buildings in the UK are at risk from any of the thousands of abandoned coal mines near the country’s surface. It’s also a threat to transport, such as road and rail. Indeed, Prometheus is backed by Network Rail, which operates Britain’s railway infrastructure.

Such grave dangers mean that old mines need periodic check-ups. To enter depths that are forbidden to traditional wheeled robots—such as those featured in the DARPA SubT Challenge—inspectors today drill boreholes down into the mine and lower scanners into the darkness.

But that can be an arduous and often fruitless process. Inspecting the entirety of a mine can take multiple boreholes, and that still might not be enough to chart a complete picture. Mines are jagged, labyrinthine places, and much of the void might lie out of sight. Furthermore, many old mines aren’t well-mapped, so it’s hard to tell where best to enter them.

Prometheus can fly around some of those challenges. Inspectors can lower Prometheus, tethered to a docking apparatus, down a single borehole. Once inside the mine, the drone can undock and fly around, using LIDAR scanners—common in mine inspection today—to generate a 3D map of the unknown void. Prometheus can fly through the mine autonomously, using infrared data to plot out its own course.

Other drones exist that can fly underground, but they’re either too small to carry a relatively heavy payload of scanning equipment, or too large to easily fit down a borehole. What makes Prometheus unique is its ability to fold its arms, allowing it to squeeze down spaces its counterparts cannot.

It’s that ability to fold and enter a borehole that makes Prometheus remarkable, says Jason Gross, a professor of mechanical and aerospace engineering at West Virginia University. Gross calls Prometheus “an exciting idea,” but he does note that it has a relatively short flight window and few abilities beyond scanning.

The researchers have conducted a number of successful test flights, both in a basement and in an old mine near Shrewsbury, England. Not only was Prometheus able to map out its space, the drone was able to plot its own course in an unknown area.

The researchers’ next steps, according to Puneet Chhabra, co-founder of Headlight AI, will be to test Prometheus’s ability to unfold in an actual mine. Following that, researchers plan to conduct full-scale test flights by the end of 2021. Continue reading

Posted in Human Robots

#438014 Meet Blueswarm, a Smart School of ...

Anyone who’s seen an undersea nature documentary has marveled at the complex choreography that schooling fish display, a darting, synchronized ballet with a cast of thousands.

Those instinctive movements have inspired researchers at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS), and the Wyss Institute for Biologically Inspired Engineering. The results could improve the performance and dependability of not just underwater robots, but other vehicles that require decentralized locomotion and organization, such as self-driving cars and robotic space exploration.

The fish collective called Blueswarm was created by a team led by Radhika Nagpal, whose lab is a pioneer in self-organizing systems. The oddly adorable robots can sync their movements like biological fish, taking cues from their plastic-bodied neighbors with no external controls required. Nagpal told IEEE Spectrum that this marks a milestone, demonstrating complex 3D behaviors with implicit coordination in underwater robots.

“Insights from this research will help us develop future miniature underwater swarms that can perform environmental monitoring and search in visually-rich but fragile environments like coral reefs,” Nagpal said. “This research also paves a way to better understand fish schools, by synthetically recreating their behavior.”

The research is published in Science Robotics, with Florian Berlinger as first author. Berlinger said the “Bluedot” robots integrate a trio of blue LED lights, a lithium-polymer battery, a pair of cameras, a Raspberry Pi computer and four controllable fins within a 3D-printed hull. The fish-lens cameras detect LED’s of their fellow swimmers, and apply a custom algorithm to calculate distance, direction and heading.

Based on that simple production and detection of LED light, the team proved that Blueswarm could self-organize behaviors, including aggregation, dispersal and circle formation—basically, swimming in a clockwise synchronization. Researchers also simulated a successful search mission, an autonomous Finding Nemo. Using their dispersion algorithm, the robot school spread out until one could detect a red light in the tank. Its blue LEDs then flashed, triggering the aggregation algorithm to gather the school around it. Such a robot swarm might prove valuable in search-and-rescue missions at sea, covering miles of open water and reporting back to its mates.

“Each Bluebot implicitly reacts to its neighbors’ positions,” Berlinger said. The fish—RoboCod, perhaps?—also integrate a Wifi module to allow uploading new behaviors remotely. The lab’s previous efforts include a 1,000-strong army of “Kilobots,” and a robotic construction crew inspired by termites. Both projects operated in two-dimensional space. But a 3D environment like air or water posed a tougher challenge for sensing and movement.

In nature, Berlinger notes, there’s no scaly CEO to direct the school’s movements. Nor do fish communicate their intentions. Instead, so-called “implicit coordination” guides the school’s collective behavior, with individual members executing high-speed moves based on what they see their neighbors doing. That decentralized, autonomous organization has long fascinated scientists, including in robotics.

“In these situations, it really benefits you to have a highly autonomous robot swarm that is self-sufficient. By using implicit rules and 3D visual perception, we were able to create a system with a high degree of autonomy and flexibility underwater where things like GPS and WiFi are not accessible.”

Berlinger adds the research could one day translate to anything that requires decentralized robots, from self-driving cars and Amazon warehouse vehicles to exploration of faraway planets, where poor latency makes it impossible to transmit commands quickly. Today’s semi-autonomous cars face their own technical hurdles in reliably sensing and responding to their complex environments, including when foul weather obscures onboard sensors or road markers, or when they can’t fix position via GPS. An entire subset of autonomous-car research involves vehicle-to-vehicle (V2V) communications that could give cars a hive mind to guide individual or collective decisions— avoiding snarled traffic, driving safely in tight convoys, or taking group evasive action during a crash that’s beyond their sensory range.

“Once we have millions of cars on the road, there can’t be one computer orchestrating all the traffic, making decisions that work for all the cars,” Berlinger said.

The miniature robots could also work long hours in places that are inaccessible to humans and divers, or even large tethered robots. Nagpal said the synthetic swimmers could monitor and collect data on reefs or underwater infrastructure 24/7, and work into tiny places without disturbing fragile equipment or ecosystems.

“If we could be as good as fish in that environment, we could collect information and be non-invasive, in cluttered environments where everything is an obstacle,” Nagpal said. Continue reading

Posted in Human Robots

#438006 Smellicopter Drone Uses Live Moth ...

Research into robotic sensing has, understandably I guess, been very human-centric. Most of us navigate and experience the world visually and in 3D, so robots tend to get covered with things like cameras and lidar. Touch is important to us, as is sound, so robots are getting pretty good with understanding tactile and auditory information, too. Smell, though? In most cases, smell doesn’t convey nearly as much information for us, so while it hasn’t exactly been ignored in robotics, it certainly isn’t the sensing modality of choice in most cases.

Part of the problem with smell sensing is that we just don’t have a good way of doing it, from a technical perspective. This has been a challenge for a long time, and it’s why we either bribe or trick animals like dogs, rats, vultures, and other animals to be our sensing systems for airborne chemicals. If only they’d do exactly what we wanted them to do all the time, this would be fine, but they don’t, so it’s not.

Until we get better at making chemical sensors, leveraging biology is the best we can do, and what would be ideal would be some sort of robot-animal hybrid cyborg thing. We’ve seen some attempts at remote controlled insects, but as it turns out, you can simplify things if you don’t use the entire insect, but instead just find a way to use its sensing system. Enter the Smellicopter.

There’s honestly not too much to say about the drone itself. It’s an open-source drone project called Crazyflie 2.0, with some additional off the shelf sensors for obstacle avoidance and stabilization. The interesting bits are a couple of passive fins that keep the drone pointed into the wind, and then the sensor, called an electroantennogram.

Image: UW

The drone’s sensor, called an electroantennogram, consists of a “single excised antenna” from a Manduca sexta hawkmoth and a custom signal processing circuit.

To make one of these sensors, you just, uh, “harvest” an antenna from a live hawkmoth. Obligingly, the moth antenna is hollow, meaning that you can stick electrodes up it. Whenever the olfactory neurons in the antenna (which is still technically alive even though it’s not attached to the moth anymore) encounter an odor that they’re looking for, they produce an electrical signal that the electrodes pick up. Plug the other ends of the electrodes into a voltage amplifier and filter, run it through an analog to digital converter, and you’ve got a chemical sensor that weighs just 1.5 gram and consumes only 2.7 mW of power. It’s significantly more sensitive than a conventional metal-oxide odor sensor, in a much smaller and more efficient form factor, making it ideal for drones.

To localize an odor, the Smellicopter uses a simple bioinspired approach called crosswind casting, which involves moving laterally left and right and then forward when an odor is detected. Here’s how it works:

The vehicle takes off to a height of 40 cm and then hovers for ten seconds to allow it time to orient upwind. The smellicopter starts casting left and right crosswind. When a volatile chemical is detected, the smellicopter will surge 25 cm upwind, and then resume casting. As long as the wind direction is fairly consistent, this strategy will bring the insect or robot increasingly closer to a singular source with each surge.

Since odors are airborne, they need a bit of a breeze to spread very far, and the Smellicopter won’t be able to detect them unless it’s downwind of the source. But, that’s just how odors work— even if you’re right next to the source, if the wind is blowing from you towards the source rather than the other way around, you might not catch a whiff of it.

Whenever the olfactory neurons in the antenna encounter an odor that they’re looking for, they produce an electrical signal that the electrodes pick up

There are a few other constraints to keep in mind with this sensor as well. First, rather than detecting something useful (like explosives), it’s going to detect the smells of pretty flowers, because moths like pretty flowers. Second, the antenna will literally go dead on you within a couple hours, since it only functions while its tissues are alive and metaphorically kicking. Interestingly, it may be possible to use CRISPR-based genetic modification to breed moths with antennae that do respond to useful smells, which would be a neat trick, and we asked the researchers—Melanie Anderson, a doctoral student of mechanical engineering at the University of Washington, in Seattle; Thomas Daniel, a UW professor of biology; and Sawyer Fuller, a UW assistant professor of mechanical engineering—about this, along with some other burning questions, via email.

IEEE Spectrum, asking the important questions first: So who came up with “Smellicopter”?

Melanie Anderson: Tom Daniel coined the term “Smellicopter”. Another runner up was “OdorRotor”!

In general, how much better are moths at odor localization than robots?

Melanie Anderson: Moths are excellent at odor detection and odor localization and need to be in order to find mates and food. Their antennae are much more sensitive and specialized than any portable man-made odor sensor. We can't ask the moths how exactly they search for odors so well, but being able to have the odor sensitivity of a moth on a flying platform is a big step in that direction.

Tom Daniel: Our best estimate is that they outperform robotic sensing by at least three orders of magnitude.

How does the localization behavior of the Smellicopter compare to that of a real moth?

Anderson: The cast-and-surge odor search strategy is a simplified version of what we believe the moth (and many other odor searching animals) are doing. It is a reactive strategy that relies on the knowledge that if you detect odor, you can assume that the source is somewhere up-wind of you. When you detect odor, you simply move upwind, and when you lose the odor signal you cast in a cross-wind direction until you regain the signal.

Can you elaborate on the potential for CRISPR to be able to engineer moths for the detection of specific chemicals?

Anderson: CRISPR is already currently being used to modify the odor detection pathways in moth species. It is one of our future efforts to specifically use this to make the antennae sensitive to other chemicals of interest, such as the chemical scent of explosives.

Sawyer Fuller: We think that one of the strengths of using a moth's antenna, in addition to its speed, is that it may provide a path to both high chemical specificity as well as high sensitivity. By expressing a preponderance of only one or a few chemosensors, we are anticipating that a moth antenna will give a strong response only to that chemical. There are several efforts underway in other research groups to make such specific, sensitive chemical detectors. Chemical sensing is an area where biology exceeds man-made systems in terms of efficiency, small size, and sensitivity. So that's why we think that the approach of trying to leverage biological machinery that already exists has some merit.

You mention that the antennae lifespan can be extended for a few days with ice- how feasible do you think this technology is outside of a research context?

Anderson: The antennae can be stored in tiny vials in a standard refrigerator or just with an ice pack to extend their life to about a week. Additionally, the process for attaching the antenna to the electrical circuit is a teachable skill. It is definitely feasible outside of a research context.

Considering the trajectory that sensor development is on, how long do you think that this biological sensor system will outperform conventional alternatives?

Anderson: It's hard to speak toward what will happen in the future, but currently, the moth antenna still stands out among any commercially-available portable sensors.

There have been some experiments with cybernetic insects; what are the advantages and disadvantages of your approach, as opposed to (say) putting some sort of tracking system on a live moth?

Daniel: I was part of a cyber insect team a number of years ago. The challenge of such research is that the animal has natural reactions to attempts to steer or control it.

Anderson: While moths are better at odor tracking than robots currently, the advantage of the drone platform is that we have control over it. We can tell it to constrain the search to a certain area, and return after it finishes searching.

What can you tell us about the health, happiness, and overall wellfare of the moths in your experiments?

Anderson: The moths are cold anesthetized before the antennae are removed. They are then frozen so that they can be used for teaching purposes or in other research efforts.

What are you working on next?

Daniel: The four big efforts are (1) CRISPR modification, (2) experiments aimed at improving the longevity of the antennal preparation, (3) improved measurements of antennal electrical responses to odors combined with machine learning to see if we can classify different odors, and (4) flight in outdoor environments.

Fuller: The moth's antenna sensor gives us a new ability to sense with a much shorter latency than was previously possible with similarly-sized sensors (e.g. semiconductor sensors). What exactly a robot agent should do to best take advantage of this is an open question. In particular, I think the speed may help it to zero in on plume sources in complex environments much more quickly. Think of places like indoor settings with flow down hallways that splits out at doorways, and in industrial settings festooned with pipes and equipment. We know that it is possible to search out and find odors in such scenarios, as anybody who has had to contend with an outbreak of fruit flies can attest. It is also known that these animals respond very quickly to sudden changes in odor that is present in such turbulent, patchy plumes. Since it is hard to reduce such plumes to a simple model, we think that machine learning may provide insights into how to best take advantage of the improved temporal plume information we now have available.

Tom Daniel also points out that the relative simplicity of this project (now that the UW researchers have it all figured out, that is) means that even high school students could potentially get involved in it, even if it’s on a ground robot rather than a drone. All the details are in the paper that was just published in Bioinspiration & Biomimetics. Continue reading

Posted in Human Robots

#437929 These Were Our Favorite Tech Stories ...

This time last year we were commemorating the end of a decade and looking ahead to the next one. Enter the year that felt like a decade all by itself: 2020. News written in January, the before-times, feels hopelessly out of touch with all that came after. Stories published in the early days of the pandemic are, for the most part, similarly naive.

The year’s news cycle was swift and brutal, ping-ponging from pandemic to extreme social and political tension, whipsawing economies, and natural disasters. Hope. Despair. Loneliness. Grief. Grit. More hope. Another lockdown. It’s been a hell of a year.

Though 2020 was dominated by big, hairy societal change, science and technology took significant steps forward. Researchers singularly focused on the pandemic and collaborated on solutions to a degree never before seen. New technologies converged to deliver vaccines in record time. The dark side of tech, from biased algorithms to the threat of omnipresent surveillance and corporate control of artificial intelligence, continued to rear its head.

Meanwhile, AI showed uncanny command of language, joined Reddit threads, and made inroads into some of science’s grandest challenges. Mars rockets flew for the first time, and a private company delivered astronauts to the International Space Station. Deprived of night life, concerts, and festivals, millions traveled to virtual worlds instead. Anonymous jet packs flew over LA. Mysterious monoliths appeared and disappeared worldwide.

It was all, you know, very 2020. For this year’s (in-no-way-all-encompassing) list of fascinating stories in tech and science, we tried to select those that weren’t totally dated by the news, but rose above it in some way. So, without further ado: This year’s picks.

How Science Beat the Virus
Ed Yong | The Atlantic
“Much like famous initiatives such as the Manhattan Project and the Apollo program, epidemics focus the energies of large groups of scientists. …But ‘nothing in history was even close to the level of pivoting that’s happening right now,’ Madhukar Pai of McGill University told me. … No other disease has been scrutinized so intensely, by so much combined intellect, in so brief a time.”

‘It Will Change Everything’: DeepMind’s AI Makes Gigantic Leap in Solving Protein Structures
Ewen Callaway | Nature
“In some cases, AlphaFold’s structure predictions were indistinguishable from those determined using ‘gold standard’ experimental methods such as X-ray crystallography and, in recent years, cryo-electron microscopy (cryo-EM). AlphaFold might not obviate the need for these laborious and expensive methods—yet—say scientists, but the AI will make it possible to study living things in new ways.”

OpenAI’s Latest Breakthrough Is Astonishingly Powerful, But Still Fighting Its Flaws
James Vincent | The Verge
“What makes GPT-3 amazing, they say, is not that it can tell you that the capital of Paraguay is Asunción (it is) or that 466 times 23.5 is 10,987 (it’s not), but that it’s capable of answering both questions and many more beside simply because it was trained on more data for longer than other programs. If there’s one thing we know that the world is creating more and more of, it’s data and computing power, which means GPT-3’s descendants are only going to get more clever.”

Artificial General Intelligence: Are We Close, and Does It Even Make Sense to Try?
Will Douglas Heaven | MIT Technology Review
“A machine that could think like a person has been the guiding vision of AI research since the earliest days—and remains its most divisive idea. …So why is AGI controversial? Why does it matter? And is it a reckless, misleading dream—or the ultimate goal?”

The Dark Side of Big Tech’s Funding for AI Research
Tom Simonite | Wired
“Timnit Gebru’s exit from Google is a powerful reminder of how thoroughly companies dominate the field, with the biggest computers and the most resources. …[Meredith] Whittaker of AI Now says properly probing the societal effects of AI is fundamentally incompatible with corporate labs. ‘That kind of research that looks at the power and politics of AI is and must be inherently adversarial to the firms that are profiting from this technology.’i”

We’re Not Prepared for the End of Moore’s Law
David Rotman | MIT Technology Review
“Quantum computing, carbon nanotube transistors, even spintronics, are enticing possibilities—but none are obvious replacements for the promise that Gordon Moore first saw in a simple integrated circuit. We need the research investments now to find out, though. Because one prediction is pretty much certain to come true: we’re always going to want more computing power.”

Inside the Race to Build the Best Quantum Computer on Earth
Gideon Lichfield | MIT Technology Review
“Regardless of whether you agree with Google’s position [on ‘quantum supremacy’] or IBM’s, the next goal is clear, Oliver says: to build a quantum computer that can do something useful. …The trouble is that it’s nearly impossible to predict what the first useful task will be, or how big a computer will be needed to perform it.”

The Secretive Company That Might End Privacy as We Know It
Kashmir Hill | The New York Times
“Searching someone by face could become as easy as Googling a name. Strangers would be able to listen in on sensitive conversations, take photos of the participants and know personal secrets. Someone walking down the street would be immediately identifiable—and his or her home address would be only a few clicks away. It would herald the end of public anonymity.”

Wrongfully Accused by an Algorithm
Kashmir Hill | The New York Times
“Mr. Williams knew that he had not committed the crime in question. What he could not have known, as he sat in the interrogation room, is that his case may be the first known account of an American being wrongfully arrested based on a flawed match from a facial recognition algorithm, according to experts on technology and the law.”

Predictive Policing Algorithms Are Racist. They Need to Be Dismantled.
Will Douglas Heaven | MIT Technology Review
“A number of studies have shown that these tools perpetuate systemic racism, and yet we still know very little about how they work, who is using them, and for what purpose. All of this needs to change before a proper reckoning can take pace. Luckily, the tide may be turning.”

The Panopticon Is Already Here
Ross Andersen | The Atlantic
“Artificial intelligence has applications in nearly every human domain, from the instant translation of spoken language to early viral-outbreak detection. But Xi [Jinping] also wants to use AI’s awesome analytical powers to push China to the cutting edge of surveillance. He wants to build an all-seeing digital system of social control, patrolled by precog algorithms that identify potential dissenters in real time.”

The Case For Cities That Aren’t Dystopian Surveillance States
Cory Doctorow | The Guardian
“Imagine a human-centered smart city that knows everything it can about things. It knows how many seats are free on every bus, it knows how busy every road is, it knows where there are short-hire bikes available and where there are potholes. …What it doesn’t know is anything about individuals in the city.”

The Modern World Has Finally Become Too Complex for Any of Us to Understand
Tim Maughan | OneZero
“One of the dominant themes of the last few years is that nothing makes sense. …I am here to tell you that the reason so much of the world seems incomprehensible is that it is incomprehensible. From social media to the global economy to supply chains, our lives rest precariously on systems that have become so complex, and we have yielded so much of it to technologies and autonomous actors that no one totally comprehends it all.”

The Conscience of Silicon Valley
Zach Baron | GQ
“What I really hoped to do, I said, was to talk about the future and how to live in it. This year feels like a crossroads; I do not need to explain what I mean by this. …I want to destroy my computer, through which I now work and ‘have drinks’ and stare at blurry simulations of my parents sometimes; I want to kneel down and pray to it like a god. I want someone—I want Jaron Lanier—to tell me where we’re going, and whether it’s going to be okay when we get there. Lanier just nodded. All right, then.”

Yes to Tech Optimism. And Pessimism.
Shira Ovide | The New York Times
“Technology is not something that exists in a bubble; it is a phenomenon that changes how we live or how our world works in ways that help and hurt. That calls for more humility and bridges across the optimism-pessimism divide from people who make technology, those of us who write about it, government officials and the public. We need to think on the bright side. And we need to consider the horribles.”

How Afrofuturism Can Help the World Mend
C. Brandon Ogbunu | Wired
“…[W. E. B. DuBois’] ‘The Comet’ helped lay the foundation for a paradigm known as Afrofuturism. A century later, as a comet carrying disease and social unrest has upended the world, Afrofuturism may be more relevant than ever. Its vision can help guide us out of the rubble, and help us to consider universes of better alternatives.”

Wikipedia Is the Last Best Place on the Internet
Richard Cooke | Wired
“More than an encyclopedia, Wikipedia has become a community, a library, a constitution, an experiment, a political manifesto—the closest thing there is to an online public square. It is one of the few remaining places that retains the faintly utopian glow of the early World Wide Web.”

Can Genetic Engineering Bring Back the American Chestnut?
Gabriel Popkin | The New York Times Magazine
“The geneticists’ research forces conservationists to confront, in a new and sometimes discomfiting way, the prospect that repairing the natural world does not necessarily mean returning to an unblemished Eden. It may instead mean embracing a role that we’ve already assumed: engineers of everything, including nature.”

At the Limits of Thought
David C. Krakauer | Aeon
“A schism is emerging in the scientific enterprise. On the one side is the human mind, the source of every story, theory, and explanation that our species holds dear. On the other stand the machines, whose algorithms possess astonishing predictive power but whose inner workings remain radically opaque to human observers.”

Is the Internet Conscious? If It Were, How Would We Know?
Meghan O’Gieblyn | Wired
“Does the internet behave like a creature with an internal life? Does it manifest the fruits of consciousness? There are certainly moments when it seems to. Google can anticipate what you’re going to type before you fully articulate it to yourself. Facebook ads can intuit that a woman is pregnant before she tells her family and friends. It is easy, in such moments, to conclude that you’re in the presence of another mind—though given the human tendency to anthropomorphize, we should be wary of quick conclusions.”

The Internet Is an Amnesia Machine
Simon Pitt | OneZero
“There was a time when I didn’t know what a Baby Yoda was. Then there was a time I couldn’t go online without reading about Baby Yoda. And now, Baby Yoda is a distant, shrugging memory. Soon there will be a generation of people who missed the whole thing and for whom Baby Yoda is as meaningless as it was for me a year ago.”

Digital Pregnancy Tests Are Almost as Powerful as the Original IBM PC
Tom Warren | The Verge
“Each test, which costs less than $5, includes a processor, RAM, a button cell battery, and a tiny LCD screen to display the result. …Foone speculates that this device is ‘probably faster at number crunching and basic I/O than the CPU used in the original IBM PC.’ IBM’s original PC was based on Intel’s 8088 microprocessor, an 8-bit chip that operated at 5Mhz. The difference here is that this is a pregnancy test you pee on and then throw away.”

The Party Goes on in Massive Online Worlds
Cecilia D’Anastasio | Wired
“We’re more stand-outside types than the types to cast a flashy glamour spell and chat up the nearest cat girl. But, hey, it’s Final Fantasy XIV online, and where my body sat in New York, the epicenter of America’s Covid-19 outbreak, there certainly weren’t any parties.”

The Facebook Groups Where People Pretend the Pandemic Isn’t Happening
Kaitlyn Tiffany | The Atlantic
“Losing track of a friend in a packed bar or screaming to be heard over a live band is not something that’s happening much in the real world at the moment, but it happens all the time in the 2,100-person Facebook group ‘a group where we all pretend we’re in the same venue.’ So does losing shoes and Juul pods, and shouting matches over which bands are the saddest, and therefore the greatest.”

Did You Fly a Jetpack Over Los Angeles This Weekend? Because the FBI Is Looking for You
Tom McKay | Gizmodo
“Did you fly a jetpack over Los Angeles at approximately 3,000 feet on Sunday? Some kind of tiny helicopter? Maybe a lawn chair with balloons tied to it? If the answer to any of the above questions is ‘yes,’ you should probably lay low for a while (by which I mean cool it on the single-occupant flying machine). That’s because passing airline pilots spotted you, and now it’s this whole thing with the FBI and the Federal Aviation Administration, both of which are investigating.”

Image Credit: Thomas Kinto / Unsplash Continue reading

Posted in Human Robots

#437301 The Global Work Crisis: Automation, the ...

The alarm bell rings. You open your eyes, come to your senses, and slide from dream state to consciousness. You hit the snooze button, and eventually crawl out of bed to the start of yet another working day.

This daily narrative is experienced by billions of people all over the world. We work, we eat, we sleep, and we repeat. As our lives pass day by day, the beating drums of the weekly routine take over and years pass until we reach our goal of retirement.

A Crisis of Work
We repeat the routine so that we can pay our bills, set our kids up for success, and provide for our families. And after a while, we start to forget what we would do with our lives if we didn’t have to go back to work.

In the end, we look back at our careers and reflect on what we’ve achieved. It may have been the hundreds of human interactions we’ve had; the thousands of emails read and replied to; the millions of minutes of physical labor—all to keep the global economy ticking along.

According to Gallup’s World Poll, only 15 percent of people worldwide are actually engaged with their jobs. The current state of “work” is not working for most people. In fact, it seems we as a species are trapped by a global work crisis, which condemns people to cast away their time just to get by in their day-to-day lives.

Technologies like artificial intelligence and automation may help relieve the work burdens of millions of people—but to benefit from their impact, we need to start changing our social structures and the way we think about work now.

The Specter of Automation
Automation has been ongoing since the Industrial Revolution. In recent decades it has taken on a more elegant guise, first with physical robots in production plants, and more recently with software automation entering most offices.

The driving goal behind much of this automation has always been productivity and hence, profits: technology that can act as a multiplier on what a single human can achieve in a day is of huge value to any company. Powered by this strong financial incentive, the quest for automation is growing ever more pervasive.

But if automation accelerates or even continues at its current pace and there aren’t strong social safety nets in place to catch the people who are negatively impacted (such as by losing their jobs), there could be a host of knock-on effects, including more concentrated wealth among a shrinking elite, more strain on government social support, an increase in depression and drug dependence, and even violent social unrest.

It seems as though we are rushing headlong into a major crisis, driven by the engine of accelerating automation. But what if instead of automation challenging our fragile status quo, we view it as the solution that can free us from the shackles of the Work Crisis?

The Way Out
In order to undertake this paradigm shift, we need to consider what society could potentially look like, as well as the problems associated with making this change. In the context of these crises, our primary aim should be for a system where people are not obligated to work to generate the means to survive. This removal of work should not threaten access to food, water, shelter, education, healthcare, energy, or human value. In our current system, work is the gatekeeper to these essentials: one can only access these (and even then often in a limited form), if one has a “job” that affords them.

Changing this system is thus a monumental task. This comes with two primary challenges: providing people without jobs with financial security, and ensuring they maintain a sense of their human value and worth. There are several measures that could be implemented to help meet these challenges, each with important steps for society to consider.

Universal basic income (UBI)

UBI is rapidly gaining support, and it would allow people to become shareholders in the fruits of automation, which would then be distributed more broadly.

UBI trials have been conducted in various countries around the world, including Finland, Kenya, and Spain. The findings have generally been positive on the health and well-being of the participants, and showed no evidence that UBI disincentivizes work, a common concern among the idea’s critics. The most recent popular voice for UBI has been that of former US presidential candidate Andrew Yang, who now runs a non-profit called Humanity Forward.

UBI could also remove wasteful bureaucracy in administering welfare payments (since everyone receives the same amount, there’s no need to prevent false claims), and promote the pursuit of projects aligned with peoples’ skill sets and passions, as well as quantifying the value of tasks not recognized by economic measures like Gross Domestic Product (GDP). This includes looking after children and the elderly at home.

How a UBI can be initiated with political will and social backing and paid for by governments has been hotly debated by economists and UBI enthusiasts. Variables like how much the UBI payments should be, whether to implement taxes such as Yang’s proposed valued added tax (VAT), whether to replace existing welfare payments, the impact on inflation, and the impact on “jobs” from people who would otherwise look for work require additional discussion. However, some have predicted the inevitability of UBI as a result of automation.

Universal healthcare

Another major component of any society is the healthcare of its citizens. A move away from work would further require the implementation of a universal healthcare system to decouple healthcare from jobs. Currently in the US, and indeed many other economies, healthcare is tied to employment.

Universal healthcare such as Medicare in Australia is evidence for the adage “prevention is better than cure,” when comparing the cost of healthcare in the US with Australia on a per capita basis. This has already presented itself as an advancement in the way healthcare is considered. There are further benefits of a healthier population, including less time and money spent on “sick-care.” Healthy people are more likely and more able to achieve their full potential.

Reshape the economy away from work-based value

One of the greatest challenges in a departure from work is for people to find value elsewhere in life. Many people view their identities as being inextricably tied to their jobs, and life without a job is therefore a threat to one’s sense of existence. This presents a shift that must be made at both a societal and personal level.

A person can only seek alternate value in life when afforded the time to do so. To this end, we need to start reducing “work-for-a-living” hours towards zero, which is a trend we are already seeing in Europe. This should not come at the cost of reducing wages pro rata, but rather could be complemented by UBI or additional schemes where people receive dividends for work done by automation. This transition makes even more sense when coupled with the idea of deviating from using GDP as a measure of societal growth, and instead adopting a well-being index based on universal human values like health, community, happiness, and peace.

The crux of this issue is in transitioning away from the view that work gives life meaning and life is about using work to survive, towards a view of living a life that itself is fulfilling and meaningful. This speaks directly to notions from Maslow’s hierarchy of needs, where work largely addresses psychological and safety needs such as shelter, food, and financial well-being. More people should have a chance to grow beyond the most basic needs and engage in self-actualization and transcendence.

The question is largely around what would provide people with a sense of value, and the answers would differ as much as people do; self-mastery, building relationships and contributing to community growth, fostering creativity, and even engaging in the enjoyable aspects of existing jobs could all come into play.

Universal education

With a move towards a society that promotes the values of living a good life, the education system would have to evolve as well. Researchers have long argued for a more nimble education system, but universities and even most online courses currently exist for the dominant purpose of ensuring people are adequately skilled to contribute to the economy. These “job factories” only exacerbate the Work Crisis. In fact, the response often given by educational institutions to the challenge posed by automation is to find new ways of upskilling students, such as ensuring they are all able to code. As alluded to earlier, this is a limited and unimaginative solution to the problem we are facing.

Instead, education should be centered on helping people acknowledge the current crisis of work and automation, teach them how to derive value that is decoupled from work, and enable people to embrace progress as we transition to the new economy.

Disrupting the Status Quo
While we seldom stop to think about it, much of the suffering faced by humanity is brought about by the systemic foe that is the Work Crisis. The way we think about work has brought society far and enabled tremendous developments, but at the same time it has failed many people. Now the status quo is threatened by those very developments as we progress to an era where machines are likely to take over many job functions.

This impending paradigm shift could be a threat to the stability of our fragile system, but only if it is not fully anticipated. If we prepare for it appropriately, it could instead be the key not just to our survival, but to a better future for all.

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