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#434544 This Week’s Awesome Stories From ...

DeepMind Beats Pros at Starcraft in Another Triumph for Bots
Tom Simonite | Wired
“DeepMind’s feat is the most complex yet in a long train of contests in which computers have beaten top humans at games. Checkers fell in 1994, chess in 1997, and DeepMind’s earlier bot AlphaGo became the first to beat a champion at the board game Go in 2016. The StarCraft bot is the most powerful AI game player yet; it may also be the least unexpected.”

Complete Axolotl Genome Could Pave the Way Toward Human Tissue Regeneration
George Dvorsky | Gizmodo
“Now that researchers have a near-complete axolotl genome—the new assembly still requires a bit of fine-tuning (more on that in a bit)—they, along with others, can now go about the work of identifying the genes responsible for axolotl tissue regeneration.”

We Analyzed 16,625 Papers to Figure Out Where AI Is Headed Next
Karen Hao | MIT Technology Review
“…though deep learning has singlehandedly thrust AI into the public eye, it represents just a small blip in the history of humanity’s quest to replicate our own intelligence. It’s been at the forefront of that effort for less than 10 years. When you zoom out on the whole history of the field, it’s easy to realize that it could soon be on its way out.”

Apple’s Finger-Controller Patent Is a Glimpse at Mixed Reality’s Future
Mark Sullivan | Fast Company
“[Apple’s] engineers are now looking past the phone touchscreen toward mixed reality, where the company’s next great UX will very likely be built. A recent patent application gives some tantalizing clues as to how Apple’s people are thinking about aspects of that challenge.”

How Do You Govern Machines That Can Learn? Policymakers Are Trying to Figure That Out
Steve Lohr | The New York Times
“Regulation is coming. That’s a good thing. Rules of competition and behavior are the foundation of healthy, growing markets. That was the consensus of the policymakers at MIT. But they also agreed that artificial intelligence raises some fresh policy challenges.”

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#434303 Making Superhumans Through Radical ...

Imagine trying to read War and Peace one letter at a time. The thought alone feels excruciating. But in many ways, this painful idea holds parallels to how human-machine interfaces (HMI) force us to interact with and process data today.

Designed back in the 1970s at Xerox PARC and later refined during the 1980s by Apple, today’s HMI was originally conceived during fundamentally different times, and specifically, before people and machines were generating so much data. Fast forward to 2019, when humans are estimated to produce 44 zettabytes of data—equal to two stacks of books from here to Pluto—and we are still using the same HMI from the 1970s.

These dated interfaces are not equipped to handle today’s exponential rise in data, which has been ushered in by the rapid dematerialization of many physical products into computers and software.

Breakthroughs in perceptual and cognitive computing, especially machine learning algorithms, are enabling technology to process vast volumes of data, and in doing so, they are dramatically amplifying our brain’s abilities. Yet even with these powerful technologies that at times make us feel superhuman, the interfaces are still crippled with poor ergonomics.

Many interfaces are still designed around the concept that human interaction with technology is secondary, not instantaneous. This means that any time someone uses technology, they are inevitably multitasking, because they must simultaneously perform a task and operate the technology.

If our aim, however, is to create technology that truly extends and amplifies our mental abilities so that we can offload important tasks, the technology that helps us must not also overwhelm us in the process. We must reimagine interfaces to work in coherence with how our minds function in the world so that our brains and these tools can work together seamlessly.

Embodied Cognition
Most technology is designed to serve either the mind or the body. It is a problematic divide, because our brains use our entire body to process the world around us. Said differently, our minds and bodies do not operate distinctly. Our minds are embodied.

Studies using MRI scans have shown that when a person feels an emotion in their gut, blood actually moves to that area of the body. The body and the mind are linked in this way, sharing information back and forth continuously.

Current technology presents data to the brain differently from how the brain processes data. Our brains, for example, use sensory data to continually encode and decipher patterns within the neocortex. Our brains do not create a linguistic label for each item, which is how the majority of machine learning systems operate, nor do our brains have an image associated with each of these labels.

Our bodies move information through us instantaneously, in a sense “computing” at the speed of thought. What if our technology could do the same?

Using Cognitive Ergonomics to Design Better Interfaces
Well-designed physical tools, as philosopher Martin Heidegger once meditated on while using the metaphor of a hammer, seem to disappear into the “hand.” They are designed to amplify a human ability and not get in the way during the process.

The aim of physical ergonomics is to understand the mechanical movement of the human body and then adapt a physical system to amplify the human output in accordance. By understanding the movement of the body, physical ergonomics enables ergonomically sound physical affordances—or conditions—so that the mechanical movement of the body and the mechanical movement of the machine can work together harmoniously.

Cognitive ergonomics applied to HMI design uses this same idea of amplifying output, but rather than focusing on physical output, the focus is on mental output. By understanding the raw materials the brain uses to comprehend information and form an output, cognitive ergonomics allows technologists and designers to create technological affordances so that the brain can work seamlessly with interfaces and remove the interruption costs of our current devices. In doing so, the technology itself “disappears,” and a person’s interaction with technology becomes fluid and primary.

By leveraging cognitive ergonomics in HMI design, we can create a generation of interfaces that can process and present data the same way humans process real-world information, meaning through fully-sensory interfaces.

Several brain-machine interfaces are already on the path to achieving this. AlterEgo, a wearable device developed by MIT researchers, uses electrodes to detect and understand nonverbal prompts, which enables the device to read the user’s mind and act as an extension of the user’s cognition.

Another notable example is the BrainGate neural device, created by researchers at Stanford University. Just two months ago, a study was released showing that this brain implant system allowed paralyzed patients to navigate an Android tablet with their thoughts alone.

These are two extraordinary examples of what is possible for the future of HMI, but there is still a long way to go to bring cognitive ergonomics front and center in interface design.

Disruptive Innovation Happens When You Step Outside Your Existing Users
Most of today’s interfaces are designed by a narrow population, made up predominantly of white, non-disabled men who are prolific in the use of technology (you may recall The New York Times viral article from 2016, Artificial Intelligence’s White Guy Problem). If you ask this population if there is a problem with today’s HMIs, most will say no, and this is because the technology has been designed to serve them.

This lack of diversity means a limited perspective is being brought to interface design, which is problematic if we want HMI to evolve and work seamlessly with the brain. To use cognitive ergonomics in interface design, we must first gain a more holistic understanding of how people with different abilities understand the world and how they interact with technology.

Underserved groups, such as people with physical disabilities, operate on what Clayton Christensen coined in The Innovator’s Dilemma as the fringe segment of a market. Developing solutions that cater to fringe groups can in fact disrupt the larger market by opening a downward, much larger market.

Learning From Underserved Populations
When technology fails to serve a group of people, that group must adapt the technology to meet their needs.

The workarounds created are often ingenious, specifically because they have not been arrived at by preferences, but out of necessity that has forced disadvantaged users to approach the technology from a very different vantage point.

When a designer or technologist begins learning from this new viewpoint and understanding challenges through a different lens, they can bring new perspectives to design—perspectives that otherwise can go unseen.

Designers and technologists can also learn from people with physical disabilities who interact with the world by leveraging other senses that help them compensate for one they may lack. For example, some blind people use echolocation to detect objects in their environments.

The BrainPort device developed by Wicab is an incredible example of technology leveraging one human sense to serve or compliment another. The BrainPort device captures environmental information with a wearable video camera and converts this data into soft electrical stimulation sequences that are sent to a device on the user’s tongue—the most sensitive touch receptor in the body. The user learns how to interpret the patterns felt on their tongue, and in doing so, become able to “see” with their tongue.

Key to the future of HMI design is learning how different user groups navigate the world through senses beyond sight. To make cognitive ergonomics work, we must understand how to leverage the senses so we’re not always solely relying on our visual or verbal interactions.

Radical Inclusion for the Future of HMI
Bringing radical inclusion into HMI design is about gaining a broader lens on technology design at large, so that technology can serve everyone better.

Interestingly, cognitive ergonomics and radical inclusion go hand in hand. We can’t design our interfaces with cognitive ergonomics without bringing radical inclusion into the picture, and we also will not arrive at radical inclusion in technology so long as cognitive ergonomics are not considered.

This new mindset is the only way to usher in an era of technology design that amplifies the collective human ability to create a more inclusive future for all.

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#433807 The How, Why, and Whether of Custom ...

A digital afterlife may soon be within reach, but it might not be for your benefit.

The reams of data we’re creating could soon make it possible to create digital avatars that live on after we die, aimed at comforting our loved ones or sharing our experience with future generations.

That may seem like a disappointing downgrade from the vision promised by the more optimistic futurists, where we upload our consciousness to the cloud and live forever in machines. But it might be a realistic possibility in the not-too-distant future—and the first steps have already been taken.

After her friend died in a car crash, Eugenia Kuyda, co-founder of Russian AI startup Luka, trained a neural network-powered chatbot on their shared message history to mimic him. Journalist and amateur coder James Vlahos took a more involved approach, carrying out extensive interviews with his terminally ill father so that he could create a digital clone of him when he died.

For those of us without the time or expertise to build our own artificial intelligence-powered avatar, startup Eternime is offering to take your social media posts and interactions as well as basic personal information to build a copy of you that could then interact with relatives once you’re gone. The service is so far only running a private beta with a handful of people, but with 40,000 on its waiting list, it’s clear there’s a market.

Comforting—Or Creepy?
The whole idea may seem eerily similar to the Black Mirror episode Be Right Back, in which a woman pays a company to create a digital copy of her deceased husband and eventually a realistic robot replica. And given the show’s focus on the emotional turmoil she goes through, people might question whether the idea is a sensible one.

But it’s hard to say at this stage whether being able to interact with an approximation of a deceased loved one would be a help or a hindrance in the grieving process. The fear is that it could make it harder for people to “let go” or “move on,” but others think it could play a useful therapeutic role, reminding people that just because someone is dead it doesn’t mean they’re gone, and providing a novel way for them to express and come to terms with their feelings.

While at present most envisage these digital resurrections as a way to memorialize loved ones, there are also more ambitious plans to use the technology as a way to preserve expertise and experience. A project at MIT called Augmented Eternity is investigating whether we could use AI to trawl through someone’s digital footprints and extract both their knowledge and elements of their personality.

Project leader Hossein Rahnama says he’s already working with a CEO who wants to leave behind a digital avatar that future executives could consult with after he’s gone. And you wouldn’t necessarily have to wait until you’re dead—experts could create virtual clones of themselves that could dispense advice on demand to far more people. These clones could soon be more than simple chatbots, too. Hollywood has already started spending millions of dollars to create 3D scans of its most bankable stars so that they can keep acting beyond the grave.

It’s easy to see the appeal of the idea; imagine if we could bring back Stephen Hawking or Tim Cook to share their wisdom with us. And what if we could create a digital brain trust combining the experience and wisdom of all the world’s greatest thinkers, accessible on demand?

But there are still huge hurdles ahead before we could create truly accurate representations of people by simply trawling through their digital remains. The first problem is data. Most peoples’ digital footprints only started reaching significant proportions in the last decade or so, and cover a relatively small period of their lives. It could take many years before there’s enough data to create more than just a superficial imitation of someone.

And that’s assuming that the data we produce is truly representative of who we are. Carefully-crafted Instagram profiles and cautiously-worded work emails hardly capture the messy realities of most peoples’ lives.

Perhaps if the idea is simply to create a bank of someone’s knowledge and expertise, accurately capturing the essence of their character would be less important. But these clones would also be static. Real people continually learn and change, but a digital avatar is a snapshot of someone’s character and opinions at the point they died. An inability to adapt as the world around them changes could put a shelf life on the usefulness of these replicas.

Who’s Calling the (Digital) Shots?
It won’t stop people trying, though, and that raises a potentially more important question: Who gets to make the calls about our digital afterlife? The subjects, their families, or the companies that hold their data?

In most countries, the law is currently pretty hazy on this topic. Companies like Google and Facebook have processes to let you choose who should take control of your accounts in the event of your death. But if you’ve forgotten to do that, the fate of your virtual remains comes down to a tangle of federal law, local law, and tech company terms of service.

This lack of regulation could create incentives and opportunities for unscrupulous behavior. The voice of a deceased loved one could be a highly persuasive tool for exploitation, and digital replicas of respected experts could be powerful means of pushing a hidden agenda.

That means there’s a pressing need for clear and unambiguous rules. Researchers at Oxford University recently suggested ethical guidelines that would treat our digital remains the same way museums and archaeologists are required to treat mortal remains—with dignity and in the interest of society.

Whether those kinds of guidelines are ever enshrined in law remains to be seen, but ultimately they may decide whether the digital afterlife turns out to be heaven or hell.

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#433803 This Week’s Awesome Stories From ...

The AI Cold War That Could Doom Us All
Nicholas Thompson | Wired
“At the dawn of a new stage in the digital revolution, the world’s two most powerful nations are rapidly retreating into positions of competitive isolation, like players across a Go board. …Is the arc of the digital revolution bending toward tyranny, and is there any way to stop it?”

Finally, the Drug That Keeps You Young
Stephen S. Hall | MIT Technology Review
“The other thing that has changed is that the field of senescence—and the recognition that senescent cells can be such drivers of aging—has finally gained acceptance. Whether those drugs will work in people is still an open question. But the first human trials are under way right now.”

Ginkgo Bioworks Is Turning Human Cells Into On-Demand Factories
Megan Molteni | Wired
“The biotech unicorn is already cranking out an impressive number of microbial biofactories that grow and multiply and burp out fragrances, fertilizers, and soon, psychoactive substances. And they do it at a fraction of the cost of traditional systems. But Kelly is thinking even bigger.”

Thousands of Swedes Are Inserting Microchips Under Their Skin
Maddy Savage | NPR
“Around the size of a grain of rice, the chips typically are inserted into the skin just above each user’s thumb, using a syringe similar to that used for giving vaccinations. The procedure costs about $180. So many Swedes are lining up to get the microchips that the country’s main chipping company says it can’t keep up with the number of requests.”

AI Art at Christie’s Sells for $432,500
Gabe Cohn | The New York Times
“Last Friday, a portrait produced by artificial intelligence was hanging at Christie’s New York opposite an Andy Warhol print and beside a bronze work by Roy Lichtenstein. On Thursday, it sold for well over double the price realized by both those pieces combined.”

Should a Self-Driving Car Kill the Baby or the Grandma? Depends on Where You’re From
Karen Hao | MIT Technology Review
“The researchers never predicted the experiment’s viral reception. Four years after the platform went live, millions of people in 233 countries and territories have logged 40 million decisions, making it one of the largest studies ever done on global moral preferences.”

The Rodney Brooks Rules for Predicting a Technology’s Success
Rodney Brooks | IEEE Spectrum
“Building electric cars and reusable rockets is fairly easy. Building a nuclear fusion reactor, flying cars, self-driving cars, or a Hyperloop system is very hard. What makes the difference?”

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#433725 This Week’s Awesome Stories From ...

The Demise of Rethink Robotics Shows How Hard It Is to Make Machines Truly Smart
Will Knight | MIT Technology Review
“There’s growing interest in using recent advances in AI to make industrial robots a lot smarter and more useful. …But look carefully and you’ll see that these technologies are at a very early stage, and that deploying them commercially could prove extremely challenging. The demise of Rethink doesn’t mean industrial robotics isn’t flourishing, or that AI-driven advances won’t come about. But it shows just how hard doing real innovation in robotics can be.”

The Human Cell Atlas Is Biologists’ Latest Grand Project
Megan Molteni | Wired
“Dubbed the Human Cell Atlas, the project intends to catalog all of the estimated 37 trillion cells that make up a human body. …By decoding the genes active in single cells, pegging different cell types to a specific address in the body, and tracing the molecular circuits between them, participating researchers plan to create a more comprehensive map of human biology than has ever existed before.”

US Will Rewrite Safety Rules to Permit Fully Driverless Cars on Public Roads
Andrew J. Hawkins | The Verge
“Under current US safety rules, a motor vehicle must have traditional controls, like a steering wheel, mirrors, and foot pedals, before it is allowed to operate on public roads. But that could all change under a new plan released on Thursday by the Department of Transportation that’s intended to open the floodgates for fully driverless cars.”

When an AI Goes Full Jack Kerouac
Brian Merchant | The Atlantic
“By the end of the four-day trip, receipts emblazoned with artificially intelligent prose would cover the floor of the car. …it is a hallucinatory, oddly illuminating account of a bot’s life on the interstate; the Electric Kool-Aid Acid Test meets Google Street View, narrated by Siri.”

New Autonomous Farm Wants to Produce Food Without Human Workers
Erin Winick | MIT Technology Review
“As the firm’s cofounder Brandon Alexander puts it: ‘We are a farm and will always be a farm.’ But it’s no ordinary farm. For starters, the company’s 15 human employees share their work space with robots who quietly go about the business of tending rows and rows of leafy greens.”

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