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#432891 This Week’s Awesome Stories From ...

TRANSPORTATION
Elon Musk Presents His Tunnel Vision to the People of LA
Jack Stewart and Aarian Marshall | Wired
“Now, Musk wants to build this new, 2.1-mile tunnel, near LA’s Sepulveda pass. It’s all part of his broader vision of a sprawling network that could take riders from Sherman Oaks in the north to Long Beach Airport in the south, Santa Monica in the west to Dodger Stadium in the east—without all that troublesome traffic.”

ROBOTICS
Feel What This Robot Feels Through Tactile Expressions
Evan Ackerman | IEEE Spectrum
“Guy Hoffman’s Human-Robot Collaboration & Companionship (HRC2) Lab at Cornell University is working on a new robot that’s designed to investigate this concept of textural communication, which really hasn’t been explored in robotics all that much. The robot uses a pneumatically powered elastomer skin that can be dynamically textured with either goosebumps or spikes, which should help it communicate more effectively, especially if what it’s trying to communicate is, ‘Don’t touch me!’”

VIRTUAL REALITY
In Virtual Reality, How Much Body Do You Need?
Steph Yin | The New York Times
“In a paper published Tuesday in Scientific Reports, they showed that animating virtual hands and feet alone is enough to make people feel their sense of body drift toward an invisible avatar. Their work fits into a corpus of research on illusory body ownership, which has challenged understandings of perception and contributed to therapies like treating pain for amputees who experience phantom limb.”

MEDICINE
How Graphene and Gold Could Help Us Test Drugs and Monitor Cancer
Angela Chen | The Verge
“In today’s study, scientists learned to precisely control the amount of electricity graphene generates by changing how much light they shine on the material. When they grew heart cells on the graphene, they could manipulate the cells too, says study co-author Alex Savtchenko, a physicist at the University of California, San Diego. They could make it beat 1.5 times faster, three times faster, 10 times faster, or whatever they needed.”

DISASTER RELIEF
Robotic Noses Could Be the Future of Disaster Rescue—If They Can Outsniff Search Dogs
Eleanor Cummins | Popular Science
“While canine units are a tried and fairly true method for identifying people trapped in the wreckage of a disaster, analytical chemists have for years been working in the lab to create a robotic alternative. A synthetic sniffer, they argue, could potentially prove to be just as or even more reliable than a dog, more resilient in the face of external pressures like heat and humidity, and infinitely more portable.”

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Posted in Human Robots

#432691 Is the Secret to Significantly Longer ...

Once upon a time, a powerful Sumerian king named Gilgamesh went on a quest, as such characters often do in these stories of myth and legend. Gilgamesh had witnessed the death of his best friend, Enkidu, and, fearing a similar fate, went in search of immortality. The great king failed to find the secret of eternal life but took solace that his deeds would live well beyond his mortal years.

Fast-forward four thousand years, give or take a century, and Gilgamesh (as famous as any B-list celebrity today, despite the passage of time) would probably be heartened to learn that many others have taken up his search for longevity. Today, though, instead of battling epic monsters and the machinations of fickle gods, those seeking to enhance and extend life are cutting-edge scientists and visionary entrepreneurs who are helping unlock the secrets of human biology.

Chief among them is Aubrey de Grey, a biomedical gerontologist who founded the SENS Research Foundation, a Silicon Valley-based research organization that seeks to advance the application of regenerative medicine to age-related diseases. SENS stands for Strategies for Engineered Negligible Senescence, a term coined by de Grey to describe a broad array (seven, to be precise) of medical interventions that attempt to repair or prevent different types of molecular and cellular damage that eventually lead to age-related diseases like cancer and Alzheimer’s.

Many of the strategies focus on senescent cells, which accumulate in tissues and organs as people age. Not quite dead, senescent cells stop dividing but are still metabolically active, spewing out all sorts of proteins and other molecules that can cause inflammation and other problems. In a young body, that’s usually not a problem (and probably part of general biological maintenance), as a healthy immune system can go to work to put out most fires.

However, as we age, senescent cells continue to accumulate, and at some point the immune system retires from fire watch. Welcome to old age.

Of Mice and Men
Researchers like de Grey believe that treating the cellular underpinnings of aging could not only prevent disease but significantly extend human lifespans. How long? Well, if you’re talking to de Grey, Biblical proportions—on the order of centuries.

De Grey says that science has made great strides toward that end in the last 15 years, such as the ability to copy mitochondrial DNA to the nucleus. Mitochondria serve as the power plant of the cell but are highly susceptible to mutations that lead to cellular degeneration. Copying the mitochondrial DNA into the nucleus would help protect it from damage.

Another achievement occurred about six years ago when scientists first figured out how to kill senescent cells. That discovery led to a spate of new experiments in mice indicating that removing these ticking-time-bomb cells prevented disease and even extended their lifespans. Now the anti-aging therapy is about to be tested in humans.

“As for the next few years, I think the stream of advances is likely to become a flood—once the first steps are made, things get progressively easier and faster,” de Grey tells Singularity Hub. “I think there’s a good chance that we will achieve really dramatic rejuvenation of mice within only six to eight years: maybe taking middle-aged mice and doubling their remaining lifespan, which is an order of magnitude more than can be done today.”

Not Horsing Around
Richard G.A. Faragher, a professor of biogerontology at the University of Brighton in the United Kingdom, recently made discoveries in the lab regarding the rejuvenation of senescent cells with chemical compounds found in foods like chocolate and red wine. He hopes to apply his findings to an animal model in the future—in this case,horses.

“We have been very fortunate in receiving some funding from an animal welfare charity to look at potential treatments for older horses,” he explains to Singularity Hub in an email. “I think this is a great idea. Many aspects of the physiology we are studying are common between horses and humans.”

What Faragher and his colleagues demonstrated in a paper published in BMC Cell Biology last year was that resveralogues, chemicals based on resveratrol, were able to reactivate a protein called a splicing factor that is involved in gene regulation. Within hours, the chemicals caused the cells to rejuvenate and start dividing like younger cells.

“If treatments work in our old pony systems, then I am sure they could be translated into clinical trials in humans,” Faragher says. “How long is purely a matter of money. Given suitable funding, I would hope to see a trial within five years.”

Show Them the Money
Faragher argues that the recent breakthroughs aren’t because a result of emerging technologies like artificial intelligence or the gene-editing tool CRISPR, but a paradigm shift in how scientists understand the underpinnings of cellular aging. Solving the “aging problem” isn’t a question of technology but of money, he says.

“Frankly, when AI and CRISPR have removed cystic fibrosis, Duchenne muscular dystrophy or Gaucher syndrome, I’ll be much more willing to hear tales of amazing progress. Go fix a single, highly penetrant genetic disease in the population using this flashy stuff and then we’ll talk,” he says. “My faith resides in the most potent technological development of all: money.”

De Grey is less flippant about the role that technology will play in the quest to defeat aging. AI, CRISPR, protein engineering, advances in stem cell therapies, and immune system engineering—all will have a part.

“There is not really anything distinctive about the ways in which these technologies will contribute,” he says. “What’s distinctive is that we will need all of these technologies, because there are so many different types of damage to repair and they each require different tricks.”

It’s in the Blood
A startup in the San Francisco Bay Area believes machines can play a big role in discovering the right combination of factors that lead to longer and healthier lives—and then develop drugs that exploit those findings.

BioAge Labs raised nearly $11 million last year for its machine learning platform that crunches big data sets to find blood factors, such as proteins or metabolites, that are tied to a person’s underlying biological age. The startup claims that these factors can predict how long a person will live.

“Our interest in this comes out of research into parabiosis, where joining the circulatory systems of old and young mice—so that they share the same blood—has been demonstrated to make old mice healthier and more robust,” Dr. Eric Morgen, chief medical officer at BioAge, tells Singularity Hub.

Based on that idea, he explains, it should be possible to alter those good or bad factors to produce a rejuvenating effect.

“Our main focus at BioAge is to identify these types of factors in our human cohort data, characterize the important molecular pathways they are involved in, and then drug those pathways,” he says. “This is a really hard problem, and we use machine learning to mine these complex datasets to determine which individual factors and molecular pathways best reflect biological age.”

Saving for the Future
Of course, there’s no telling when any of these anti-aging therapies will come to market. That’s why Forever Labs, a biotechnology startup out of Ann Arbor, Michigan, wants your stem cells now. The company offers a service to cryogenically freeze stem cells taken from bone marrow.

The theory behind the procedure, according to Forever Labs CEO Steven Clausnitzer, is based on research showing that stem cells may be a key component for repairing cellular damage. That’s because stem cells can develop into many different cell types and can divide endlessly to replenish other cells. Clausnitzer notes that there are upwards of a thousand clinical studies looking at using stem cells to treat age-related conditions such as cardiovascular disease.

However, stem cells come with their own expiration date, which usually coincides with the age that most people start experiencing serious health problems. Stem cells harvested from bone marrow at a younger age can potentially provide a therapeutic resource in the future.

“We believe strongly that by having access to your own best possible selves, you’re going to be well positioned to lead healthier, longer lives,” he tells Singularity Hub.

“There’s a compelling argument to be made that if you started to maintain the bone marrow population, the amount of nuclear cells in your bone marrow, and to re-up them so that they aren’t declining with age, it stands to reason that you could absolutely mitigate things like cardiovascular disease and stroke and Alzheimer’s,” he adds.

Clausnitzer notes that the stored stem cells can be used today in developing therapies to treat chronic conditions such as osteoarthritis. However, the more exciting prospect—and the reason he put his own 38-year-old stem cells on ice—is that he believes future stem cell therapies can help stave off the ravages of age-related disease.

“I can start reintroducing them not to treat age-related disease but to treat the decline in the stem-cell niche itself, so that I don’t ever get an age-related disease,” he says. “I don’t think that it equates to immortality, but it certainly is a step in that direction.”

Indecisive on Immortality
The societal implications of a longer-living human species are a guessing game at this point. We do know that by mid-century, the global population of those aged 65 and older will reach 1.6 billion, while those older than 80 will hit nearly 450 million, according to the National Academies of Science. If many of those people could enjoy healthy lives in their twilight years, an enormous medical cost could be avoided.

Faragher is certainly working toward a future where human health is ubiquitous. Human immortality is another question entirely.

“The longer lifespans become, the more heavily we may need to control birth rates and thus we may have fewer new minds. This could have a heavy ‘opportunity cost’ in terms of progress,” he says.

And does anyone truly want to live forever?

“There have been happy moments in my life but I have also suffered some traumatic disappointments. No [drug] will wash those experiences out of me,” Faragher says. “I no longer view my future with unqualified enthusiasm, and I do not think I am the only middle-aged man to feel that way. I don’t think it is an accident that so many ‘immortalists’ are young.

“They should be careful what they wish for.”

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#432467 Dungeons and Dragons, Not Chess and Go: ...

Everyone had died—not that you’d know it, from how they were laughing about their poor choices and bad rolls of the dice. As a social anthropologist, I study how people understand artificial intelligence (AI) and our efforts towards attaining it; I’m also a life-long fan of Dungeons and Dragons (D&D), the inventive fantasy roleplaying game. During a recent quest, when I was playing an elf ranger, the trainee paladin (or holy knight) acted according to his noble character, and announced our presence at the mouth of a dragon’s lair. The results were disastrous. But while success in D&D means “beating the bad guy,” the game is also a creative sandbox, where failure can count as collective triumph so long as you tell a great tale.

What does this have to do with AI? In computer science, games are frequently used as a benchmark for an algorithm’s “intelligence.” The late Robert Wilensky, a professor at the University of California, Berkeley and a leading figure in AI, offered one reason why this might be. Computer scientists “looked around at who the smartest people were, and they were themselves, of course,” he told the authors of Compulsive Technology: Computers as Culture (1985). “They were all essentially mathematicians by training, and mathematicians do two things—they prove theorems and play chess. And they said, hey, if it proves a theorem or plays chess, it must be smart.” No surprise that demonstrations of AI’s “smarts” have focused on the artificial player’s prowess.

Yet the games that get chosen—like Go, the main battlefield for Google DeepMind’s algorithms in recent years—tend to be tightly bounded, with set objectives and clear paths to victory or defeat. These experiences have none of the open-ended collaboration of D&D. Which got me thinking: do we need a new test for intelligence, where the goal is not simply about success, but storytelling? What would it mean for an AI to “pass” as human in a game of D&D? Instead of the Turing test, perhaps we need an elf ranger test?

Of course, this is just a playful thought experiment, but it does highlight the flaws in certain models of intelligence. First, it reveals how intelligence has to work across a variety of environments. D&D participants can inhabit many characters in many games, and the individual player can “switch” between roles (the fighter, the thief, the healer). Meanwhile, AI researchers know that it’s super difficult to get a well-trained algorithm to apply its insights in even slightly different domains—something that we humans manage surprisingly well.

Second, D&D reminds us that intelligence is embodied. In computer games, the bodily aspect of the experience might range from pressing buttons on a controller in order to move an icon or avatar (a ping-pong paddle; a spaceship; an anthropomorphic, eternally hungry, yellow sphere), to more recent and immersive experiences involving virtual-reality goggles and haptic gloves. Even without these add-ons, games can still produce biological responses associated with stress and fear (if you’ve ever played Alien: Isolation you’ll understand). In the original D&D, the players encounter the game while sitting around a table together, feeling the story and its impact. Recent research in cognitive science suggests that bodily interactions are crucial to how we grasp more abstract mental concepts. But we give minimal attention to the embodiment of artificial agents, and how that might affect the way they learn and process information.

Finally, intelligence is social. AI algorithms typically learn through multiple rounds of competition, in which successful strategies get reinforced with rewards. True, it appears that humans also evolved to learn through repetition, reward and reinforcement. But there’s an important collaborative dimension to human intelligence. In the 1930s, the psychologist Lev Vygotsky identified the interaction of an expert and a novice as an example of what became called “scaffolded” learning, where the teacher demonstrates and then supports the learner in acquiring a new skill. In unbounded games, this cooperation is channelled through narrative. Games of It among small children can evolve from win/lose into attacks by terrible monsters, before shifting again to more complex narratives that explain why the monsters are attacking, who is the hero, and what they can do and why—narratives that aren’t always logical or even internally compatible. An AI that could engage in social storytelling is doubtless on a surer, more multifunctional footing than one that plays chess; and there’s no guarantee that chess is even a step on the road to attaining intelligence of this sort.

In some ways, this failure to look at roleplaying as a technical hurdle for intelligence is strange. D&D was a key cultural touchstone for technologists in the 1980s and the inspiration for many early text-based computer games, as Katie Hafner and Matthew Lyon point out in Where Wizards Stay up Late: The Origins of the Internet (1996). Even today, AI researchers who play games in their free time often mention D&D specifically. So instead of beating adversaries in games, we might learn more about intelligence if we tried to teach artificial agents to play together as we do: as paladins and elf rangers.

This article was originally published at Aeon and has been republished under Creative Commons.

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#432456 This Planned Solar Farm in Saudi Arabia ...

Right now it only exists on paper, in the form of a memorandum of understanding. But if constructed, the newly-announced solar photovoltaic project in Saudi Arabia would break an astonishing array of records. It’s larger than any solar project currently planned by a factor of 100. When completed, nominally in 2030, it would have a capacity of an astonishing 200 gigawatts (GW). The project is backed by Softbank Group and Saudi Arabia’s new crown prince, Mohammed Bin Salman, and was announced in New York on March 27.

The Tengger Desert Solar Park in China, affectionately known as the “Great Wall of Solar,” is the world’s largest operating solar farm, with a capacity of 1.5 GW. Larger farms are under construction, including the Westlands Solar Park, which plans to finish with 2.7 GW of capacity. But even those that are only in the planning phases are dwarfed by the Saudi project; two early-stage solar parks will have capacity of 7.2 GW, and the plan involves them generating electricity as early as next year.

It makes more sense to compare to slightly larger projects, like nations, or even planets. Saudi Arabia’s current electricity generation capacity is 77 GW. This project would almost triple it. The current total solar photovoltaic generation capacity installed worldwide is 303 GW. In other words, this single solar farm would account for a similar installed capacity as the entire world’s capacity in 2015, and over a thousand times more than we had in 2000.

That’s exponential growth for you, folks.

Of course, practically doubling the world’s solar capacity doesn’t come cheap; the nominal estimate for the budget is around $200 billion (compared to $20 billion for around half a gigawatt of fusion, though, it may not seem so bad.) But the project would help solve a number of pressing problems for Saudi Arabia.

For a start, solar power works well in the desert. The irradiance is high, you have plenty of empty space, and peak demand is driven by air conditioning in the cities and so corresponds with peak supply. Even if oil companies might seem blasé about the global supply of oil running out, individual countries are aware that their own reserves won’t last forever, and they don’t want to miss the energy transition. The country’s Vision 2030 project aims to diversify its heavily oil-dependent economy by that year. If they can construct solar farms on this scale, alongside the $80 billion the government plans to spend on a fleet of nuclear reactors, it seems logical to export that power to other countries in the region, especially given the amount of energy storage that would be required otherwise.

We’ve already discussed a large-scale project to build solar panels in the desert then export the electricity: the DESERTEC initiative in the Sahara. Although DESERTEC planned a range of different demonstration plants on scales of around 500 MW, its ultimate ambition was to “provide 20 percent of Europe’s electricity by 2050.” It seems that this project is similar in scale to what they were planning. Weaning ourselves off fossil fuels is going to be incredibly difficult. Only large-scale nuclear, wind, or solar can really supply the world’s energy needs if consumption is anything like what it is today; in all likelihood, we’ll need a combination of all three.

To make a sizeable contribution to that effort, the renewable projects have to be truly epic in scale. The planned 2 GW solar park at Bulli Creek in Australia would cover 5 square kilometers, so it’s not unreasonable to suggest that, across many farms, this project could cover around 500 square kilometers—around the size of Chicago.

It will come as no surprise that Softbank is involved in this project. The founder, Masayoshi Son, is well-known for large-scale “visionary” investments. This is suggested by the name of his $100 billion VC fund, the Softbank Vision Fund, and the focus of its investments. It has invested millions of dollars in tech companies like Uber, IoT, NVIDIA and ARM, and startups across fields like VR, agritech, and AI.

Of course, Softbank is also the company that bought infamous robot-makers Boston Dynamics from Google when their not-at-all-sinister “Project Replicant” was sidelined. Softbank is famous in Japan in part due to their mascot, Pepper, which is probably the most widespread humanoid robot on the planet. Suffice it to say that Softbank is keen to be a part of any technological development, and they’re not afraid of projects that are truly vast in scope.

Since the Fukushima disaster in 2011 led Japan to turn away from nuclear power, Son has also been focused on green electricity, floating the idea of an Asia Super Grid. Similar to DESERTEC, it aims to get around the main issues with renewable energy (the land use and the intermittency of supply) with a vast super-grid that would connect Mongolia, India, Japan, China, Russia, and South Korea with high-voltage DC power cables. “Since this is such a grandiose project, many people told me it is crazy,” Son said. “They said it is impossible both economically and politically.” The first stage of the project, a demonstration wind farm of 50 megawatts in Mongolia, began operating in October of last year.

Given that Saudi Arabia put up $45 billion of the Vision Fund, it’s also not surprising to see the location of the project; Softbank reportedly had plans to invest $25 billion of the Vision Fund in Saudi Arabia, and $1 billion will be spent on the first solar farms there. Prince Mohammed Bin Salman, 32, who recently consolidated power, is looking to be seen on the global stage as a modernizer. He was effusive about the project. “It’s a huge step in human history,” he said. “It’s bold, risky, and we hope we succeed doing that.”

It is the risk that will keep renewable energy enthusiasts concerned.

Every visionary plan contains the potential for immense disappointment. As yet, the Asian Super Grid and the Saudi power plan are more or less at the conceptual stage. The fact that a memorandum of understanding exists between the Saudi government and Softbank is no guarantee that it will ever be built. Some analysts in the industry are a little skeptical.

“It’s an unprecedented construction effort; it’s an unprecedented financing effort,” said Benjamin Attia, a global solar analyst for Green Tech Media Research. “But there are so many questions, so few details, and a lot of headwinds, like grid instability, the availability of commercial debt, construction, and logistics challenges.”

We have already seen with the DESERTEC initiative that these vast-scale renewable energy projects can fail, despite immense enthusiasm. They are not easy to accomplish. But in a world without fossil fuels, they will be required. This project could be a flagship example for how to run a country on renewable energy—or another example of grand designs and good intentions. We’ll have to wait to find out which.

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#432311 Everyone Is Talking About AI—But Do ...

In 2017, artificial intelligence attracted $12 billion of VC investment. We are only beginning to discover the usefulness of AI applications. Amazon recently unveiled a brick-and-mortar grocery store that has successfully supplanted cashiers and checkout lines with computer vision, sensors, and deep learning. Between the investment, the press coverage, and the dramatic innovation, “AI” has become a hot buzzword. But does it even exist yet?

At the World Economic Forum Dr. Kai-Fu Lee, a Taiwanese venture capitalist and the founding president of Google China, remarked, “I think it’s tempting for every entrepreneur to package his or her company as an AI company, and it’s tempting for every VC to want to say ‘I’m an AI investor.’” He then observed that some of these AI bubbles could burst by the end of 2018, referring specifically to “the startups that made up a story that isn’t fulfillable, and fooled VCs into investing because they don’t know better.”

However, Dr. Lee firmly believes AI will continue to progress and will take many jobs away from workers. So, what is the difference between legitimate AI, with all of its pros and cons, and a made-up story?

If you parse through just a few stories that are allegedly about AI, you’ll quickly discover significant variation in how people define it, with a blurred line between emulated intelligence and machine learning applications.

I spoke to experts in the field of AI to try to find consensus, but the very question opens up more questions. For instance, when is it important to be accurate to a term’s original definition, and when does that commitment to accuracy amount to the splitting of hairs? It isn’t obvious, and hype is oftentimes the enemy of nuance. Additionally, there is now a vested interest in that hype—$12 billion, to be precise.

This conversation is also relevant because world-renowned thought leaders have been publicly debating the dangers posed by AI. Facebook CEO Mark Zuckerberg suggested that naysayers who attempt to “drum up these doomsday scenarios” are being negative and irresponsible. On Twitter, business magnate and OpenAI co-founder Elon Musk countered that Zuckerberg’s understanding of the subject is limited. In February, Elon Musk engaged again in a similar exchange with Harvard professor Steven Pinker. Musk tweeted that Pinker doesn’t understand the difference between functional/narrow AI and general AI.

Given the fears surrounding this technology, it’s important for the public to clearly understand the distinctions between different levels of AI so that they can realistically assess the potential threats and benefits.

As Smart As a Human?
Erik Cambria, an expert in the field of natural language processing, told me, “Nobody is doing AI today and everybody is saying that they do AI because it’s a cool and sexy buzzword. It was the same with ‘big data’ a few years ago.”

Cambria mentioned that AI, as a term, originally referenced the emulation of human intelligence. “And there is nothing today that is even barely as intelligent as the most stupid human being on Earth. So, in a strict sense, no one is doing AI yet, for the simple fact that we don’t know how the human brain works,” he said.

He added that the term “AI” is often used in reference to powerful tools for data classification. These tools are impressive, but they’re on a totally different spectrum than human cognition. Additionally, Cambria has noticed people claiming that neural networks are part of the new wave of AI. This is bizarre to him because that technology already existed fifty years ago.

However, technologists no longer need to perform the feature extraction by themselves. They also have access to greater computing power. All of these advancements are welcomed, but it is perhaps dishonest to suggest that machines have emulated the intricacies of our cognitive processes.

“Companies are just looking at tricks to create a behavior that looks like intelligence but that is not real intelligence, it’s just a mirror of intelligence. These are expert systems that are maybe very good in a specific domain, but very stupid in other domains,” he said.

This mimicry of intelligence has inspired the public imagination. Domain-specific systems have delivered value in a wide range of industries. But those benefits have not lifted the cloud of confusion.

Assisted, Augmented, or Autonomous
When it comes to matters of scientific integrity, the issue of accurate definitions isn’t a peripheral matter. In a 1974 commencement address at the California Institute of Technology, Richard Feynman famously said, “The first principle is that you must not fool yourself—and you are the easiest person to fool.” In that same speech, Feynman also said, “You should not fool the layman when you’re talking as a scientist.” He opined that scientists should bend over backwards to show how they could be wrong. “If you’re representing yourself as a scientist, then you should explain to the layman what you’re doing—and if they don’t want to support you under those circumstances, then that’s their decision.”

In the case of AI, this might mean that professional scientists have an obligation to clearly state that they are developing extremely powerful, controversial, profitable, and even dangerous tools, which do not constitute intelligence in any familiar or comprehensive sense.

The term “AI” may have become overhyped and confused, but there are already some efforts underway to provide clarity. A recent PwC report drew a distinction between “assisted intelligence,” “augmented intelligence,” and “autonomous intelligence.” Assisted intelligence is demonstrated by the GPS navigation programs prevalent in cars today. Augmented intelligence “enables people and organizations to do things they couldn’t otherwise do.” And autonomous intelligence “establishes machines that act on their own,” such as autonomous vehicles.

Roman Yampolskiy is an AI safety researcher who wrote the book “Artificial Superintelligence: A Futuristic Approach.” I asked him whether the broad and differing meanings might present difficulties for legislators attempting to regulate AI.

Yampolskiy explained, “Intelligence (artificial or natural) comes on a continuum and so do potential problems with such technology. We typically refer to AI which one day will have the full spectrum of human capabilities as artificial general intelligence (AGI) to avoid some confusion. Beyond that point it becomes superintelligence. What we have today and what is frequently used in business is narrow AI. Regulating anything is hard, technology is no exception. The problem is not with terminology but with complexity of such systems even at the current level.”

When asked if people should fear AI systems, Dr. Yampolskiy commented, “Since capability comes on a continuum, so do problems associated with each level of capability.” He mentioned that accidents are already reported with AI-enabled products, and as the technology advances further, the impact could spread beyond privacy concerns or technological unemployment. These concerns about the real-world effects of AI will likely take precedence over dictionary-minded quibbles. However, the issue is also about honesty versus deception.

Is This Buzzword All Buzzed Out?
Finally, I directed my questions towards a company that is actively marketing an “AI Virtual Assistant.” Carl Landers, the CMO at Conversica, acknowledged that there are a multitude of explanations for what AI is and isn’t.

He said, “My definition of AI is technology innovation that helps solve a business problem. I’m really not interested in talking about the theoretical ‘can we get machines to think like humans?’ It’s a nice conversation, but I’m trying to solve a practical business problem.”

I asked him if AI is a buzzword that inspires publicity and attracts clients. According to Landers, this was certainly true three years ago, but those effects have already started to wane. Many companies now claim to have AI in their products, so it’s less of a differentiator. However, there is still a specific intention behind the word. Landers hopes to convey that previously impossible things are now possible. “There’s something new here that you haven’t seen before, that you haven’t heard of before,” he said.

According to Brian Decker, founder of Encom Lab, machine learning algorithms only work to satisfy their preexisting programming, not out of an interior drive for better understanding. Therefore, he views AI as an entirely semantic argument.

Decker stated, “A marketing exec will claim a photodiode controlled porch light has AI because it ‘knows when it is dark outside,’ while a good hardware engineer will point out that not one bit in a register in the entire history of computing has ever changed unless directed to do so according to the logic of preexisting programming.”

Although it’s important for everyone to be on the same page regarding specifics and underlying meaning, AI-powered products are already powering past these debates by creating immediate value for humans. And ultimately, humans care more about value than they do about semantic distinctions. In an interview with Quartz, Kai-Fu Lee revealed that algorithmic trading systems have already given him an 8X return over his private banking investments. “I don’t trade with humans anymore,” he said.

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