Steve LeVine
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A quarter trillion dollars is at risk when bitcoin crashes — and that’s just for starters

Illustration: Lazaro Gamio / Axios

One day, it's assumed, the technology underlying bitcoin will trigger serious financial disruption. But as of now, that tech — called blockchain — is hindered by stubborn shortcomings. And one of the biggest potential bombshells — a shakeup of the $8 trillion-a-year credit card industry — may be a decade away, if it happens at all, experts tell Axios.
Driving the news: Like tulips and dotcom shares before them, crypto-currencies—the only blockchain technology currently operating at large scale — have gripped the wise and reckless alike. Investors won't lose all the $250 billion in bitcoin that they currently hold when the fever inevitably breaks, but many will forgo paper profits, plus much of their original investment.

Meanwhile, fraud, theft and other mischief threatens the first bitcoin futures trading, which began last night, per the Wall Street Journal. The futures price for January bitcoin surged to $18,850 at one point early today and twice triggered a halt to trading.

How it works: Invented in 2008, blockchain is a secure ledger where users can record transactions like payments, a chain of supply, a contract, and the origin of commodities like pork or diamonds.
  • The main blockchain technology — crypto-currencies, digital cash with no central organizer like the Fed — took off this year, with people pouring money into launch events called Initial Coin Offerings (ICOs) by dozens of the new currencies.
  • Most of the money has gone into bitcoin, the most popular crypto-currency, whose face value has surged by 15X this year. From about $960 at the start of January, bitcoins were selling for more than $15,000 as of last evening.
  • A way to abandon the dollar: The central banks of some nations are studying the creation of their own digital currencies: Earlier this month, Venezuela said it will create the oil-backed "petro." Russia is launching its own as well, reportedly to be called the CryptoRuble.
But that craze is only the most visible part of a powerful blockchain fever. Deloitte Consulting found that 23 industries — effectively every one that the firm studies — are working on blockchain strategies. "Blockchain is coming. The question is how fast," Deloitte's Eric Piscini tells Axios. "Ten or 20 years from now, we'll use blockchain without knowing it."
Here are the sectors that are the furthest along in blockchain pilot projects, according to Courtney Rickert-McCaffrey, a manager at AT Kearney, a management consulting firm.
  • Cross-border payments: Investment banks and tech companies like IBM, Citi and JP Morgan are running blockchain projects that would take over the transfer, clearing and settlement of international payments currently handled mostly by SWIFT. The SWIFT system can take days to clear a payment and charge about $50, but Piscini said blockchain can accomplish the whole thing in seconds and cost 20 cents.
  • Consumer product verification: Walmart has carried out pilot projects with IBM, using blockchain to track Chinese pork, with the idea of lessening the chance that it comes from infected farms, and Mexican mangoes. Now it has expanded its pilot to include Kroger, Tyson's Foods and other companies.
  • Supply chain management: Roche and Pfizer are among the major pharmaceutical companies working with a pilot project that uses blockchain to track the trace components of drugs and prevent counterfeiting and contamination. Generally speaking, blockchain is seen as simplifying supply chain management, the movement of stuff to and from ports and all the way to consumers.
  • Data storage: Northern Trust, a Chicago asset management company, is using blockchain to record investment transactions.
"Blockchain is part of the C-suite zeitgeist," Rickert-McCaffrey said.
The problem: All of these, save crypto-currencies, are pilot projects. No one knows how and when they can be scaled up to broad use. There are two main reasons:
  • Blockchain is super-slow when compared with what's already available. Bitcoin can handle just seven transactions per second. Some startups report technological fast lanes — side roads operating out of the main blockchain — that process 10,000 transactions a second. But that is still slow — current systems can do them five times faster.
  • The second obstacle is the very boom in blockchain, which has sprouted hundreds of platforms, none of which can interact with the other. That hinders the communication that is crucial to blockchain being useful. Neither are there agreed-upon blockchain standards for specific uses, like the global transfer of money.
In addition, a substantial part of the economy is largely left out in all this talk, and that is the consumer. While buyers can be surer about the source of the fish they buy, there is no indication as of now that the ordinary global citizen will derive much value, or save any money.
Campbell Harvey, a professor of finance at Duke University, thinks one sector ripe for a shakeup is credit cards. Visa, Mastercard and American Express charge merchants 2% to 3% of a purchase, a cost of doing business that merchants work into their product prices. The presumption is that blockchain can substantially reduce that cost.
Startups such as Coinbase have launched "digital wallets." Almost all of them still rely on the major credit card systems, but Harvey thinks entrepreneurs will devise a blockchain card.
"They are angling for a product that is so simple that the average consumer doesn't need to know what is happening," he said in an email exchange. "You will have a credit/debit card and pay in USD. However, in the background, there is a switch to a cryptocurrency from the consumer to the retailer and then the retailer switches back into USD."
But other blockchain experts think the credit card companies are safe from disruption. In a report last year, Credit Suisse said that transactions are so smooth for consumers that few will demand the invention of a better system.
And even if entrepreneurs create one, it will be hard to scale up to the size of the major credit card companies, with a half-century lead time and trust relationships with more than 20,000 retailers across the globe. Moreover, the cost of blockchain may not be much cheaper than the credit card companies currently charge, many experts say. Just in case they do end up threatened, VISA and MasterCard have themselves invested in blockchain technologies — in October, Mastercard began allowing payments by blockchain, and, in a collaboration with Chain, a San Francisco startup, VISA says it will offer up its own system next year.
  • Blockchain is "not really optimized for retail payments," Joseph Bonneau, a researcher at Stanford University's Applied Crypto Group, told Axios. "Perhaps in the long term, but they have a ways to go. Maybe 10 years or more." Deloitte's Piscini said blockchain credit cards may never be created.
Featured

New paper: China is going head-to-head with the U.S. in AI

Alibaba's Jack Ma increasingly goes after the same market as Amazon. (Mark Lennihan / AP)

China's massive churn of raw data and determination to own the technologies of the future put it in a head-to-head race with the United States for dominance in artificial intelligence, according to a new paper co-authored by Kai-fu Lee, China's most prominent VC and the former head of Google China.
Why it matters: AI is widely expected to be the next broad technological advance that revolutionizes global business and whole economies. If Lee is right, China's advantages give it a strong chance to win the economic and geopolitical muscle that will accrue to whoever grabs the lead in AI research and applications. "A very good scientist with a ton of data will beat a super scientist with a small amount of data," Lee wrote, along with Eurasiagroup's Paul Triolo. "This is not always well understood, but it is critical to determining which companies–and countries–will take the global lead in AI development."

Here are key takeaways from the paper:

  • China's No. 1 advantage is its huge data sets and flexibility to use them in AI applications: Chinese use phones to pay for goods 50X more than Americans; they use them for food delivery 10X more than the US; and shared bicycles 300X more. All of that churns out data. "This single advantage will be insurmountable by other countries," the paper says.
  • Another advantage: China puts up few bureaucratic roadblocks, such as local and federal governments that sometimes embroil tech issues in "endless debates," and labor attempting to delay projects such as autonomous trucks.
  • Chinese self-driving tech is two years behind the US, but its companies will later at least co-lead in autonomous vehicles, in addition to optics and "Internet AI," business built around the amassing of data.
  • Beijing will become a co-leader with Silicon Valley as an AI innovation center.
  • China's Alibaba will hold its own against Amazon, and Tencent will "lead Facebook." Baidu will continue to lag Google in AI.
Featured

Good news: inequality shrinking

Income inequality — the stubborn curse of the current era and, many think, a key factor in the global uprising against establishment powers — appears to be on a solid, steady decline in the U.S., according to a new report.

Data: Indeed analysis of BLS monthly jobs data; Chart: Axios Visuals

Quick take: For more than a year, the wage gap has been closing between American workers with the least and the highest education—wages have been going up the most for workers who need it the most, according to Jed Kolko, chief economist for Indeed, the jobs website. And this year, the most chronically unemployed Americans began to return to work.

What we don't know: The trend is coming on slowly rather than hitting workers in one bang. It will take time before it's clear whether the added dollars begin to erode the deep public antipathy and distrust of the system that seem to be at least in part fueled by a loss of hope in the economy.

It's also not clear who may gain politically from this shift: President Trump is likely to claim that he is delivering on his promise to the forgotten working class during his 2016 campaign. Democrats, however, will probably note that there have been 85 months of consecutive job growth leading to today's 4.1% jobless rate, and argue that these dividends for the working class are the product mostly of President Obama's economic program.

The details: For the last year or two, economists and politicians have fretted over how to loosen up worker wages, which have been effectively stagnant since the 1970s. Flat wages have been set against the meteoric rise of a new class of billionaire plutocrats to create a picture of massive and chronic income inequality and unfairness, and that impression appeared to help elect Trump.

  • But for three consecutive years, wages have been rising the fastest for jobs with the lowest pay, Kolko tells Axios. And now the economy is specifically lifting up workers with the least education, a key social and economic dividing line—there have been five straight quarters of a shrinkage of the wage inequality gap, Kolko said, with surging wage gains for those with only a high school diploma.
  • The median wage for someone with a high school degree grew to $714 a week as of the end of September, from $700 at the same point in 2016; high-wage workers just budged up to $1,271 a week, though, from $1,266. So the gap between them narrowed to $557 from $566, almost 2%.
  • "This past year has been good news for the least-educated workers," Kolko tells Axios.

Metrics for the hard-core unemployed and lowest-paid workers—part of the core of the Trump base—have all seen significant gains.

  • Broad unemployment including those no longer searching for work and involuntarily working part time fell to 7.9% in October, from 9.2% at the beginning of the year, Kolko said.
  • And the share of the main working population that is employed — those 25 to 54 —grew to 78.8%, from 78.2%.

Those are the best numbers since 2000. In December 2000—the last time unemployment was at 4.1% — broad unemployment was at 6.9%. And the working population 25 to 54 years old was 81.4%.

That means that well over 1 million Americans still need to be drawn back into the work force.

And there are signs that the most stubborn unemployed are trying to return to work. Kolko said that searches are up at Indeed for the terms "no background check" and "felony-friendly jobs." "This suggested that people who have struggled more in the past to find jobs are encouraged by the tightening labor market to look for work," he said.

Featured

Future of Work

Welcome back. Please invite your friends and colleagues to join the conversation. Tell me anything on your mind, including what you think about what you are reading here and in the daily stream. Just reply to this email, or reach me at steve@axios.com. Let's start with ...

1 big thing: The shrinking of inequality

Data: Indeed analysis of BLS monthly jobs data; Chart: Axios Visuals

Income inequality — the stubborn curse of the current era and, many think, a key factor in the global uprising against establishment powers — appears to be on a solid decline in the U.S., according to a new report.

Quick take: Wages have been going up the most for workers who need it the most, according to Jed Kolko, chief economist for jobs website Indeed. And this year, he says, the most chronically unemployed Americans began to return to work.

  • For three consecutive years, wages have been rising the fastest for jobs with the lowest pay, Kolko tells Axios.
  • And now the economy is specifically lifting up workers with the least education, a key social and economic dividing line. There have been five straight quarters of shrinkage in the wage inequality gap, Kolko said, with surging gains in wages for those with high school diplomas.
  • The median wage for someone with a high school degree grew to $714 a week as of the end of September, from $700 at the same point in 2016; workers with an undergraduate college degree budged up slightly to $1,271 a week, from $1,266. So the gap between the two narrowed to $557 from $566, almost 2%.
  • "This past year has been good news for the least-educated workers," Kolko tells Axios.

Why it matters: For the last year or two, economists and politicians have fretted over how to loosen up worker wages, which have been effectively stagnant since the 1970s. Flat wages have been set against the meteoric rise of a new class of billionaire plutocrats to create a picture of massive and chronic income inequality and unfairness, and that impression appeared to help elect President Trump. More broadly, it helped lead to Brexit and other anti-elite movements in Europe.

Thought bubble: The trend is coming on slowly rather than hitting workers in one bang. It will take time before it's clear whether the added dollars begin to erode the deep public antipathy and distrust of the system that seem to be at least partly fueled by a loss of hope in the economy.

Go deeper: It's also not clear who may gain politically from this shift. Trump is likely to claim that he is delivering on his promise to the "forgotten working class" during his 2016 campaign. Democrats, however, will probably note that there have been 85 months of consecutive job growth leading to today's 4.1% jobless rate, and argue that these dividends for the working class are mostly the product of former President Obama's economic program.

Read the full piece here.

2. Primitive AI

Data: Artificial Intelligence Index; Chart: Chris Canipe / Axios

Artificial intelligence, it is said, will solve many of our most vexing problems once it is fully developed. However, despite advances, it's still in a rudimentary state compared with the ambitions, according to a report published recently by Stanford University.

Where it stands: Some of the best progress has been in the narrow realm of games. In a paper released yesterday, Alphabet's DeepMind, a top AI lab, revealed AlphaZero. This is the algorithm that in just 24 hours learned chess and its Japanese version Shogi, and went on to beat world champions in both.

Why it matters: The advances in games are important but life isn't a game. AI progress outside of these areas has been harder to define.

"The most important thing for AI is to go from exceptional promise to use in actual everyday life," Martial Hebert, director of the Robotics Institute at Carnegie Mellon University, tells Axios.

Here are some key takeaways from the AI Index report:

  • AI investment is through the roof: Between 2000 and 2017, the number of AI startups in the U.S. grew 14 times — from 47 to 649. Annual venture capital investment in AI rose 6 times last year, to $3.5 billion (see chart above).
  • Skills are in demand: The number of U.S. job postings listing AI as a required skill was about 11,100 last year. So far this year, the number is 31,000.
  • A race is on between the U.S. and China: Kai-fu Lee, CEO of Beijing-based VC firm Sinovation, said in the report that China is making impressive progress in AI, and has far more data — the main building block of robust AI — to work with than anyone else. "In this age of AI, I predict that the United States-China duopoly is not only inevitable. It has already arrived," he said.
  • Experts worry about hype: In expert comment included in the report, Michael Wooldridge, head of computer science at Oxford University, said exaggeration has created an AI bubble and that there is the potential for a third "AI winter," a period of disillusion and a drawdown of investment as the field regroups.

"There are plenty of charlatans and snake oil salesmen out there, who are quite happy to sell whatever they happen to be doing as AI, and it is a source of great personal frustration that the press are happy to give airtime to views on AI that I consider to be ill-informed at best, lunatic fringe at worst," Wooldridge wrote.

Read the full piece here, written with Science editor Alison Snyder.

3. The smart speaker war

Illustration: Rebecca Zisser / Axios

Retailers think this is the holiday season of the smart speaker, with Google, Amazon, and other tech firms spending big on marketing and discounts to get their voice-assistant technology into as many living rooms as possible.

The numbers: David Watkins of Strategy Analytics tells Axios' Chris Matthews that 14 million smart speakers will be sold globally during the final three months of the year, driven by heavy discounting of Google's Home and Amazon's Echo devices, and evidence that Alibaba's Genie is outselling expectations in China.

Why it matters: That's a lot of smart speakers – these devices tend to be bought one or two per home, and there are just 125 million U.S. households. Amazon and Google are going all out to move them, not because they earn a profit, but to hook consumers and open up e-commerce and advertising revenue down the road.

  • Quick take: Think of them as the new search engine.

Thumbs on the scale: Suzanne Tager, a senior director at Bain, says they conducted a survey and found that Alexa-enabled Amazon devices first steer customers toward Amazon's private label items "even though these products represent only about 2%" of total goods sold. Tager also says the Amazon devices point to goods the consumer has previously bought.

Amazon did not respond to emails asking for a response.

Read the rest of Chris' post.

4. Worthy of your time

YouTube logo. Photo: Rego Korosi via Flickr CC

A surge in Americans living on the street (AP's Christopher Weber and Geoff Mulvihill)

Wanted ads: the soon-to-be growing profession of Google content reviewer (Axios)

Behind the boom in machine learning (Axios)

Childhood surroundings top the reasons for later ingenuity (The Economist)

5. 1 fun thing: Toronto's big year

Toronto's MaRS tech incubator. Photo: MaRS Discovery District

In June, the New York Times declared Toronto "a high-tech hotbed," one of a slew of splashy articles that the paper lavished on the Canadian city this year. In August, London's Daily Telegraph devoted a three-part series to Toronto's tech and science sector.

The big picture: Toronto has been the fastest growing tech city in North America this year, according to real estate and investment firm CBRE, in part because it's cheaper to live and work there than in Silicon Valley or Seattle. Toronto also has been pushing to become one of the world's leading hubs for R&D of artificial intelligence.

  • Earlier this year, the city opened the Vector Institute, an AI research center situated within the gigantic MaRS tech incubator, funded with $130 million from the government and companies like Google and Nvidia.
  • Geoffrey Hinton, the leading pioneer of machine learning, will be Vector's chief scientific adviser. Hinton also opened Google Brain Toronto, another artificial intelligence lab.
  • Canada has prioritized luring home Canadian talent who had drifted to Silicon Valley. For this purpose, Prime Minister Justin Trudeau allocated $93 million for AI research centers in 3 Canadian cities including Toronto.

Other moves: The city is also gussying itself up. In October, Alphabet's Sidewalk Labs said it will turn 800 acres of Toronto's Lake Ontario waterfront into a walkable, urban and tech-infused district. It's planning what it calls "the world's first neighborhood built from the internet up," with streets designed for driverless cars, delivery robots and heated sidewalks.

Be smart: Toronto also has profited from the U.S. crackdown on immigration, which has made places like it more attractive for leading science and tech students and professionals seeking to study and work outside their home country.

Featured

AI can beat humans only one game at a time

Despite all of the potential for artificial intelligence to solve our most vexing problems, it's still in a primitive state, according to a new report by Stanford University. But a separate paper, this one by Alphabet's DeepMind, suggests again that it has made some of its best progress in the narrow realm of games.

Why it matters: Those advances are important, but life isn't a game. AI progress outside of these areas has been harder to define and track. "The most important thing for AI is to go from exceptional promise to use in actual everyday life," Martial Hebert, director of the Robotics Institute at Carnegie Mellon University, tells Axios.

Note: Funding data for 2017 is partial through July. Data: Artificial Intelligence Index; Chart: Chris Canipe / Axios

Here are key takeaways from the Stanford report, called the AI Index:

  • AI investment is through the roof: Between 2000 and 2017, the number of AI startups in the U.S. grew 14X — from 47 to 649. Annual VC investment in AI rose 6X last year, to $3.5 billion.
  • AI skills are in demand: The number of U.S. job postings on Monster.com listing AI as a required skill was about 11,100 last year. So far this year, the number is 31,000.
  • A race is on between the U.S. and China: Kai-fu Lee, CEO of Sinovation, a Beijing-based VC firm, said in the report that China is making impressive progress in AI, and has far more data—the main building block of robust AI—to work with than anyone else. "In this age of AI, I predict that the United States-China duopoly is not only inevitable. It has already arrived," he said.
  • AI is good—at some things: AI is on par or better than humans at detecting objects in an image. (Machines can do this with half the error rate of humans.).
  • Yes, but: Algorithms struggle to capture the nuanced meaning in the words we use and how we use them. This is an active area of research. At the Allen Institute for Artificial Intelligence, an algorithm now scores about 42% on science questions an 8th grader might encounter, an improvement of 12% since the beginning of 2016. "We continue to move the score higher and higher," says Institute director Oren Etzioni.

The new advances in games: In a paper released yesterday, DeepMind, a top AI lab, introduced AlphaZero, an algorithm that in just 24 hours learned chess and its Japanese version Shogi, and went on to beat world champions in both.

  • AI is beating us at other games, too: It has beat expert humans at Go, Pac-Man and Texas Hold'Em. Work on the latter won the award for best paper at a top AI conference underway this week in Long Beach, CA.

Why it matters: Poker is particularly interesting for AI researchers because information in the game—an opponent's hand, for one—is hidden and deception is a key part of a player's strategy. That makes the game similar to real-world financial markets and political campaigns, where AI could eventually be deployed.

Along the same lines, Facebook and DeepMind are looking to conquer StarCraft, a multiplayer videogame of complexity that dwarfs Go.

  • And experts worry about hype: In an expert comment included in the Stanford report, Michael Wooldridge, head of computer science at Oxford University, said exaggeration has created an AI bubble:
"There are plenty of charlatans and snake oil salesmen out there, who are quite happy to sell whatever they happen to be doing as AI, and it is a source of great personal frustration that the press are happy to give airtime to views on AI that I consider to be ill-informed at best, lunatic fringe at worst."

What's needed: Gregory Allen, an adjunct fellow at the Center for a New American Security, said the field should establish solid long-term milestones for future progress. In the space race, the milestones were breaking the sound barrier, reaching space, reaching orbit, then reaching the Moon.

"If we want to think about future implications of AI in society, it would be helpful to have a longer runway," he said.

Featured

Future of Work

Welcome back. Please invite your friends and colleagues to join the conversation. Tell me anything on your mind, including what you think about what you are reading here and in the daily stream. Just reply to this email, or reach me at steve@axios.com. Let's start with ...

1 big thing: The occupations of the future

Illustration: Lazaro Gamio / Axios

We know that automation is wiping out whole occupations, but are leading experts correct that the unemployed will eventually shift into new professions created by the vibrant economy? And if so, what are some of these new jobs?

21 jobs of the future: In a new report, IT services firm Cognizant identifies 21 jobs that, given economic and commercial trends, people could reasonably be expected to hold – like chief trust officer and man-machine teaming manager.

But how can we track these jobs as they materialize? Cognizant then found proxies for them in Bureau of Labor Statistics data — existing occupations that the agency already follows. Using Axios' Lazaro Gamio's card deck, you can flip through the occupations, and see how the BLS foresees employment and salary developing for each. Next year, the BLS will update the numbers in a new report covering 20182028.

Why it matters: The key question of the age of automation is whether this time of technological disruption is different from all the others that have occurred over the last two centuries. That is, will the economy produce sufficient well-paying jobs for everyone, or will there be profound and intractable joblessness? To begin to answer that question, we need to know what at least some of those jobs might be.

2. Jobs — and troubles — aplenty

Construction workers are among those most at risk in the automation wave. Photo: Ben McCanna / Portland Press Herald via Getty Images

One answer to the above question comes from McKinsey, which is out today with a new report that says governments across the globe will have to intervene massively to hold societies together against the ravages of labor disruption over the next 13 years. Up to 800 million people — including a third of the work force in the U.S. and Germany — will be thrown out of work by 2030, the study says.

The bottom line: The economy of most countries will eventually replace the lost jobs, the study says, but many of the unemployed will need considerable help to shift to new work, and salaries could continue to flatline. "It's a Marshall Plan size of task," Michael Chui, lead author of the McKinsey report, tells Axios.

The numbers: In the eight-month study, the McKinsey Global Institute found that up to 375 million people, comprising 14% of the global work force, will have to shift to a new occupation, since their old one will either no longer exist or need far fewer workers. Chinese will have the highest such absolute numbers — 100 million people changing occupations, or 12% of the country's 2030 work force.

I asked Chui what surprised him the most of the findings. "The degree of transition that needs to happen over time is a real eye opener," he said.

The details, here.

Bonus: AI night at the French residence

Standing at left, French Ambassador to the U.S. Gerard Araud. (Photo: Kim Dozier / TheCipherBrief.com)

The worry about runaway AI and automation is global. At a dinner of about 60 people at his residence Monday evening, French Ambassador to the U.S. Gerard Araud said that the problem is not only about work and society but power.

"If we don't solve our problems together, China or Russia will impose their standards on us," Araud said.

Andrew McAfee, an MIT researcher and co-author most recently of "Machine, Platform, Crowd," said the middle class, as we have come to know it in the post-war decades, is on the way out. The challenge is to figure out a way to recreate it.

"No country will have a stable, prosperous, large middle class doing routine work," McAfee told the dinner, a joint gathering with The Atlantic magazine. "These routine jobs are already in the rear view mirror. Automation will bring shock to more and more professions."

3. Big Tech's next prey

Illustration: Rebecca Zisser / Axios

With tens of billions of dollars in fees at stake, the financial sector seems on the verge of disruption from the next burst of technologies, including artificial intelligence and blockchain. Axios' Shane Savitsky reports that data-laden tech giants including Amazon, Google, and China's Alibaba and Tencent are invading an industry dominated for more than a century by firms like JPMorgan Chase and Goldman Sachs.

Why it matters: Look for Big Tech, with caches of data about billions of people around the globe, to power the next jumps in financial technology ("fintech"), keeping users reined within their own, ever-expanding platforms and absorbing billions in profit that otherwise would have gone to traditional financiers.

  • Amazon Lending, the platform's finance arm, has lent $3 billion to merchants since 2011.
  • Google's venture arm is ramping up investments in cross-border currency transfers and blockchain.
  • And now China's tech giants have crashed onto American shores: last month, cabs in New York and Las Vegas began accepting Alipay, Alibaba's mobile payment juggernaut.

The future is here: Lex Sokolin, global director of fintech strategy at Autonomous Next, said that for Amazon, the shift to lending is natural. And the same goes for people who use the platform. "Amazon knows something about me that a bank never will," he told Axios. "It knows everything about my revenue, and they know my audience — that's something that I might not even know. It lets Amazon take this risk that a bank cannot."

  • China is already in a consumer fintech explosion: Apps like Alibaba's Alipay and Tencent's WeChat Pay are the dominant means of payment in a booming market that lacks credit cards. China's big tech companies have moved laterally to offer a range of classic financial services to individuals and small businesses. In 2016, China had $5.5 trillion in mobile payments, 91% of which are handled by Alipay and WeChat.

Read the rest of Shane's post.

4. A pop-up in London

Photo: Amazon

Black Friday, a holiday linked to Thanksgiving, isn't just for acquisitive Americans anymore. For a third-straight year, U.K. retailers celebrated it wildly, and Amazon dived into the spirit, deploying a five-room, 3,000-square-foot pop-up shop in London's Soho square, Axios' Chris Matthews reports.

Why it matters: Retail startups, e-commerce outlets, and brands are increasingly looking to pop-up stores as a means for driving sales and creating brand awareness. PopUp Republic, a services provider for the pop-up industry, estimates that broadly measured, these stores generate $50 billion in sales in the U.S. annually.

Amazon has opened dozens of smaller pop-ups across America this year, aimed at showcasing its hardware products, like the Kindle Fire. But this was the first in Europe, and, according to Alvaro Morilla, an analyst with Kantar Retail, it hints at a new model for how e-commerce companies will test products, learn about consumer tastes, and burnish their brands.

The London pop-up is not about capturing traditional retail sales at all.

  • Amazon furnished the entire townhouse to look like a family home, with Amazon products strategically placed in rooms where they would be used.
  • "With no checkout point at the store, Amazon was clearly trying to make this about having fun," says Morilla, who argues that Amazon's goal is not to generate in-store sales, but to "create retail theater and hospitality," and encourage shoppers to buy via its increasingly popular smartphone app.
  • "All the staff we spoke to were helpful, and more interested in creating an experience and [a] guided shop over actually 'selling,'" says Morilla.

Read the rest of Chris' post.

5. Worthy of your time

Microcentro Downtown in Buenos Aires, Argentina. Photo: Kike Calvo / AP

The six laws of technology (WSJ's Christopher Mims)

Triumph of the Latin American mall (Citylab's Nolan Gray)

College tuition is up, but not salaries (Marketwatch's Jillian Berman)

The frenzy to lure Amazon (Axios)

Can artificial intelligence be taught to explain itself? (NYT Magazine's Cliff Kuang)

6. 1 forged thing: AI as art sleuth

A forged example of work by artist Mark Rothko. Photo: Patrick Semansky / AP

When the expert eye seems uncertain, infrared and x-ray imaging, carbon dating and chemical analysis are the go-to arbiters of an artwork's authenticity. But in a new paper, U.S. and Swiss researchers say artificial intelligence could be the best detective of all — sometimes from a single stroke, AI can detect a fake every time.

The stakes: An unknown percentage of the artwork currently for sale around the world is fake: Estimates range to well over half. Combine that with the high sums paid for the rarest works — earlier this month, Da Vinci's Salvator Mundi sold for $450 million — and it's clear why the industry can be fraught over authenticity.

"Authenticity is the third rail. Historically, it's the most challenging risk issue for the art market going back to the Renaissance," Laura Patten, who leads the art and finance practice for Deloitte, tells Axios.

The details:

  • Researchers at Rutgers and the Atelier for Restoration and Research of Paintings in The Hague broke down 297 line drawings largely by four major artists — Pablo Picasso, Henry Matisse, Amedeo Modigliani and Egon Schiele — into about 80,000 individual strokes.
  • Then they ran those into two systems of artificial intelligence — machine learning and a deep recurrent neural network. When they applied both of them together, they detected the precise artist about 80% of the time, and the fakes every time.

Why it works: "Most forged art works are based on copying certain compositional and subject matter-related elements and patterns," the researchers said. But they add: "[T]he characteristics of individual strokes carry the artist's unintentional signature, which is hard to imitate or forge, even if the forger intends to do."

Yes, but: Patten said the researchers set a low bar for themselves by commissioning fakes. Next, she said, they should test their system against real fakes.

Read the whole post.

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Researchers say AI can detect art forgeries

A forged example of work by artist Mark Rothko (Photo: Patrick Semansky / AP)

When the expert eye seems uncertain, infrared and x-ray imaging, carbon dating and chemical analysis are the go-to arbiters of an artwork's authenticity. But in a new paper, U.S. and Swiss researchers say artificial intelligence could be the best detective of all—sometimes from a single stroke, AI can detect a fake every time.

The stakes: An unknown percentage of the artwork currently for sale around the world is fake: Estimates range to well over half. Combine that with the sums paid for the rarest works are so high — earlier this month, Da Vinci's Salvator Mundi sold for $450 million — and it's clear why the industry can be fraught over authenticity. "Authenticity is the third rail. Historically, it's the most challenging risk issue for the art market going back to the Renaissance," Laura Patten, who leads the art and finance practice for Deloitte, tells Axios.

The details

  • The researchers at Rutgers and the Atelier for Restoration and Research of Paintings in The Hague broke down 297 line drawings largely by four major artists — Pablo Picasso, Henry Matisse, Amedeo Modigliani and Egon Schiele — into about 80,000 individual strokes.
  • Then they ran those into two systems of artificial intelligence — machine learning and a deep recurrent neural network (RNN). When they applied both of them together, they detected the precise artist about 80% of the time, and the fakes every time.
  • They say they are able to distinguish spontaneous from "inhibited" strokes made by a forger.
  • As an experiment, they commissioned fake drawings.
  • The method is inspired by Maurits Michel van Dantzig, the father of this method of detecting art forgery, who called it Pictology.

Why it works: "Most forged art works are based on copying certain compositional and subject matter-related elements and patterns," the researchers said. But they add, "the characteristics of individual strokes carry the artist's unintentional signature, which is hard to imitate or forge, even if the forger intends to do."

But but but: Patten said the researchers set a low bar for themselves by commissioning fakes. Next, she said, they should test their system against real fakes.

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21 occupations of the future

In a new report, Cognizant, the IT services firm, identifies 21 jobs that, given economic and commercial trends, people could reasonably be expected to hold, like chief trust officer and man-machine teaming manager.

Why it matters: The key question of the age of automation is whether this time of technological disruption is different from all the others that have occurred over the last two centuries. That is, will the economy produce sufficient well-paying jobs for everyone, or will there be profound and intractable joblessness? To begin to answer that question, we've needed to know what at least some of those jobs might be.

Data: Cognizant Jobs of the Future report, Bureau of Labor Statistics employment projections and 2016 wage data. Pictograms: Lazaro Gamio / Axios

How it's done: Cognizant found proxies for them in Bureau of Labor Statistics data — existing occupations that the agency already follows. You can flip through the occupations above and see how the BLS foresees employment and salary developing for each. Next year, the BLS will update the numbers in a new report covering 2018-2028.

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McKinsey: automation may wipe out 1/3 of America’s workforce by 2030

Photo: Ben McCanna / Portland Press Herald via Getty Images

In a new study that is optimistic about automation yet stark in its appraisal of the challenge ahead, McKinsey says massive government intervention will be required to hold societies together against the ravages of labor disruption over the next 13 years. Up to 800 million people—including a third of the work force in the U.S. and Germany—will be made jobless by 2030, the study says.

The bottom line: The economy of most countries will eventually replace the lost jobs, the study says, but many of the unemployed will need considerable help to shift to new work, and salaries could continue to flatline. "It's a Marshall Plan size of task," Michael Chui, lead author of the McKinsey report, tells Axios.

In the eight-month study, the McKinsey Global Institute, the firm's think tank, found that almost half of those thrown out of work—375 million people, comprising 14% of the global work force—will have to find entirely new occupations, since their old one will either no longer exist or need far fewer workers. Chinese will have the highest such absolute numbers—100 million people changing occupations, or 12% of the country's 2030 work force.

I asked Chui what surprised him the most of the findings. "The degree of transition that needs to happen over time is a real eye opener," he said.

The details:

  • Up to 30% of the hours worked globally may be automated by 2030.
  • The transition compares to the U.S. shift from a largely agricultural to an industrial-services economy in the early 1900s forward. But this time, it's not young people leaving farms, but mid-career workers who need new skills. "There are few precedents in which societies have successfully retrained such large numbers of people," the report says, and that is the key question: how do you retrain people in their 30s, 40s and 50s for entirely new professions?
  • Just as they are now, wages may still not be sufficient for a middle-class standard of living. But "a healthy consumer class is essential for both economic growth and social stability," the report says. The U.S. should therefore consider income supplement programs, to establish a bottom-line standard of living.
  • Whether the transition to a far more automated society goes smoothly rests almost entirely "on the choices we make," Chui said. For example, wages can be exacerbated or improved. Chui recommended "more investment in infrastructure, and that those workers be paid a middle wage."
  • Do not attempt to slow the rollout of AI and robotization, the report urged, but instead accelerate it, because a slowdown "would curtail the contributions that these technologies make to business dynamism and economic growth."

Editor's Note: Get more stories like this by signing up for our weekly robotics, AI and labor newsletter, Future of Work.

Expert Voices Featured

Five experts and a bot predict Putin's next big surprise

Illustration: Axios Visuals

Three times over the last three years, Russian President Vladimir Putin has surprised nearly everyone: in 2014, when he invaded and annexed Crimea; in 2015, when he put down a big military footprint in Syria; and last year, when he manipulated the U.S. presidential election.

The common thread was Putin's ultimate perceived advantages — unpredictability and a willingness to gamble hugely. It's how he has resurrected Russia as an essential power. The question is, what will Putin's next surprise be?

For the answer, we asked five experts: