Monday, September 24, 2018

"Drivers for Uber, Lyft are earning less than half of what they did four years ago, study finds"

The MIT study from February was mistaken and garnered our standard correction:

You Trusted Me and I Failed You

When a journalist accidently misquotes a source

Regret the error.

So you'll understand a bit of hesitance linking to this piece.
Oh who am I kidding, if story shows a hole in the Ubesters business plan we'll probably run with it.

From Dow Jones' MarketWatch:

Drivers earned 53% less in 2017 than they did in 2013 
Drivers for online platforms including Uber and Lyft are making less than half of what they did four years ago, even as more and more people are drawn into working for them.

A new report from the JPMorgan Chase Institute, based on payments directed to 2.3 million families, showed that average monthly platform earnings dropped considerably — by 53% — between 2013 and 2017.

These drivers made $783 per month in 2017 versus $1,469 in 2013.

In the first quarter of 2014, nearly half of drivers who work for on demand platform such as Uber and Lyft, earned $900 a month or more. However during the first quarter of 2018, less than 25% of drivers were able to earn more than $900, the report found.

“These declines in monthly earnings among drivers may reflect the fact that the growth in the number of drivers could have put downward pressure on hourly wages; they may also reflect a potential decline in the number of hours drivers are driving,” the report stated.

“Regardless of whether the drop in earnings was caused by a fall in wages or hours or both, it indicates that driving has become less and less likely to replace a full-time job over the past five years, as more drivers have joined the market.”...MORE
Attentive readers, i.e. those not distracted by the correction .gif, have probably spotted at least two errors in methodology and/or presentation of the study but as I said, we'll run with it.

"News Site to Investigate Big Tech, Helped by Craigslist Founder"

How did  Craig come up with $20 mil. to give away?
Kids, now do you understand how profitable classified advertising used to be for newspapers?
And Craigslist is, for the most part, free.

Enough digression, on to investigation.

From the New York Times, Sept. 23:

The Markup, dedicated to investigating technology and its effect on society, will be led by two former ProPublica journalists. Craig Newmark gave $20 million to help fund the operation. 
When the investigative journalist Julia Angwin worked for ProPublica, the nonprofit news organization became known as “big tech’s scariest watchdog.” 

By partnering with programmers and data scientists, Ms. Angwin pioneered the work of studying big tech’s algorithms — the secret codes that have an enormous impact on everyday American life. Her findings shed light on how companies like Facebook were creating tools that could be used to promote racial bias, fraudulent schemes and extremist content. 

Now, with a $20 million gift from the Craigslist founder Craig Newmark, she and her partner at ProPublica, the data journalist Jeff Larson, are starting The Markup, a news site dedicated to investigating technology and its effect on society. Sue Gardner, former head of the Wikimedia Foundation, which hosts Wikipedia, will be The Markup’s executive director. Ms. Angwin and Mr. Larson said that they would hire two dozen journalists for its New York office and that stories would start going up on the website in early 2019. The group has also raised $2 million from the John S. and James L. Knight Foundation, and $1 million collectively from the Ford Foundation, the John D. and Catherine T. MacArthur Foundation, and the Ethics and Governance of Artificial Intelligence Initiative.
Ms. Angwin compares tech to canned food, an innovation that took some time to be seen with more scrutiny.

“When canned food came out, it was amazing,” said Ms. Angwin, who will be the site’s editor in chief. “You could have peaches when they were out of season. There was a whole period of America where every recipe called for canned soup. People went crazy for canned food. And after 30 years, 40 years, people were like, ‘Huh, wait.’

“That is what’s happened with technology,” Ms. Angwin said, calling the 2016 election a tipping point. “And I’m so glad we’ve woken up.”

The site will explore three broad investigative categories: how profiling software discriminates against the poor and other vulnerable groups; internet health and infections like bots, scams and misinformation; and the awesome power of the tech companies. The Markup will release all its stories under a creative commons license so other organizations can republish them, as ProPublica does....

News You Can Use: "Google’s AI to detect toxic comments can be easily fooled with ‘love’"

From The Next Web:
A group of researchers has found that simple changes in sentences and its structure can fool Google’s perspective AI, made for detecting toxic comments and hate speech. These methods involve inserting typos, spaces between words or add innocuous words to the original sentence.

The AI project, which was started in 2016 by a Google offshoot called Jigsaw, assigns a toxicity score to a piece of text. Google defines a toxic comment as a rude, disrespectful, or unreasonable comment that is likely to make you leave a discussion. The researchers suggest that even a slight change in the sentence can change the toxicity score dramatically. They saw that changing “You are great” to “You are fucking great”, made the score jump from a totally safe 0.03 to a fairly toxic 0.82.
Simple changes in the sentence fools Google AI
This clearly denotes that the toxicity score is probably not the best measure to identify hate speech. Last year, another study found that inserting spaces and making typos reduced the toxicity score drastically. Google has improved its AI since then to detect these changes. But it’s not perfect, the researchers presenting the latest study said if someone introduced a word like ‘love’ in these sentences the score took a plunge....MORE

Why Are People Linking to a Four-Year Old Story On Anti-Vaxxers?

The story is from the Atlantic:
Wealthy L.A. Schools' Vaccination Rates Are as Low as South Sudan's
And is dated:
Sep 16, 2014
Its source is The Hollywood Reporter story "Hollywood's Vaccine Wars..." which itself is dated
9/10/2014 9:00 am PDT 
Since last week it has been linked in a half dozen places.

None of the linkers mention the date and none of the linkers dig further into the story with updates on the effects of the California immunization law which actually is a story:
Medical Xpress: "Vaccine opt-outs dropped slightly when California added more hurdles"
KPDB: "Medical Exemptions Up As Vaccination Rates For Kindergartners Decline In State, San Diego County"
and a bit spookier from The Sacramento Business Journal:
ICAN vs. HHS: Key Legal Win Recasts Vaccine Debate

What's up?
You've got record measles outbreaks in Europe and mumps in the U.S. who (WHO?) needs old news?

"How Jim Chanos Uses Cynicism, Chutzpah — and a Secret Twitter Account — to Take on Markets (and Elon Musk)"

From Institutional Investor, September 17, 2018:

The LeBron James of short-selling talks Ponzinomics.
It’s a sweltering, 95-degree August day in Manhattan, but Jim Chanos — fresh off a two-week holiday, rocking a sharkskin suit — is pumped: Elon Musk had once again called a hero of the Thai cave rescue a pedophile.It’s 1:30 in the afternoon. Chanos bolts through the door to his office building on West 55th Street, grabs the journalist waiting for him, and, on the elevator ride to his eighth-floor office, fills her in on the latest news.

“Musk is at it again. He’s doubling down on his pedophile comment,” Chanos says, amusement noticeable in his voice. Minutes earlier the CEO of Tesla Motors — who is already under investigation by the Securities and Exchange Commission for a tweet about taking the company private — had returned to an earlier tweetstorm in which he accused the British cave diver of being a “pedo guy”.

“You don't think it’s strange he hasn’t sued me?" Musk tweeted at 12:30 p.m. on August 28. Tesla shares immediately began to slide, and within hours the diver’s lawyer reportedly informed Musk that he would, indeed, be sued.

Recent months have seen one bizarre event after another in the saga of the electric-automaker and its iconic boss, and Chanos has been watching it all. The 61-year-old founder of hedge fund Kynikos Associates announced his short against Tesla in the fall of 2015 and has been nursing losses ever since — for despite a raft of bad news and the increasingly controversial, and potentially illegal, behavior of Musk, Tesla’s stock, while off significantly from its highs, has stubbornly refused to crash.

The Tesla short made for a tense working vacation for Chanos, who had left New York for his annual trek to the Greek island of Mykonos on August 9. That was just two days after Musk tweeted that he was considering taking Tesla private — with the now-infamous “funding secured” line — and Wall Street went into a frenzy trying to see if it could happen.

Chanos was skeptical.

“I thought immediately it was not true, because I know Elon Musk at this point,” he said during a two-hour interview that touched on everything from hedge funds and short-selling to politics and the history of fraud, then, eventually, got back to social media and Musk. “The way it came out during market hours, right after the Saudi passive investment announcement [the Saudi sovereign wealth fund has reportedly taken a 5 percent stake in Tesla] — it was so irresponsible, number one, and was not clearly vetted, because no one who vetted that would’ve let him put that out.”

Although Kynikos’s two senior portfolio partners, Chuck Hobbs and David Glaymon, were monitoring the stock from New York, Chanos couldn’t stay away from the news, even in Mykonos. “It was breaking so fast,” Chanos says. As the stock rallied, he sold more shares short.
Finally, at 11:00 p.m. on Friday, August 24, Musk ended the suspense with a statement on Tesla’s blog. He had decided against going private.

Tesla has been the biggest short in the market for much of this past year, with nearly $10 billion wagered that its stock will fall. Chanos is hardly the only one who takes that view. Kynikos now runs less than $2 billion, and with individual short positions capped at 5 percent each for risk management purposes, Tesla represents at most about $100 million of the firm’s total short bets, which it currently has on 65 companies.

Win or lose, the Tesla short won’t make much of a difference to Kynikos’s bottom line. But for Chanos — who claims he’s also advising much larger “pools of capital” on their Tesla shorts — there’s more than money at stake.

Kynikos is the lone short-selling hedge fund of any size — and the only one that that has been in business since 1985.

That’s no mean feat, as the stock market has risen almost 1,500 percent since Kynikos’s debut. Chanos has lived through at least three bear markets — the 1987 crash, the bursting of the dot-com bubble in 2000, and the global financial crisis of 2008 — and he’s waiting patiently for the next one.
“I’m not saying it’s the top of the market, but on the other hand, bear markets haven’t been outlawed,” he quips.

Chanos, of course, is already a legend. He will go down in Wall Street history for predicting the demise of Enron Corp., whose collapse resulted in a wave of prosecutions and the imprisonment of top executives — the kind of harsh penalties that have not been seen since.
But that was in 2001 — 17 years ago.

Since the financial crisis year of 2008, Kynikos’s shorts overall have been bleeding red ink, and investors have bailed. Kynikos has lost almost three quarters of its assets since the end of 2008. This year alone, its funds had fallen between 9 percent and 19 percent through July (net of fees), depending on the fund, according to a report to investors Institutional Investor has seen that has not been previously reported on.

“It has been one giant short-squeeze market,” he moans.

Take Tesla. To Chanos it represents a market euphoria last witnessed during the dot-com craze. Although Tesla is unprofitable and loaded with debt, its market cap rivals that of General Motors. A rush to meet production targets on its midprice Model 3 sedan this year has been accompanied by defective cars, unhappy employees-turned-whistleblowers, and a stream of exiting executives — not to mention ever-stranger outbursts by a CEO under enormous pressure to meet the projections he promised shareholders. The current stock price of about $299 per share (above Chanos’s average cost of $250) is based on ambitious plans for the future. But what most people are missing, says Chanos, is that Tesla has quit making the capital investments required to realize those ambitions. It can no longer afford to do so.

But facts don’t seem to matter. As Chanos reminds us, referring to President Trump and his supporters, we are living in “a post-truth environment.” That translates, he argues, into a mood in which investors are also willing to suspend disbelief.

“If we don’t hold our leaders to that standard,” muses Chanos, “then why should we hold managements to that standard? I think that’s part of where we are now.”
Chanos, who jokes that he is considered an anarchist on Wall Street for his liberal political views, is not prone to proselytizing. He doesn’t write letters to the Securities and Exchange Commission or publish long treatises on his short theses. Though he believes the political environment has an impact on the market, he never counts on the SEC to take down the bad guys. “They’re archaeologists, not detectives,” he scoffs.

Chanos can appear world-weary and somewhat guarded — but, as the saying goes, in every cynic beats the bleeding heart of an idealist. “There’s more than a little of the crusader in him,” says longtime friend Jim Grant, founder and editor of Grant’s Interest Rate Observer. “He would like to clean up Wall Street. He would like to improve the quality of corporate reporting. He would like to rid Wall Street of the scoundrels and clean up corporate management.”

That might explain what happened earlier this summer....

HT: Barry Ritholtz but we don't have a specific post. So here's The Big Picture.

Luxembourg's ^#@*&! Space Agency and Fund

This is a couple weeks old but we've been keeping track of  the goings-on in the Grand Duchy for quite a while (some links below) and thought this should be on the blog.

From Space News, September 13:

Luxembourg establishes space agency and new fund
The government of Luxembourg continued work to expand its role in the global space economy Sept. 12 by formally establishing a national space agency, a move designed in part to ensure the effort continues after an upcoming election.

In a ceremony in Luxembourg City, Étienne Schneider, deputy prime minister and minister of the economy, formally announced the creation of the Luxembourg Space Agency. The agency will be led by Marc Serres, previously the head of space affairs at the Ministry of the Economy.

Unlike traditional national space agencies, which support spacecraft missions and scientific research, the Luxembourg Space Agency will focus primarily on building up the country’s space industry as well as supporting education and workforce development.

Schneider noted that Luxembourg’s recent efforts, most notably the project to attract companies working in the nascent space resources field, had led to 20 countries establishing a presence in the country. “All this is why it’s so important to me to launch today this Luxembourg Space Agency in order to professionalize our approach to this new community,” he said.

Serres said that the agency will work with a wide range of other organizations, both within the government and the private sector, to meet the agency’s goals. “The agency will be well-equipped to support industry in their daily challenges, and it leads to the most favorable environment for this sector to continue to grow,” he said, describing its four “strategic lines” as expertise, innovation, skills and funding.

That last item will include a new fund for supporting space companies. Schneider announced that the space agency will work with other government agencies and the private sector to establish the Luxembourg Space Fund, valued at 100 million euros ($116 million). The fund, according to a government statement, will “provide equity funding for new space companies with ground-breaking ideas and technology.”

Only part of the new fund will involve government money. “It will be a public-private partnership, where the government will take a share of 30 to 40 percent,” Schneider said....MORE
In more mundane Luxembourg news:
EU says McDonald's, Luxembourg tax deal not illegal

Also on the Luxembourg Channel:

Goldman Sachs on Asteroid Mining: As If Luxembourg Wasn't Insufferable Already
Luxembourg, with their #3 in the world GDP per capita (PPP) and their Jean-Claude Juncker and...
Insufferable. It's like Bono and Elevation Partners. Besides being Bono, they ran $90 mil. to $1.5 billion in Facebook.
Billion with a 'B'. As in Bono....
[re the Goldman bit]
...It's a 24 minute podcast, something one could listen to while in transit but did anyone bother to tell me about it?
No. That's why we're getting to it a year late, despite my avowed interest in becoming the world's first trillionaire.
And ignoring that Alchemist's Fallacy thing and all.

Here's ZeroHdge from April 19th (yes, they're a year late as well but how does that help moi?): 
The World's First Trillionaire Will Be A Space Miner 
Huh, I must have been crabby that day.
Anyhoo, onwards:

Dammit! Luxembourg Is Not A Microstate!
From Brilliant Maps:

The map above shows how big Luxembourg is compared to Singapore, Andorra, Malta, Liechtenstein, San Marino, Monaco, and the Vatican.

Luxembourg is 2,586.4 km2 (998.6 sq mi) with a population of 576,249, making it one of the world’s smallest states; 168th by size or 164th by population.

However, it’s still bigger than Singapore, Andorra, Malta, Liechtenstein, San Marino, Monaco, and the Vatican combined!

Here’s how big they are respectively:...MORE
Crabby that day as well.

Previously on the wonder that is Luxembourg:
What's the Scam? Why Did Deloitte Set Up Their Art & Finance Practice In Luxembourg?
Luxembourg’s Asteroid Mining Plan
Luxembourg Invests €25 million in Asteroid Mining 
Luxembourg’s Bid to Become the Silicon Valley of Space Mining
Luxembourg's New Space Mining Law Is Basically "Finders, Keepers"
"Oligarchs and Orchestras: Inside Luxembourg’s Secretive Low-Tax ‘Fortress of Art’ Warehouse"
Uh Oh: "Bail-In Blues: Luxembourg Warns of Investor Flight from Europe"
Luxembourg and Switzerland are two of the "Banking-assets-an-order-of-magnitude-bigger-than-GDP" powerhouses....
Short The Swiss (and Luxembourg)
Maybe Liechtenstein too. Never much cared for Doha either. And then there's...
errrmmm, excuse me.... 

Luxembourg-based Rare Earth Company Hoping to Mine in South Africa by 2014 Does Oversubscribed IPO in Toronto (FRO.tsx)

FREFF 0.012  0.00

For some reason posting on Luxembourg seems to bring out the worst in me.

Finland's Dry Bulk Carrier ESL Shipping Claims First LNG-Powered Handysize, First Northern Sea Route Transit

And speaking of Russia and natural gas...
From the Barents Observer, Sept. 21:

World’s first LNG-fueled bulk carriers cross Northern Sea Route
The two brand new 160-meter long vessels that are making it through the Russian Arctic shipping route produce less than half of normal vessels’ carbon dioxide emissions.
 The "Haaga" sails from Japan to Sweden through the NSR. Photo: ESL Shipping
The 25,600 dwt sister ships «Haaga» and «Viikki» are getting their maiden voyage through some of the toughest waters on earth. The two ships built in China for Finnish company ESL Shipping will make it to their home port in Finland through the Northern Sea Route.

«They are the world’s most environmentally friendly bulk carriers, and their passage via the Northern Sea Route is a concrete indication of the impact of climate change - but also of new business opportunities,» company ESL Shipping says.

According to information from the Northern Sea Route Administration, the «Haaga» on the 14th September sailed into the eastern part of the Arctic shipping route and was on 21st September anticipated to pass archipelago Novaya Zemlya with course for Norwegian waters.

The ship is built by the Jinling shipyard in Nanjing, China, and loaded raw material cargo in Japan before it set course for the Arctic. It is estimated to arrive in the Swedish port of Oxelösund around 1st October.

According to company Managing Director Mikki Koskinen, the ship had Russian icebreaker assistance when it crossed the East Siberian Sea. Ice data from the Russian Arctic and Antarctic Research Institute show that the remaining parts of the NSR now are practically all ice-free.
The second ship, the «Viiki», was delivered by the yard on 4th September and is expected to start its Arctic voyage in about two weeks....MORE

Natural Gas: "EU Taxpayers Aren't Funding Nord Stream 2 So Why The Hubbub"—Gazprom

Interesting pitch from Sputnik:
Sweet, innocent, a bit like putting this guy in the role of the ingénue:

EU Taxpayers Not Funding Nord Stream 2, Political Tension Surprising - Gazprom
EU taxpayers are not funding the Nord Stream 2 gas pipeline, Russia's Gazprom Export Director General Elena Burmistrova has stated, stressing that the political tensions surrounding the project were surprising.
"We really feel quite a political tension, not to mention our biggest infrastructure project such as Nord Stream 2. For me, it is quite a surprise because I see a lot of debates in this respect. But at the same time, all of us understand that it is a 100 percent commercial project and it is not paid by taxpayers of the European Union, it is a 100 percent commercial capital that was invested there," Burmistrova said during a session at the Gastech conference in Barcelona.
Some of the European countries have repeatedly expressed their concerns over the project, while others, such as Germany and Austria, have welcomed the new pipeline.

Nord Stream 2 AG is owned by Public Joint Stock Company Gazprom, while its investors include France's Engie, Austria's OMV AG, UK-Dutch Royal Dutch Shell, and Germany's Uniper and Wintershall. The pipeline is expected to bring gas from Russia to Germany via the Baltic Sea.

The project has been welcomed by some countries in Europe, such as Germany and Austria, and opposed by others, including Ukraine, which may suffer transit revenue drops if Nord Stream 2 becomes operational.

Energy Ties With China Will Not Affect European Supplies
Russian energy giant Gazprom's supply of gas to China, including via western route, will not affect the volume of the company's deliveries to Europe, Burmistrova stated.

Earlier in September, an official from China's National Energy Administration (NEA) said that Beijing intended to increase imports of natural gas from Russia and Kazakhstan in the near future. Also this month, Russian energy company Rosneft and Chinese National Oil and Gas Corporation (CNPC) agreed on broader cooperation in the area of exploration and extraction.
"I would not say it would affect our relationship with Europe. It has always been our natural customer, a partner as well, geographically. We are lucky to be just in the middle. China is our new partner and we are happy that our project is finally alive and we can talk about new options. It will be different fields and I do not think it will somehow influence our European supplies," Burmistrova said.
In 2014, Gazprom and China's CNPC signed a framework agreement on the delivery of 38 billion cubic meters of natural gas annually. The agreement stipulates the construction of appropriate infrastructure for the gas deliveries....MORE
Re: the pic in the intro, if you're thinking "I recognize the face but can't quite recall the name", it's Russia's Sergey Shoigu.
I was thinking of him this weekend after his U.S. counterpart, Secretary of Defense Mattis said “What I want our adversary to know is please work with our State Department. You really don’t want to work with me. That’s our message.”

Sunday, September 23, 2018

Wow: Anatomy of an AI System (everything that goes into Amazon's Echo)

This is a stunning piece of research.
note: this version of the map is via the Verge, HT up fron to Professor Crawford's twitter feed which points up a giant wall-sized copy at the V and A.

From NYU's Kate Crawford:

The Amazon Echo as an anatomical map of human labor, data and planetary resources
By Kate Crawford 1 and Vladan Joler 2

Download map in pdf format here


A cylinder sits in a room. It is impassive, smooth, simple and small. It stands 14.8cm high, with a single blue-green circular light that traces around its upper rim. It is silently attending. A woman walks into the room, carrying a sleeping child in her arms, and she addresses the cylinder.
‘Alexa, turn on the hall lights’

The cylinder springs into life. ‘OK.’ The room lights up. The woman makes a faint nodding gesture, and carries the child upstairs.

This is an interaction with Amazon’s Echo device. 3 A brief command and a response is the most common form of engagement with this consumer voice-enabled AI device. But in this fleeting moment of interaction, a vast matrix of capacities is invoked: interlaced chains of resource extraction, human labor and algorithmic processing across networks of mining, logistics, distribution, prediction and optimization. The scale of this system is almost beyond human imagining. How can we begin to see it, to grasp its immensity and complexity as a connected form? We start with an outline: an exploded view of a planetary system across three stages of birth, life and death, accompanied by an essay in 21 parts. Together, this becomes an anatomical map of a single AI system.

Amazon Echo Dot (schematics)
Amazon Echo Dot (schematics)


The scene of the woman talking to Alexa is drawn from a 2017 promotional video advertising the latest version of the Amazon Echo. The video begins, “Say hello to the all-new Echo” and explains that the Echo will connect to Alexa (the artificial intelligence agent) in order to “play music, call friends and family, control smart home devices, and more.” The device contains seven directional microphones, so the user can be heard at all times even when music is playing. The device comes in several styles, such as gunmetal grey or a basic beige, designed to either “blend in or stand out.” But even the shiny design options maintain a kind of blankness: nothing will alert the owner to the vast network that subtends and drives its interactive capacities. The promotional video simply states that the range of things you can ask Alexa to do is always expanding. “Because Alexa is in the cloud, she is always getting smarter and adding new features.”
How does this happen? Alexa is a disembodied voice that represents the human-AI interaction interface for an extraordinarily complex set of information processing layers. These layers are fed by constant tides: the flows of human voices being translated into text questions, which are used to query databases of potential answers, and the corresponding ebb of Alexa’s replies. For each response that Alexa gives, its effectiveness is inferred by what happens next:
Is the same question uttered again? (Did the user feel heard?)

Was the question reworded? (Did the user feel the question was understood?)

Was there an action following the question? (Did the interaction result in a tracked response: a light turned on, a product purchased, a track played?)
With each interaction, Alexa is training to hear better, to interpret more precisely, to trigger actions that map to the user’s commands more accurately, and to build a more complete model of their preferences, habits and desires. What is required to make this possible? Put simply: each small moment of convenience – be it answering a question, turning on a light, or playing a song – requires a vast planetary network, fueled by the extraction of non-renewable materials, labor, and data. The scale of resources required is many magnitudes greater than the energy and labor it would take a human to operate a household appliance or flick a switch. A full accounting for these costs is almost impossible, but it is increasingly important that we grasp the scale and scope if we are to understand and govern the technical infrastructures that thread through our lives.


The Salar, the world's largest flat surface, is located in southwest Bolivia at an altitude of 3,656 meters above sea level. It is a high plateau, covered by a few meters of salt crust which are exceptionally rich in lithium, containing 50% to 70% of the world's lithium reserves. 4 The Salar, alongside the neighboring Atacama regions in Chile and Argentina, are major sites for lithium extraction. This soft, silvery metal is currently used to power mobile connected devices, as a crucial material used for the production of lithium-Ion batteries. It is known as ‘grey gold.’ Smartphone batteries, for example, usually have less than eight grams of this material. 5 Each Tesla car needs approximately seven kilograms of lithium for its battery pack. 6 All these batteries have a limited lifespan, and once consumed they are thrown away as waste. Amazon reminds users that they cannot open up and repair their Echo, because this will void the warranty. The Amazon Echo is wall-powered, and also has a mobile battery base. This also has a limited lifespan and then must be thrown away as waste.

According to the Aymara legends about the creation of Bolivia, the volcanic mountains of the Andean plateau were creations of tragedy. 7 Long ago, when the volcanos were alive and roaming the plains freely, Tunupa - the only female volcano – gave birth to a baby. Stricken by jealousy, the male volcanos stole her baby and banished it to a distant location. The gods punished the volcanos by pinning them all to the Earth. Grieving for the child that she could no longer reach, Tunupa wept deeply. Her tears and breast milk combined to create a giant salt lake: Salar de Uyuni. As Liam Young and Kate Davies observe, “your smart-phone runs on the tears and breast milk of a volcano. This landscape is connected to everywhere on the planet via the phones in our pockets; linked to each of us by invisible threads of commerce, science, politics and power.” 8


Our exploded view diagram combines and visualizes three central, extractive processes that are required to run a large-scale artificial intelligence system: material resources, human labor, and data. We consider these three elements across time – represented as a visual description of the birth, life and death of a single Amazon Echo unit. It’s necessary to move beyond a simple analysis of the relationship between an individual human, their data, and any single technology company in order to contend with with the truly planetary scale of extraction. Vincent Mosco has shown how the ethereal metaphor of ‘the cloud’ for offsite data management and processing is in complete contradiction with the physical realities of the extraction of minerals from the Earth’s crust and dispossession of human populations that sustain its existence. 9 Sandro Mezzadra and Brett Nielson use the term ‘extractivism’ to name the relationship between different forms of extractive operations in contemporary capitalism, which we see repeated in the context of the AI industry. 10 There are deep interconnections between the literal hollowing out of the materials of the earth and biosphere, and the data capture and monetization of human practices of communication and sociality in AI. Mezzadra and Nielson note that labor is central to this extractive relationship, which has repeated throughout history: from the way European imperialism used slave labor, to the forced work crews on rubber plantations in Malaya, to the Indigenous people of Bolivia being driven to extract the silver that was used in the first global currency. Thinking about extraction requires thinking about labor, resources, and data together. This presents a challenge to critical and popular understandings of artificial intelligence: it is hard to ‘see’ any of these processes individually, let alone collectively. Hence the need for a visualization that can bring these connected, but globally dispersed processes into a single map.
Extractive operations


If you read our map from left to right, the story begins and ends with the Earth, and the geological processes of deep time. But read from top to bottom, we see the story as it begins and ends with a human. The top is the human agent, querying the Echo, and supplying Amazon with the valuable training data of verbal questions and responses that they can use to further refine their voice-enabled AI systems. At the bottom of the map is another kind of human resource: the history of human knowledge and capacity, which is also used to train and optimize artificial intelligence systems. This is a key difference between artificial intelligence systems and other forms of consumer technology: they rely on the ingestion, analysis and optimization of vast amounts of human generated images, texts and videos.

...MUCH MORE (an incredible amount of work went into this)

Why the World Only Has Two Words For Tea

From Quartz:

Tea if by sea, cha if by land: Why the world only has two words for tea
With a few minor exceptions, there are really only two ways to say “tea” in the world. One is like the English term— in Spanish and tee in Afrikaans are two examples. The other is some variation of cha, like chay in Hindi.

Both versions come from China. How they spread around the world offers a clear picture of how globalization worked before “globalization” was a term anybody used. The words that sound like “cha” spread across land, along the Silk Road. The “tea”-like phrasings spread over water, by Dutch traders bringing the novel leaves back to Europe.
The term cha (茶) is “Sinitic,” meaning it is common to many varieties of Chinese. It began in China and made its way through central Asia, eventually becoming “chay” (چای) in Persian. That is no doubt due to the trade routes of the Silk Road, along which, according to a recent discovery, tea was traded over 2,000 years ago. This form spread beyond Persia, becoming chay in Urdu, shay in Arabic, and chay in Russian, among others. It even made its way to sub-Saharan Africa, where it became chai in Swahili. The Japanese and Korean terms for tea are also based on the Chinese cha, though those languages likely adopted the word even before its westward spread into Persian.

But that doesn’t account for “tea.” The Chinese character for tea, 茶, is pronounced differently by different varieties of Chinese, though it is written the same in them all. In today’s Mandarin, it is chá. But in the Min Nan variety of Chinese, spoken in the coastal province of Fujian, the character is pronounced te. The key word here is “coastal.”

The te form used in coastal-Chinese languages spread to Europe via the Dutch, who became the primary traders of tea between Europe and Asia in the 17th century, as explained in the World Atlas of Language Structures....MORE
If interested see also:
The Great British Tea Heist: Or How England Stole the Secret, Discovered a Fraud and Created the Modern World

"Christopher Hitchens And George Orwell’s Ironclad Rules for Making a Good Cup of Tea"

Watch Out Mary Poppins: The World's First Tea Brewing System Utilizing Machine-Learning Algorithms Has Received Pre-Launch Seed Funding (plus a Princess Rap Battle)

The recent price action looks like a cartel is in place.
From Index Mundi:

It's Been Four Years Since We Posted "Deep Learning is VC Worthy" (and what's coming)

Let's see how it turned out.
August 21, 2014
From recode:

Nervana Raises Second Round This Year, as Silicon Valley Bets Big on Deep Learning
Nervana Systems, another player in the suddenly hot “deep learning” space, has closed its second round of capital in the last four months.

The San Diego startup said it raised $3.3 million in Series A funding led by DFJ, which comes on top of a $600,000 seed round in April.

DFJ’s Steve Jurvetson will take a seat on the company’s board as part of the latest investment. Allen & Co., AME Cloud Ventures and Fuel Capital also participated.

Deep learning is a form of artificial intelligence that researchers have credited with recent leaps in areas like speech recognition and image search. That has sparked growing interest in Silicon Valley, with Google, Facebook and Twitter making notable acquisitions or hires in recent months and various prominent players betting their own money on the space.
As Re/code explained in an earlier piece:
Deep learning is a form of machine learning in which researchers attempt to train computer algorithms to spot meaningful patterns by showing them lots of data, rather than trying to program in every rule about the world. Taking inspiration from the way neurons work in the human brain, deep learning uses layers of algorithms that successively recognize increasingly complex features — going from, say, edges to circles to an eye in an image.
Notably, these techniques have allowed researchers to train algorithms using unstructured data, where features haven’t been laboriously labeled by human beings ahead of time. It’s not a new concept, but recent refinements have resulted in significant advances over traditional AI approaches.
Nervana is aiming to distinguish itself in the nascent field by focusing on building hardware optimized for deep learning software — and vice versa....MORE
 On August 9, 2016 Intel purchased Nervana for a rumored $408 million.

Here's Semiconductor Engineering, September 11, 2018 with the story that spurred this stroll down Memory Lane:

Intel’s Next Move
Gadi Singer, vice president and general manager of Intel’s Artificial Intelligence Products Group, sat down with Semiconductor Engineering to talk about Intel’s vision for deep learning and why the company is looking well beyond the x86 architecture and one-chip solutions.

SE: What’s changing on the processor side?
Singer: The biggest change is the addition of deep learning and neural networks. Over the past several years, the changes have been so fast and profound that we’re trying to assess the potential and what we do with it. But at the same time, you also need to step back and think about how that fits in with other complementary capabilities. That’s part of the overall transition.

SE: What really got this going was a recognition that you could develop algorithms with machines rather than by hand, right?
Singer: The original approach was from the 1960s, and it went dormant until [computer scientist Geoffrey] Hinton and others found a better way to deal with multiple layers effectively in the early 2000s. The big breakthrough, when deep learning was recognized as a major computational force, occurred a couple of years ago. That was when ImageNet showed you can reach near-human accuracy with image recognition. We started to see great results on speech recognition. Around 2015 and into 2016, results began to look promising enough to be a major change factor. At that time, the world was basically flat, at least in terms of images. It was relatively simple images and simple, direct speech. Most of the effort was proving things were possible with deep learning so you could reach some level of accuracy or some set of results. In terms of the way to create and prove models, the main architectures were CPUs and GPUs. The way to do the problem before that was C++, like some of the predecessors to Caffe, and with proprietary environments such as CUDA. It required a lot of expertise and effort in building the compute architecture, as well as in the deployment. In terms of who was involved, if you look at the technology in the field today, those were the early adopters.

SE: What’s changed since then?
Singer: Over the last few years, we’ve seen the coming of age of deep learning. The data itself has become much more complex. We’ve moved from 2D to 3D images. We’re working with Novartis, which is looking at 3D microscopic images of cells, trying to identify potentially malignant cells. The images themselves are 25 times more complex in terms of data, but what you’re identifying is a more refined model.

SE: Where does Intel fit in with these architectures. One of the big problems with AI and deep learning is they’re changing quickly, so you need a very flexible architecture. What does Intel plan here?
Singer: In the past, the problem statement was clear. You knew what you needed for a graphics chip or a CPU chip two or three years out, and companies competed on having the best solution for a known problem. Deep learning is a space where companies compete based on who best understands the problem as it evolves. You need an architecture that is able to understand and foresee trends, and be ready for what is coming when it’s out there in the market in full production and deployment—not when it’s being designed and tested....

Proto-Facebook, Proto-Google: Know Everything About Everybody

From the Social Science Research Network:

"'Know Everything that Can Be Known About Everybody': The Birth of the Credit Report"
A remarkable amount of our personal information is in the hands of corporations such as the Experian credit bureau; strangers to us, they make their money by collecting our data, processing it and selling it to others. Other firms make decisions shaping our lives on the basis of credit ratings the credit bureaus assign to us. Those companies have profound impact on our lives, but we are not their customers and have no control over them. Most of us assume that this state of being, in which we find ourselves at the mercy of firms whose business is to process and sell our information, is a new thing – a product of the Information Age, credit cards, and mainframe computers. In fact, it's much older than that. The story of the 21st-century credit bureau echoes that of the first credit bureau, initially known as the Mercantile Agency, founded before the Civil War. In a world in which such things were unknown, the Mercantile Agency sought to establish and maintain a file on every American who might ever seek commercial credit. Deeply controversial and deeply influential, the Mercantile Agency created an early, computer-free, version of the database system, maintaining and updating files on well over a million people by 1890. It and its rivals put in place a new, pervasive, network of social monitoring that became a central part of the nation's economic infrastructure. The early credit bureaus faced some of the same issues that the modern ones do, and inspired deep privacy fears. Modern privacy law didn't exist yet, and so privacy issues found their way into the law of credit bureaus in the context of defamation lawsuits. The resulting defamation case law displays remarkably modern concerns about the commoditization of information, and about the untrammeled distribution of information about individuals. It suggests possibilities in the evolution of the law that ultimately went unrealized.
...But that too is not really new. The Mercantile Agency and Bradstreet Company ratings codes were products of the nineteenth century 's anticipation of the black - box algorithm . Though they were the triggers of (sometimes catastrophic) action, from the point of view of the data subject , they were the result of the agencies' processing unknown facts through an opaque filter. That's part of what made them so difficult to challenge...
—pp 37
SSRN download page (41 page PDF)

Saturday, September 22, 2018

Frank Pasquale—From Territorial to Functional Sovereignty: The Case of Amazon (AMZN

A repost but worth a second look (or a first).
January 17. 2018

Professor Pasquale has a very interesting way of looking at things, we are fans. *

From Law & Political Economy:
Economists tend to characterize the scope of regulation as a simple matter of expanding or contracting state power. But a political economy perspective emphasizes that social relations abhor a power vacuum. When state authority contracts, private parties fill the gap. That power can feel just as oppressive, and have effects just as pervasive, as garden variety administrative agency enforcement of civil law. As Robert Lee Hale stated, “There is government whenever one person or group can tell others what they must do and when those others have to obey or suffer a penalty.”

We are familiar with that power in employer-employee relationships, or when a massive firm extracts concessions from suppliers. But what about when a firm presumes to exercise juridical power, not as a party to a conflict, but the authority deciding it? I worry that such scenarios will become all the more common as massive digital platforms exercise more power over our commercial lives.
A few weeks ago, the Friedrich Ebert Stiftung (a think tank affiliated with the Social Democratic Party in Germany) invited me to speak at their Conference on Digital Capitalism. As European authorities develop long-term plans to address the rise of powerful platforms, they want to know: What is new, or particularly challenging, in digital capitalism? 

My answer focused on the identity and aspirations of major digital firms. They are no longer market participants. Rather, in their fields, they are market makers, able to exert regulatory control over the terms on which others can sell goods and services. Moreover, they aspire to displace more government roles over time, replacing the logic of territorial sovereignty with functional sovereignty. In functional arenas from room-letting to transportation to commerce, persons will be increasingly subject to corporate, rather than democratic, control. 

For example: Who needs city housing regulators when AirBnB can use data-driven methods to effectively regulate room-letting, then house-letting, and eventually urban planning generally? Why not let Amazon have its own jurisdiction or charter city, or establish special judicial procedures for Foxconn? Some vanguardists of functional sovereignty believe online rating systems could replace state occupational licensure—so rather than having government boards credential workers, a platform like LinkedIn could collect star ratings on them. 

In this and later posts, I want to explain how this shift from territorial to functional sovereignty is creating a new digital political economy. Amazon’s rise is instructive. As Lina Khan explains, “the company has positioned itself at the center of e-commerce and now serves as essential infrastructure for a host of other businesses that depend upon it.” The “everything store” may seem like just another service in the economy—a virtual mall. But when a firm combines tens of millions of customers with a “marketing platform, a delivery and logistics network, a payment service, a credit lender, an auction house…a hardware manufacturer, and a leading host of cloud server space,” as Khan observes, it’s not just another shopping option. 

Digital political economy helps us understand how platforms accumulate power. With online platforms, it’s not a simple narrative of “best service wins.” Network effects have been on the cyberlaw (and digital economics) agenda for over twenty years. Amazon’s dominance has exhibited how network effects can be self-reinforcing. The more merchants there are selling on (or to) Amazon, the better shoppers can be assured that they are searching all possible vendors. The more shoppers there are, the more vendors consider Amazon a “must-have” venue. As crowds build on either side of the platform, the middleman becomes ever more indispensable. Oh, sure, a new platform can enter the market—but until it gets access to the 480 million items Amazon sells (often at deep discounts), why should the median consumer defect to it? If I want garbage bags, do I really want to go over to to re-enter all my credit card details, create a new log-in, read the small print about shipping, and hope that this retailer can negotiate a better deal with Glad? Or do I, ala Sunstein, want a predictive shopping purveyor that intimately knows my past purchase habits, with satisfaction just a click away?
As artificial intelligence improves, the tracking of shopping into the Amazon groove will tend to become ever more rational for both buyers and sellers. Like a path through a forest trod ever clearer of debris, it becomes the natural default. To examine just one of many centripetal forces sucking money, data, and commerce into online behemoths, play out game theoretically how the possibility of online conflict redounds in Amazon’s favor. If you have a problem with a merchant online, do you want to pursue it as a one-off buyer? 
...MUCH MORE (the good stuff)

See also the post immediately below:
Amazon’s mission is to make customer identity more primary than citizenship (AMZN)
Jan. 5, 2018
Corporations Aren't People, Corporations Are Sovereign
Or at least they might be.
In Nebraska,
Part of Nebraska.

From the Lincoln Nebraska Journal-Star:
Senator proposes sovereignty as a way to economic development
*Previously from the P-Dawg:
March 2015
Nudge This: "The Algorithmic Self"

The writer,  Frank Pasquale, is a professor of law at the University of Maryland, and is the author of the forthcoming book The Black Box Society: The Secret Algorithms That Control Money and Information.
And, on the off chance Bloomberg View's Matt Levine should see this, 38 footnotes!
If Interested here are a couple more pieces by Pasquale:
Algorithims Are Judging You

And writing at the Guardian, "Uber and the lawlessness of 'sharing economy' corporates"

Amazon’s mission is to make customer identity more primary than citizenship (AMZN)

From Real life Magazine, Sept. 10:

The Constant Consumer
Every day, the imperative to perceive oneself as a customer grows across a range of experiences and institutions: in the shopping centers and business improvement districts that have replaced public squares and parks; in the schools and hospitals, where offerings are tailored not to general social welfare but to individual consumer choice and what each can afford; and in the gym, where exercise, nutrition, and other forms of wellness have been redefined as personal lifestyle choices.

If the customer is always right, then you’re never wrong when you’re consuming. No contemporary company has offered that Faustian bargain more broadly and aggressively than Amazon. In a previous era, being at home meant you probably weren’t shopping. The mall was, as Ian Bogost noted in an essay for the Atlantic, where “consumerism roared and swelled but, inevitably, remained contained.” Freeing consumerism from that containment was one of the internet’s earliest applications, streamlining the process of shopping at home, and later, on phones.
Recent technologies have enabled the role of customer to be fused with the newer role of user, who inhabits an entire system rather than a specific transaction

Recent technologies have enabled the role of customer to be fused with the newer role of user, who inhabits an entire system rather than a specific transaction.
 Exploring that transition, writer Kevin Slavin describes how the experience of app-based food delivery narrows one’s perspective: “For users, this is what it means to be at the center: to be unaware of anything outside it.” Those apps’ minimal interfaces, requiring little more than the push of a button to order food, conceal the labor and logistical sophistication that make it possible. Users don’t need to understand the messy complexity that supports their simplified solipsism. In Slavin’s example, that insight wouldn’t help them order more food, so the user experience excludes it. 

Amazon similarly merges the customer and the user within its own optimized environments, letting these subjects exist at the center of an ever-expanding system. Imagine an avid Amazon customer’s typical day living with a near future iteration of the platform: He wakes up and speaks his first words of the morning to his Amazon Echo in the kitchen, asking Alexa to order toothpaste after noticing he was running low. Upon checking his email, he gives Alexa a few more instructions, adding social engagements and reminders to his calendar, checking the weather, and finally opening the garage door once he’s ready to leave for work. At the office throughout the day, idle shopping fills his distracted moments. He browses books, clothing, and even furniture, placing orders within seconds, many of which automatically appear in his shopping cart based on patterns from his activity history (he even knows that some of what he buys will be waiting at home tonight). During the evening commute another Alexa-enabled device in his car prompts him to send his sister a birthday card, an action he asks Alexa to do for him. He stops by Whole Foods to pick up groceries — as an Amazon Prime member, it’s always the most cost-effective option in his neighborhood. He arrives home to find a variety of Amazon packages stacked neatly on the living room coffee table, delivered throughout the day by part-time contractors who let themselves into the house via the smart lock on the front door. The soundtrack to his entire day is provided by Amazon Music, in which his Prime membership has automatically enrolled him for a small monthly fee. Few parts of this hypothetical day, which is already within the realm of possibility, remain untouched by Amazon’s user experience.
Amazon, as much as any single company, is transforming the environments in which we live and embedding itself within the fabric of daily existence. Beyond individual experience, those changes also manifest themselves in the physical environment. Many physical retail stores have been rendered obsolete as Amazon and other online retailers started undercutting them on price and offering a wider selection. (Bookstores experienced this first but it eventually spread to almost every form of retail.) Sidewalks and building lobbies have become staging areas for packages, with delivery vehicles exacerbating traffic and obstructing bike lanes as piles of brown Amazon boxes increasingly take up space. As Amazon and food delivery apps eliminate some of the most common reasons to leave one’s house one wonders what sort of neighborhood life will be sustainable in affluent urban areas. 

In light of Amazon’s all-encompassing ambitions, the strategy behind several of the company’s most important product initiatives — Alexa, Amazon Prime, physical retail stores (including Amazon Go and Whole Foods), and Amazon Key — becomes clearer. These products seek to redefine what being a customer means by immersing us more completely within the Amazon universe. Formerly, being a customer was a role one assumed upon physically entering a store or ordering something from a company. Amazon promises to create a newer type of environment, a hybrid of the digital and the physical, that lets us permanently inhabit that role: the world as Everything Store, which we’re always inside.

Amazon represents its efforts to erase the remaining bulwarks against consumerism as its “customer obsession.” Throughout Amazon’s existence, the company has claimed that traditional corporate priorities, from high-profile retail partnerships to short-term profitability to the company’s stock price, have always ranked below customer satisfaction. Early in the company’s history, CEO Jeff Bezos sometimes insisted on keeping one seat open at the conference room table during meetings “for the customer,” and he still scans customer feedback himself, escalating problems to relevant departments with emails that consist of a single question mark.

Part of being “right” was being offered choices to be right about
Bezos’s letter to Amazon’s shareholders on April 18, 2018, praised the company’s customers for being “divinely discontent,” unfailingly raising their expectations beyond whatever standard a company sets for them. In the letter, Bezos likens this force to nothing less than evolution — “We didn’t ascend from our hunter-gatherer days by being satisfied” — and goes on to describe the “customer empowerment phenomenon” that informs Amazon’s approach: Consumers’ access to product reviews, price comparisons, and shipping timelines has created a space where they and not retailers call the shots. To succeed in this landscape, Bezos suggests, companies must respond to their customers’ ever-increasing power by treating them like the linchpins that they are; whoever does this best will rightfully dominate its market.

Amazon’s obsession with customers appears to have endeared them, again and again, to a public that should know better: Earlier this year, Amazon announced that Prime memberships had surpassed 100 million globally, with more new members joining in 2017 than in any previous year. The company’s second-quarter sales in 2018 grew 39 percent versus the previous year. Many have started welcoming Amazon’s physical presence into their homes, with Alexa-enabled devices ranking among the company’s best-selling items. “Customer obsession” is a happier narrative for this dominance than one of aggressive market capture, anti-competitive tactics, and ruthless labor exploitation. Like “support the troops,” or “what about the children,” caring about the customer seems like an impregnable position to take. It’s a more specific iteration of Google’s “Don’t Be Evil”: How could a consumer-focused company be evil, when we are all consumers? What could be wrong with the company being focused on our needs?...

If interested see also the post immediately above:
Frank Pasquale—From Territorial to Functional Sovereignty: The Case of Amazon (AMZN 

For Sale: Heinz—Vanderbilt—Merrill House, NYC

From Town & Country:

Heinz Heiress's Sutton Place Townhouse Listed for $21 Million
The 7,000-square-foot home has been owned by Drue Heinz, Anne Vanderbilt, and Charles Merrill.;0,0.192xh&resize=768:*
Only months after the passing of Drue Heinz, wife of Henry John Heinz II, the couple’s New York City townhouse at One Sutton Place has hit the market for $21 million. The grand scale, Georgian-style home was designed in 1920 for Anne Vanderbilt, wife of William Vanderbilt, and was also owned by Charles Merrill of Merrill Lynch. The house sits on the corner for 57th street and Sutton Place, with breathtaking river views and an expansive shared garden. Drue Heinz, who was a philanthropist most noted for her contributions to the literary community, made the decision to donate a portion of the profit from this sale to charities that she had supported in her lifetime.

The home is nothing short of magnificent, featuring a gracious entrance hall, abundant outdoor space, and of course, a prodigious legacy. Here's a tour of the stunning estate....
The fourth floor terrace room opens to a sun room, complete with a glass ceiling and walls, overlooking the river.;center,top&resize=980:*

Travis Mark for Sotheby's International Realty

AI: "Kai-Fu Lee"

Following up on Wednesday's "If You Read Only One Column On Artificial Intelligence This Month...".
If you read more than one, here's:

From IEEE Spectrum:

Former Head of Google China Foresees an AI Crisis—and Proposes a Solution
Q&A: Kai-Fu Lee talks about AI, jobs, and the human heart
When the former president of Google China talks about artificial intelligence and its potential to cause global upheaval, people listen. His hope is that enough people will listen to avert catastrophic disruption on three different scales: to the global balance of power, to national economies, and to human beings’ delicate souls.

Kai-Fu Lee has been fascinated by AI since he was an eager computer science student applying to Carnegie Mellon University’s Ph.D. program; his admission essay extolled the promise of AI, which he called “the quantification of the human thinking process.” His studies led him to executive positions in Apple, Microsoft, and Google China, before his 2009 founding of Sinovation Ventures, a venture-capital firm focusing on high-tech companies in China.
His new book, AI Superpowers: China, Silicon Valley, and the New World Order (Houghton Mifflin Harcourt), is something of a bait and switch. The first half explores the diverging AI capabilities of China and the United States and frames the discussion as a battle for global dominance. Then, he boldly declares that we shouldn’t waste time worrying about who will win and says the “real AI crisis” will come from automation that wipes out whole job sectors, reshaping economies and societies in both nations. 

“Lurking beneath this social and economic turmoil will be a psychological struggle,” he writes. “As more and more people see themselves displaced by machines, they will be forced to answer a far deeper question: In an age of intelligent machines, what does it mean to be human?”
In a wide-ranging Q&A with IEEE Spectrum, Lee not only explored this question further, he also gave his answer. 
Kai-Fu Lee on . . .
  1. Why China Will Overtake the U.S. in AI
  2. “50 Percent of Jobs Are in Danger”
  3. The Inevitability of the AI Revolution 
  4. Facing Death
  5. A “Blueprint for Coexistence”

Why China Will Overtake the U.S. in AI

IEEE Spectrum: Why do you believe that China will soon match or even overtake the United States in developing and deploying AI?
Kai-Fu Lee: The first and foremost reason is that we’ve transitioned out of an era of discovery—when the person who makes the discovery has a huge edge—and into an era of implementation. The algorithms for AI are pretty well known to many practitioners. What matters now is speed, execution, capital, and access to a large amount of data. In each of these areas, China has an edge.

That’s why I began the book by talking about China’s entrepreneurism. It’s not like Silicon Valley, which is built on iPhone breakthroughs and SpaceX innovations, it’s built on incredibly hard work. Chinese entrepreneurs find areas where there’s enough data and a commercially viable application of AI, and then they work really hard to make the application work. It’s often very hard, dirty, ugly work. The data isn’t handed to you on a silver platter.

Spectrum: You say that Chinese tech giants like Tencent have a clear advantage in terms of access to data that’s needed to train AI. Do they really have more data than companies like Google?
Lee: There are a few ways to look at the data advantage. The first is how many users you have. Google probably has more users than Tencent, because it’s international. The second question is: How homogenous is your data set? Google’s data from Estonia may not help its work in India. It may be better to have rich data from one set of people who have the same language, culture, preferences, usage patterns, payment methods, and so on.

The third way to measure is how much data you have about each person. Tencent has a catch-all app, WeChat, that does basically everything. The average Chinese Internet user spends half of his or her time online in WeChat. When you open WeChat, you have access to everything U.S. users get from Facebook, Twitter, iMessage, Uber, Expedia, Evite, Instagram, Skype, PayPal, GrubHub, LimeBike, WebMD, Fandango, YouTube, Amazon, and eBay.

Spectrum: You describe China’s startup ecosystem as a brutal “coliseum” where companies don’t win because they’re the most innovative, but rather because they’re the best at copying, using dirty tricks, and working insane schedules.
Lee: There is creativity, but it’s just one tool. Another is copying. Entrepreneurs do whatever it takes to win, to build value for the user, and to make money. If you look at WeChat, you can’t point to one moment when it shocked the world like an iPhone. WeChat today is an amazing innovation, but it didn’t come about because someone at Tencent dreamed it up and built it and shocked the world. They kept layering on features that users wanted, they iterated, they threw away the features that didn’t work, and at the end they had a product that was the most innovative social network. It’s so good that Facebook is now copying them.


“50 Percent of Jobs Are in Danger”

Spectrum: You write that the big AI question isn’t whether China or the United States will dominate. Instead it’s how we’ll deal with the “real AI crisis” of job losses, wealth inequality, and people’s sense of self-worth.
Lee: AI will take many single-task, single-domain jobs away. You can argue that humans have abilities that AI does not: We can conceptualize, strategize, create. Whereas today’s AI is just a really smart pattern recognizer that can take in data, optimize, and beat humans at a given task. But how many jobs in the world are simple repetitions of tasks that can be optimized? How many jobs require no creativity, strategizing,
conceptualization? Most jobs are repetitive: truck-driving, telemarketing, dishwashing, fruit picking, assembly-line work, and so on. I’m afraid that about 50 percent of jobs in the world are in danger.

Whether these jobs will disappear in 15 years or 20 or 30, that’s debatable. But it’s inevitable. Not only can AI do a better job, it can do the job for almost marginal cost. Once you get the system up and running you just pay for the server, electricity, bandwidth. To be competitive, companies will be forced to automate. And this shift will happen a lot faster than has ever happened before in the history of humanity.

Spectrum: Why do you think “techno-utopians” have it wrong when they say that AI will ultimately create entirely new categories of jobs, just like the industrial revolution?