May 14, 2019

Axios Future

By Bryan Walsh
Bryan Walsh

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Any stories we should be chasing? Hit reply to this email or message me at steve@axios.com. Kaveh Waddell is at kaveh@axios.com and Erica Pandey at erica@axios.com.

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1 big thing: The new sharecroppers

Illustration: Aïda Amer/Axios

Invisible to most of us, an underclass of labor has evolved behind the artificial intelligence revolution — thousands of low-wage workers in the U.S. and across the globe who painstakingly inventory millions of pieces of data and images, giving power to AI programs. Some critics call them the new "sharecroppers."

  • Kaveh and I report: These workers — people who affix labels to data so computers can understand the information — are starting to attract the interest of social scientists and other experts. They say labelers may at least in part explain the nagging conundrum of American income inequality — and perhaps how to fix it.

Background: AI seems all-knowing, but actually it's only partly so. When it comes to the AI behind driverless technology, for instance, sensors can take fantastically granular pictures of streets and hazards of all types, and AI can be fed with the experience of every type of driving situation. But autonomous technology companies still need humans to inform the AI what it's looking at — to circle things like trees, stop signs and crosswalks.

  • Without human labeling, AI is dumb. It doesn’t know a skyscraper from a spider.
  • But that doesn't mean companies pay labelers well. Instead, they are compensated like bottom-of-the-barrel workers.
  • In the U.S., companies say they are paying such workers $7–$15 an hour, but that may be the top of the pay scale. Labelers also take on piecework from crowdsourcing platforms. In Malaysia, the pay can be around $2.50 an hour.

The big picture: The winners are AI companies, which are mostly in the U.S., Europe and China. The losers are workers in both rich and relatively poor countries who are paid little.

How the companies are managing the labelers: Nathaniel Gates, CEO of Alegion, a Texas-based crowdsourcing platform, said his firm intentionally reduces the job of labeling to the simplest, most routine task possible. While this narrows a worker's chance to move up the skills — and wage — ladder, Gates argues that he is at least "opening new doors that were never available to them."

  • “We are creating digital jobs that didn’t exist before. Oftentimes, the folks doing this work are coming from farms and agriculture or factories that dried up because of automation,” Gates tells Axios.

But some experts say such practices builds inequality into the AI economy.

  • In a new book called "Ghost Work," Microsoft Research's Mary Gray and Siddharth Suri argue that workers such as labelers are a significant part of one of the most dynamic parts of the economy.
  • "Economists don't have a handle on how to price the market," Gray tells Axios. "We've been pricing this labor as a durable good, but it's the collective intelligence that's the value proposition."

James Cham, a partner with Bloomberg Beta, the venture capital firm, thinks that AI companies are gaming the system.

  • "The companies derive benefit over a long time, while workers are paid just once. They are paid like sharecroppers, making subsistence wages. The landowners get all the returns because of how the system is set up," Cham tells Axios.
  • "It's one big arbitrage."
2. The AI acquisitions war
Expand chart
Data: CB Insights; Chart: Harry Stevens/Axios

Big Tech has snapped up more than 50 AI companies since 2010, carving out another front in the nonstop war among the giants for AI talent, data and ideas, Kaveh writes.

The clamor reflects a scarcity of AI expertise, as we've reported in the past. But it also allows Big Tech companies to reinforce their advantage over the upstarts, each time making it harder for a new entrant to strike gold.

The big picture: Several of the top AI researchers and most lucrative products at leading tech firms came from acquisitions, according to data compiled by CB Insights.

  • In 2010, Apple purchased Siri, the digital assistant that's become a cornerstone in its phones, tablets, computers and speakers.
  • In 2013, Amazon acquired British tech company Evi, which went on to contribute to its market-leading Alexa assistant.
  • In 2014, Google bought up DeepMind, the pioneering research outfit behind the computers that beat humans at Go. And a 2013 acquisition brought Geoffrey Hinton, the father of deep learning, to Google.

Between the lines: The more these large companies buy up AI talent and software, the larger they expand the buffer between them and everyone else.

  • The acquisitions chart above "is certainly consistent with the theory that Big Tech companies are consolidating to expand their reach, talent pool and market share," says Yoshua Bengio, a prominent AI researcher at the University of Montreal.
  • Frantic company recruiting and acquisitions are just getting started, says Deepashri Varadharajan, lead analyst at CB Insights. "And Big Tech companies that are trillion-dollar conglomerates have an advantage here."

These companies haven't swallowed up the whole AI field. There are still plenty of startups with smart people and innovative products.

  • "The acquisitions reflect the strategic importance of AI — nothing more," says Oren Etzioni, CEO of the Allen Institute for AI, a nonprofit.
  • In December, we reported that 10% of the world's AI talent works at 10 huge companies. That still leaves a long tail of talent to work at smaller shops around the world.

The bottom line: The front-runners' gravitational pull intensifies as they accumulate talent, data and computing power at a scale unattainable for academics or startups, such that the best minds in AI find it increasingly difficult to do boundary-stretching work elsewhere.

Go deeper: An AI feud between corporate research labs and academia (Axios)

3. The fate of a shuttered Sam's Club

Photo: Seth McConnell/The Denver Post/Getty

In an unmistakable sign of the times, Walmart has converted a closed, 139,000-square-foot Sam’s Club into a warehouse for online orders.

Erica writes: The new space is in Worcester, Massachusetts, reports Supply Chain Dive. It’s a perfect place for a fulfillment center, as three major highways cross through the city.

The big picture: Look for Walmart to bolster its warehouse network as it competes with Amazon on speedy shipping.

  • Walmart today announced one-day shipping for 220,000 products in Las Vegas and Phoenix, with plans to expand to other places. There’s no hefty membership fee. Customers just need to order at least $35 worth of stuff.
  • Worth noting: Amazon’s one-day shipping — though available only through Prime — is meant to eventually be available to all members across the world for 100 million products.

Go deeper: Dead malls are turning into warehouses

4. Worthy of your time

Photo: Adam Bettcher/Getty

AI needs more "why" (Alexander Lavin — Forbes)

Dig in for a much longer trade war (Jonathan Swan — Axios)

In London, 96% facial recognition failure rate (Tim Cushing — Techdirt)

German businessmen to voters: resist populists (Guy Chazan, Olaf Storbeck — FT)

Nearly 20 years ago, cocaine washed up on this island (Matthew Bremner — The Guardian)

5. 1 more pay gap: What influencers make

The Kardashian clan at the 2019 Met Gala. Photo: Gilbert Carrasquillo/GC Images

In the nascent social media influencing industry, women are paid less than men — even though they outnumber men 3 to 1.

Erica writes: As younger consumers spend more and more time on social media apps, the power of influencers — models and celebrities with large followings — is also growing.

And although influencers are 75% female, the industry has a wide gender pay gap, Quartz reports.

  • On average, women charge $351 per post. That’s 23% less than the $459 per post that men charge.
  • One explanation, per Quartz, is that the large pool of female influencers has driven prices down.

The big picture: As we’ve reported, several U.S. industries are closing the pay gap. But in a few, including media and retail, the difference remains large.

Bryan Walsh