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Tech’s new labor movement is harnessing lessons learned a century ago

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Tech’s new labor movement is harnessing lessons learned a century ago


The rise of the tech worker

Even in the early 1990s, when Lerner went to war with Apple as an organizer of the Justice for Janitors campaign and won union rights for subcontracted cleaning workers across the tech sector, the question of “Who is a tech worker?” loomed large. Through those successful campaigns, Lerner helped extend the definition of a tech worker to virtually anyone who makes a tech company run. Cori Crider, an attorney with Foxglove, a firm that aims to challenge the power of Big Tech, has been working with subcontracted content moderators—real humans who sift through posts with violence and racism and graphic sex every day, trying to determine what violates a constantly shifting set of rules. 

Those workers are often bound by nondisclosure agreements that keep them from speaking publicly about their working conditions. That allows companies like Facebook to deny they exist—an assertion the company stuck with last year even after reports emerged that moderators working for the outsourcing firm Accenture were being pushed back into the office during the pandemic. 

Tech workers outside the normal definition of “employees” are still finding ways to organize and protect themselves. Coworker.org, a campaign platform for labor organizing, is using donations from well-off tech workers to build a “solidarity fund” distributed to workers on the other side of the tech supply chain. Gig workers on Amazon’s Mechanical Turk platform are using the site Turkopticon to come together and fight for better terms. 

A wave of rebellions within the unions and wildcat strikes challenged the idea that automation was making their jobs easier. 

At the other end of the tech-worker spectrum are those building electric cars at Tesla’s plant in Fremont, California. Before Elon Musk’s company bought the Fremont facility, it was known as New United Motors Manufacturing, Inc., or NUMMI, a collaboration between General Motors and Toyota where Japanese “lean production” was brought to America. NUMMI didn’t survive GM’s bankruptcy in 2008, and Tesla snatched it up. 

Cooperating with the United Auto Workers was one of NUMMI’s big innovations, but Tesla’s gone another way. Recently, an administrative judge at the NLRB ruled that several of the company’s actions in response to worker organizing were illegal—including a couple of Musk’s tweets as well as harassment of workers passing out union pamphlets, banning of pro-union T-shirts and buttons, and the interrogation of organizers and firing of one. The NLRB’s penalties amount to little more than a finger-wag—Musk must read a statement telling workers that they have the right to unionize, and rehire the fired worker. He’s appealed the decision anyway.

The workers at the plant, even the union supporters, are enthusiastic about producing electric vehicles, but they note that the technical sophistication of the plant does not prevent a lot of backbreaking manual labor—or injuries. Jose Moran, one of the leaders of the union drive and a former NUMMI worker, wrote a blog post about the things he wanted to improve, including the grueling pace of the work and some badly designed machinery. 

Autoworkers have struggled with machinery since the days of Henry Ford. But Tesla workers’ stories echo the complaints of autoworkers in the 1960s who battled “speed-up”—the way management would use new technology to ratchet up the pace of work—in places like Lordstown, Ohio, and Detroit. A wave of rebellions within the unions and wildcat strikes challenged the idea that automation was making their jobs easier. 

As machines sped up the manufacturing process, workers had to hustle faster to keep up. The autoworkers at Tesla, far from representing a labor aristocracy among autoworkers, say they make less than unionized workers at GM and Ford. As Moran wrote, “I often feel like I am working for a company of the future under working conditions of the past.” 

The long game

In the Amazon warehouses, too, everything old is new again. “The auto industry tried to do lots of automation back in the ’80s, ’70s, whatever, and they basically plateaued out where they couldn’t do it anymore. And Tesla basically tried to do the same thing,” says Tyler Hamilton, an Amazon warehouse worker from Minneapolis. “It’s the same thing with Amazon. There’s only so much you can do with automation.” 

Mohamed Mire, a coworker of Hamilton’s, explains that most of Amazon’s vaunted technology goes to tracking the workers rather than making the work efficient. Scanners that the workers use to scan packages also keep track of their so-called “time off task,” and they get written up if their productivity rate falls. Robots that Hamilton likens to “giant Roombas” carry merchandise around the warehouse but malfunction often—lately his job has included setting the robots right when they stop working. Data from Amazon shows that injury rates are higher at facilities with robots than without them. 

Tech

The Download: COP28 controversy and the future of families

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The Download: COP28 controversy and the future of families


The United Arab Emirates is one of the world’s largest oil producers. It’s also the site of this year’s UN COP28 climate summit, which kicks off later this week in Dubai. 

It’s a controversial host, but the truth is that there’s massive potential for oil and gas companies to help address climate change, both by cleaning up their operations and by investing their considerable wealth and expertise into new technologies.

The problem is that these companies also have a vested interest in preserving the status quo. If they want to be part of a net-zero future, something will need to change—and soon. Read the full story.

—Casey Crownhart

How reproductive technology can reverse population decline

Birth rates have been plummeting in wealthy countries, well below the “replacement” rate. Even in China, a dramatic downturn in the number of babies has officials scrambling, as its population growth turns negative.

So, what’s behind the baby bust and can new reproductive technology reverse the trend? MIT Technology Review is hosting a subscriber-only Roundtables discussion on how innovations from the lab could affect the future of families at 11am ET this morning, featuring Antonio Regalado, our biotechnology editor, and entrepreneur Martín Varsavsky, founder of fertility clinic Prelude Fertility. Don’t miss out—make sure you register now.

The must-reads

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Unpacking the hype around OpenAI’s rumored new Q* model

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Unpacking the hype around OpenAI’s rumored new Q* model


While we still don’t know all the details, there have been reports that researchers at OpenAI had made a “breakthrough” in AI that had alarmed staff members. Reuters and The Information both report that researchers had come up with a new way to make powerful AI systems and had created a new model, called Q* (pronounced Q star), that was able to perform grade-school-level math. According to the people who spoke to Reuters, some at OpenAI believe this could be a milestone in the company’s quest to build artificial general intelligence, a much-hyped concept referring to an AI system that is smarter than humans. The company declined to comment on Q*. 

Social media is full of speculation and excessive hype, so I called some experts to find out how big a deal any breakthrough in math and AI would really be.

Researchers have for years tried to get AI models to solve math problems. Language models like ChatGPT and GPT-4 can do some math, but not very well or reliably. We currently don’t have the algorithms or even the right architectures to be able to solve math problems reliably using AI, says Wenda Li, an AI lecturer at the University of Edinburgh. Deep learning and transformers (a kind of neural network), which is what language models use, are excellent at recognizing patterns, but that alone is likely not enough, Li adds. 

Math is a benchmark for reasoning, Li says. A machine that is able to reason about mathematics, could, in theory, be able to learn to do other tasks that build on existing information, such as writing computer code or drawing conclusions from a news article. Math is a particularly hard challenge because it requires AI models to have the capacity to reason and to really understand what they are dealing with. 

A generative AI system that could reliably do math would need to have a really firm grasp on concrete definitions of particular concepts that can get very abstract. A lot of math problems also require some level of planning over multiple steps, says Katie Collins, a PhD researcher at the University of Cambridge, who specializes in math and AI. Indeed, Yann LeCun, chief AI scientist at Meta, posted on X and LinkedIn over the weekend that he thinks Q* is likely to be “OpenAI attempts at planning.”

People who worry about whether AI poses an existential risk to humans, one of OpenAI’s founding concerns, fear that such capabilities might lead to rogue AI. Safety concerns might arise if such AI systems are allowed to set their own goals and start to interface with a real physical or digital world in some ways, says Collins. 

But while math capability might take us a step closer to more powerful AI systems, solving these sorts of math problems doesn’t signal the birth of a superintelligence. 

“I don’t think it immediately gets us to AGI or scary situations,” says Collins.  It’s also very important to underline what kind of math problems AI is solving, she adds.

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The Download: unpacking OpenAI Q* hype, and X’s financial woes

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📈


This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology.

Unpacking the hype around OpenAI’s rumored new Q* model

Ever since last week’s dramatic events at OpenAI, the rumor mill has been in overdrive about why the company’s board tried to oust CEO Sam Altman.

While we still don’t know all the details, there have been reports that researchers at OpenAI had made a “breakthrough” in AI that alarmed staff members. The claim is that they came up with a new way to make powerful AI systems and had created a new model, called Q* (pronounced Q star), that was able to perform grade-school level math.

Some at OpenAI reportedly believe this could be a breakthrough in the company’s quest to build artificial general intelligence, a much-hyped concept of an AI system that is smarter than humans.

So what’s actually going on? And why is grade-school math such a big deal? Our senior AI reporter Melissa Heikkilä called some experts to find out how big of a deal any such breakthrough would really be. Here’s what they had to say.

This story is from The Algorithm, our weekly newsletter giving you the inside track on all things AI. Sign up to receive it in your inbox every Monday.

The must-reads

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 X is hemorrhaging millions in advertising revenue 
Internal documents show the company is in an even worse position than previously thought. (NYT $)
+ Misinformation ‘super-spreaders’ on X are reportedly eligible for payouts from its ad revenue sharing program. (The Verge)
It’s not just you: tech billionaires really are becoming more unbearable. (The Guardian)
 
2 The brakes seem to now be off on AI development 
With Sam Altman’s return to OpenAI, the ‘accelerationists’ have come out on top. (WSJ $)
Inside the mind of OpenAI’s chief scientist, Ilya Sutskever. (MIT Technology Review)
 
3 How Norway got heat pumps into two-thirds of its households
Mostly by making it the cheaper choice for people. (The Guardian)
Everything you need to know about the wild world of heat pumps. (MIT Technology Review)
 
4 How your social media feeds shape how you see the Israel-Gaza war
Masses of content are being pumped out, rarely with any nuance or historical understanding. (BBC)
China tried to keep kids off social media. Now the elderly are hooked. (Wired $)
 
5 US regulators have surprisingly little scope to enforce Amazon’s safety rules
As demonstrated by the measly $7,000 fine issued by Indiana after a worker was killed by warehouse machinery. (WP $)
 
6 How Ukraine is using advanced technologies on the battlefield 
The Pentagon is using the conflict as a testbed for some of the 800-odd AI-based projects it has in progress. (AP $)
Why business is booming for military AI startups. (MIT Technology Review)
 
7 Shein is trying to overhaul its image, with limited success
Its products seem too cheap to be ethically sourced—and it doesn’t take kindly to people pointing that out. (The Verge)
+ Why my bittersweet relationship with Shein had to end. (MIT Technology Review)
 
8 Every app can be a dating app now 💑
As people turn their backs on the traditional apps, they’re finding love in places like Yelp, Duolingo and Strava. (WSJ $)
+ Job sharing apps are also becoming more popular. (BBC)
 
9 People can’t get enough of work livestreams on TikTok
It’s mostly about the weirdly hypnotic quality of watching people doing tasks like manicures or frying eggs. (The Atlantic $)
 
10 A handy guide to time travel in the movies
Whether you prioritize scientific accuracy or entertainment value, this chart has got you covered. (Ars Technica)

Quote of the day

“It’s in the AI industry’s interest to make people think that only the big players can do this—but it’s not true.”

—Ed Newton-Rex, who just resigned as VP of audio at Stability.AI, says the idea that generative AI models can only be built by scraping artists’ work is a myth in an interview with The Next Web

The big story

The YouTube baker fighting back against deadly “craft hacks”

rainbow glue coming out of a hotglue gun onto a toothbrush, surrounded by caution tape

STEPHANIE ARNETT/MITTR | ENVATO, GETTY

September 2022

Ann Reardon is probably the last person you’d expect to be banned from YouTube. A former Australian youth worker and a mother of three, she’s been teaching millions of subscribers how to bake since 2011. 

However, more recently, Reardon has been using her platform to warn people about dangerous new “craft hacks” that are sweeping YouTube, such as poaching eggs in a microwave, bleaching strawberries, and using a Coke can and a flame to pop popcorn.

Reardon was banned because she got caught up in YouTube’s messy moderation policies. In doing so, she exposed a failing in the system: How can a warning about harmful hacks be deemed dangerous when the hack videos themselves are not? Read the full story.

—Amelia Tait

We can still have nice things

A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or tweet ’em at me.)

+ London’s future skyline is looking increasingly like New York’s.
+ Whovians will never agree on who has the honor of being the best Doctor.
+ How to get into mixing music like a pro.
+ This Japanese sea worm has a neat trick up its sleeve—splitting itself in two in the quest for love.
+ Did you know there’s a mysterious tunnel under Seoul?



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