Four Union Strategies to Fight on A.I.

A corporate artificial intelligence frenzy is sowing fear for workers on a massive scale. Seventy-one percent of people in the U.S., according to a Reuters poll on A.I., are concerned “too many people will lose jobs.”

Wall Street and Big Tech are running a huge hype machine to back up their massive, risky investment in A.I., pledging it will drive a “productivity surge,” meaning fewer workers and more profits.

But workers can take heart that, so far, it’s mostly hot air. To date, A.I. is making little profits. It can be helpful at a few tasks—rough drafts of computer code, summaries of reams of data—but is rarely the equal of human talent otherwise.

Nonetheless, investors are on track to pour more than $5 trillion worldwide into A.I. over the next five years. To make good on that cash outlay, expect CEOs to sell A.I. as the salve for everything from logistics to loneliness.

A.I is a management power grab, disguised as an inevitable technical upgrade. To fight it, workers can use four strategies proven in the past: name the real problem; unionize it; ransom it; and block it.

NAME THE REAL PROBLEM

The first step for workers is to cut through the hype. At your job, what are the specific uses of automation or A.I. that management aims to roll out?

Which uses are likely to be a dud, and which are a real threat to union power, job security, and the quality of what you do? Are there uses that your co-workers want, on their own terms?

These tough questions are best answered collectively, with knowledge from different departments and job types, whether that discussion takes place in union meetings or on lunch breaks.

At the United Caucuses of Rank-and-File Educators conference last summer, teacher activists from across the country held a discussion like this. Many hated A.I. being pushed into the classroom. Others felt it could make onerous parts of their job easier.

The teachers opposed to A.I. shared examples of how it had been used against workers and how it was promoting plagiarism and misinformation. Participants keyed in on a few uses they might want as options, like class planning or reviewing students’ past work, but agreed it should never be mandated by management.

National Nurses United released “A.I. justice” principles last year that highlight specific threats, like an automated algorithm deciding how many nurses to schedule on shift or which tests should be ordered for a patient. The union argues that computer systems can’t replace human expertise.

Executives often tell on themselves. To stay ahead of management’s game, unions can recruit member volunteers to read what CEOs in your sector are bragging about in the business press and scour the web for what they’re promising their higher-ups.

In fact, the heaviest A.I. users are in the C-suite. A recent survey of the U.S. and five other countries found 87 percent of executives and 57 percent of managers were using A.I. tools, versus 27 percent of employees. These tools can’t nurse a patient, but they can hack a passable version of management’s tasks: surveilling workers, summarizing information, and telling investors what they want to hear.

Job cuts from A.I. may be a real threat in your sector, but not because automation can actually do your work well. Executives may not care whether students are nurtured, real facts are reported, or patients are healed. They just want to make a buck. A.I. gives them cover to allow the quality of work to degrade.

Software executive and critic Anil Dash recently observed that half a million tech workers have been laid off since the release of ChatGPT mainly because execs “now have A.I. to use as an excuse for going after workers they’ve wanted to cut all along.”

Junior programming jobs have been heavily cut, while senior engineers are kept on to fix the buggy code dreamed up by A.I. But where will the next generation of senior engineers come from, if they’re not learning on the job as junior coders? These short-sighted cuts are creating new leverage for experienced programmers, who could push worker-run solutions for training the next generation.

UNIONIZE IT

New tech could become an excuse to outsource your work to non-union hands. To keep it union, you can bargain contract language, make direct demands on management, and take a proactive union approach to learning technology.

In the 1970s and ’80s, Mike Parker, an Auto Workers electrician and Labor Notes co-founder, kept track of auto company plans for robotics and computers, and developed union training programs on the new gear.

When managers proposed to bring in the robots, they said non-union specialists would have to take on installation and maintenance. Parker and his co-workers asserted they were ready to handle the work on union terms, and often won.

It’s too bad the union as a whole didn’t follow his lead. Every decade since the late 1940s, auto company CEOs have made grand promises of automation by robotics, and Auto Workers top officers generally gave up the fight. Still, most job cuts were caused by work speed-up, mandatory overtime, and outsourcing to third-party parts suppliers and non-union Southern factories.

As the San Francisco-to-Oakland Bay Bridge got rebuilt two decades ago, private contractors planned to outsource the work on massive new welding machines to non-union workers. “The company came to the union and said, ‘We’ve got a contract with you, but you don’t have welders certified on those machines locally,’” said Mike Munoz, then a leader with the Pile Drivers in Oakland.

“Our union bought one of the machines and started teaching the members to weld on it,” said Munoz. “We can train our members to do anything. We certified all the welders who went out on the Bay Bridge. It became our work because we threw ourselves into it.”

When it comes to new A.I. and automation schemes from management, workers can refuse to let non-union contractors take charge. An army of consultants has sprung up to advise bosses on A.I. implementation for hospitals and schools, grifting millions from actual education and care.

Your union contract may already have language requiring management to bargain over major changes in unit work. Where it doesn’t, you can push for specific new language. If you accept some A.I. tools, like to summarize a thousand pages of patient records, which union job classifications will run the robots and double-check their work? Keeping the work in union hands is a first step to steer what A.I. is and isn’t used to do.

RANSOM IT

Another union strategy worth considering: force management to pay workers extra, as a condition of rolling out new technology.

The most famous deal like this, for longshore workers, shows short-term gains and big long-term limits for the approach.

In a landmark 1960 agreement, the militant West Coast Longshore union (ILWU) agreed to allow mechanization and shipping containers at the ports, in exchange for expanded pay, pensions, and a guarantee of a certain number of union jobs at each port. If the port owners dropped hiring below that number, they still had to pay that number of union members indefinitely.

The agreement came with big tradeoffs, as members were split into three tiers with radically different job security. Only the A-tier got the guaranteed jobs or payouts. When port owners slashed hiring, A-tier longshore workers and union officers didn’t feel the urgency to organize the jobs in new hubs of the supply chain.

“The containers go inland,” said Peter Olney, who came into the union as a lead organizer decades later. “Do you follow the work inland, unloading and warehousing them? That fell by the wayside.”

Another kind of ransom can be won by those building out the new technology and its infrastructure. Construction workers have a particularly direct kind of leverage over the A.I. boom: it can’t be built without them.

Much of the massive data center construction behind A.I. is getting unionized, even in far-flung boomtowns. That’s because building trade unions have national networks of trained, traveling members to call up through their hiring halls, and can meet the labor demand fast.

In the next wave, many “hyperscale” data centers are planned to be 10 times the size of those already built. The largest will guzzle as much electricity as the entire city of Philadelphia.

The vast labor demand of those projects gives building trade unions leverage, if they seize it: to bring new members in, to turn down work on the projects facing the most local opposition, and to demand concessions for public services and the environment.

An upsurge of local grassroots campaigns blocked 25 data centers last year. When unions partner with community groups, they both can squeeze more from developers and governments, like dropping the billion-dollar data center tax giveaways that can bankrupt local schools and roads. In California, such alliances unionized gas and solar power plants and won a few community demands.

At best, these kinds of “ransom” deals can raise the costs for management to force in a new technology, and buy time for workers to go on offense with organizing.

BLOCK IT

With enough strength, workers may manage to draw the line against certain uses of A.I. altogether.

In their 2023 Hollywood strikes, the Writers Guild and Screen Actors won restrictions on the use of A.I. writing or replicas of actors’ faces and voices. But in a media industry that’s getting more consolidated and corporate every year, bosses are finding workarounds, and unions are fighting to keep up.

The NewsGuild launched a national campaign in December for “News, Not Slop,” using contract negotiations and public pressure to demand limits on A.I.-generated news content.

In their recent strike, 15,000 New York City nurses won language against some kinds of A.I. misuse.

Oil refinery Steelworkers, in national pattern bargaining this year, aim to block management from using A.I. tools to monitor workers’ movements, assess their productivity, and dish out automatic discipline.

Existing contract language on working conditions could be used against degrading uses of A.I. Use your discipline process to limit the use of automated demerits. Use worker oversight of safety to push back against allowing A.I. tools to make risky decisions. Use staffing limits to draw a line against bigger workloads disguised as high-tech efficiency.

The most degrading effect of A.I., after all, isn’t just to our work, but to our skills and imaginations. When music and movies are made by a robot cobbling together past works, it cheats audiences and artists alike of newer, wilder dreams.

Even in more rote work, we learn by doing. A.I. is no unstoppable force of progress. In fact, if it’s done how CEOs want, it would dry up the well of progress: worker know-how.

Standing up to management’s technological power grab is one big step to take responsibility for the world we make on the job—and to keep open the path to a better one.