The Collective Action Problem of Gig Work: Why Platforms Win and Drivers Lose
When Uber, Lyft, and other gig platforms talk about their drivers, they always highlight one thing: independence. Drivers are free to log on when they want, pick up extra cash on their schedule, and be their own boss.
But scratch beneath the surface, and that “independence” looks pretty thin. Drivers don’t set their own prices. They don’t negotiate with customers. They don’t even control which rides they’re offered. Instead, they compete as individuals against an algorithm designed to maximize the company’s bottom line.
And here’s the rub: independence without coordination means no bargaining power.
Why the system works so well for the company
Platforms hold nearly all the cards. They’ve built a system where refusing bad deals is nearly impossible:
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Someone else will take it – With thousands of drivers on the road, if you turn down a low-paying fare, it just goes to the next person.
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The algorithm punishes non-compliance – Decline too many rides and your “acceptance rate” drops. That can cost you access to promotions, bonuses, or high-value trips. In extreme cases, drivers risk deactivation.
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Lack of transparency – Drivers don’t know what other drivers earn, how fares are really calculated, or what share of the fare the company keeps. It’s like playing poker where the house hides the cards.
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Psychological levers – Fear of missing out (FOMO) keeps drivers chasing the next ping. And because the platform controls visibility, many drivers believe they’ll be pushed into obscurity if they don’t play along.
In short, platforms have created an environment where drivers can say no in theory, but feel like they can’t in practice.
Why it harms independent workers
This setup isn’t just inconvenient — it systematically disadvantages drivers:
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Earnings get squeezed – Without collective resistance, rates hover just above the bare minimum needed to keep people driving.
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No real independence – Drivers carry the risks of being contractors (no benefits, no protections), but lack the actual freedom to set prices or negotiate terms.
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Voice is absent – The algorithm is judge, jury, and dispatcher. Drivers can’t appeal or bargain; they just adapt or log off.
So instead of a “flexible side hustle,” many drivers find themselves working long hours for shrinking returns, with little recourse.
What drivers could do
Ironically, drivers’ greatest power lies in the one thing platforms train them not to do: refuse bad fares. If enough drivers in a city collectively declined low-paying rides, platforms would have no choice but to raise pay to move customers.
But three obstacles stand in the way:
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Penalty systems – The algorithm subtly punishes refusal.
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Lack of communication – There’s no built-in way for drivers to coordinate across a city. Everyone is in their own car, playing their own game.
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Distrust and turnover – With high churn and varied motivations (part-time vs. full-time), it’s hard to build solidarity.
Some drivers are fighting back through independent associations, online forums, and even informal “strike days.” But without widespread participation, these efforts struggle to move the needle.
The limits of bargaining power
Even if drivers organized successfully, there’s a ceiling to how far rates can go. Customers still compare the price of a ride to alternatives: driving themselves, taking a cab, or carpooling. If driver pay gets pushed too high, demand will dry up.
That doesn’t mean drivers shouldn’t fight for more — only that gains must balance with the economic value customers perceive. The sweet spot is making rides profitable for drivers and still worthwhile for riders.
What broader change might take
For real balance, outside forces may need to step in:
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Policy intervention – Cities like New York and Seattle have set minimum pay floors for ride-hail drivers, ensuring a baseline standard of fairness.
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Sectoral bargaining – Legal frameworks could allow contractors to negotiate collectively without being accused of price-fixing.
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Transparency rules – Forcing platforms to disclose fare breakdowns, pay structures, and algorithmic penalties would let drivers make informed decisions.
These changes don’t eliminate flexibility, but they inject accountability into a system tilted too heavily toward corporate interests.
The bottom line
Gig platforms survive by keeping workers atomized, dependent on the algorithm, and afraid to refuse low pay. Drivers do have leverage — platforms collapse without them — but as long as that leverage is scattered and uncoordinated, the company wins.
For drivers, the path forward means finding ways to act together, even informally, and pushing for policies that give independents a fair shot at shaping the terms of their work. Independence should mean more than working alone under someone else’s rules.
In the meantime, drivers can help themselves by refusing rides that don’t meet a clear personal minimum — for example, only accepting trips that pay at least $1.20 per mile or $25/hour effective. If enough drivers set that kind of baseline, platforms are forced to adjust upward.
How to Set a Personal Minimum Fare (Baseline)
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Know your costs
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Fuel: $X per mile (varies by gas prices & vehicle efficiency).
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Maintenance: Tires, oil, brakes, depreciation. A common estimate is $0.15–$0.20 per mile.
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Insurance & misc. overhead: Divide your monthly costs by your estimated gig miles to get a per-mile number.
Many drivers use the IRS standard mileage rate as a shortcut. For 2025, that’s 67 cents per mile. That’s what the government considers the cost of operating a car.
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Decide your hourly target
What do you want to earn before expenses? For example, $25/hour gross is a common target because after car costs and taxes, that still leaves you with ~$15–18/hour net. -
Do the math for each trip
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Estimate trip time (pickup wait + driving).
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Estimate distance.
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Plug into:
If either falls below your personal minimums (say, $1.20/mile or $25/hour), decline.
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Set your baseline rule
For example:-
Don’t accept rides under $7, no matter how short.
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Require at least $1.20/mile AND $25/hour effective.
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Stick to it
The key is consistency. If enough drivers refuse underpriced rides, the platform will have to raise pay in that area to keep customers moving.
Written by me, in collaboration with ChatGPT.
