Gig Companies Are Using Your Data to See How Low a Wage You’ll Accept

Gig workers in the US are being offered individualised wages depending on what algorithms decide about how desperate they are for work.

Ride-hailing companies have long used algorithms to determine how much to pay drivers for a trip – and tech vendors in the US are now exporting that model to other sectors, according to a Washington Center for Equitable Growth report from last year.

According to the report, platforms like Uber and Lyft track users’ personal data – like how often they find work through the app and for what wage – to find workers who will accept the bare minimum without the protections that come with fixed-term contracts. 

One Lyft driver in the US found that over a two-month period, it took her longer and longer to earn $200. It seemed like the longer she spent on the app, the less she would be paid per trip. 

“Uber was the baseline model, and we are seeing that model being exported into different industries,” Travis Hall, state director for the Center for Democracy and Technology, told Bloomberg Law. 

A report from the Roosevelt Institute found that the staffing platforms now used by gig nurses in the US use algorithms to determine pay for individual shifts – resulting in nurses being paid different amounts for the same work within the same facility. 

Experts fear that the same trend is being repeated across diverse industries, including HR, customer services and retail.

In the UK, experts from the Institute of Employment Rights argue that more needs to be done to regulate algorithmic pay practices. 

Non-profit Worker Info Exchange found that since Uber introduced ‘dynamic pay’ practices in the UK in 2024, drivers in the country have lost out on an estimated £1.2bn in pay in the 12 months to March 2025.  

James Farrar, director of Worker Info Exchange, said: “Uber UK managers must now come clean and explain to their workers how their pay is set – and how much of each fare the company is taking.

“If Uber is allowed to continue getting away with the algorithmic trickery of its so-called ‘dynamic pay’ model, we should not be surprised when hyper-variability and AI-induced precarity in pay become the norm across the entire labour market.”