The human price of dynamic pay
At first, he saw it as a pathway to better pay and more freedom.
That sense of autonomy faded as platforms introduced dynamic pricing. Early “boosts” and promotional rates disguised an underlying trend of falling pay. “They didn’t really increase the pay,” he said.
“They just had these promotional things…called Boost where if you were getting, say, £2 for a certain trip it was now sort of doubled or tripled… but that was temporary. So, when that went down, they went back to their normal calculations and, and that's when I realised how bad it really was, you know? So, from that point, the pay started getting bad.”
As base rates fell, he relied on long hours to reach a minimum earnings target of £100 per day, based on what was necessary to cover their living expenses.
“But it means you start early in the morning and finish at least 10 to 12 at night … and you need to be working literally Monday to Sunday to make the money that you can pay your bills… I'm not sure you can have enough for saving… We have to work those hours because if you don't … then you're not going to survive.”
The system, he explained, rewards constant availability and penalises selective behaviour. “It knows how far you are willing to go, the type of pay you … prepare to accept. So, for instance, as a minimum fee, if you keep accepting £3…it will always come to you with £3.”
He described it as a form of auction: “It will send the same order to about 20 or even more drivers, and whoever accepts first gets the order. And so that basically means … [the chances of] a low order being accepted by somebody is very high, especially when it is very slow”.
He spoke about a recent innovation involving multiple orders being added together and presented as a single order of high value, which he regarded as a way of manipulating riders and drivers into accepting while also offering the company a higher profit margin.
Claude also noticed that dynamic pricing shaped not only pay but the rhythm of daily life. Over time, the pressure created exhaustion, poor sleep, and declining health.
“It means really you're not very stable on the wheel because you’re actually sleepy… how many hours you're working and how well you are sleeping per day … most drivers do not always have a good sleep if they're trying to reach a certain target.”
Despite the apparent flexibility, Claude felt increasingly dependent on the platform and linked this to deteriorating mental health and social isolation.
“Bike could break … any time. And if you don't have any money to fix it, that's you done. If you take a holiday or you … fell sick for too long … if anything happens and you are unable to work, then it means that you're going to be behind, your bills will be kicking in and that will affect your mental health and it becomes a horrible place to be. So many drivers trying to keep up with that by having a target and consistently working almost without break.”
Claude’s account captures the broader dynamics of algorithmic management, surveillance, constant competition, and wage instability, that push workers to accept declining pay for fear of losing access to work. Dynamic pricing feels like, he said, “it is trying to get drivers to accept the least amount possible.”
For Claude, flexibility has become an illusion. The platform decides when he works, what he earns, and how long he stays on the road. His experience reveals how data-driven pay systems reconfigure risk and dependency, reducing workers’ bargaining power and blurring the line between autonomy and control.
Claude’s account illustrates how behavioural data and acceptance histories are folded into dynamic pay, reinforcing downward pressure on earnings and dependence on long working hours.
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