If you’re out late and banking on a rideshare to get you home, make sure your phone battery is charged. The less juice in your phone, and the geater the urgency of the call, the more the trip will cost you. Splashing out on a meal delivery now your salary has come through? Yep, the bill for your meal will likely be higher at the beginning of the month than at the end when you’re skint. If you’re buying on Amazon, don’t imagine that the products you are offered are the same, or in the same order, or at the same price as those proposed to a friend or relation just down the road, or indeed to yourself half an hour ago.

Welcome to surveillance pricing.

So far most people have been fatalistic about the tacit bargain embedded in the ‘free’ internet. ‘I know they know stuff about me, but I don’t have anything to hide, right?’; ‘Yes, the ads are a pain but I never respond to them; and I get search and email for free, so I’ll take it.’ This is the line of least resistance that regulators have taken too – until recently. But now the chickens are coming home to roost, with a vengeance. It’s not just surveillance pricing – surge prices that vary according to time and demand, booking and other add-on junk fees, algorithmic price-setting where a whole industry outsources its price-setting functions to the same third-party software – what all these add up to is that if companies have their way, the era of stable, open prices that we grew up in is coming to an end, with implications that go well beyond individual wallets and piggy banks.

Although Uber denies using battery status, which it admits tracking, in pricing rides, experiments suggest otherwise. McDonald’s, with 150m global users of its mobile app, uses ‘insight based targeting’ to ‘customise’ your ‘engagement’ based on time of day, product and ordering preferences, as well as location, weather, social interactions, and ‘relevance to key moments i.e. pay day.’ Amazon changes its prices every 10 minutes. A profusion of pricing consultancies have sprung up to exploit the rich layers of personal data available online to craft what they prefer to call ‘personalised’ pricing models, for companies such as McDonald’s and many others.

Surge pricing ‘will eventually be everywhere,’ according to one insider’s prediction. At least it is visible. The same can’t be said for the much slyer surveillance pricing. Long a marketer’s pipedream, individualised prices have had to wait for the combination of smartphone and apps to come to full flowering. Ever wondered why every website wants you to download its app? The latter, with its ability to mine data and simultaneously offer tempting prices displayed privately and in real time, is in effect a high tech, and vastly more potent, loyalty card. It is this app-smartphone combo that is at the heart of what Cory Doctorow terms ‘enshittification’ – the process whereby a genuinely useful service gradually morphs into its dark opposite as the algorithm learns how to exploit both buyers and sellers to dial up profit for its own shareholders.

First, says Doctorow, ‘the platform is good to its users, then, it abuses its users to make things better for its business customers; finally, it abuses those business customers to claw back all the value for itself’.

Take Uber (Amazon, Google Search, Facebook and X would do just as well). At its birth, Uber was touted as a new way of matching passengers with part-time drivers who, as with Airbnb, were happy to use spare capacity of a major asset for profit (hence the euphemism of ‘ridesharing’). For passengers, this was a great deal. Massively subsidised by shareholders, rides were both cheap and convenient. They were hooked. But after the initial euphoria, driving was a harder sell, and still is. So in its second phase Uber upped its rates for drivers. Now, however, having at last turned the corner into profit (although not much of it from rides), it is entering the third phase. Having racked up an astonishing $32bn of accumulated losses in its short life, Uber reckons it is payback time.

So here comes the smart part. Stuffed with electronics and software, new cars are already a privacy nightmare – surveillance devices on wheels, as they have been termed (one brand reportedly tracks occupants’ sex lives). Without going that far, Uber taps its ever-growing trove of car-borne and third-party-derived data to play passengers and drivers off against each other. Neither can see the price data shown to the other; surge pricing injects another variable that the algorithm can juggle to maximise Uber’s take from both sides of its market. In London at least, Uber fares are now in many cases little different from those of black cabs. Or maybe I’m just one of the suckers who’s taken for the more expensive ride?

Platforms are ripe for price maximisation in another way. Let’s stay with cars – yes, they are platforms too! – whose computers and sensors can harvest not only data but rents. BMW caused outrage when it decided to charge customers a monthly sum to activate already-installed seat heating. On certain models Mercedes charges owners a subscription of $1200 a year to use the car’s full performance capabilities. Tesla (who else) is reported to have disabled autopilot and other advanced features of a second-hand Tesla on the grounds that the new owner ‘hadn’t paid for them’. It can also remotely, and legally, disable cars to prevent them being fixed by an unauthorised repairer or modified in unapproved ways. Smart TVs that can read your mood and sell to you accordingly are on the way. Expect more of this, much more, in future.

Price holds an almost mystical aura in neo-liberal economics. At the precise point where demand and supply curves meet, price is ‘discovered’ by the magic of the market. Enthusiasts for the new pricing argue that it is fixed prices that are the anomaly here: what we are seeing now is a digitised return to the rule of the bazaar that applied up to the 19th century, when every purchase was bargained for: what could be more efficient than supply and demand in individual equilibrium? Yet it is obvious that the aim of companies flocking to emulate McDonald’s or Uber is not the pursuit of economic aesthetics, but that of profit improvement at the expense of producers, workers and advertisers who are not privy to the same information. Individualised pricing is an ‘expression of surveillance capitalism’s information asymmetries,’ sums up Shoshana Zuboff.

Prices and pricing aren’t of interest only to individuals, of course. Policymakers and economists study their movements intently, and often act on them. In crude terms, they see rising prices as a result of too much money chasing too few goods, and often choose to raise interest rates to persuade consumers to buy less. But what if rising prices are instead the consequence of price trickery by powerful companies (for which there is some, although inconclusive evidence) through the abuse of those information asymmetries? Or through informal industry price-setting via third-party software intermediaries that all hoteliers, airlines and agribusinesses (for instance) use? There should be no illusions. If they can do it, they will. ‘People of the same trade seldom meet together, even for merriment and diversion, but the conversation ends in a conspiracy against the public, or in some contrivance to raise prices,’ Adam Smith noted in The Wealth of Nations back in 1776. As he was already well aware, ‘twas ever thus.