Digital platforms can algorithmically change rules, prices, and recommendations on a per-user, per-session basis, a practice called "twiddling." This leverages surveillance data to maximize extraction, such as raising prices on payday or offering lower wages to workers with high credit card debt, which was previously too labor-intensive for businesses to implement.
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As AI assistants learn an individual's preferences, style, and context, their utility becomes deeply personalized. This creates a powerful lock-in effect, making users reluctant to switch to competing platforms, even if those platforms are technically superior.
The current era of exploitative digital platforms was made possible by a multi-decade failure to enforce antitrust laws. This policy shift allowed companies to buy rivals (e.g., Facebook buying Instagram) and engage in predatory pricing (e.g., Uber), creating the monopolies that can now extract value without competitive consequence.
Platform decay isn't inevitable; it occurred because four historical checks and balances were removed. These were: robust antitrust enforcement preventing monopolies, regulation imposing penalties for bad behavior, a powerful tech workforce that could refuse unethical tasks, and technical interoperability that gave users control via third-party tools.
Technology in finance is a double-edged sword. While it can increase access, it can also be used to gamify trading, encourage impulse spending with 'buy-now-pay-later' schemes, and circumvent traditional consumer protection laws.
Platforms first attract users with good service, then lock them in. Next, they worsen the user experience to benefit business customers. Finally, they squeeze business customers, extracting all value for shareholders, leaving behind a dysfunctional service.
While AI shopping agents promise to protect consumer privacy by abstracting away direct retailer relationships, this is a false dawn. Power will likely centralize with the major tech companies providing these agents, not empower individual users with decentralized control. The battle for "owning the customer" simply moves to a new layer.
Platforms first attract users with a great service, then pivot to monetizing those users for business customers, and finally extract all value for themselves, degrading the experience for everyone else. This cycle, termed "inshittification," is enabled by locking in users and businesses who become too dependent to leave.
Meta's ad recommendations excel because Apple's privacy changes created a do-or-die situation. This necessity forced them to pioneer GPU-based AI for ad targeting, a move competitors without the same pressure failed to make, despite having similar data and talent.
AI uses shopper clickstream and sales data to segment customers and SKUs with precision. This allows brands to offer targeted discounts where needed, maintaining trust by avoiding deceptive practices like shrinkflation and being transparent about necessary price increases on less elastic products.
In markets like air travel, competing companies using sophisticated pricing algorithms will naturally converge on the same high price. Each AI optimizes against the others in real-time, leading to a de facto monopoly outcome for consumers, even without any illegal communication between the companies themselves.
