304 - Localization Scaling

One of the sleaziest tricks that both employers and market platforms are known to engage in is the "localization scaling" of both salaries and price tags. If public outrage results from two people who perform the same work being paid drastically different amounts due to them being of different genders, then the outrage for the same thing occurring at far greater scales and across much larger monetary differences for two people living in different countries should be no less potent.

Of course, while "rationally" true, humans are cognitively biased to feel far more outrage and empathy more generally for those close to them, which inherently reduces their relative empathy and general concern for people on the other side of the world. See the "Identifiable Victim Effect" for more on this cognitive bias.

In my world travels I've noted differences like the cost of a 3-month subscription in one country giving a lifetime subscription in another, and I've had subscription costs of some services cut to less than half of their advertised dollar value just from my payment method being reassigned to a different currency.

Many of these same platforms also engage in a variety of "dark patterns" to manipulate people into remaining on them, another big bag of sleazy and widespread methods. For example, Audible, Adobe, Amazon, Bitdefender, and countless others will offer big discounts when a user attempts to cancel their subscriptions to a service.

However, these sleazy methods only continue to remain viable so long as they remain invisible and/or under-utilized by a majority of customers. If more people started switching to payment via currencies that offer a far cheaper price tag and made a habit of walking through the steps of canceling their services the moment any dark pattern discount expired, often getting a new discount offer in the process, then the profits for these companies could well come crashing down.

"Dark Patterns" and such obvious forms of discrimination are the hallmarks of bad actors. Some of them may look good on a KPI spreadsheet, but that doesn't budge the culpability of parties setting or striving for those KPIs by a single nanometer.

"AI Agents" certainly aren't up to the task of performing those actions necessary for people to overcome these dark patterns and discrimination, nor could they ever realistically be, but that isn't true of more capable and fundamentally different technology. The potential savings shown below are just one example of the tip of the iceberg.