Looks very relevant. If the same service (e.g same instance of the model, or even different instances of the same model) is provided to more than one client, I'd guess a prosecutor might reach for it.
Easiest but most costly way this could be avoided is by creating new models for each client using the client's own specific data and keeping the data and models fully isolated for each client.
If derivative insights are gathered across all models, it'd have to be one-way informing e.g business decisions for the overall company rather than informing how the models themselves operate.
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edit: "We pivoted to a 'global model' that used data across countries to significantly reduce the amount of data required in any one country."
This might paint a bullseye on their back, but I'm a security and risk person, not a lawyer.
There's a lot of existing legislation around the world about discounting as well.
In many countries to be able to discount you need to have sold an item at full price for a certain amount of time, and you can't discount for more than another amount of time (i.e. to prevent perpetual discounting).
In some countries you can't sell the same item at different prices for different customers. You can issue different discount codes to different customers, but those would likely need to be widely applicable so that it's not just different pricing in disguise.
Having worked in an ecommerce company, I'm excited by the prospect of better automated pricing tools and tools that can do things like target sell-through by a particular date. However as a consumer and keen advocate for consumer rights, I'm concerned about a future where every last penny is eeked out of consumers by automated systems designed to identify ways they can be exploited with pricing.
Easiest but most costly way this could be avoided is by creating new models for each client using the client's own specific data and keeping the data and models fully isolated for each client.
If derivative insights are gathered across all models, it'd have to be one-way informing e.g business decisions for the overall company rather than informing how the models themselves operate.
---
edit: "We pivoted to a 'global model' that used data across countries to significantly reduce the amount of data required in any one country."
This might paint a bullseye on their back, but I'm a security and risk person, not a lawyer.