Personal privacy is a paper tiger, as Facebook and others have proven again and again. You only need to look at the consequence-free landscape of privacy breaches to understand that people have no meaningful right to avoid direct marketing and spillage of their contact info.
On the other hand, confidential information of corporations is pretty well guarded, and confidential contract terms, costs, pricing, and other information that doesn't get shared among peer companies or competitors is what will propel AI into the economic stratosphere. Finding ways to get confidential data into learning systems and provide actionable feedback is the killer app.
I am not sure I get it. If I am Ford and get access to GMs Salary database or factory electrical meter, do I win much? It's almost certain I know the ballpark frommrunning my own factory and probably have hired three of GMs managers with detailed knowledge in their heads last week.
Or is it more hedge funds - like satellite images of Walmart car parks to estimate the revenue figures?
Either way these don't seem like things we need AI to pick out patterns ?
It's about normalizing pricing and terms in the supply chain. (You chose bad examples, as the larger buyers implicate antitrust/competition rules and illegal collusion.)
If an AI has access to a broad spectrum of confidential information, it can reliably answer questions about the state of the market on an anonymized basis. This has the effect of normalizing sourcing behavior, which reduces purchasing and sales friction and improves overall efficiencies.
On the other hand, confidential information of corporations is pretty well guarded, and confidential contract terms, costs, pricing, and other information that doesn't get shared among peer companies or competitors is what will propel AI into the economic stratosphere. Finding ways to get confidential data into learning systems and provide actionable feedback is the killer app.