| The FAANG people also have a lot of direct personal experience contradicting a lot of mainstream FUD titled "All your data is being sold to the lowest bidder". Having worked at one of those companies (and having quit that job being disillusioned by a lot of things), there is still so much mainstream misinformation about this. Yes data is often used for tracking and training. In aggregate form. Sensitive data is anonymized/de-id-ed. The leading research on these techniques are also coming out from these companies btw. There are layers and layers of policy and permission safeguards before you're allowed to access user data directly as an engineer. And if/when someone tries to exploit the legitimate pathways to touch user data (say customer support), they get promptly fired. But it's much easier to believe that FAANG is some great monolithic evil, out to surveil you personally for some vague benefit that never gets specified. All the legitimate concrete monetary benefits (e.g. tracking for ad targeting work and training ML models) can be had just as well with aggregate data, but privacy FUD doesn't want to listen to that. Meanwhile stupid legislation and the ability of courts and law-enforcement to subpoena any data they want whenever they want keeps data on their servers longer than they'd want to. Yet people will prefer to blame the "Evil Tech Cartel" instead of multiple branches of their government wanting to read their texts and GPS logs. |
There aren't that many possibilities on how geolocation data vendors get access to high-precision location data of millions of people. A publicly traded company that generates revenue from targeted ads can never be fully trusted to behave. A social network that optimizes for time spent looking at ads will never really care about its users well-being. Algorithmic feeds are responsible for a widening social divide and loneliness. Highly detailed behavioral analysis can hurt people even when aggregated, for example when they get less favorable insurance terms based on their spending habits. Data that can be used to increase revenue will not be left untouched just to keep moral higher ground. Sensitive information shared with an LLM that end up in training data today might have dangerous consequences tomorrow, there is no way to know yet.
This isn't even about proper handling of individual pieces of data, but the higher-order effects of handing control over both the world's information and the attention of its inhabitations to shareholder-backed mega-corporations. There are perverse incentives at play here, and anyone engaging in this game carries responsibility for the outcome.