Essentialness of Data |
July 13th, 2021 |
privacy, tech |
Learning from implicit feedback: dictation software can operate without learning what corrections people make, or a search engine can operate without learning what links people click on, but the overall quality will be lower. Each individual piece of information isn't required, but the feedback loop allows building a substantially better product.
Incremental rollouts: when you make changes to software that operates in complex environments it can be very difficult to ensure that it operates correctly through testing alone. Incremental rollouts, with telemetry to verify that there are no regressions or that relevant bugs have been fixed, produces better software. Even Firefox collects telemetry by default.
Ads: most websites are able to offer their writing for free, without a paywall, because they can get paid for showing ads. Collecting more data makes ads more efficient, which makes them more profitable for the sites, which translates into more competition to provide users with things to read. (more)
Instead of pushing for "don't collect data", I think it would make a lot more sense for advocates to push for "only collect data privately" and work to make that easier (carrot) or mandatory (stick). None of these uses require individual level data, they're just easiest to implement by sending all of the data back to a central server and processing it there.
(What does "private" mean? Ideally it means that no one reviewing the data can tell what your, or any other individual's, contribution was. This is formalized as differential privacy, and is typically implemented by adding noise proportional to the maximum contribution any individual could have. In some cases k-anonymity may also provide good protection, but it's trickier. And this is only the beginning; privacy researchers and engineers have been putting a lot of work into this space.)
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