• Fake4000@lemmy.world
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    11 months ago

    That’s because his/her data isn’t included. The decision would be different if that data included his/her shopping history.

    • mannycalavera@feddit.uk
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      11 months ago

      That’s no fun for the guardian. Gotta get those clicks with controversial misleading headlines. Totally not a tabloid, totally…

      What this article fails to explain is what exactly they are selling and how that is matched up to groups of users. It also fails to explain how advertising is linked to anonymous users at the other end and how throughout all of this it’s just a random ID they are targeting rather than Mr Phillips from Doncaster. It doesn’t explain at all the mechanism to do this because it doesn’t match the narrative they want to push of outrage. It only mentions it in passing and of you don’t already know how these things work you’re still none the wiser.

      Never stop being the guardian, never stop. 😂🤣😂.

      • HeartyBeast@kbin.social
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        11 months ago

        It looks like the Guardian is basing this off reports from Dispatches and The Times and iy seems that it’s really mot quite clear how it works. Here’s the de-paywalled Times report: https://archive.is/s5eDe

        … a “clean room” can match specific shoppers, or small groups of shoppers, with specific television viewers and work out when they are likely to be the same person.

        Few experts are willing to reveal the exact science, but the software can make a remarkably accurate match. This is because supermarket shoppers reveal so much about their income, lifestyle, location and family set-up from what they put in their baskets — and because television viewers expose so much about their habits, income and location from what they watch.

        For example, the experts will know when someone has stopped watching I’m a Celebrity, but still watches Coronation Street, and where they log on to watch it. “With data matching, they tend to use ‘lookalike data’ — this person [on a supermarket database] looks very much like the same person [on a broadcaster’s database],” explains Duff.

        They can also add in third party databases, such as Facebook, and the matching is uncannily accurate, as well as being privacy compliant, according to experts.

        • mannycalavera@feddit.uk
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          11 months ago

          You absolutely can anonymise data.

          However it’s also true that of you don’t do it correctly users can be identified. Sounds like Netflix didn’t do it properly. I don’t know, do you have a link I could look at?

          • Primarily0617@kbin.social
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            11 months ago

            anonymising data is a treadmill problem

            what might work now won’t hold up to the de-anonymising techniques of a few years from now

            so no, you can’t really

            • mannycalavera@feddit.uk
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              11 months ago

              Create anonymous UUID, store interactions against this in a separate table, ensure PII is removed prior to storing. So instead of Max Reboo has purchased a subscription to jugs and hooters it’s user 12345678901234576 has purchased jugs and hooters. How can a future treadmill de-anonymise this? For sure if the storage is done badly then you can track back to a particular user.

              Also, once again, can you link to the netflix issue you quoted above please. Thanks.

              • Primarily0617@kbin.social
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                11 months ago

                Create anonymous UUID, store interactions against this in a separate table, ensure PII is removed prior to storing

                which is more or less exactly what netflix did -> the whole thing’s not that hard to find on google

                but you need something to distinguish users at least a bit or the data’s equivalent to sales figures

                you combine that “not-quite-pii” with other independent data sources that have similar “not-quite-pii” and build a complete picture

                the treadmill effect comes from active research in this exact area trying to de-anonymise data sets finding new techniques to get around old ones