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>"After all, there's no reason for accounts in good standing to lie, right?" No reason is different from no good reason. Also, 99.99% only seems like a high nu
by YossarianFrPrez 5y ago
>"After all, there's no reason for accounts in good standing to lie, right?" No reason is different from no good reason.
Also, 99.99% only seems like a high number when we think anecdotally, not statistically. For anything at Facebook's scale, the number of nines should be increased! Because .01% of the actions of three billion people on a single day gives you a city roughly the size of Tampa, Florida (~300,000 people).
Given Facebook's financial resources, it should be no problem to increase the size of the team working on the tool. Like any engineering problem, the problem can be broken down into smaller parts, the edge cases can be caught and/or anticipated, creative solutions can be applied, etc.
If history teaches us anything, it's that all public facing systems will be exploited. Those who design them should anticipate this.
(Thanks, by the way, for posting about your perspective. It looks very different to those of us on the outside.)
- nindalf 5y ago> Given Facebook's financial resources, it should be no problem to increase the size of the team working on the tool. Like any engineering problem, the problem can be broken down into smaller parts And I worked for 4 years on one such small part (internally called UFAC), trying to help potential false positives of such a system. As for classifier with a true positive rate of 99.99999%, I don't know much but I don't think it's possible. But if there's someone out there who might know, then they should say so.
- YossarianFrPrez 5y agoNo classification system can be perfect; we are in agreement there. From the outside, it doesn't seem like a strictly data science problem. Instead, it seems like a design / product / brand expectation issue as well.