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A Bloom Filter For Truth


In computer science, a Bloom filter is a technique to quickly check “do I probably have X in some set of things?”. It is a really fast technique, and that speed comes at the cost of allowing false positives. But what makes it so useful is that false negatives are not possible.

If that doesn’t make sense, don’t worry. Here is an example: imagine you own a zoo and you have a Bloom filter of all the animals at your zoo. If someone asks, “do you have a Siberian tiger?” the Bloom filter could be like “no, we definitely don’t have a Siberian tiger.” And if someone asks, “do you have a Ruddy duck?” the Bloom filter could be like, “I know we have ducks, but I am not sure if we specifically have a Ruddy duck or not.” The Bloom filter will never answer “we definitely have X.” You have to check somewhere else to know that your zoo definitely has X. Got it?

In my 2020 crash course into learning about things falling under the sphere of political discussion, I’m less interested in ideologies (“this one simple trick for viewing the world will help in all situations” 😉 ). I’m also less interested in tribal affiliations. What I really seek to develop is a Bloom filter for the truth.

Example: I was slightly ahead of the curve on reading up on Covid at the beginning of the year. So when someone made claim Z, it was easy for me to be like: I don’t know if fact Z is true or not, but if it is true, it contradicts previously “known” facts X and Y. All three can’t be true at once. Please explain the discrepancy.

/shower thoughts