David Cameron wants social media companies to invent a terrorism-detection algorithm and send all the "bad guys" it detects to the police -- but this will fall prey to the well-known (to statisticians) "paradox of the false positive," producing tens of thousands of false leads that will drown the cops.
And that's just the tip of the iceberg -- the problems implicit in using Kafkaesque algorithms to determine guilt are myriad (and well-explained in this Guardian piece by James Ball).
Data strategist Duncan Ross set out what would happen if someone could create an algorithm that correctly identified a terrorist from their communications 99.9% of the time – far, far more accurate than any real algorithm – with the assumption that there were 100 terrorists in the UK.
The algorithm would correctly identify the 100 terrorists. But it would also misidentify 0.1% of the UK’s non-terrorists as terrorists: that’s a further 60,000 people, leaving the authorities with a still-huge problem on their hands. Given that Facebook is not merely dealing with the UK’s 60 million population, but rather a billion users sending 1.4bn messages, that’s an Everest-sized haystack for security services to trawl.
'You're the bomb!' Are you at risk from the anti-terrorism algorithms? [James Ball/The Guardian]
(Image: Haystacks, John Pavelka, CC-BY)
There are plugins and obscure settings that will get this behavior, but, as the saying goes, "defaults matter": Firefox 66 will not play any audio or video until "a web page has had user interaction to initiate the audio." (via Four Short Links)
Johannes Grenzfurthner writes, "My film 'Glossary of Broken Dreams' (which is getting more and more relevant, given all the political turmoil currently around) (previously) is finally available on Vimeo on Demand (buying and renting).
Scott Alexander continues to delight with his works of short, sharp science fiction (previously): this time, it's "Sort by Controversial," a teachnolovecraftian story of training a machine learning system to recognize (and then produce) "controversial" stories by exploiting Reddit's "sort by controversial" feature to obtain training data.
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