Ed Felten has posted an intriguing rumination on the possible failure modes of Bayesian spam-filtering -- filtering that uses word-frequency statistics to classify email as spam or ham. As Ed points out, Bayesian filters are trained by the spammers, who, by choosing the vocabulary of their messages carefully, can make messages containing certain words or phrases undeliverable on the Internet.
Now suppose a big spammer wanted to poison a particular word, so that messages containing that word would be (mis)classified as spam. The spammer could sprinkle the target word throughout the word salad in his outgoing spam messages. When users classified those messages as spam, the targeted word would develop a negative score in the users' Bayesian spam filters. Later, messages with the targeted word would likely be mistaken for spam.
This attack could even be carried out against a particular targeted user. By feeding that user a steady diet of spam (or pseudo-spam) containing the target word, a malicious person could build up a highly negative score for that word in the targeted user's filter.
I asked Amy Parness, the co-founder of Sparkle Labs, maker of fantastic educational electronics kits, to write a Medium post about gender and the business of being a maker business person. Her terrific essay calls out the problems with “pink girly engineering kits.” From Medium:
Zero UI is the new term for “invisible interfaces”—what happens in the future when all the clicking and tapping and typing is history: “If you look at the history of computing, starting with the jacquard loom in 1801, humans have always had to interact with machines in a really abstract, complex way.” [Fast Company]
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