Lyft’s algorithm is trying to block people with names like ‘Dick’ and ‘Cummings’
Besides the humor of how Lyft's filter flagged traditionally Caucasian names like "Cummings" – <i>in addition</i> to the usual issues with non-Western names, e.g. Pimpong and Poon – I'm fascinated/confused how this made it into production? The user database <i>already</i> exists and was currently being used by the live application. Before deploying this new filter onto the production database, wouldn't you do a dry run to get not <i>only</i> the count of users who will be flagged and notified, but a listing of frequently flagged names? Which you could easily manually eyeball to make sure there weren't obvious false positives?<p>With a userbase as big as Lyft's, I'm sure there were a ton of obvious true positives (anyone named "Fuck", ostensibly). I just can't believe they didn't notice a surname as relatively common as Cumming/Cummings. Yes, the apparent naivety of the regex is an issue, but this seems like a system for which a lot of testing on actual data would be easy and natural to do as part of the QA process.