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Unfortunately, once you place the imprimatur of machine learning upon it, people will tend to conflate "perceived safety" with "actual safety." At the extreme,
by HillRat 12y ago
Unfortunately, once you place the imprimatur of machine learning upon it, people will tend to conflate "perceived safety" with "actual safety." At the extreme, it becomes a way to create an apparent but false confirmation of the prejudices of the crowd.
This is one of those rare cases in computer science research where there is an actual ethical component to the work being done; while machine scoring landscapes according to their relative attractiveness is fairly harmless, scoring them according to "perceived safety" without mentioning the obvious limitations thereof is heading towards trouble. As I recall, there was a crowdsourced app last year that supposedly would inform its users if they were in "bad" neighborhoods (using the opinions of other users to tag areas), and it received a wave of criticism for essentially similar reasons.
- duderific 12y agoIf it was crowdsourced, why would you need an app to know if you were in a bad neighborhood? Your perception should be roughly similar to those who had contributed their opinions as crowd source data. Kind of like needing an app to tell you it's raining when you're standing in a downpour.
- notahacker 12y agoThe act of using the app can increase that perception though; if you get mugged whilst checking your smartphone in the middle of the street it's a pretty good indicator the area isn't safe :-)