Wow. Bit of context missing in the feature set...
An example of algorithmic bias leading to negative consequences: drivers are being steered to "open" routes - open because the neighborhoods are on fire.https://twitter.com/joelrubin/status/938574971852304384 …
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Nice way of putting it.
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It's not so much about "bias" but about a bad operations management in the product. This sort of thing can not be handled by ML, it should be communicated to the operators of the nav app by the police, who should block the roads.
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Neither Caltrans nor CA municipalities have much of a record in providing machine-readable feeds of road closures 1/2
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Could also be handled by measuring uncertainty in estimates of travel time to areas with abnormally low traffic
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It also doesn't help that they're randomly and capriciously closing routes without notification and/or updating those apps with the realtime closures.http://boffosocko.com/2017/12/06/mismanaged-road-closures-on-210-freeway-for-the-creek-fire-and-others/ …
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Please explain how this is an issue of bias as opposed to a bug resp. lack of data?
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I have conflicting views about this.
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Example of Algorithms devoid of feelings resulting in utter disregard for people safety
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Interesting case, thanks! I feel it is an example of the inherent limitations of algorithmic models rather than algorithmic bias.
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