Adventures in Computation explains a recent political discussion:
Algorithmic Unfairness Without Any Bias Baked In
"Discussion of (un)fairness in machine learning hit mainstream political discourse this week, when Representative Alexandria Ocasio-Cortez discussed the possibility of algorithmic bias, and was clumsily "called out" by Ryan Saavedra on twitter.
...
"Bias in the data is certainly a problem, especially when labels are gathered by human beings. But its far from being the only problem. In this post, I want to walk through a very simple example in which the algorithm designer is being entirely reasonable, there are no human beings injecting bias into the labels, and yet the resulting outcome is "unfair".
Algorithmic Unfairness Without Any Bias Baked In
"Discussion of (un)fairness in machine learning hit mainstream political discourse this week, when Representative Alexandria Ocasio-Cortez discussed the possibility of algorithmic bias, and was clumsily "called out" by Ryan Saavedra on twitter.
...
"Bias in the data is certainly a problem, especially when labels are gathered by human beings. But its far from being the only problem. In this post, I want to walk through a very simple example in which the algorithm designer is being entirely reasonable, there are no human beings injecting bias into the labels, and yet the resulting outcome is "unfair".
Posts
No comments:
Post a Comment