3 ms·
Interesting paper, thanks! See how you sway the argument in your favour using words with negative connotations like "fairness through blindness" and "hurt mean
by igravious 10y ago
Interesting paper, thanks!
See how you sway the argument in your favour using words with negative connotations like "fairness through blindness" and "hurt meaning and accuracy". Nobody would want to deliberately blind or hurt something, would they? How about rebalance or recalibrate or re-correct.
A concrete analogy:
1) I have a meter measuring stick but I discover that it was made wrong, it is actually 2mm shorter than advertised. Every time I make a measurement with it I have to add 2mm to the measurement. Would it not be better to use a more accurate stick and not have to continually compensate?
- im4w1l 10y agoStereotypes have great predictive power. The reason we sometimes avoid them is they can lead to outcomes that are seen as undesirable.
- pixl97 10y agoWith your analogy that would assume we know exactly how long a meter is. "We know that we are wrong, but we don't know the exact right answer". Also language shifts and biases are not constants. Oh, then you have the issue of a corpus attempting to manipulate the learning algorithm itself.