That is certainly embarassing. But in the same time, I think it is a debate worth having. What corrections to the training dataset biases are acceptable.
Is it acceptable to correct the answer to the query "Eminent scientist" from 95% men, 5% woment to 50%/50% or to the current ratio of men/women in science ?
Should we correct the ratio of black to white people in answering a generic question to average across the globe or US ?
In my opinion, some corrections are worthwhile. In this case they clearly overdone it or it was a broken implementation. For sure there will be always people who are not satisfied.
But I also think that the AI services should be more open about exact guidelines they impose, so we can debate those.
In my opinion, some corrections are worthwhile. In this case they clearly overdone it or it was a broken implementation. For sure there will be always people who are not satisfied. But I also think that the AI services should be more open about exact guidelines they impose, so we can debate those.