A statistical read about gender splits in teaching evaluations

A recent article on NYT's upshot shared a recent visualization project of teaching evaluations on "rate my professor", 14 millions of them. Reading this article after a long day in the office made me especially "emotional." It confirmed that I have not been delusional.

It suggests that people tend to think more highly of men than women in professional settings, praise men for the same things they criticize women for, and are more likely to focus on a woman’s appearance or personality and on a man’s skills and intelligence.

Actually, the study didn't find people focus on a woman's appearance as much as expected. 

The article made an important point:"The chart makes vivid unconscious biases. " The 14 millions reviewers were not posted to intentionally paint a biased picture of female professors compared with their male colleagues. The universities didn't only assign star male professors to teach alongside of mediocre female professors. Online teaching evaluations have known biases as people who feel strongly about what they have to say are more likely to post reviews. But this selection bias cannot explain away the "gender splits" observed. They are due to "unconscious biases" towards women.

What does this term, "unconscious biases", actually suggest? It suggests that if you are thinking that you are being fair to your female colleagues, female students or professors, you are probably not. If the biases were unconscious, how can we possibly assert that we do not have them? Most of those who wrote the 14 millions review must have felt they were giving fair reviews. Therefore, statistically speaking, if 14 millions intended "fair" reviews carried so much unconscious biases, we then have to act more aggressively better than just being fair to offset these unconscious biases.