Google Research Promotes Equality In Machine Learning, Doesn't Mention Age

An anonymous reader writes: New research from Google Brain examines the problem of 'prejudice by inference' in supervised learning -- the syndrome by which 'fairness through unawareness' can fail; for example, when the information that a loan applicant is female is not included in the data set, but gender can be inferred from other data factors which are included, such as whether the applicant is a single parent. Since 82% of single parents are female, there is a high probability that the applicant is female. The proposed framework shifts the cost of poor predictions to the decision-maker, who is responsible for investing in the accuracy of their prediction systems. Though Google Brain's proposals aim to reduce or eliminate inadvertent prejudice on the basis of race, religion or gender, it is interesting to note that it makes no mention of age prejudice -- currently a subject of some interest to Google.

Comments

Why have AI at all?

[Merk42]

The only "solution" will be if every living thing has the same result, so just ignore all values and hardcode the one output.

Re:affirmative action

[kosh271]

I have no problems if the scales are tipped, just so long as they are in my favor.

If you want to be fair, instead of "order by score, race", you should "order by score, random". Ordering by race is racism plain and simple. Why not sort by shoe size? The answer is simple: shoe size (for most jobs) does not apply when analyzing for job qualifications. Your job qualifications are (mostly) not dependent on the color of your skin (with exceptions such as actors).

To help those out with a lack of understanding - Racisim(2): racial prejudice or discrimination.