Jobs for the girls

Peregrinus wrote: »

Which just goes to show that a "gender-blind" formula isn't necessarily truly gender-blind. What seems to be at work here is that the formula implicitly endorses the more typically male prioritisation of speed over safety, and therefore pays more money to drivers who share this priority, who are mostly men.

It's not that different from saying that an employment requirement of "must be at least 1.80 metres in height" is gender-blind. Formally it's gender-blind, but in practical operation it's anything but; it will result in an overwhelmingly male workforce.

Peregrinus wrote: »

It depends on what you mean by "gender-blind".

To go back to an earlier example, a job requirement of "must be at least 1.80m in height" is formally gender-blind, but of course will exclude far more women than men. In its impact it's not gender-neutral at all.

Suppose we adopt this requirement for, say, a retail sales assistant position. Leaving aside the question of justice/fairness to applicants, there's an issue from the employer's point of view; lots of otherwise well-qualified applicants are going to be excluded by this. And, in other respects, some of them might make better sales assistants that some of the people who meet the criterion - they might be better at communicating with customers, for example, or more creative in meeting customers needs. And this doesn't just affect the employers, of course, but also the customers.

So we should ask ourselves "Why is this requirement here? Just how important is it that the assistants should be at least 1.80m tall?" And we might find that the requirement was included, say, because of a need to reach goods stored on the top shelf. In which case we should at least consider whether a better approach - better for employers, better for customers, fairer to jobseekers - might be to drop the requirement and instead provide footstools, or rearrange the shelving. Everyone's a winner!

Right: The Uber case. According to the article, the gender disparity was the result of a number of factors:

- Experience: 77% of women quity driving for Uber within 6 months, as compared with 65% of men. Longer-serving drivers tend to earn more.

- Speed: The male drivers tend to drive faster. The algorithm rewards this.

- Pitch: The male drivers are more likely to ply for hire in areas of higher demand, and more frequent surge pricing.

OK: Without thinking too deeply about it, two things leap out. First, the higher dropout rate for female drivers is in itself concerning, no? The gig economy is supposed to be flexible, to suit those who seek control over their work /life balance, etc. It's supposed to address the problems of inflexibility and demands for a 40-hour commitment that work to women's disadvantage in more traditionally-structured employments. But that doesn't seem to be working here. Why? There have already been reports of toxic and abusive culture at Uber; are these two things connected? It certainly seems worth looking into. This doesn't necessarily suggest that the algorithm needs changing, but it does point to other action that may need to be taken.

Secondly, the algorithm rewards speed, but does it ignore the safety/punctuality bonuses that are associated with driving at lower speed? If it rewards the one but not the other, that looks skewed, and it's a skew that impacts differently on men and women. It may be there's a good reason the relative rewards attached to speed and to safety/punctuality but, given that they impact differently on different genders, this looks like indirect discrimination unless and until that reason is identified and found to be objectively justified.

So, yeah, formal gender-blindness isn't really enough to avoid either the moral or the economic problems that result from employment/payment practices that tend to disfavour one gender.