There is no way to read that graph, or the data behind it, that indicates things should stay the way they are.
You can say there's no way to read it as indicating things should stay the way they are. I believe azth's point is that there's no way to read it as saying anything coherent at all.
(EDIT: Typo.)
Of course, but it's a different problem with a different solution. Isn't that important to know?
If pay is heavily influenced by seniority, and a profession used to be sexist in its hiring practices but no longer is, then it follows that there'll be a significant gender pay gap until the older - mostly male - members of a profession die out.
Of course, there are many ways to read it negatively too. It's so devoid of information that it's just meaningless.
The graph alone doesn't tell us a whole lot, other than women are almost always compensated less than men. There seems to be quite a bit of variation across job functions, which might be unexpected. Understanding why that variation exists might be useful in addressing the perceived problem, and avoiding corporate policies that accidentally make things worse.
For example, if the bulk of pay gap is years of experience, it would be foolhardy to increase starting salary for women; you'd be giving equally qualified men a competitive advantage in hiring they don't need. Similarly, the situation could be understated -- if I'm reading the methodology correctly, CPS data doesn't include independent contractors, since they buy health insurance separately, I expect a number of men forgo insurance entirely and pocket the difference, a gamble few women of child bearing age dare take. Corporate policy here could try to prohibit independent contractors, but that would substantially reverse the trend. Better, IMO, would be single payer health care, or at least an end to the tax subsidy we give employer paid health care.
More dimensions will give us a more nuanced view of reality, and a better grasp on the degree to which the gap is systemic vs personal.