Mathmetician Eugenia Cheng has written an opinion piece for the NY Times in which she relates her own conversion story. She went from believing in merit as a fair system in work and academia to believing in the benefits of DEI. Her article making the case for DEI is carefully written to be as idealized and unobjectionable as possible but there are obvious holes in it which would never fly in solving a math problem.
As a woman in the male-dominated field of mathematics, I once opposed targeted efforts to help women succeed — what we now call diversity, equity and inclusion initiatives, which are currently facing fierce backlash. I wanted to be judged on the merit of my mathematics alone.
When I was admitted to the University of Cambridge as an undergraduate in math in 1994, I felt that I was a part of a clear minority. I struggled to keep up with some of the men in my class, many of whom had gone to elite boys’ schools where they had intense preparation. Yet I would progress to a Ph.D. and a career as a research mathematician.
As my career has advanced, what I’ve learned is that D.E.I. initiatives helped others see value in my abilities and experience that would have been missed otherwise. And it was through the lens of math that I came to understand this.
In 1994 she struggled to keep up with the boys “many of whom had gone to elite boys’ schools where they had intense preparation.” The way she’s written this is clearly meant to imply she was being judged unfairly because she hadn’t had the same rigorous preparation and therefore there was a clear reason she wasn’t keeping up with the boys.
But even if that’s true it doesn’t change the fact that, in 1994, they were better at math than she was. They had worked harder and longer than she had at that point in time. The relevant question here is one about how to allocate scarce resources. Specifically, we need to ask if one of those boys who had worked hard and gotten the best education to make them better at math should be asked to step aside and lose out on a chance to attend Cambridge so that someone like Cheng, who hadn’t worked as hard (at that point in time) could maybe catch up later?
Cheng’s answer to that question seems to be yes because, in her case, she went on to get a Ph.D. and become a research mathematician. But that’s an anecdote, not a representative sample of the group she represents in this situation. How many girls who couldn’t keep up with the boys in math went on to become research mathematicians? Did it work out for all of them? For 25% of them? How did their outcomes compare to the boys who were already working at a higher level when entering Cambridge?
Does DEI always work out or does it put some people in an untenable situation? In other words, how often does this gamble on someone who can’t (by her own admission) do math as well as the best students, pan out. How often instead does the student who is behind when entering college stay behind and give up on math? Or simply fail out? If you only look from the perspective of one success, you have no way to know if this is a good way to distribute resources. It’s a good story, but not necessarily a good plan for everyone involved. To answer my own question: It would not be fair to take a spot away from someone who has demonstrated the ability to do the harder work and replace them with someone who hasn’t, especially if you know in advance that this trade often won’t work out well.
Eugenia Cheng needs to show her work and she hasn’t here. Instead she turns to “metric spaces” which is just a dressed up version of a very old (and tired) DEI argument.
A metric is a way of measuring the distance between two points but not necessarily physical distance; it could be how much time it takes with traffic as a factor or how much energy will be expended, depending on whether you’re going uphill or downhill. A distance cannot be measured based on the position of a single point. It requires the effort of measuring the distance between two points. This may sound redundant, but it’s an important clarification: Metrics can be measured only by taking into account the starting point and ending point, as well as relevant features of the journey — the whole story…
If we are selecting sprinters for a track team, we might look at their best times for the 100-meter dash. But if someone had, for some reason, only ever run races uphill or against the wind, it would make sense to take that into account and not compare that runner’s times to others’ directly. We would be treating those people differently but only because their paths were different; really we’d be evaluating their paths fairly relative to their contexts.
She’s saying this:
What’s noxious here isn’t just the idea that some runners have it tougher than others. That’s undoubtedly true. It’s the idea that you can summarize those differences by looking at skin color which is certainly false.
The examples Cheng offers as analogies are dumb though. Is there a runner who has only ever run the 100-meter dash uphill? There is not. Is there one who has only run into the wind? There is not. Is there a runner who had to leap over a pool of sharks in the middle of the track (as seen in the silly video)? There is not.
If your analogy has to start with a fantasy of things that never really happen in real life, it’s probably not a very good analogy. What does actually happen? Some runners might have blisters. Some runners might be getting over a cold. Some runners may have stayed up too late or not eaten well the day before. There are all sorts of things that could happen to anyone and sometimes they do. All runners have to deal with these things by making choices prior to the race. And yet, when runners get to the finish line of a race, whether that’s in high school or college or at the Olympics, we only care about who ran the fastest race. We don’t have a special category for runners having an off day.
Let me interrupt this spiel with a true story. My son happens to be a pretty good high school runner. He started running varsity races his freshman year. His team was invited to an invitational race in northern California about 6 hours away. This meant leaving school early on a Friday and taking a school van on the long drive north and then staying at a hotel for the night so they could be up for the race early the next morning.
For reasons I won’t get into, they wound up in a not great motel in a not great part of town and a literal motorcycle club was staying there. This was not a friendly group. The MC guys stayed up all night in the parking lot blasting music, drinking beer, laughing loudly and breaking bottles. Someone called the police who only showed up hours later.
As a result, my son and the other boys in his room on the 2nd floor of this crappy motel got about 4 hours of sleep. As you’d imagine, they did not perform well at the race the next morning. All of them were exhausted and no one set a personal record time that day. So here’s the question. Did the kids who won the races that day really win or did they cheat?
Answer: They really won. It’s not their fault that my son and his team weren’t at their best for race time. It’s not their job to make sure kids they don’t know booked a decent hotel six months earlier instead of waiting too long and ending up in a rathole. (We personally took care of this the next year.)
Can you imagine having some DEI investigator at the race that morning who tries to balance all of this out? If the boys from Orange County didn’t get much sleep the night before, one winning slot at the end of the race must be reserved for team sleepy. Or maybe because they were running the same race on less sleep they get a 10 yard head start. It’s absurd and yet that’s what this DEI analogy of “metric spaces” would look like in real life. How would anyone benefit from such a system? The medals should go to the kids who could run the fastest. That’s it. That’s how races work.
Other forms of achievement are not as straightforward to measure, but the idea is analogous. If someone achieved a certain SAT score after months of tutoring and someone else earned the same score having never seen an SAT before, it would be reasonable to be more impressed with the latter result and think that the second test taker has more potential. We should think of D.E.I. efforts as the best versions of this and aim to design systems that can measure the fuller picture of someone’s professional journey, not just the current result.
Again, it all sounds very reasonable but this is carefully crafted to obscure what actually happens in the name of DEI. What actually happens, as we learned in the Harvard admissions case, is that being a black applicant to Harvard grants you about 200 points of buffer on your SAT score compared to Asian kids. So, contrary to Cheng’s example, this isn’t about kids with less training getting the same result, it’s about kids with lower scores getting a spot at Harvard ahead of an Asian kid with much higher scores because that’s considered equitable.
How insane did Harvard’s affirmative action policies get?
An African American student in the 40th percentile of their academic index is more likely to get it than an Asian student in the 100th percentile.
Black students in the 50th percentile are more likely to get in that… pic.twitter.com/9vvBuQXA24
— Greg Price (@greg_price11) June 29, 2023
The math to justify this literally does not add up. There is no way to judge if a given individual applicant was “running uphill” their entire life. Most of the black kids who get into elite schools come from relatively well off families. So how do you quantify growing up in a home with a father who is an engineer instead of a doctor. How do you calculate the metric spaces of going to a poor high school compared to going to a top prep school in New England. The answer is that you can’t possibly do it. Any number you put on this is a guess. You’re not doing math, you’re reaching for preferred demographic conclusions without any real data that can be tested or quantified.
One of the commenters, who supports Dr. Cheng’s argument, actually makes the case for my position:
DEI helps us recognize unconscious biases and give advice and support to the people who aren’t getting them organically because of their ethnicity or gender. It levels the playing field so we can focus on talent.
Unconscious biases? Level playing fields? Again, if the only way to explain your position is with reference to fantasy psychology and imaginary sporting situations, you probably don’t have a good argument. But at least some people can see through this nonsense.
Your example of selecting Sprinters to best compete in the 100 yard dash is so off mark. Today we wouldn’t select the fastest sprinters (all Male)…we would forcibly select some slower female sprinters to Diversify the track team so we could be Equitable and Inclusive. Thus, making the group less competitive against other peer teams.
DEI is a fantasy that replaces actual merit with wishful thinking and just so stories. It’s a shame that Dr. Cheng is using her position to defend this nonsense.
Join Hot Air VIP and use the promo code FIGHT to get 60% off your VIP membership!
