Here’s a misery-filled dynamic that I believe commonly plays out regarding small observed differences between groups:
(1) Two groups have a small (but meaningful) difference in their average value of some trait, with heavily overlapping distributions.
(2) Some people (“Oversimplifiers”) observe this difference (in their everyday life or media reports) and turn this small average difference into a (sometimes very harmful) oversimplification: “A’s are like this, B’s are like that.”
(3) Other people (“Difference Deniers”), usually acting with good intentions, criticize this oversimplification, which they correctly perceive as harmful. But instead of saying some combination of:
- “the difference in averages is small”
- “the distributions are heavily overlapping”
- “judging an individual based on a small difference in group averages is a poor way to make predictions, as well as unjust”
- “we shouldn’t judge people for differing on that trait” (if it’s not a trait one should be judged on)
- “if we want to remove the difference in averages, we should consider implementing policy XYZ”
they say “the difference in averages does not exist.” After denying the difference and seeing those they respect deny it, some of them become convinced anyone who believes in the existence of this (actually existing) small average difference is nefarious (and lump such people in with those who harmfully oversimplify people into “A’s are like this, B’s are like that.”) Others among them know the average difference exists but pretend not to because they want to fit into the group that adamantly denies the difference, or because they feel guilty about believing it (even though they are right about it existing).
(4) Oversimiplifiers from (2), who remain totally convinced an average difference exists (and are correct about its existence but exaggerate its magnitude), assume that the Difference Deniers from (3) must be either stupid (for not realizing there is a difference), or untrustworthy liars (for denying what they must see is true), or cruel lunatics (for getting enraged at people for believing in “the truth”).
Queue endless fights between the Oversimplifiers and the Difference Deniers, both of which are misrepresenting the actual reality of the situation, and demonizing each other.
The problem with turning small averages into “A’s are like this, B’s are like that” is that it is an inaccurate oversimplification and often unfair to A’s or B’s or both.
The problem with denying the existence of average differences that, while small, really do exist is that you end up believing falsehoods, or you end up lying, or both, and you may end up unfairly misjudging people who are (without malice) reporting on real average differences.
To avoid the weaknesses of both the Oversimplifiers and the Difference Deniers, I think the best way to handle these cases is to:
1) Avoid pre-judging people based on their membership in broad groups – learn about people as individuals before coming to judgments about them.
2) Avoid language like “A’s are like this, B’s are like that” so that you aren’t an Oversimplifier.
3) Avoid denying that an average difference exists when it really does exist, so that way, you aren’t a Difference Denier.
4) When relevant, remind people that small average differences are not a good basis for judging individuals (epistemically and morally), and point out that the distributions between the two groups are heavily overlapping (when they are) to combat people using differences in the average as a justification for stereotyping.
5) Point to (when relevant, helpful, and accurate) policies that may help close the gap between the two groups (keeping in mind that some gaps in averages are fine if the trait in question is merely a difference and not something “good” or “bad”)
6) Point out (when the difference in question is not something people should be judged for) that this attribute should not be a basis for judging people, i.e., that having different values of that trait is completely okay.
Another approach that can be taken when the group differences in the average are small but meaningful is well described by Guy Srinivasan in the comments on an earlier draft of this post: “Can we agree to make decisions as if there were no average difference, since usually all such decisions would turn out the same, and usually when they wouldn’t it’s perpetuating systemic problems to make the decision differently?”
Of course, as with any binary categories, some people will only be partial Difference Deniers or Oversimplifiers – people are absurdly complex, and this model I present here is purposely simplified in order to help communicate this dynamic clearly.
Okay, but are there cases where the Oversimplifiers or Difference Deniers are actually just right?
Absolutely, there are some.
When a group difference is SO huge that the distributions are nearly non-overlapping, then it’s reasonable to say, “A’s are like this, and B’s are like that.” For instance, it makes sense to say that “blue whales are big, mice are small.” In such cases, the Oversimplifiers aren’t really oversimplifying. But when we’re talking about human groups, this kind of situation is very rare.
And in situations when the difference in averages between groups is so small as to be essentially insignificant for all purposes, the Difference Deniers aren’t actually denying reality. For instance, if it turns out that right-handed people are 0.001% better at school than left-handed people, that difference is so small as to not be meaningfully different from zero for all purposes, and so saying there is “no difference” is an extremely reasonable thing to do. There are, in fact, many attributes along which human groups differ so little that “no difference” is an accurate way to describe it (even though the difference is not literally zero to the 10th decimal point).
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