TL;DR: Group stereotyping, when based on actual group data, is most valuable where it is most unfair and vice versa.
Group stereotyping seems like it would be most useful, and also most unfair, where one uses a proxy for a information that is difficult to obtain. It is hard to come up with an example that is not a political or identity-based mind-killer. So here’s a metaphor, with the wariness that a metaphor can mislead as much as it elucidates.
Let’s say that we are in the business of basket-weaving. It turns out that the median left-handed person makes baskets worth 5% more than than comparable baskets made by the median right-handed person. As an industry, we have no idea why, but it is demonstrably true, and significant to our business. People invent all kinds of reasons, but no research proves out any of the reasons.
A basket business can test for the value of any individual’s baskets by hiring them, having them produce baskets for a couple months, and track the sales price of their baskets. But that is a substantial investment just to get the information. The problem here is the cost of information. Group-stereotyping is the most useful when the cost of information is high. So an approach might be to prefer to hire lefties. But (unless there are asymmetries in the cost of information), it also where it is most unfair to the group member, because it is most costly to provide the information to rebut the stereotype. We end up ignoring the earnest righties who tell us for sure that they can make better baskets than the lefties we are hiring—and they might very well be correct.
It also seems to me that using group stereotypes is most justified and least unfair where there is high asymmetry in the cost of obtaining (and verifying, if needed) the information, such that the group member can provide at trivial cost the information that is highly costly for the decision-maker to get, and the situation prompts the group member to do so. For example, if our righty basket-maker had a letter from a prior employer that explained how unusually profitable the basket-maker’s baskets were, that would defeat the stereotype, because we would know to update our stereotype with individualized data that is actually probative. (An aside: in this situation, we have to avoid being distracted by things that are not probative, such as emotional appeals, irrelevant but positive information, the good looks of the applicant, and all the other things that can lead to an unreliable decision.) In our scenario, the availability of a letter of recommendation doesn’t help all the novice basket-makers who are applying for their first basket-making job, so it is not a 100% solution.
One potential solution to this problem is prices, but they have their own problems. If, on average, lefties are worth 5% more than righties in making baskets, the basket industry could adopt pay practices that are directly related to the value of the baskets produced. The problem with that is complexity. That’s a broad category, but I can’t come up with anything else that holds all the instances. Prices are not determined just by one party; they are determined largely by the market, which means that they are path-dependent, but also evolved. In our particular situation, changing compensation models can run into issues that economists study under the heading of agency or the theory of the firm—basically, the idea here is that we could have all kinds of unanticipated effects by changing how we put prices on the work of our basket-makers. Still, one could see adopting a test period where lefties got paid 5% more than righties, until the results were in. That doesn’t really change things all that much, except that it puts a limit on the period of unfairness, and puts a deadline on updating our information.
Technology is another solution to this problem. For example, one could invent the basket-value test. It’s a cheap test that is based on an academic observation of a strong correlation between your ability to identify certain visual patterns with the value of baskets produced. Presumably, if businesses are really missing the boat by failing to hire talented righties, then there is an incentive for someone to invent this technology, because it will lead businesses to use a deeper poo of labor (which presumably lowers their wage costs). What we’d really be doing is substituting one group stereotype (performance on the test) for another (handedness). That would be worth doing if the test were more specific or more precise than handedness in predicting the value of basket production.
But until that technology comes along, it does seem unfair to the specific righties to judge their productivity based strictly on membership in a group (even if for a limited period until real data arrives). If you don’t agree, steel yourself against mind-killing, then take the metaphor and map it to race and conviction rates.
TL;DR: Group stereotyping, when based on actual group data, is most valuable where it is most unfair and vice versa.
Group stereotyping seems like it would be most useful, and also most unfair, where one uses a proxy for a information that is difficult to obtain. It is hard to come up with an example that is not a political or identity-based mind-killer. So here’s a metaphor, with the wariness that a metaphor can mislead as much as it elucidates.
Let’s say that we are in the business of basket-weaving. It turns out that the median left-handed person makes baskets worth 5% more than than comparable baskets made by the median right-handed person. As an industry, we have no idea why, but it is demonstrably true, and significant to our business. People invent all kinds of reasons, but no research proves out any of the reasons.
A basket business can test for the value of any individual’s baskets by hiring them, having them produce baskets for a couple months, and track the sales price of their baskets. But that is a substantial investment just to get the information. The problem here is the cost of information. Group-stereotyping is the most useful when the cost of information is high. So an approach might be to prefer to hire lefties. But (unless there are asymmetries in the cost of information), it also where it is most unfair to the group member, because it is most costly to provide the information to rebut the stereotype. We end up ignoring the earnest righties who tell us for sure that they can make better baskets than the lefties we are hiring—and they might very well be correct.
It also seems to me that using group stereotypes is most justified and least unfair where there is high asymmetry in the cost of obtaining (and verifying, if needed) the information, such that the group member can provide at trivial cost the information that is highly costly for the decision-maker to get, and the situation prompts the group member to do so. For example, if our righty basket-maker had a letter from a prior employer that explained how unusually profitable the basket-maker’s baskets were, that would defeat the stereotype, because we would know to update our stereotype with individualized data that is actually probative. (An aside: in this situation, we have to avoid being distracted by things that are not probative, such as emotional appeals, irrelevant but positive information, the good looks of the applicant, and all the other things that can lead to an unreliable decision.) In our scenario, the availability of a letter of recommendation doesn’t help all the novice basket-makers who are applying for their first basket-making job, so it is not a 100% solution.
One potential solution to this problem is prices, but they have their own problems. If, on average, lefties are worth 5% more than righties in making baskets, the basket industry could adopt pay practices that are directly related to the value of the baskets produced. The problem with that is complexity. That’s a broad category, but I can’t come up with anything else that holds all the instances. Prices are not determined just by one party; they are determined largely by the market, which means that they are path-dependent, but also evolved. In our particular situation, changing compensation models can run into issues that economists study under the heading of agency or the theory of the firm—basically, the idea here is that we could have all kinds of unanticipated effects by changing how we put prices on the work of our basket-makers. Still, one could see adopting a test period where lefties got paid 5% more than righties, until the results were in. That doesn’t really change things all that much, except that it puts a limit on the period of unfairness, and puts a deadline on updating our information.
Technology is another solution to this problem. For example, one could invent the basket-value test. It’s a cheap test that is based on an academic observation of a strong correlation between your ability to identify certain visual patterns with the value of baskets produced. Presumably, if businesses are really missing the boat by failing to hire talented righties, then there is an incentive for someone to invent this technology, because it will lead businesses to use a deeper poo of labor (which presumably lowers their wage costs). What we’d really be doing is substituting one group stereotype (performance on the test) for another (handedness). That would be worth doing if the test were more specific or more precise than handedness in predicting the value of basket production.
But until that technology comes along, it does seem unfair to the specific righties to judge their productivity based strictly on membership in a group (even if for a limited period until real data arrives). If you don’t agree, steel yourself against mind-killing, then take the metaphor and map it to race and conviction rates.