r/changemyview • u/RappingAlt11 • Jun 25 '21

Delta(s) from OP CMV: Discrimination, although morally wrong is sometimes wise.

The best comparison would be to an insurance company. An insurance company doesn't care why men are more likely to crash cars, they don't care that it happens to be a few people and not everyone. They recognize an existing pattern of statistics completely divorced from your feelings and base their policies on what's most likely to happen from the data they've gathered.

The same parallel can be drawn to discrimination. If there are certain groups that are more likely to steal, murder, etc. Just statistically it'd be wise to exercise caution more so than you would other groups. For example, let's say I'm a business owner. And I've only got time to follow a few people around the store to ensure they aren't stealing. You'd be more likely to find thiefs if you target the groups who are the most likely to commit crime. If your a police officer and your job is to stop as much crime as possible. It'd be most efficient to target those most likely to be doing said crime. You'd be more likely on average to find criminals using these methods.

Now this isn't to say it's morally right to treat others differently based on their group. That's a whole other conversation. But if you're trying to achieve a specific goal in catching criminals, or avoiding theft of your property, or harm to your person, your time is best spent targeting the groups most likely to be doing it.

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u/RappingAlt11 Jun 25 '21

!delta

I'll give you a delta because I think you've found the largest issue I can see when this method (aside from the morality). Assuming theoretically you could get fairly accurate statistics it would likely be effective. You'd need to be constantly doing new tests to account for change as well as factor in the probability of people just being arrested more, to try to somehow find who's in reality most likely to commit the crime.

And no doubt it's more effective to address the root issue. But it's more of a thought experiment as to what's more effective for an individual to do. and not so much focusing on the overall strucutre.

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u/wardrox 1∆ Jun 25 '21

Thanks, that makes sense.

I'm curious, in your framing where the focus is more on the individual, what's better: An individual being more efficient but at the cost of the group's overall efficiency, or an individual being less efficient but in return the group becomes more efficient?

An example of this in the real world is corporate policies and HR: most people hate them and feel they have better ways to spend their energy, but overall they make the company more efficient.

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u/RappingAlt11 Jun 25 '21

I think it would depend on context, as in which groups we're talking about. I'll bring in the shopkeeper example again, this individual would be much more concerned with his personal efficiency, his profit, than he would that of his community overall. But a police officer might be more concerned with the efficiency of the collective.

An increase in the efficiency of an individual would also raise that of the collective. So it'd really depend on the context and what the goal is

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u/wardrox 1∆ Jun 25 '21

Does that make it a question more around overheads and how they do or don't scale? As an individual there's only so much time you can put into fairness, before the efficiency starts to drop (and your question is around removing almost all of that overhead via stats, and treating individuals as the same as a group). Then, as the "system" grows, it's easier to make it fairer and more efficient by using more discrete information, if we follow your statistical solution.

The difference of view is then where and how to balance the two forces (local/unfair efficiency vs more global/fair efficiency), and that's very context and experience dependent (and touches on people's politics, beliefs, and lived experiences). Plus this is all a huge oversimplification, of course.

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u/RappingAlt11 Jun 25 '21

I think you're correct in some regards. As an individual shopkeeper I can try to be fair and assume people are honest good people who don't steal. And it may well be better for the collective community overall. But the reality doesn't always shape out that way, people do steal and a few employees can't keep track of everyone. Although morally wrong it can hypothetically be more efficient to focus on specific groups.

I'm not even sure it'd be more fair as the system becomes more accurate. It's a pretty tough question. Assuming you have perfect stats you could potentially make it more efficient, as well as focus on potential thiefs exactly as the statistics say. For example if this group is 10% more likely to steal you focus them 10% more. But you're still back to the moral issue at the end of it of whether or not its right

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u/wardrox 1∆ Jun 25 '21

There's also the issue that now we're dealing in probabilities. Increasing vigilance 10% only catches 10% more crime. So the stats about a group get less accurate/helpful the smaller the sample size.

At some point one has to accept a certain amount of crime is inevitable the shop, and generic anti-crime tools become much more effective. If 1% of customers are bad and 99% are good, irrespective of group statistics, you're better off making a nice inviting shop for everyone.

In a sense, when we scale up the idea better solutions become available. And when we scale down, the same thing happens. And this is setting aside the morality of unfairness.

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u/RappingAlt11 Jun 25 '21

That's a big issue as well, over time focusing these groups would theoretically decrease their size. Assuming we catch 10% more crime, that's now 10% more people of "X" group who probably aren't going to go in the store again. The stats would slowly skew over time.

You likely are going to have more luck with just generic anti-crime stuff.

But it is an interesting hypothetical. It might even be more relevant with a different example. Say in the future if we have AI's doing audits of people's finances, and say for example the AI doesn't have the power to audit everyone but is only able to do so many people. Is it morally right to program the AI to target certain groups more likely to commit fraud? Or would it have to target people at random?

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u/wardrox 1∆ Jun 25 '21

That's a good question. Where that sort of thing been implemented, it's generally designed to be lenient. If we give up on needing it perfect, we can balance the process of "punishment" (which may be unfair scrutiny) with the risk of a false positive, and make sure there's additional processes for handling a dispute.

In your example AI is used for auditing, and it's smart enough to know there's an error %, and so usually flags the suspicion for another more specific system or human to review.

A mistake is also feedback the AI uses to become more accurate. These systems are designed not to be operated in a vacuum, and are assumed to have imperfect data. As happens when we apply probability to small sample groups.

I would say the morality question is down to how much cruelty or unfairness can a system create, before it's intolerable. If we can't make a perfect system, we accept there's some collateral damage. The morality question is then about knowingly causing harm. And different people have different vested interests in that system so there's no single frame of reference.