81–90 of 165 posts
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You are completely missing the point and just making up assumptions to argue, stop
I wasn't arguing with or misunderstanding the point being made. I was just disputing that DDG usage would be positively related to credit unworthiness. I admit that it was pedantic.
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I think the key is "feedback loops". We're not failing to price in inherent differences, out of some moral ideal - we're trying to fix a larger inefficiency, which is that some groups of people are unable to reach their full potential. It's not a cost - it's an investment . It's regulation to fix a negative externality. [digression into risky territory, here be dragons] ...at least, that's the idea if you believe tha…
Doesn't need to be inherent to "races". Why wouldn't culture / way of living be the elephant in the room?
But then on the flip side, if you look at say, athletic selection for a sport like basketball or athletics, you'd find that race is inherently a criteria, because certain races seems to have an inherent advantage (or more correctly, certain races seems to have a _disadvantage). But nobody ever says anything in those cases.
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You are completely missing the point and just making up assumptions to argue, stop
I wasn't arguing with or misunderstanding the point being made. I was just disputing that DDG usage would be positively related to credit unworthiness. I admit that it was pedantic.
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Doesn't need to be inherent to "races". Why wouldn't culture / way of living be the elephant in the room?
well, you could change your culture/way of living. But you can't change your race. If it turned out that race is indeed a component, with proven confidence and evidence, that indicates financial stability or security, then being the wrong race will cause problems for you. But then on the flip side, if you look at say, athletic selection for a sport like basketball or athletics, you'd find that race is inherently a cr…
I think a charitable explanation for why this is, is sports is pretty much always a voluntary activity, so it's natural to not get as worked up over either implicitly or explicitly favoring a race, compared to, say, doing the same thing in employment or scoring someone's credit, which will almost certainly impact everyone in society involuntarily.
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The point is that these algorythms do study your behaviour and correlate it with the behaviour of others. These predictions don't have to be 100% accurate to be useful. What's wrong with 70% of tall people benefiting from being associated with the other 30%? This only lasts until someone figures out how they are different and breaks the association right?
> This only lasts until someone figures out how they are different and breaks the association right? Would you be OK if banks started charging you 4% more interest because say you have irish heritage? Your behaviour hasn't changed and nobody can explain why it matters that your father was irish, but the models determined it's statistically significant, What if at some point 30 years down the line it's determined it w…
What if, one bank started doing it because they used this model. But another bank doesn't, because they don't believe this model?
If you were an irish person, you would just move banks. And if it turns out, indeed, that the first bank was over-charging the 4% (ie., no irish person defaults due to their being irish), then they've lost business for no reason, and the 2nd bank got more business.
However, if it turns out that being irish _does_ indeed cause you to default more, then the bank charging an extra 4% was correct. The 2nd bank, upon finding proof of this, would also start charging an extra 4% (otherwise, they'd be losing out money to the first bank).
So in the end, a bank can only charge the most appropriate interest rate for the market to bear.
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It is already in motion, cryptocurrency will accept you no matter what your credit score or browsing history is. “The computer can be used as a tool to liberate and protect people, rather than to control them.” -Hal Finney
How are you planning on allocating those bitcoin distributions? Do you have the context for the Finney quote? Apparently from a set of released emails: https://news.bitcoin.com/researcher-publishes-never-before-s... The larger context, from a 1992 Cypherpunks email: "Here we are faced with the problems of loss of privacy, creeping computerization, massive databases, more centralization - and [David] Chaum offers a co…
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More accurate isn't always good because creditworthiness is all about stereotyping people. Consider this example: lesbians are statistically more likely to divorce. The ML models decides that lesbians are a higher mortgage risk and raises their interest rates. It does this indirectly by raising interest rates on married couples with different last names and owners of Subaru vehicles. In another, the model sees that p…
A lot to unpack here, let me try. Are machine learning algorythms capable of stereotyping people? How accurate does a stereotype have to be before it's a useful predictor? If these models lead to good data, then what's wrong with them? If people who follow the NBA do in fact default on their loans more, shouldn't they pay higher interest? I agree that the healthy should not be compelled to subsidize the costs of heal…
Because it makes health insurance impossible to get when you need it most. It makes health insurance a scam because any serious illness and your company will fire you and you won't be able to get any other insurance. Insurance becomes cheap because it's useless.
Wealth inequality is a problem because money = power. Extreme wealth concentration is not compatible with democracy because eventually these people and corporations are so wealthy they can just buy votes. Spiraling wealth inequality gets you a Russia situation, an Oligarchy in everything but name.
Your argument is not a far stretch from "why don't we just let poor and sick people die". It's pretty much equivalent to "why don't we allow anyone to discriminate however they want", which got us great things like slavery
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When I have this conversation with myself, here's what I come up with: Shouldn't we be allowed to everything into account when determining credit worthiness? Even if it's socially uncomfortable? We get locally more accurate pricing / risk assessment that way, but we also create feedback loops that we as a society have decided we want to not contribute to. The cost for this is the pricing inaccuracy which we collectiv…
That is a good summary. An analogy I might add that could further clarify things would be preexisting condition protections for health insurance. Preventing insurance companies from turning down people who they know will require expensive medical care is going to lead to worse pricing for the rest of us. However much of society has decided that is a cost worth enduring in the name of fairness.
It’s like applying for home fire insurance and saying you burned down your previous 3 homes and will likely burn down this one.
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I wasn't arguing with or misunderstanding the point being made. I was just disputing that DDG usage would be positively related to credit unworthiness. I admit that it was pedantic.
I think the denial to credit for DDG is less about credit worthyness and more about "deplatforming" based on personal details. Or thats what it'll become.
If you're a rich white guy, this oppression is unlikely to apply to your choices. Instead, your choices will be used as filters to identify you at the exclusion of others
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No. Credit worthiness should be because of an individuals past actions and not some attribute they may have been born with. Why should a tall individual who's never missed a payment have some invisible penalization applied because some other tall people are worse at re-paying loans. Don't you see the issue here? You're penalizing individuals not based on their own measurable behavioral signals, but simply due to some…
We must disambiguate between political objectives and the practice of credit risk modelling. Credit risk, f(X), is an unknown population function that needs to be estimated using observed data X. If including tallness into X improves our estimate of f(X), then we've gotten a better model. You've asserted that X should only contain an individual's past actions instead of their inherent traits such as tallness. This ma…
Consider a sample size of 10/1million with height value of 7m. And somehow 7/10 had poor ability to repay loans. With such a small sample size of this relevant factor be a good thing to rely on?