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You're right within the boundaries of what you're considering, meaning testing the profitability of marginal borrowers, etc. But you're missing the big picture

by rlucas 10y ago

You're right within the boundaries of what you're considering, meaning testing the profitability of marginal borrowers, etc. But you're missing the big picture question about the use of ML in making political decisions (and yes, the question of who gets mortgages is very much a political one). For example, in the earliest days of the creation of the US national mortgage market, conforming to FHA standards meant following more or less explicit racial guidelines (not to mention car-promoting platting and urban planning guidelines). That amounted to a political decision to reward people who invested (and/or resided) in white suburbia with greater liquidity and hence price appreciation. Focusing on the marginal profitability of individual loans ignore the bigger issue, which is that choosing the rules often encodes a much larger set of political preferences or goals. Then, the critique of using opaque algos is, for me, less that they hide the use of some verboten input variable like race or sex, but that by focusing on the algos we ignore the bigger question. (it's a subclass of what I call the scalar fallacy, where any real world outcome being reduced to a scalar always collapses a multidimensional space into a single dimension, and that projection contains a huge set of silent preferences)

yummyfajitas 10y ago
I'm aware that political processes surrounding loans were racially biased. That's not evidence that a profit maximizing algorithm will be. That's really just a claim that "this was once politicized, therefore it must remain political forever". The whole benefit of using algorithms is that you make your goals explicit and non-opaque; you just look at the objective function. Opacity of the models isn't really a big deal - machine learning is fundamentally the mathematics of studying opaque models. It's the objective function that should be transparent. If the objective function says "minimize defaults", that's your explicit goal. If the objective function says "maximize # of blacks getting loans", that's what you'll do. But it will do one or the other, unless you explicitly set your objective function to a x "minimize defaults" + b x "maximize blacks". The tricky bit is that by doing this, we are explicitly and verifiably lowering the bar. Just witness how much flak people get for discussing this: https://techcrunch.com/2015/11/03/twitter-engineering-manager-leslie-miley-leaves-company-because-of-diversity-issues/ https://techcrunch.com/2015/11/03/twitter-engineering-manage... But unfortunately, an optimization system won't give you what you want unless you explicitly put what you want in the objective function, something our modern activists (probably including Cathy O'Neil) refuse to do.

by rlucas 10y ago

yummyfajitas 10y ago

I'm aware that political processes surrounding loans were racially biased. That's not evidence that a profit maximizing algorithm will be. That's really just a claim that "this was once politicized, therefore it must remain political forever". The whole benefit of using algorithms is that you make your goals explicit and non-opaque; you just look at the objective function. Opacity of the models isn't really a big deal - machine learning is fundamentally the mathematics of studying opaque models. It's the objective function that should be transparent. If the objective function says "minimize defaults", that's your explicit goal. If the objective function says "maximize # of blacks getting loans", that's what you'll do. But it will do one or the other, unless you explicitly set your objective function to a x "minimize defaults" + b x "maximize blacks". The tricky bit is that by doing this, we are explicitly and verifiably lowering the bar. Just witness how much flak people get for discussing this: https://techcrunch.com/2015/11/03/twitter-engineering-manager-leslie-miley-leaves-company-because-of-diversity-issues/ https://techcrunch.com/2015/11/03/twitter-engineering-manage... But unfortunately, an optimization system won't give you what you want unless you explicitly put what you want in the objective function, something our modern activists (probably including Cathy O'Neil) refuse to do.