4 ms·
Getting rid of algorithms means replacing them with humans. And humans are far worse. Humans are terribly biased. Racial bias isn't even anywhere near the stro
by Houshalter 9y ago
Getting rid of algorithms means replacing them with humans. And humans are far worse.
Humans are terribly biased. Racial bias isn't even anywhere near the strongest bias we have. Unattractive people get sentences twice as long as attractive people. Judges give far harsher sentences before lunch, when they are hungriest. Socially awkward people seem to be pretty strongly discriminated against. Studies have found people discriminate by politics even more than race. Job interviews have actually been shown to degrade performance over just judging resumes. Before statistics and credit ratings, getting a good loan required being an old friend of the banker.
It's not just that humans are unfair. We are objectively terrible. Very simple statistical algorithms beat human "experts" in almost every domain they get tried on. As early as the 1920s, a statistician came up with a formula that was better at predicting recidivism than a group of 3 prison psychologists.
Simple linear regression has predicted the success of medical treatments better than doctors, diagnosed psychoticism better than trained psychiatrists, predicted academic success much better than admissions officers, predicted loan risk better than bank officers, etc, etc. To say nothing of modern machine learning methods on modern computers. It's insane we allow humans to continue doing these tasks at all.
But there has been huge resistance to algorithms in every domain. From people who stand to lose their jobs and be put to shame by them of course. But also even outsiders tend to reject algorithms. And overly trust humans. Psychologists have actually studied this. They call it a bias labelled "Algorithm Aversion". http://opim.wharton.upenn.edu/risk/library/WPAF201410-AlgorthimAversion-Dietvorst-Simmons-Massey.pdf http://opim.wharton.upenn.edu/risk/library/WPAF201410-Algort... The study showed that humans were willing to forgive the mistakes of humans far more than those of algorithms, even when the algorithm made far fewer of them.
This is why they aren't everywhere already. The last thing we need is fear mongering like this. As shown, humans are far worse. If an algorithm shouldn't do it, then a human certainly should not.
A big part of the case these people make is a reference to a propublica study that found a slight bias against race in an algorithm once. Yet that study wasn't peer reviewed. The findings weren't statistically significant. https://www.chrisstucchio.com/blog/2016/propublica_is_lying.html https://www.chrisstucchio.com/blog/2016/propublica_is_lying....
Also, A.I. ‘Bias’ Doesn’t Mean What Journalists Say it Means: https://jacobitemag.com/2017/08/29/a-i-bias-doesnt-mean-what-journalists-want-you-to-think-it-means/ https://jacobitemag.com/2017/08/29/a-i-bias-doesnt-mean-what...
- quotemstr 9y agoIt depends on your objective function, doesn't it? Computer models definitely do better than humans on the ostensible objective function --- predicting recidivism --- but computer models don't have decades of exposure to subtle social cues that signal to humans that the real objective function is one subtly different from the one that a naive understanding of the system would suggest. That's really the beautiful thing about our shift toward algorithms: we'll no longer be able to rely on these subtle social pressures. If we want to optimize a specific function, we need to put that function in the open, where everyone can see it. Then, as the linked article demonstrates, we can compare the idealized and actually-desired functions and perform a real cost-benefit analysis.