patrick.net

What do you do if decisions that used to be made by humans, with all their biases, start being made by algorithms that are mathematically incapable of bias? If you’re rational, you should celebrate. If you’re a militant liberal, you recognize this development for the mortal threat it is, and scramble to take back control. ...

Every paper describing how to speed up an algorithm, for example, now needs to have a section on the social goods and evils of this obscure technical advance. ‘Regardless of scientific quality or contribution,’ stated the call for papers, ‘a submission may be rejected for . . . including methods, applications, or data that create or reinforce unfair bias.’

This was only the latest turn of the ratchet. Previous ones have included renaming the conference to something more politically correct and requiring attendees to explicitly accept a comprehensive ‘code of conduct’ before they can register, which allows the conference to kick attendees out for posting something on social media that officials disapproved of. ...

I posted a few tweets raising questions about the latest changes — and the cancel mob descended on me. Insults, taunts, threats — you name it. You’d think that scientists would be above such behaviors, but no. ...

But machine-learning algorithms, like pretty much all algorithms you find in computer-science textbooks, are essentially just complex mathematical formulas that know nothing about race, gender or socioeconomic status. They can’t be racist or sexist any more than the formula y = a x + b can.

Daniel Kahneman’s bestselling book, Thinking, Fast and Slow, has a whole chapter on how algorithms are more objective than humans, and therefore make better decisions. To the militant liberal mind, however, they are cesspools of iniquity and must be cleaned up.

What cleaning up algorithms means, in practice, is inserting into them biases favoring specific groups, in effect reestablishing in automated form the social controls that the political left is so intent on. ‘Debiasing’, in other words, means adding bias. Not surprisingly, this causes the algorithms to perform worse at their intended function. Credit-card scoring algorithms may reject more qualified applicants in order to ensure that the same number of women and men are accepted. Parole-consultation algorithms may recommend letting more dangerous criminals go free for the sake of having a proportional number of whites and blacks released. ...

The more prominent the researcher that gets canceled, the better, because it sends the most chilling message to everyone else, particularly junior researchers. ...

Algorithms increasingly run our lives, and they can impose a militantly liberal (in reality illiberal) society by the back door. Every time you do a web search, use social media or get recommendations from Amazon or Netflix, algorithms choose what you see. Algorithms help select job candidates, voters to target in political campaigns, and even people to date. Businesses and legislators alike need to ensure that they are not tampered with. And all of us need to be aware of what is happening, so we can have a say.