Machine-learning algorithms are complex mathematical formulae that carry out their human-written code. But to the militant liberal mind, algorithms are potentially iniquitous and must be “cleaned up” to favour particular groups. In The Spectator USA, Pedro Domingos argues that the “debiasing” of algorithms makes machine learning and all its benefits impossible.

Keeping the AI Apocalypse at Bay
Writing in City Journal, Judge Glock examines legal efforts to control AI and dismisses the current fixation on suing for specific harms, such as bad advice. “The idea that we should treat Big Tech, including AI companies, like we treated Big Tobacco, is exactly the wrong idea,” he observes. A better approach is to assess product liability based on which parties can perform the task at the cheapest cost, as is the case with the regulation of medical equipment. This “has the benefit of putting the onus on companies themselves to game out dangerous scenarios and prevent them,” he advises. For more on AI, see this C2C article.


