Problems with algorithmic policy-making

Posted to Statistics  |  Tags: ,  |  Nathan Yau

Virginia Eubanks for Slate describes the dangers of relying too heavily on black-boxed algorithms to create and enforce policies.

Policy algorithms promise increased efficiency, consistent application of rules, timelier decisions, and improved communication. But they also raise issues of equity and fairness, challenge existing due process rules, and can threaten Americans’ well-being. Predictive policing relies on data built upon a foundation of historical racial inequities in law enforcement. Remote eligibility systems run on the questionable assumption that lacking a single document—in a process that often requires dozens of pages of supporting material—is an affirmative refusal to cooperate with the welfare determination process.

Favorites

One Dataset, Visualized 25 Ways

“Let the data speak” they say. But what happens when the data rambles on and on?

Famous Movie Quotes as Charts

In celebration of their 100-year anniversary, the American Film Institute selected the 100 most memorable quotes from American cinema, and …

Interactive: When Do Americans Leave For Work?

We don’t all start our work days at the same time, despite what morning rush hour might have you think.

Where People Run in Major Cities

There are many exercise apps that allow you to keep track of your running, riding, and other activities. Record speed, …