If you fill out the "Forgot Password" form but don't get an email to reset your password within 5-10 minutes, please email logistics@ire.org for assistance.
$0.00
We need data on public institutions so that we can keep them accountable. But when that data is collected and shared by the institution itself, they are in a powerful position to control the narrative. What can we as data practitioners do to help identify potentially biased narratives that could exist in this type of data? Because blindly trusting a biased dataset is just as harmful as blindly trusting a biased source. We would like to talk a little about a vetting process, and about a few important types of biases in data that you should have in mind. This list is by no means complete and is still a work in progress, but it includes some of the more major types of bias that we’ve noticed in data, and what we think you can do about them.
Looks like you haven't made a choice yet.