And since we're on the car insurance subject, minorities pay morefor car insurance than white people in similarly risky neighborhoods. If we don't put in place reliable, actionable, and accessible solutions to approach bias in data science, these type of usually unintentional discrimination will become more and more normal, opposing a society and institutions that on the human side are trying their best to evolve past bias, and move forward in history as a global community. Last but definitely not least, there's a specific bias and discrimination section, preventing organizations from using data which might promote bias such as race, gender, religious or political beliefs, health status, and more, to make automated decisions (except some verified exceptions). It's time to make that training broader, and teach all people involved about the ways their decisions while building tools may affect minorities, and accompany that with the relevant technical knowledge to prevent it from happening.
Aug-29-2017, 15:00:07 GMT