Baking Bias into Targeted Ads

Advertisements compete for people’s attention. To make ad delivery more “efficient” and “relevant”, both advertisers and media platforms want to leverage the power of data and algorithms to maximize their efficiency. While it seems reasonable to target the right people, biases and social issues are coded into this ad targeting system to classify people and decide who is eligible to see the ad. This project focuses on STEM ads. Following the principles of Data feminism by Catherine D'Ignazio and Lauren F. Klein, I analyze how the ad targeting systems reinforce power structures and oppression and also suggest potential strategies to mitigate the negative impacts these systems.

This video blog was created as part of Dr. Jada Watson's course ISI 6300 - Special Topics in Information Studies: Big Data, Culture and Society.

My name is XINLEI ZHOU and I am from China. I just finished my Master of Arts in Communication with a focus on media studies. I worked in marketing research and media agencies in China for almost six years, where I served clients in a variety of domains: alcohol, beauty & fashion, baby care, and more! I am particularly interested in how people perceive ads and how we should evaluate ad performance. In my spare time, I enjoy hiking, cycling, and cooking.