BIAS DETECTION

In the digital world, bias in diversity, equity, and inclusion (DEI)-related topics is increasingly influencing people’s thoughts and behaviors.  While extensive research has been conducted on DEI in recent years, there has been relatively little focus on Generation Z (Gen-Z) and the unique DEI challenges they face in an online landscape.

In the past few years, there has been an exponential increase in online bias as many websites and social media platforms have required users to reveal their identities.

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For example, a 2017 study revealed that 59% of Black internet users and 48% of Hispanic users experienced some type of online bias, compared to 41% of White users (Duggan, 2017). Online bias can also come in more user-implicit forms, such as algorithmic bias, which continues to plague prominent tech companies. For example, when searching for “black-sounding” names on Google, profiles with arrest records were more likely to show up, even if fake (Lee, 2016).

 

 

 

Our research aim was to examine the risk of bias in DEI through the eyes of Gen-Z and provide AI-based solutions for detecting gender, race, and income biases. We decided to focus on gender, race, and income for two reasons; first, these are three pivotal aspects of an individual’s identity, and second, there continues to be much prejudice and discrimination in these three categories.