Introduction
Hey everyone! My name is Akshita Khanna, and my senior project examines the demographic disparities in AI-induced job displacement.
My prior computational experience, from analyzing the All of Us Database to examine neurotrauma due to elder abuse through the University of Arizona KEYS Internship to studying the women’s lack of healthcare rights in Senegal and Colombia, ignited my passion for applying computer science to societal issues. I realized that data science is far more than just running code or statistical tests; it is a powerful tool that allows us to protect vulnerable populations, ultimately improving lives.
The idea that Artificial Intelligence will eventually take over our jobs is commonly seen in contemporary science fiction literature and film. Recently, however, major news outlets such as CNN, CBS, and Fox News have also raised this concern; in fact, a recent study from the World Economic Forum predicted that by 2027, 42% of business tasks will be automated. As I read articles predicting increased job displacement due to the development of AI, my concern that AI may deepen existing social inequalities grew.
In this project, I want to combine data science with econometrics to study the impact of AI and computerization on different demographics within the U.S. labor market, specifically based on sex, age, race, level of education, years of residency in the U.S. (for immigrants), and occupation type. To examine differences in job types, I will classify occupations as “white-collar” or “blue-collar,” and will group them by industry (e.g., healthcare, IT, manufacturing) to evaluate sector-specific patterns. I will also analyze the regression interactions between each race and occupation type to understand why workers of a certain race might exhibit lower/higher AI exposure compared to other racial groups. I plan to use residual plots to assess model fit, and heat maps or scatterplots to better illustrate demographic disparities in AI exposure across different regions of the U.S.
Next week, I’ll be diving into the historical context of automation in the workforce and how past technological advancements have impacted different demographic groups. By looking at these patterns, I hope to build a foundation for understanding how AI-driven changes might unfold in the upcoming weeks.
Thank you for joining me in my research journey. Please stay tuned for more updates!
Comments:
All viewpoints are welcome but profane, threatening, disrespectful, or harassing comments will not be tolerated and are subject to moderation up to, and including, full deletion.