Algorithmic decision-making (ADM) is interwoven in every minute facet of society. ADM is being used to complete a task as inconsequential as recommending a song on Spotify to making a decision that’s instrumental to a person’s life, such as determining a person’s candidacy for college. However, an algorithm has the possibility to propagate harm, if it is trained on biased data. This paper presents a way to potentially mitigate ADM bias by incorporating the second pillar of the liberatory computing framework, critical consciousness, into intersectional data analysis on the college admission process. Developing a critical consciousness will diversify computing and the data incorporated into ADM systems. This paper discusses the preliminary findings from teaching a two-day computing activity to high school students.