Tuck MBA Essay: Tell us who you are. How have your values and experiences shaped your identity and character? How will your background contribute to the diverse Tuck culture and community? (289 words)
Background Information: The applicant noticed a strange bias emerging in a machine learning algorithm despite data verification. The solution to the bias and the creation of an algorithm review process is the core of the narrative.
Theme: AI, Bias, DEI
Theme (Explained): AI works on data – tons of data. Applicants who have worked in the function create themes around bias, inaccuracies, and errors in decision-making. Most interventions are around solutions. A better and more impactful narrative is in facilitating or directly creating review processes that address biases and inaccuracies.
Profile: Admissions
Industry: Education
MBA Essay Strategy: With machine learning algorithms improving by the day, addressing a fundamental assumption in machine learning is the focus of the narrative.
In the essay, the algorithm unintentionally filtered minorities from the application pool. Instead of making the essay all about algorithms, I have also addressed systemic biases emerging from certain traditions in student-run clubs.
The applicant wants to bring her expertise in dismantling biases by assisting the DEI working team with review plans and setting milestones to address biases in all aspects of the student experience, from the language used in the course material to outreach to admissions to student-run elections to recruitment practices.
Opener: I wanted to start with algorithms and the information bubbles it creates before transitioning to bias.
Sample Tuck MBA Who you are and how you will contribute Essay: DEI and AI’s Filter Bubble (289 Words)
Algorithms mixed our tribal instincts with our desire to seek distraction. The combination with companies’ incentive to monetize the maxim – higher viewing time equals a higher likelihood of purchase led to the creation of information bubbles.
Influencers on both sides of the political aisle exist in silos breaking down decades of bipartisanship that was the cornerstone of a vibrant democracy.
I saw biases accentuated by algorithms even in 2016 while assisting the college admissions team. We pushed for greater representation of US minorities, second-generation immigrants, and international minorities in our admissions ...
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