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Ethical Considerations in AI: Investigating Bias in Machine Learning Algorithms and its Impact on Societal Equity
Project Abstract
This research explores machine learning bias in gender, race, and age using the Adult dataset. As AI becomes more pervasive, it’s crucial to address biases for fairness. By analyzing logistic regression, decision trees, and SVM, this study aims to uncover and mitigate biases. Through data preprocessing, model training, and bias assessment, it reveals disparities in predictive outcomes. Ultimately, this research contributes to the dialogue on ethical AI development, advocating for fairness and transparency in AI systems. The project addresses several issues, including the serious effects that these biases are already having on some members of society, how we are responsible for AI’s biases and how we are ultimately responsible for finding a solution.
Keywords: AI Bias Research, Ethical human computer impact, Machine learning algorithm training
Conference Details
Session: Poster Session B at Poster Stand 61
Location: Sir Stanley Clarke Auditorium at Wednesday 8th 09:00 – 12:30
Markers: Troy Astarte, Muneeb Ahmad
Course: BSc Computer Science, 3rd Year
Future Plans: I’m looking for work