"Sinful" Algorithms? A Hamartiological Analysis of Structural Bias in Machine Learning
DOI:
https://doi.org/10.5281/zenodo.21723856Keywords:
Algorithmic Bias, Structural Sin, Hamartiology, Machine Learning, Total DepravityAbstract
The myth of technological neutrality suggests that algorithms are objective mathematical entities, free from human prejudice. However, the phenomenon of "algorithmic bias" in Machine Learning—where AI exhibits racism, sexism, and systemic injustice—shatters this illusion. This research investigates the theological implications of such bias through the lens of Reformed Hamartiology (Doctrine of Sin). Using a qualitative interdisciplinary method, this study correlates the technical concept of "training data bias" with the theological concepts of "Original Sin" (Peccatum Originale) and "Structural Sin." The findings reveal a paradox: while AI lacks the volition to commit active sin, it ontologically inherits moral corruption from its creators through the historical data it absorbs. AI acts as a "broken mirror," amplifying human sin into invisible structures of digital oppression. Therefore, Christian theology must reject naive technocracy and view AI ethics as an urgent mandate to restrain the spread of structural sin in cyberspace.
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