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13.10: Algorithmic Amplification and Digital Redlining

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    324980
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    Conflict theory warns that technology often reproduces existing inequalities. Algorithmic bias is a fundamental concern: machine learning systems trained on historically biased data perpetuate discrimination, from facial recognition software that misidentifies people of color to ad delivery algorithms that “digitally redline” by showing fewer ads for high-paying jobs to Black users. These are not glitches but automated forms of institutional racism. Furthermore, platforms’ engagement-driven logic often amplifies extreme and polarizing content, including racist hate speech and disinformation, which can fuel real-world violence and deepen partisan divides over the reality of racism itself (Pew Research Center 2025).


    13.10: Algorithmic Amplification and Digital Redlining is shared under a CC BY-NC-SA 4.0 license and was authored, remixed, and/or curated by LibreTexts.

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