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Bias influences technology by shaping the design, development, and deployment of algorithms and systems, often reflecting the prejudices and assumptions of their creators. This can lead to discriminatory outcomes, such as biased hiring practices or unfair law enforcement surveillance, as technology may reinforce existing societal inequalities. Additionally, biased data used to train machine learning models can result in skewed predictions and decisions, impacting various sectors from finance to healthcare. Addressing bias is crucial for ensuring ethical and equitable technology that serves all users fairly.

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2w ago

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