Bias and Discrimination in AI-Generated Code
AI models can perpetuate biases present in training data, leading to discriminatory algorithms and unfair system behaviors.
Types of Bias
- Gender bias in hiring algorithms
- Racial bias in facial recognition
- Socioeconomic bias in credit scoring
- Age bias in recommendation systems
Biased Code Example
// AI might generate biased logic:
function evaluateCandidate(resume) {
let score = 0;
// Unconscious bias in AI training data
if (resume.name.includes("John") || resume.name.includes("Michael")) {
score += 10; // ❌ Gender bias
}
if (resume.university.includes("Ivy")) {
score += 20; // ❌ Elitist bias
}
return score;
}
Always audit AI-generated algorithms for fairness.
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