AI systems can produce biased decisions from the data on which they are trained. This "AI bias" creates both ethical and legal problems.
Common AI Bias Scenarios
- HR CV screening (eliminates women)
- Loan application rejection (ethnic-based)
- Insurance premium (based on gender)
- Face recognition (does not recognize colored skin)
- Criminal verdicts (US COMPAS example)
From the Perspective of Turkish Law
- Constitution Article 10: Principle of Equality
- Labor Law Article 5: Prohibition of discrimination
- KVKK Article 11/g: Right to object to automatic decision
- TKHK: Against the consumer discrimination
Proof
- Statistical evidence (profile similar to the algorithm, different result)
- Algorithm description (if explainable)
- Comparable profile
Rights of the Victim
- Administrative/labor court case
- Material and moral compensation
- Algorithm replacement
- Requesting human auditing
EU AI Act Approach
- Bias testing mandatory for “high risk AIs”
- Transparency report
- Human intervention
- Regular auditing
What Companies Must Do
- Diversity in training data
- Bias tests
- Regular audit
- Explainable AI (XAI)
- Human intervention mechanism
Artificial intelligence and equality law lawyer recommended.