Algorithmic Safeguards
Implementing robust safeguards for bias detection and mitigation is essential for developing ethical and responsible AI.
Algorithmic bias occurs when an AI system systematically and unfairly discriminates against certain individuals or groups. This bias can stem from various sources:
Biased training data
Flawed algorithm design
Incomplete feature selection
Improper model selection
Biased human intervention in the development process
