IBM Explains Algorithmic Bias

IBM views algorithmic bias as a serious issue stemming from systematic errors in machine learning algorithms that produce unfair or discriminatory outcomes, often reflecting or reinforcing existing socioeconomic, racial, and gender biases. This bias can lead to harmful decisions in critical areas like healthcare, law enforcement, and human resources, while also posing legal, financial, and reputational risks to organizations through perpetuated discrimination, inequality, and erosion of trust in AI systems.