AI Ethics & Safety

AI systems impact millions of people through hiring, lending, healthcare, and criminal justice decisions. Understanding ethics ensures these systems are fair, transparent, and don't perpetuate harmful biases.

Common biases include training data bias, selection bias, confirmation bias, and representation bias. These can lead to unfair outcomes for underrepresented groups in areas like facial recognition and hiring.

Many AI ethics courses are designed for non-technical audiences including managers, policymakers, and designers. Technical courses on bias detection and mitigation do require programming skills.

The EU AI Act, NIST AI Risk Management Framework, and various national guidelines set standards. Many organizations also adopt voluntary frameworks like the IEEE Ethically Aligned Design principles.