Ethical Principles in AI: Fairness, Transparency, Accountability, and Privacy

Core ethical principles underpin responsible AI.

• Fairness: Ensuring AI systems do not discriminate based on race, gender, or other protected attributes. Techniques include bias mitigation algorithms and diverse training data.
• Transparency: Making AI operations understandable, e.g., using interpretable models or explainable AI techniques.
• Accountability: Assigning responsibility for AI decisions, fostering mechanisms such as audit logs and clear governance structures.
• Privacy: Safeguarding user data via encryption, anonymization, and complying with data protection laws like GDPR.

Example: A loan approval AI must avoid biased outcomes (fairness) and provide explanations (transparency), while the organization remains responsible for its decisions (accountability) and protects applicant data (privacy).