AI Ethics, Bias & Global Governance
The deployment of artificial intelligence raises critical ethical, legal, and safety considerations regarding algorithmic bias, surveillance, data privacy, and accountability. Algorithmic bias occurs when training datasets contain historical disparities, leading models to perpetuate demographic inequities in hiring, criminal justice, or lending. Explainable AI (XAI) develops interpretable methods (such as SHAP and LIME) to audit 'black box' machine decisions. In 2024, the European Union approved the EU Artificial Intelligence Act, the world's first comprehensive risk-based horizontal regulation for AI systems, categorizing models into unacceptable, high, and minimal risk tiers. India engages through the Global Partnership on Artificial Intelligence (GPAI) and NITI Aayog's National Strategy for AI.
Key Concepts & Examination Highlights
- The European Union adopted the EU AI Act in 2024, establishing the world's first comprehensive risk-tiered regulatory framework for artificial intelligence.
- The Global Partnership on Artificial Intelligence (GPAI) is an international multi-stakeholder initiative formed in 2020 to guide responsible AI development.
- Explainable AI (XAI) frameworks like SHAP (Shapley Additive Explanations) provide mathematical interpretability for complex machine learning predictions.