Artificial Intelligence
Technology, Risks, and Governance Concepts
Artificial intelligence refers broadly to computational systems that perform tasks requiring human-like cognition — pattern recognition, language understanding, decision-making, and prediction. The current wave of AI is driven by large language models (LLMs) and foundation models trained on vast datasets using deep learning techniques.
- AI systems are broadly categorised into Narrow AI (designed for specific tasks — e.g., image recognition, language translation) and General AI (hypothetical systems with human-level reasoning across domains); current systems are narrow.
- The principal risks from AI identified by researchers and governance bodies include: algorithmic bias (discriminatory outputs from biased training data), misinformation (AI-generated deepfakes and synthetic content), autonomous weapons, economic displacement through automation, and catastrophic misuse.
- The EU AI Act (2024) — the world's first comprehensive AI regulation — categorises AI applications by risk level: unacceptable risk (banned), high risk (strict requirements), limited risk (transparency obligations), and minimal risk (largely unregulated).
- India's approach, expressed through the 2025 AI Governance Guidelines, contrasts with the EU model by adopting a "soft law," principles-based approach — designed to enable innovation while managing risks through existing legal frameworks.
● Tracked since February 16, 2026 · last seen May 20, 2026 · updates as the daily brief publishes
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