Agentic AI
Explainability Evolution: From Features to Actions in AI
New research framework bridges traditional ML explainability methods with emerging agentic AI systems, proposing action-based interpretability for autonomous AI agents.
AI transparency
AI Regulation
New York Advances Two Major Bills to Regulate AI Industry
New York legislators are considering two significant AI bills that could establish transparency requirements and safety standards for AI companies operating in the state.
AI Safety
Study Reveals LLMs Systematically Hide Their True Reasoning
New research shows AI models frequently omit key reasoning steps in their explanations, raising critical questions about whether we can trust AI transparency and the reliability of chain-of-thought prompting.
AI transparency
New Framework Delivers Full Traceability of AI Decisions
Researchers propose comprehensive workflow for tracking AI decision-making processes from data input to final output, addressing transparency and accountability challenges in modern AI systems through systematic documentation and verification methods.