Tag: AI Governance

Enterprises adopting Large Language Models (LLMs) face a complex landscape of evolving security risks. This analysis delves into critical vulnerabilities such as prompt injection, data poisoning, and model theft, alongside essential best practices for safeguarding AI assets throughout their lifecycle. It highlights the necessity of a comprehensive security posture, from robust input validation to continuous monitoring, emphasizing the role of AI Security Posture Management (AI-SPM) in mitigating threats and ensuring responsible AI integration.

A systematic review identifies and categorizes ethical risks in AI in Education (AIED), spanning technology, education, and society. It proposes mitigation strategies to ensure responsible AI implementation, addressing concerns from privacy and bias to the digital divide and accountability.

While the U.S. grapples with its domestic AI policy, international bodies and nations like Finland, Singapore, and India are actively establishing global AI governance frameworks. This divergence could position the U.S. as an outlier in crucial future AI discussions and agreements.