AI governance is the process by which organizations and societies regulate artificial intelligence to ensure its ethical and legal application. This article explores the importance, approaches, and impact of AI governance in an increasingly AI-driven world.
AI accountability refers to the responsibility for bad outcomes resulting from artificial intelligence systems, which can be difficult to assign due to the complexity and opacity of these technologies. As AI systems are often criticized for being “black boxes,” understanding the decision-making process is essential for ensuring accountability and transparency.
The AI Accountability Framework developed by ITI aims to promote responsible development and deployment of AI systems, particularly in high-risk scenarios. It emphasizes shared responsibility among developers, deployers, and integrators, and outlines key practices to enhance transparency and accountability in AI governance.
Organizations often struggle with managing and deploying AI systems responsibly. The U.S. Government Accountability Office has developed a framework to ensure accountability throughout the AI life cycle, focusing on governance, data, performance, and monitoring.
The integration of AI and biometric technologies, such as facial recognition, has transformed security across various sectors but raises significant ethical and regulatory concerns. To navigate these challenges, organizations must adhere to standards like BS 9347 and comply with regulations such as the EU AI Act, ensuring transparency, accountability, and fairness in their deployment.