Accountable AI
Posted: Thu Feb 12, 2026 10:50 am
Accountable AI
Accountability is a key pillar of AI Governance, establishing clear responsibilities and mechanisms for addressing any negative impacts or harms caused by AI systems. It involves creating pathways for redress for those adversely affected by AI decisions and ensuring that there are checks and balances in place to hold developers, deployers, and operators of AI systems responsible. This might include regulatory frameworks, auditing requirements, and legal structures that enable accountability.
Identifying who is responsible for the decisions made by AI systems, including developers, operators, and deployers.
Making the operations and decision-making processes of AI systems open and accessible for inspection and review.
Providing mechanisms (redress) for rectifying adverse outcomes or harms caused by AI systems, including avenues for affected individuals to seek recourse.
Accountability is a key pillar of AI Governance, establishing clear responsibilities and mechanisms for addressing any negative impacts or harms caused by AI systems. It involves creating pathways for redress for those adversely affected by AI decisions and ensuring that there are checks and balances in place to hold developers, deployers, and operators of AI systems responsible. This might include regulatory frameworks, auditing requirements, and legal structures that enable accountability.
Identifying who is responsible for the decisions made by AI systems, including developers, operators, and deployers.
Making the operations and decision-making processes of AI systems open and accessible for inspection and review.
Providing mechanisms (redress) for rectifying adverse outcomes or harms caused by AI systems, including avenues for affected individuals to seek recourse.