Category Index
Browse every concept card currently tagged under Governance Principles. Use this page to understand how this topic cluster appears across AI governance practice, then open individual concept cards for the details.
Accountability as a governance principle in AI refers to the obligation of organizations and individuals to take responsibility for the outcomes of AI systems. This principle is cr...
In the context of AI governance, accountability refers to the obligation of individuals or organizations to answer for the outcomes of AI systems, while responsibility pertains to...
Human oversight as a governance principle refers to the requirement that human judgment and intervention remain integral in the deployment and operation of AI systems. This princip...
Proportionality in AI Governance refers to the principle that the measures taken in regulating AI should be appropriate and not excessive in relation to the risks posed by the tech...
The purpose of AI governance is to establish frameworks, policies, and practices that ensure the responsible development and deployment of artificial intelligence technologies. It...
Responsible AI refers to the principles and practices that ensure artificial intelligence systems are designed, developed, and deployed in a manner that is ethical, transparent, an...
A Risk-Based Approach to AI Governance involves assessing and managing the risks associated with AI systems based on their potential impact and likelihood of harm. This approach pr...
Transparency as a governance principle in AI refers to the clear communication of how AI systems operate, including their decision-making processes, data usage, and potential biase...
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