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Governance Principles, Frameworks & Program Design
Core ideas for defining AI governance principles, comparing frameworks, assigning responsibilities, and designing a program that can work in practice.
OpenGeneral concept cards
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OpenAccountability as a Governance Principle
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...
OpenAccountability for High-Risk AI Systems
Accountability for High-Risk AI Systems refers to the responsibility of organizations and individuals to ensure that AI systems classified as high-risk are designed, implemented, a...
OpenAccountability vs Responsibility in AI Contexts
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...
OpenAccountability vs Responsibility vs Authority
Accountability, responsibility, and authority are critical components of AI governance that delineate roles in decision-making processes. Accountability refers to the obligation to...
OpenAdapting Compliance Strategy to Emerging Rules
Adapting Compliance Strategy to Emerging Rules involves the proactive adjustment of an organization's compliance framework to align with new regulations and standards in AI governa...
OpenAI Governance Implications of Risk Classification
AI Governance Implications of Risk Classification refers to the systematic categorization of AI systems based on their potential risks and impacts on society. This classification i...
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