A-Z Index
Browse concept cards whose titles begin with C. This is useful when you want an alphabetical view of the library rather than browsing by governance topic or category.
Centralised vs Federated AI Governance refers to two distinct approaches in managing AI systems and their compliance with regulations and ethical standards. Centralised governance...
Clarifying Ownership Across Governance Domains refers to the clear identification of stakeholders responsible for AI systems across various governance frameworks, such as ethical,...
Committees, councils, and decision forums are structured groups within organizations that oversee AI governance processes, ensuring alignment with ethical standards, regulatory com...
Common Ethical Frameworks in AI Governance refer to established guidelines and principles that guide the ethical development and deployment of AI technologies. These frameworks, su...
Communicating Assurance Outcomes to Stakeholders involves transparently sharing the results of assessments regarding AI systems' performance, risks, and compliance with ethical sta...
Communicating with Regulators and Stakeholders involves the transparent exchange of information between AI developers, regulatory bodies, and affected parties. This practice is cru...
Compliance as a Strategic Capability refers to the proactive integration of compliance measures into an organization's strategic framework, particularly in the context of AI govern...
Consistency of Governance Decisions Across Contexts refers to the principle that AI governance frameworks should apply uniform standards and policies regardless of the specific app...
Coordinating Compliance Obligations Across Domains refers to the process of harmonizing and managing regulatory requirements and ethical standards across various sectors that AI sy...
The Core Components of an AI Compliance Framework refer to the essential elements that ensure AI systems adhere to legal, ethical, and operational standards. These components typic...
Conflicting Regulatory Obligations refer to situations where an AI system or organization must comply with multiple, often contradictory, regulations from different jurisdictions....
Cross-Border Consent and User Expectations refer to the legal and ethical requirements for obtaining user consent when personal data is processed across national borders. In AI gov...
Consent and data collection in AI contexts refer to the ethical and legal requirement that individuals must provide explicit permission before their personal data is collected, pro...
Core components of an AI Impact Assessment (AIA) include identifying potential risks, evaluating ethical implications, assessing societal impacts, and ensuring compliance with lega...
Communication during AI incidents refers to the structured process of informing stakeholders about issues arising from AI systems, including failures, biases, or security breaches....
Conflicting Governance Objectives refer to the situation where different stakeholders or regulatory frameworks impose divergent goals on AI systems, such as prioritizing innovation...
In AI governance, 'Controls', 'Monitoring', and 'Audit' refer to distinct yet interconnected processes for ensuring AI systems operate within defined parameters. Controls are proac...
Corrective Actions and Remediation Measures refer to the strategies and processes implemented to address and rectify failures or non-compliance in AI systems. In AI governance, the...
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