Example Concept: Accountability frameworks in AI often involve assigning roles and responsibilities across the AI lifecycle, from design to deployment. Developers are responsible for ensuring the model is trained on unbiased data, deployers must monitor the system's impact in real-world settings, and users need to be informed about the system's capabilities and limitations. Governance frameworks like the NIST AI Risk Management Framework provide guidelines for assigning accountability to prevent and mitigate unintended consequences.