Governance, Ethics & Risks

Incident response for AI systems involves detecting, containing, and recovering from AI failures or harms, ensuring accountability and protection in high-stakes mission-driven sectors.

This article explores intellectual property concerns in AI training data, emphasizing legal, ethical, and equity issues for mission-driven organizations to ensure compliance and community respect.

Jailbreaks and safety bypasses in AI systems enable harmful outputs by circumventing safeguards, posing risks in health, education, and humanitarian sectors. Understanding and mitigating these threats ensures AI safety and trustworthiness.

Model and dataset licensing defines legal and ethical terms for AI use, crucial for mission-driven organizations to innovate responsibly and maintain community trust while avoiding legal risks.

Model and system cards provide standardized documentation to enhance transparency, accountability, and responsible AI adoption across sectors including health, education, and humanitarian work.

Open source licensing governs the use, sharing, and modification of AI software and datasets, enabling mission-driven organizations to collaborate responsibly while addressing legal and ethical challenges.

Privacy threats and data leakage pose risks of exposing sensitive information through AI systems, impacting vulnerable populations and requiring strong safeguards and compliance to maintain trust and protect data.

The regulatory landscape governs AI development and use through laws and policies worldwide, impacting mission-driven organizations by ensuring compliance, managing risks, and promoting responsible innovation across sectors.

Responsible AI prioritizes fairness, transparency, and accountability to ensure ethical AI development and deployment, especially for mission-driven organizations working with vulnerable populations and sensitive data.

Risk assessment for AI identifies and mitigates technical, ethical, and societal risks to protect vulnerable communities and ensure safe, fair, and accountable AI deployment in mission-driven sectors.