When trust in AI matters, system cards keep score

The rapid advancement of Artificial Intelligence (AI) has introduced significant challenges, including bad chatbot advice and slanderous hallucinations, tempering enthusiasm for AI adoption. What is hindering your organization’s AI adoption?

System cards offer a thorough, transparent, and structured evaluation of AI systems, enabling stakeholders to confidently assess, govern, and monitor AI at scale.

Unlike model cards that focus solely on individual machine learning models, system cards provide a broader view, covering the entire AI system, including its intended use, data considerations, components, and limitations. This holistic approach helps stakeholders and regulators build trust and confidence in AI technologies.

It is essential for organizations to prioritize a systematic approach to monitoring, evaluating and reporting on the trustworthiness of their AI systems. In this article we examine how AI system cards can help organizations:

• Enhance Transparency: Document how AI systems are currently being used within an organization, through a business, technology, and risk lens
• Improve Explainability: Clarify the inner workings of AI systems, including capabilities, limitations, reasoning methods, data sources, and model designs
• Drive Accountability: Promote rigorous AI governance and compliance management processes ensuring responsibility and alignment with ethical standards and emerging regulations
• Foster Trust: Increase user confidence in AI systems by simply explaining their operations in a way that promotes user confidence and drives adoption.

Learn how system cards can help you operationalize transparency, build trust, and confidence.