AI Risk Assessment

AI Risk Assessment

AI Risk Assessments aim at identifying and assessing risks of AI, with the view to mitigating them. These assessments would be required to probe the transparency, robustness, and accuracy of the systems, affirming they do not cause any harm. Any risks identified from vendors’ AI risk assessments, AI impact assessments, or readiness assessments can be treated under an AI risk assessment.

It is important to assess the risks of your AI systems at pre-development and development stages and implement risk mitigation steps. This involves leveraging model cards that offer predefined risk evaluations for AI models, including a model’s description, intended use, limitations, and ethical considerations. These risk ratings provide comprehensive details, covering aspects such as toxicity, maliciousness, bias, copyright considerations, hallucination risks, and even model efficiency in terms of energy consumption and inference runtime. This step is essential for aligning AI systems and models with the classifications imposed by global regulatory bodies, ensuring compliance with these standards. Based on risk ratings (e.g., high risk or low risk), you can decide which models to sanction for deployment and use, which models to block, and which ones need additional guardrails before consumption.