Cyber & IT Supervisory Forum - Additional Resources

MAP 3.5

About As AI systems have evolved in accuracy and precision, computational systems have moved from being used purely for decision support—or for explicit use by and under the control of a human operator—to automated decision making with limited input from humans. Computational decision support systems augment another, typically human, system in making decisions. These types of configurations increase the likelihood of outputs being produced with little human involvement. Defining and differentiating various human roles and responsibilities for AI systems’ governance, and differentiating AI system overseers and those using or interacting with AI systems can enhance AI risk management activities. In critical systems, high-stakes settings, and systems deemed high-risk it is of vital importance to evaluate risks and effectiveness of oversight procedures before an AI system is deployed. Ultimately, AI system oversight is a shared responsibility, and attempts to properly authorize or govern oversight practices will not be effective without organizational buy-in and accountability mechanisms, for example those suggested in the GOVERN function. Processes for human oversight are defined, assessed, and documented in accordance with organizational policies from GOVERN function. Suggested Actions Identify and document AI systems’ features and capabilities that require human oversight, in relation to operational and societal contexts, trustworthy characteristics, and risks identified in MAP-1. Establish practices for AI systems’ oversight in accordance with policies developed in GOVERN-1. Define and develop training materials for relevant AI Actors about AI system performance, context of use, known limitations and negative impacts, and suggested warning labels.

91