Why We Need to Audit Government AI | Montreal AI Ethics Institute

The large-scale implementation of AI in governments requires corresponding efforts from the AI Ethics community to provide a method to audit and oversee AI at scale, across complex enterprises. In the past, the AI Ethics community has focused on high-level, and recently on bias mitigation. It is easy to assume that an ML model trained on a representative dataset tested for statistical bias and embedded fairness metrics will continue to perform ethically without oversight. In reality, the environment in which the model is operating is constantly changing, and auditors need to periodically reassess model performance and outcomes with thorough, multidisciplinary auditing teams to avoid unethical outcomes seeping into the models over time since ethics is not a ‘bolt-on’, but a continuous process. Ensuring that ML algorithms behave ethically requires regulation, measurement, and consistent auditing.