Assess Criminal Recidivism Risk
Approximately one-fifth of all convicted criminal offenders in Switzerland reoffend after serving their sentence. Reducing this recidivism rate is crucial to prevent future crimes and assist former convicts in reintegrating into society. In other words, law enforcement agencies require robust and ethical predictive tools to determine who is likely to commit another criminal offense.
Law enforcement agencies possess extensive information on convicted criminals, including their criminal records, disciplinary infractions while imprisoned, and more. Law enforcement agents can build and apply Machine Learning (ML) models to predict if a convicted individual is likely to reoffend. Moreover, ML models can highlight which parameters are critical for making a prediction, allowing law enforcement professionals to decide on the right preventive measures.
In this process, the adoption of responsible AI ensures the ethical handling of sensitive data, the reduction of bias in predictions, and the transparency and interpretability of the models used. It places a high priority on ethical considerations, especially crucial when dealing with sensitive personal data, such as criminal records.
Significantly, the use of AI in such high-risk sectors must comply with the EU AI Act, which underlines the need for lawful and transparent data processing, upholding individuals’ rights, and implementing robust risk management systems.
Modulos offers a Responsible AI Platform that addresses the challenges of complying with diverse frameworks, mitigating risks, and guaranteeing the implementation of responsible AI practices. It ensures that the predictive tools used to assess recidivism risk are not only data-driven but also ethically sound and compliant with EU regulations.
Our platform can also be deployed on-premise, making it highly suitable for the analysis of potentially sensitive data. With Modulos, law enforcement agencies can confidently predict recidivism risk, knowing their strategies are not only effective but also ethically responsible and aligned with necessary regulatory frameworks.