Advancements in AI technologies bring with it not only increased efficiencies but also impacts on data privacy. AI systems often rely on vast amounts of data, including personal and sensitive information, to function effectively. This data-driven approach opens up potential risks for unauthorized access, data breaches, and misuse of personal information. The privacy concerns of transparency, accountability, and data subjects’ rights are not new or unique to AI. Rather, AI highlights the need to incorporate privacy principles as we navigate the development and implementation of new technologies.
Privacy Considerations for AI Systems
In assessing a proposed AI system, the potential harms should be considered based on the full breadth of stakeholders including anticipated users and individuals whose data is used to training the AI. Consideration should be given to the sensitivity of personal information to be collected, the intended use, and the stakeholders. The harms are then balanced by any mitigating controls such as privacy enhancing techniques or human oversight. The linked document is a summary of key considerations common to many AI impact assessment frameworks.
Privacy Considerations for AI Systems
Use of AI Assistants
AI assistants are designed to collect, process, and analyze vast amounts of data to provide personalized and efficient user experiences. However, this capability raises significant privacy concerns when the data collected includes sensitive personal information as described in this notice to the Yale community.