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Security and Privacy Statement on Artificial Intelligence | Office of Technology and Digital Innovation

University-wide: Level 2 and above confidential data (including non-public research data, finance, HR, student records, medical information) should not be entered into publicly-available generative AI tools. Such data may only be entered into generative AI tools that have been assessed and approved by Harvard's Information Security and Data Privacy office.

ANU approved six institutional AI principles via Academic Board in June 2023, covering excellence/integrity, research engagement, clear guidance, AI literacy, access/privacy/security, and collaborative policy development.

When AI-supported marking and feedback practices are used, student-facing information should explain why and how AI tools are used, human oversight, academic judgement, and privacy concerns about student data or work.

UWA research-writing guidance says authors are responsible for ensuring inputs to AI tools are suitable for uploading and processing and that use complies with copyright, privacy, ethics, data-sensitivity policies, and legislation.

KU researcher guidance says researchers should comply with sponsor, publisher, institutional, and disciplinary rules when using GenAI and should consider confidentiality, privacy, intellectual property, and disclosure requirements.

UW-Madison states that it has vetted and secured contracts for listed generative AI services that are available university-wide for free and provide higher data security and privacy protection than public services.

University of Toronto teaching guidance says Microsoft Copilot is the recommended generative AI tool to use at U of T and, when signed in with University credentials, conforms to U of T privacy and security standards for use with up to level 3 data.