Ensure data security and compliance

  • 4 minutes

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Implementing security is critical to protecting AI systems and sensitive data in education. Strong security measures help prevent unauthorized access, data breaches, and other cyber threats. A comprehensive security framework reinforces data protection, ensuring confidentiality, integrity, and compliance. Use these strategies to strengthen your security posture and safeguard AI-driven systems.

Establish identity access

Secure identity access protocols and user policies help institutions enhance privacy and security. Explore these Microsoft tools to set up and manage access controls.

  • Microsoft Entra ID: Control access to Microsoft Copilot tools and data. Use secure authentication and adaptive policies based on risk.
  • Intune for Education: Use security, configuration, and compliance policies for devices. This way, school-issued endpoints get baseline protection while using AI systems.

Apply sensitivity labels

Collaboration goes beyond your institution's walls. This means content often travels around the world across different devices, apps, and services. It's crucial that content stays secure and follows your policies. Microsoft Purview Information Protection uses sensitivity labels to classify and protect data without disrupting productivity or collaboration. Copilot and agents use sensitivity labels in user interactions to keep labeled data safe. Consider these questions.

  • What types of sensitive information need protection?
  • How will sensitivity labels be deployed and managed?
  • How will the effectiveness of sensitivity labels be checked?

Compliance with data privacy regulations

Using AI in education requires careful handling of student and faculty data. This includes academic performance, learning habits, and private personal information. Protecting this data's privacy is essential. Before deploying an AI system, it's important to review internal policies and access protocols. Start with these two important considerations:

  • Privacy impact assessment: Find privacy risks in your IT systems and define strategies to mitigate them.
  • Privacy policies: Check how your vendors handle data. This ensures they follow the law and keep student privacy safe.

These practical tips help minimize data privacy concerns:

  • Collect and use only the minimum data needed for the task.
  • Anonymize student data to protect their identities by removing personal data or using pseudonyms when you can.
  • Conduct a privacy impact assessment to evaluate risks.
  • Review the privacy policies of all AI solutions they use.