DPAI-07

Do you have safeguards in place to protect institutional data and data privacy from unintended AI queries or processing?

Explanation

This question is asking whether your organization has implemented measures to prevent institutional data from being inadvertently exposed to or processed by artificial intelligence systems in ways that could compromise privacy or security. With the rise of AI tools like large language models (LLMs), there's an increasing risk that sensitive data could be unintentionally fed into these systems through user queries, automated processes, or integration points. Once data enters these AI systems, it might be used for model training, stored indefinitely, or potentially accessed by unauthorized parties. The security assessment is asking this question because: 1. AI systems often operate as black boxes, making it difficult to track what happens to data once it's processed 2. Users might inadvertently paste sensitive information into AI tools without understanding the privacy implications 3. Automated systems might feed institutional data into AI services without proper controls 4. Many AI providers reserve rights to use submitted data for improving their models A good answer should describe specific technical and policy controls implemented to prevent unauthorized AI processing of institutional data, such as: - Data loss prevention (DLP) tools that detect and block sensitive data from being sent to external AI services - Clear policies on what institutional data can and cannot be used with AI tools - Technical controls that restrict access to AI services for certain data categories - Monitoring and auditing of AI tool usage across the organization - Vendor assessments for any AI tools used in the environment

Example Responses

Example Response 1

Yes, we have implemented comprehensive safeguards to protect institutional data from unintended AI processing Our approach includes: (1) A Data Loss Prevention (DLP) system that scans outbound traffic and blocks sensitive data patterns from being sent to known AI service endpoints; (2) Network-level controls that restrict access to unauthorized AI services; (3) A formal AI usage policy that clearly defines what institutional data can and cannot be processed using AI tools; (4) Regular training for all employees on safe AI usage practices; (5) Custom enterprise agreements with our approved AI vendors that include data protection addendums prohibiting the use of our data for model training; and (6) Technical controls in our approved AI tools that prevent data persistence beyond the immediate session We also maintain audit logs of all interactions with approved AI services and conduct quarterly reviews of these logs to identify potential policy violations.

Example Response 2

Yes, we implement multiple layers of protection against unintended AI processing of institutional data Our technical controls include a zero-trust architecture where all AI service connections require explicit authorization, with data classification tags that automatically prevent sensitive or regulated data from being processed by external AI systems We've deployed browser extensions and API gateways that warn users before submitting institutional data to AI services and require justification for such submissions For our internally developed AI systems, we maintain strict data segregation, implement differential privacy techniques, and conduct regular privacy impact assessments Our governance framework includes a dedicated AI Ethics Committee that reviews all AI implementations for privacy implications, and we maintain a comprehensive inventory of approved AI use cases with corresponding data handling requirements.

Example Response 3

We are currently developing our AI governance framework and do not yet have comprehensive safeguards specifically designed for AI data protection While our general data protection controls (such as access controls, encryption, and data classification) provide some protection, we recognize the unique challenges posed by AI systems Currently, we rely primarily on our acceptable use policy that instructs employees not to share sensitive information with external AI tools, but we do not have technical controls to enforce this policy We are in the process of implementing a DLP solution that will include AI-specific detection patterns, and we're drafting a formal AI usage policy We expect to have these controls in place within the next 6 months, and in the interim, we've conducted awareness training for staff on the risks of sharing institutional data with AI systems.

Context

Tab: Privacy
Category: Privacy and AI