A systems administrator is reviewing a developer's workflow. The developer frequently pastes large code snippets, which include proprietary logic and service account credentials, into a public, cloud-hosted AI chat service for debugging assistance. Which of the following is the most significant data governance risk associated with this practice?
Using a public AI service will violate the corporate policy on 'Shift-left testing'.
The developer could become overly reliant on the AI, leading to a degradation of their own debugging skills.
The AI model might generate inefficient or non-compliant code, increasing technical debt.
The sensitive data could be incorporated into the AI's training data or be exposed through human review, leading to a potential data breach.
The correct answer identifies the primary data governance risk. Pasting sensitive information like proprietary code and credentials into a public AI service exposes that data to the service provider. Many public AI services state in their terms of use that they may use customer data to train their models, and they may also employ human reviewers who can see the data. This creates a significant risk of that confidential data being absorbed into the model and potentially exposed to other users, or being otherwise compromised, leading to a serious data breach. The other options describe valid but less significant or different types of risks. Generating inefficient code is a code quality risk, not a data governance risk. Violating 'shift-left testing' is a process issue. A developer's skill degradation is a personnel risk, not a data governance risk.
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CompTIA Linux+ XK0-006 (V8)
Automation, Orchestration, and Scripting
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