From the course: CompTIA SecAI+ (CY0-001) Cert Prep
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Human validation
From the course: CompTIA SecAI+ (CY0-001) Cert Prep
Human validation
Human validation focuses on what happens after an AI system makes its decisions. Unlike human-in-the-loop or human oversight, human validation is an evaluation activity performed through audits. It involves reviewing the model's outputs to detect errors, bias, and unintended consequences. For example, a financial institution might use AI to approve loan applications automatically. Even if no human approves each decision in real-time, analysts can later audit a sample of the system's outputs to make sure approvals are fair and compliant with regulations. This kind of ongoing validation ensures that the AI continues to perform as intended and does not drift into biased or unsafe territory. Human validation is also essential in creative and generative AI systems. When an AI generates reports, marketing content, or policy recommendations, human reviewers should sample and audit the content for accuracy, appropriateness, and brand fit. These reviews help maintain quality and ensure that…
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Contents
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The AI lifecycle1m 39s
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Business alignment in the AI lifecycle1m 43s
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Data collection2m 20s
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Data preparation3m 15s
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Model development and selection2m 13s
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Model evaluation and validation2m 29s
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Model deployment and integration3m 25s
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Monitoring and maintenance3m 19s
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Manipulating application integrations4m 8s
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AI supply chain attacks2m 4s
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Insecure plug-in design2m 9s
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Insecure output handling1m 23s
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Output integrity attacks2m 8s
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Model denial of service1m 31s
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Excessive agency1m 33s
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Overreliance1m 34s
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AI hallucinations1m 4s
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Monitoring prompts and responses2m 51s
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Log monitoring4m 30s
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Rate and cost monitoring5m 1s
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Auditing for AI hallucinations3m 33s
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Auditing for accuracy3m 29s
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Auditing for bias and fairness4m 35s
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Auditing access and security compliance3m 48s
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Responsible AI5m 29s
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AI risks2m 23s
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Introduction of bias2m 37s
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Accidental data leakage2m 53s
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Reputational loss2m 11s
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Accuracy and performance of the model2m 22s
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Intellectual property risks3m 31s
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Autonomous systems2m 27s
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Shadow IT and shadow AI1m 48s
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Awareness training2m 21s
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