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CompTIA

CY0-001 · Question #99

A data set containing medical information is put into a machine learning (ML) model that is designed to predict specific illnesses for a population. In the process of verifying the reliability of…

The correct answer is A. Bias. The model's inability to reliably predict illnesses for certain population segments indicates bias in the dataset or training process. This leads to unfair or inaccurate outcomes for specific groups, making bias the most applicable risk in this case. Exam Questions, Study…

Vulnerability Management

Question

A data set containing medical information is put into a machine learning (ML) model that is designed to predict specific illnesses for a population. In the process of verifying the reliability of the system, the compliance officer realizes that the system cannot reliably predict illnesses for certain segments of the population. Which of the following types of risk is most applicable to this case?

Options

  • ABias
  • BConsistency
  • CTransparency
  • DInclusiveness

How the community answered

(28 responses)
  • A
    86% (24)
  • B
    4% (1)
  • C
    4% (1)
  • D
    7% (2)

Explanation

The model's inability to reliably predict illnesses for certain population segments indicates bias in the dataset or training process. This leads to unfair or inaccurate outcomes for specific groups, making bias the most applicable risk in this case. Exam Questions, Study Guides, Practice Tests. Lead the way to help you pass any IT Certification exams, 100% Pass Guaranteed or Full Refund. Especially Cisco, Microsoft, CompTIA, Citrix, EMC, HP, Oracle, VMware, Juniper, Check Point, LPI, Nortel, EXIN and so on. Our Slogan: First Test, First Pass. Help you to pass any IT Certification exams at the first try. You can reach us at any of the email addresses listed below. Any problems about IT certification or our products, you could rely upon us, we will give you satisfactory answers in 24 hours.

Topics

#AI bias#model fairness#healthcare AI#population representation

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