Dell EMC Exam D-GAI-F-01 Topic 3 Question 23 Discussion

Actual exam question for Dell EMC's D-GAI-F-01 exam

Question #: 23
Topic #: 3

[All D-GAI-F-01 Questions]

What impact does bias have in Al training data?

AIt ensures faster processing of data by the model.

BIt can lead to unfair or incorrect outcomes.

CIt simplifies the algorithm's complexity.

DIt enhances the model's performance uniformly across tasks.

Show Suggested Answer

Suggested Answer: B

Definition of Bias: Bias in AI refers to systematic errors that can occur in the model due to prejudiced assumptions made during the data collection, model training, or deployment stages.

Impact on Outcomes: Bias can cause AI systems to produce unfair, discriminatory, or incorrect results, which can have serious ethical and legal implications. For example, biased AI in hiring systems can disadvantage certain demographic groups.

Mitigation Strategies: Efforts to mitigate bias include diversifying training data, implementing fairness-aware algorithms, and conducting regular audits of AI systems.

by Elvis at May 01, 2025, 03:18 AM

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Cherilyn

1 months ago

Option B is the one. Bias can be a real problem, like having a reality TV star as president. Oh wait, that already happened. But I digress, Option B is the right choice here.

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Lynette

4 days ago

D) It enhances the model's performance uniformly across tasks.

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Eden

7 days ago

C) It simplifies the algorithm's complexity.

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Lavonne

22 days ago

B) It can lead to unfair or incorrect outcomes.

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Melinda

25 days ago

A) It ensures faster processing of data by the model.

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Joanna

1 months ago

Hmm, I'd say Option B is the way to go. Bias in data can really mess things up. It's like trying to build a house on a crooked foundation - not gonna end well.

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Winfred

5 days ago

We need to be careful and make sure our data is unbiased for accurate results.

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Nguyet

8 days ago

I agree, bias in AI training data can definitely lead to problems.

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Casie

21 days ago

Option B) It can lead to unfair or incorrect outcomes.

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Jaclyn

1 months ago

While bias may simplify the algorithm, it ultimately hinders the model's performance by leading to unfair outcomes.

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Mari

2 months ago

But doesn't bias also simplify the algorithm's complexity?

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Dick

2 months ago

Option B is clearly the correct answer. Bias in training data can lead to biased and unfair outcomes. We can't ignore this issue, it's crucial for ethical AI development.

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