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Salesforce Exam Salesforce AI Associate Topic 4 Question 27 Discussion

Actual exam question for Salesforce's Salesforce AI Associate exam
Question #: 27
Topic #: 4
[All Salesforce AI Associate Questions]

What is a potential outcome of using poor-quality data in AI application?

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Suggested Answer: B

''A potential outcome of using poor-quality data in AI applications is that AI models may produce biased or erroneous results. Poor-quality data means that the data is inaccurate, incomplete, inconsistent, irrelevant, or outdated for the AI task. Poor-quality data can affect the performance and reliability of AI models, as they may not have enough or correct information to learn from or make accurate predictions. Poor-quality data can also introduce or exacerbate biases or errors in AI models, such as human bias, societal bias, confirmation bias, or overfitting or underfitting.''


by Eve at Sep 12, 2024, 03:04 AM

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Brande
2 months ago
Hmm, I'm thinking C might be the hidden gem here. More interpretable AI models? Sign me up! Although, I'd hate to be the AI trying to interpret my handwriting.
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Kimberlie
24 days ago
C) AI models become more interpretable
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Tamra
29 days ago
B) AI models may produce biased or erroneous results.
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Devorah
1 months ago
A) AI model training becomes slower and less efficient
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Lucy
2 months ago
I'm going with B too. Who needs biased or erroneous AI results when you can have efficient, unbiased ones? That's my vote.
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Marlon
1 months ago
I'm going with B too. Who needs biased or erroneous AI results when you can have efficient, unbiased ones? That's my vote.
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Cristina
1 months ago
B) AI models may produce biased or erroneous results.
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Art
1 months ago
I'm going with B too. Who needs biased or erroneous AI results when you can have efficient, unbiased ones? That's my vote.
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Bernadine
1 months ago
B) AI models may produce biased or erroneous results.
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Rosendo
2 months ago
A) AI model training becomes slower and less efficient
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Lavonna
2 months ago
A) AI model training becomes slower and less efficient
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Essie
3 months ago
Option B all the way! Garbage in, garbage out, as they say. Poor data leads to poor AI models - can't argue with that.
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Dottie
2 months ago
B) AI models may produce biased or erroneous results.
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Tamekia
2 months ago
A) AI model training becomes slower and less efficient
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Antonio
3 months ago
But wouldn't using poor-quality data make AI models more interpretable?
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In
3 months ago
I agree, it can also make AI model training slower and less efficient.
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Marisha
3 months ago
Using poor-quality data in AI can lead to biased results.
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