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Salesforce Exam Salesforce AI Associate Topic 4 Question 35 Discussion

Actual exam question for Salesforce's Salesforce AI Associate exam
Question #: 35
Topic #: 4
[All Salesforce AI Associate Questions]

What is one technique to mitigate bias and ensure fairness in AI applications?

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Suggested Answer: A

A technique to mitigate bias and ensure fairness in AI applications is ongoing auditing and monitoring of the data used in AI applications. Regular audits help identify and address any biases that may exist in the data, ensuring that AI models function fairly and without prejudice. Monitoring involves continuously checking the performance of AI systems to safeguard against discriminatory outcomes. Salesforce emphasizes the importance of ethical AI practices, including transparency and fairness, which can be further explored through Salesforce's AI ethics guidelines at Salesforce AI Ethics.


by Rosendo at Dec 11, 2024, 06:43 AM

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Ashley
2 months ago
Ooh, I bet the answer is 'All of the above' - that's always the safe choice, right? Just kidding, just kidding. Gotta keep those AI models in check, though.
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Delsie
10 days ago
A) Ongoing auditing and monitoring of data that is used in AI applications
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Delisa
24 days ago
C) Using data that contains more examples of minority groups than majority groups
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Stanford
29 days ago
B) Excluding data features from the AI application to benefit a population
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Son
1 months ago
A) Ongoing auditing and monitoring of data that is used in AI applications
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Mohammad
2 months ago
Using more data on minority groups? Now that's an interesting idea. But I wonder if it would just create a new kind of bias. Hmm, tough choice.
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Jenise
1 months ago
C) Using data that contains more examples of minority groups than majority groups
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Alyce
1 months ago
B) Excluding data features from the AI application to benefit a population
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Mose
1 months ago
A) Ongoing auditing and monitoring of data that is used in AI applications
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Carman
2 months ago
Excluding data features? Sounds like a quick fix, but we all know that can lead to other problems. Better to get that data in order first.
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Shenika
27 days ago
C) Using data that contains more examples of minority groups than majority groups
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Gerald
1 months ago
A) That's true, ongoing auditing and monitoring of data is crucial to ensure fairness in AI applications.
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Carisa
2 months ago
B) Excluding data features from the AI application to benefit a population
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Anastacia
2 months ago
A) Ongoing auditing and monitoring of data that is used in AI applications
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Reita
2 months ago
I think excluding data features from the AI application to benefit a population could also help in mitigating bias.
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Laquanda
2 months ago
I believe option C) Using data that contains more examples of minority groups is also a good technique to ensure fairness.
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Samira
3 months ago
Ongoing auditing and monitoring of data is the way to go. Gotta keep an eye on those AI models to make sure they're not biased, you know?
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Alishia
2 months ago
B) Excluding data features from the AI application to benefit a population
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Darell
2 months ago
That's right, we need to constantly check the data to ensure fairness.
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Shanice
2 months ago
A) Ongoing auditing and monitoring of data that is used in AI applications
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Ivory
3 months ago
I agree with Lisha. It's important to regularly check the data for bias.
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Lisha
3 months ago
I think the answer is A) Ongoing auditing and monitoring of data.
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