Deal of The Day! Hurry Up, Grab the Special Discount - Save 25% - Ends In 00:00:00 Coupon code: SAVE25
Welcome to Pass4Success

- Free Preparation Discussions
Mail Us support@pass4success.com
Location US
Mob_nav_barsMENU

Salesforce AI Associate Exam - Topic 2 Question 53 Discussion

How does data quality impact the trustworthiness of Al-driven decisions?
B) High-quality data improves the reliability and credibility of Al-driven decisions, fostering trust among users.
A) The use of both low-quality and high-quality data can improve the accuracy and reliability of AI-driven decisions.
C) Low-quality data reduces the risk of overfitting the model, improving the trustworthiness of the predictions.

Salesforce AI Associate Exam - Topic 2 Question 53 Discussion

Actual exam question for Salesforce's Salesforce AI Associate exam
Question #: 53
Topic #: 2
[All Salesforce AI Associate Questions]

How does data quality impact the trustworthiness of Al-driven decisions?

Show Suggested Answer Hide Answer
Suggested Answer: B

''High-quality data improves the reliability and credibility of AI-driven decisions, fostering trust among users. High-quality data means that the data is accurate, complete, consistent, relevant, and timely for the AI task. High-quality data can improve the performance and reliability of AI systems, as they have enough and correct information to learn from and make accurate predictions. High-quality data can also improve the trustworthiness of AI-driven decisions, as users can have more confidence and satisfaction in using AI systems.''


by Meaghan at Mar 05, 2026, 05:34 PM

Limited Time Offer

25%

Off

Get Premium Salesforce AI Associate Questions as Interactive Web-Based Practice Test or PDF

Contribute your Thoughts:

0/2000 characters
Submit Cancel
Argelia
4 days ago
Totally agree, trust comes from reliable data sources!
upvoted 0 times
...
Filiberto
9 days ago
Wait, low-quality data reducing overfitting? That sounds off.
upvoted 0 times
...
Jarod
14 days ago
I disagree, low-quality data can lead to bad decisions.
upvoted 0 times
...
Josephine
19 days ago
High-quality data is definitely key for trust in AI!
upvoted 0 times
...
Gary
24 days ago
Not sure about that, I've seen AI fail with "good" data too.
upvoted 0 times
...
Rusty
2 months ago
Absolutely, high-quality data builds user confidence in AI decisions!
upvoted 0 times
...
Elena
2 months ago
Wait, how does low-quality data reduce overfitting? That sounds off.
upvoted 0 times
...
Carolynn
3 months ago
I disagree, low-quality data can still be useful in some cases.
upvoted 0 times
...
Wilda
3 months ago
High-quality data is definitely key for trust in AI!
upvoted 0 times
...
Carissa
3 months ago
I recall that data quality directly affects AI outcomes, and I feel like B aligns with what we learned about fostering user trust.
upvoted 0 times
...
Eveline
3 months ago
I’m a bit confused about option C. I thought low-quality data usually leads to worse predictions, not better trustworthiness.
upvoted 0 times
...
Benton
3 months ago
I think I came across a practice question that emphasized how high-quality data builds user trust. So, I’m leaning towards option B being the correct answer.
upvoted 0 times
...
Deeanna
4 months ago
I remember studying how high-quality data is crucial for AI, but I'm not entirely sure if low-quality data can ever help improve accuracy.
upvoted 0 times
...
Paris
4 months ago
From what I studied, high-quality data definitely enhances credibility, so I would lean towards option B again.
upvoted 0 times
...
Carolann
4 months ago
I feel like I've seen practice questions where low-quality data was linked to overfitting, but I can't recall if that really boosts trustworthiness.
upvoted 0 times
...
Clay
4 months ago
I'm a bit unsure about option A; I thought mixing low and high-quality data could actually confuse the model rather than improve accuracy.
upvoted 0 times
...
Markus
4 months ago
I remember discussing how high-quality data is crucial for building trust in AI systems, so I think option B makes the most sense.
upvoted 0 times
...

Save Cancel