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 Exam Salesforce AI Associate Topic 4 Question 28 Discussion

Actual exam question for Salesforce's Salesforce AI Associate exam
Question #: 28
Topic #: 4
[All Salesforce AI Associate Questions]

What is a potential source of bias in training data for AI models?

Show Suggested Answer Hide Answer
Suggested Answer: B

To enhance the quality of lead data in their CRM system, the most effective process is to review and update missing lead information. This process involves identifying incomplete records and filling in missing details, which can significantly improve the accuracy and usefulness of lead data. Accurate and complete lead information is crucial for effective lead scoring, prioritization, and follow-up, enhancing overall sales performance. Salesforce CRM offers data quality tools and features that assist in regularly reviewing and maintaining the accuracy of lead data. Information on managing lead data quality in Salesforce can be found at Salesforce Lead Management.


by Olga at Sep 19, 2024, 01:41 AM

Limited Time Offer

25%

Off

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

Contribute your Thoughts:

Submit Cancel
Alyce
1 months ago
Okay, let's think this through. Option B sounds like the clear winner here. Skewed data = biased models. I'm feeling pretty confident about this one.
upvoted 0 times
Darrin
2 days ago
It's important to consider where the data is coming from to avoid bias in AI models.
upvoted 0 times
...
Rasheeda
16 days ago
Yeah, option B makes the most sense. We need diverse data for accurate results.
upvoted 0 times
...
Brinda
22 days ago
I agree, biased training data can lead to biased AI models.
upvoted 0 times
...
...
Micah
2 months ago
Haha, I bet the exam writers would love to see us all pick option A and watch us all fail. 'The data is collected in area time from sources systems' - what even is that?
upvoted 0 times
Detra
6 days ago
Definitely, we have to watch out for biased training data in AI models.
upvoted 0 times
...
Weldon
27 days ago
I think option B is more likely. Bias can come from data skewed towards a specific group.
upvoted 0 times
...
Daron
29 days ago
Yeah, option A sounds like a trap. It doesn't even make sense.
upvoted 0 times
...
...
Amber
2 months ago
Ah, I see what they're getting at. If the data is collected from a diverse range of sources and demographics, that's actually less prone to bias. Gotta watch out for those sneaky exam writers!
upvoted 0 times
Carla
1 months ago
C) The data is collected from a diverse range of sources and demographics.
upvoted 0 times
...
Jordan
1 months ago
B) The data is skewed toward is particular demographic or source.
upvoted 0 times
...
Aliza
1 months ago
A) The data is collected in area time from sources systems.
upvoted 0 times
...
...
Dong
3 months ago
Hmm, answer B sounds about right. Training data that's skewed toward a particular demographic or source could definitely introduce bias into the model. I hope the exam writers didn't just throw that option in as a distractor!
upvoted 0 times
Karima
1 months ago
It's important to ensure that the data used is representative of the diverse range of sources and demographics.
upvoted 0 times
...
Deeann
2 months ago
Yes, I agree. Bias in training data can really affect the accuracy of AI models.
upvoted 0 times
...
...
Elli
3 months ago
But what if the data is collected from a diverse range of sources and demographics? Wouldn't that help reduce bias in the AI models?
upvoted 0 times
...
Maia
3 months ago
I agree with Twanna. If the training data is not diverse enough, it could lead to biased AI models.
upvoted 0 times
...
Twanna
3 months ago
I think a potential source of bias could be if the data is skewed toward a particular demographic or source.
upvoted 0 times
...

Save Cancel