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 4 Question 28 Discussion

What is a potential source of bias in training data for AI models?
B) The data is skewed toward is particular demographic or source.
A) The data is collected in area time from sources systems.
C) The data is collected from a diverse range of sources and demographics.

Salesforce AI Associate Exam - 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:

0/2000 characters
Submit Cancel
Hubert
9 months ago
C is not a source of bias, that's a good thing!
upvoted 0 times
...
Quentin
10 months ago
I think A is a bigger issue than B.
upvoted 0 times
...
Anjelica
10 months ago
Wait, how can diverse sources lead to bias?
upvoted 0 times
...
Brandon
10 months ago
Totally agree, B is spot on!
upvoted 0 times
...
Kerrie
10 months ago
Bias can definitely come from skewed demographics.
upvoted 0 times
...
Alana
10 months ago
I’m a bit confused about the wording, but I think bias comes from the data being collected from limited sources. That might be option B?
upvoted 0 times
...
Karl
11 months ago
I feel like we practiced a question similar to this, and it was about how biased data can lead to unfair AI outcomes. Option B sounds familiar.
upvoted 0 times
...
Brynn
11 months ago
I’m not entirely sure, but I think option C is actually a good thing, right? It’s about diversity in data, so it shouldn’t introduce bias.
upvoted 0 times
...
Alishia
11 months ago
I remember discussing how bias can arise when data is skewed toward a specific demographic. That seems relevant here.
upvoted 0 times
...
Lettie
11 months ago
I feel pretty good about this one. Bias in training data is a key challenge in AI development, and option B captures a common source of that bias. I'll select that and move on to the next question.
upvoted 0 times
...
Tayna
11 months ago
I'm a bit confused by this question. Are they looking for specific examples of bias, or just a general understanding of the concept? I'll have to re-read the question and options carefully.
upvoted 0 times
...
Aretha
11 months ago
Okay, I've got this. The correct answer is B - the data is skewed toward a particular demographic or source. That's a common issue that can lead to biased models that don't generalize well.
upvoted 0 times
...
William
11 months ago
Hmm, I'm a bit unsure about this one. I know bias in training data is an important issue, but I'm not sure I can confidently identify all the potential sources. I'll have to think this through carefully.
upvoted 0 times
...
India
11 months ago
This seems like a straightforward question. I think the key is to identify potential sources of bias in the training data, which could lead to biased AI models.
upvoted 0 times
...
Vanda
11 months ago
Hmm, I'm a bit unsure about this one. There are a few different options that seem relevant, like setting up service locations, work types, and resource skills. I'll need to carefully review each choice to determine the best approach.
upvoted 0 times
...
Alyce
1 year 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
Alpha
1 year ago
Definitely, we have to be careful with the sources of our training data to ensure fairness.
upvoted 0 times
...
Darrin
1 year ago
It's important to consider where the data is coming from to avoid bias in AI models.
upvoted 0 times
...
Rasheeda
1 year ago
Yeah, option B makes the most sense. We need diverse data for accurate results.
upvoted 0 times
...
Brinda
1 year ago
I agree, biased training data can lead to biased AI models.
upvoted 0 times
...
...
Micah
1 year 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
1 year ago
Definitely, we have to watch out for biased training data in AI models.
upvoted 0 times
...
Weldon
1 year ago
I think option B is more likely. Bias can come from data skewed towards a specific group.
upvoted 0 times
...
Daron
1 year ago
Yeah, option A sounds like a trap. It doesn't even make sense.
upvoted 0 times
...
...
Amber
1 year 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 year ago
C) The data is collected from a diverse range of sources and demographics.
upvoted 0 times
...
Jordan
1 year ago
B) The data is skewed toward is particular demographic or source.
upvoted 0 times
...
Aliza
1 year ago
A) The data is collected in area time from sources systems.
upvoted 0 times
...
...
Dong
1 year 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 year ago
It's important to ensure that the data used is representative of the diverse range of sources and demographics.
upvoted 0 times
...
Deeann
1 year ago
Yes, I agree. Bias in training data can really affect the accuracy of AI models.
upvoted 0 times
...
...
Elli
1 year 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
1 year ago
I agree with Twanna. If the training data is not diverse enough, it could lead to biased AI models.
upvoted 0 times
...
Twanna
1 year 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