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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?

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Suggested Answer: B

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

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Hubert
3 months ago
C is not a source of bias, that's a good thing!
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Quentin
3 months ago
I think A is a bigger issue than B.
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Anjelica
3 months ago
Wait, how can diverse sources lead to bias?
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Brandon
4 months ago
Totally agree, B is spot on!
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Kerrie
4 months ago
Bias can definitely come from skewed demographics.
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Alana
4 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?
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Karl
4 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.
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Brynn
4 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.
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Alishia
5 months ago
I remember discussing how bias can arise when data is skewed toward a specific demographic. That seems relevant here.
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Lettie
5 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.
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Tayna
5 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.
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Aretha
5 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.
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William
5 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.
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India
5 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.
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Vanda
5 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.
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Alyce
9 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.
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Alpha
8 months ago
Definitely, we have to be careful with the sources of our training data to ensure fairness.
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Darrin
8 months ago
It's important to consider where the data is coming from to avoid bias in AI models.
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Rasheeda
8 months ago
Yeah, option B makes the most sense. We need diverse data for accurate results.
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Brinda
9 months ago
I agree, biased training data can lead to biased AI models.
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Micah
10 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?
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Detra
8 months ago
Definitely, we have to watch out for biased training data in AI models.
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Weldon
9 months ago
I think option B is more likely. Bias can come from data skewed towards a specific group.
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Daron
9 months ago
Yeah, option A sounds like a trap. It doesn't even make sense.
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Amber
10 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!
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Carla
9 months ago
C) The data is collected from a diverse range of sources and demographics.
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Jordan
9 months ago
B) The data is skewed toward is particular demographic or source.
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Aliza
9 months ago
A) The data is collected in area time from sources systems.
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Dong
11 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!
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Karima
9 months ago
It's important to ensure that the data used is representative of the diverse range of sources and demographics.
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Deeann
10 months ago
Yes, I agree. Bias in training data can really affect the accuracy of AI models.
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Elli
11 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?
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Maia
11 months ago
I agree with Twanna. If the training data is not diverse enough, it could lead to biased AI models.
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Twanna
11 months ago
I think a potential source of bias could be if the data is skewed toward a particular demographic or source.
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