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Dell EMC Exam D-GAI-F-01 Topic 5 Question 10 Discussion

Actual exam question for Dell EMC's D-GAI-F-01 exam
Question #: 10
Topic #: 5
[All D-GAI-F-01 Questions]

A team is analyzing the performance of their Al models and noticed that the models are reinforcing existing flawed ideas.

What type of bias is this?

Show Suggested Answer Hide Answer
Suggested Answer: A

When AI models reinforce existing flawed ideas, it is typically indicative of systemic bias. This type of bias occurs when the underlying system, including the data, algorithms, and other structural factors, inherently favors certain outcomes or perspectives. Systemic bias can lead to the perpetuation of stereotypes, inequalities, or unfair practices that are present in the data or processes used to train the model.

The Official Dell GenAI Foundations Achievement document likely covers various types of biases and their impacts on AI systems. It would discuss how systemic bias affects the performance and fairness of AI models and the importance of identifying and mitigating such biases to increase the trust of humans over machines123. The document would emphasize the need for a culture that actively seeks to reduce bias and ensure ethical AI practices.

Confirmation Bias (Option OB) refers to the tendency to process information by looking for, or interpreting, information that is consistent with one's existing beliefs. Linguistic Bias (Option OC) involves bias that arises from the nuances of language used in the data. Data Bias (Option OD) is a broader term that could encompass various types of biases in the data but does not specifically refer to the reinforcement of flawed ideas as systemic bias does. Therefore, the correct answer is A. Systemic Bias.


Contribute your Thoughts:

Elke
2 months ago
Systemic bias, for sure. The whole system is set up to reinforce those flawed ideas. Time to rethink the entire approach.
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Dorthy
2 months ago
Ah, the age-old problem of AI models being as biased as their creators. Classic!
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Valentine
2 months ago
Linguistic bias, maybe? If the language used to train the models is biased, that could definitely lead to these issues. Something to consider.
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Bev
14 days ago
D: Yeah, Linguistic Bias could definitely play a role. If the language used in training the models is biased, it can perpetuate flawed ideas.
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Latonia
28 days ago
C: Confirmation Bias makes sense too. If the team is only looking for evidence that supports their existing ideas, it can lead to reinforcing flawed concepts.
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Patrick
1 months ago
B: Systemic Bias could also be a factor. If there are systemic issues in the organization, it can impact the performance of the AI models.
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Celia
1 months ago
A: I think it might be Data Bias. If the data used to train the models is biased, it can lead to reinforcing flawed ideas.
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Malcom
2 months ago
Hmm, I'm not so sure. Could it be data bias, where the training data itself is flawed and skewing the model's performance? Just a thought.
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Ronny
28 days ago
A: That's a good point, it could be either data bias or confirmation bias.
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Lavonda
1 months ago
B: Maybe it's confirmation bias, where the model is reinforcing existing flawed ideas.
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Terrilyn
1 months ago
A: I think it could be data bias, the training data might be flawed.
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Kendra
2 months ago
This sounds like a classic case of confirmation bias. The AI models are simply reinforcing the preexisting flawed ideas, instead of objectively analyzing the data.
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Raylene
2 months ago
D: That's a problem, we need to address this bias in our models.
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Ellsworth
2 months ago
C: So, it's not really analyzing the data objectively.
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Rebecka
2 months ago
B: Yeah, the AI models are just confirming what they already believe.
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Rupert
2 months ago
A: I think it's confirmation bias.
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Leatha
3 months ago
But could it also be Data Bias since the flawed ideas might be coming from biased data?
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Abraham
3 months ago
I agree with Judy, Confirmation Bias makes sense because the models are reinforcing existing flawed ideas.
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Judy
3 months ago
I think the bias in the AI models is Confirmation Bias.
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