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Oracle Exam 1Z0-1122-24 Topic 1 Question 17 Discussion

Actual exam question for Oracle's 1Z0-1122-24 exam
Question #: 17
Topic #: 1
[All 1Z0-1122-24 Questions]

What is the difference between classification and regression in Supervised Machine Learning?

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Suggested Answer: A

Explicability is the AI Ethics principle that leads to the Responsible AI requirement of transparency. This principle emphasizes the importance of making AI systems understandable and interpretable to humans. Transparency is a key aspect of explicability, as it ensures that the decision-making processes of AI systems are clear and comprehensible, allowing users to understand how and why a particular decision or output was generated. This is critical for building trust in AI systems and ensuring that they are used responsibly and ethically.

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Laurel
5 days ago
I see your point, Gianna. So, the answer is indeed A) Explicability.
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Gianna
8 days ago
Fairness is important too, but in this case, it's more about being able to understand and explain the AI's decisions.
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Mabel
11 days ago
But what about fairness? Doesn't that also play a role in transparency?
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Laurel
15 days ago
I agree with Gianna, transparency is all about being able to explain how AI decisions are made.
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Gianna
18 days ago
I think the answer is A) Explicability.
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Felicitas
22 days ago
Haha, I bet the AI assistant created this question. But I'll go with A) Explicability - it seems like the most relevant principle for requiring transparency.
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Krystina
1 days ago
User1: I think A) Explicability is the right answer.
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Barbra
24 days ago
Hmm, I'm not sure. I was thinking D) Fairness might be the right answer since being transparent is important for ensuring AI is fair and unbiased.
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Nan
27 days ago
I think the answer is A) Explicability. It makes sense that being transparent about how AI systems work is part of the Responsible AI principle.
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Allene
8 days ago
Transparency is crucial for building trust in AI systems.
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Viola
13 days ago
I agree, A) Explicability is the right answer.
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