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

Oracle Exam 1Z0-1122-24 Topic 6 Question 13 Discussion

Actual exam question for Oracle's 1Z0-1122-24 exam
Question #: 13
Topic #: 6
[All 1Z0-1122-24 Questions]

Which AI Ethics principle leads to the Responsible AI requirement of transparency?

Show Suggested Answer Hide Answer
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.

Top of Form

Bottom of Form


Contribute your Thoughts:

Leanna
4 months ago
Hmm, this is a tough one. I'm going to go with A) Explicability. It just makes the most sense for transparency, doesn't it? Although, I'm not sure if the other options are completely wrong either.
upvoted 0 times
...
Elsa
4 months ago
The answer has to be C) Respect for human autonomy. Transparency allows users to make informed decisions and maintain control over the AI system.
upvoted 0 times
Kaitlyn
2 months ago
D) Fairness
upvoted 0 times
...
Marvel
2 months ago
C) Respect for human autonomy
upvoted 0 times
...
Arlette
3 months ago
B) Prevention of harm
upvoted 0 times
...
Delfina
3 months ago
A) Explicability
upvoted 0 times
...
...
Gwenn
4 months ago
B) Prevention of harm is my guess. Transparency helps users understand how the AI is making decisions, which is crucial for mitigating potential harms.
upvoted 0 times
Emogene
3 months ago
C) Respect for human autonomy and Fairness are also crucial AI Ethics principles, but they may not directly lead to transparency like Explicability does.
upvoted 0 times
...
Cornell
3 months ago
B) Prevention of harm is important too, but in this case, it's Explicability that directly relates to transparency.
upvoted 0 times
...
Doug
3 months ago
A) Explicability is the principle that leads to transparency. It ensures that AI systems are understandable to users.
upvoted 0 times
...
...
Reid
4 months ago
D) Fairness seems like the most relevant option here. Responsible AI requires transparency to ensure fairness and avoid bias in the system.
upvoted 0 times
...
Mammie
4 months ago
I think the answer is A) Explicability. Transparency is about making the AI system's decision-making process understandable, which aligns with the explicability principle.
upvoted 0 times
Lorean
3 months ago
A) Explicability is essential for ensuring that AI systems are accountable and can be scrutinized for any biases or errors.
upvoted 0 times
...
Bok
4 months ago
Transparency is key for building trust in AI systems. A) Explicability ensures that the decision-making process is clear and understandable.
upvoted 0 times
...
Rosalia
4 months ago
I agree, A) Explicability is the right answer. Transparency is crucial for understanding how AI systems make decisions.
upvoted 0 times
...
...
Dorothea
4 months ago
I think the answer is A) Explicability too, as it directly relates to transparency.
upvoted 0 times
...
Willie
4 months ago
I believe it could also be D) Fairness, as being transparent is also about being fair.
upvoted 0 times
...
Della
4 months ago
I agree with Viva, because transparency requires explanations.
upvoted 0 times
...
Viva
5 months ago
I think the answer is A) Explicability.
upvoted 0 times
...

Save Cancel
az-700  pass4success  az-104  200-301  200-201  cissp  350-401  350-201  350-501  350-601  350-801  350-901  az-720  az-305  pl-300  

Warning: Cannot modify header information - headers already sent by (output started at /pass.php:70) in /pass.php on line 77