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CertNexus Exam AIP-210 Topic 1 Question 9 Discussion

Actual exam question for CertNexus's AIP-210 exam
Question #: 9
Topic #: 1
[All AIP-210 Questions]

An AI practitioner incorporates risk considerations into a deployment plan and decides to log and store historical predictions for potential, future access requests.

Which ethical principle is this an example of?

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Suggested Answer: B

The final stage of the data management life cycle is data destruction, which is the process of securely deleting or erasing data that is no longer needed or relevant for the organization. Data destruction ensures that data is disposed of in compliance with any legal or regulatory requirements, as well as any internal policies or standards. Data destruction also protects the organization from potential data breaches, leaks, or thefts that could compromise its privacy and security. Data destruction can be performed using various methods, such as overwriting, degaussing, shredding, or incinerating


by Jovita at Dec 15, 2023, 01:58 AM

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Denise
14 days ago
Ah, the old 'log everything and hope for the best' approach. Ethical, sure, but it's like trying to fact-check a politician's speech – good luck with that!
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Stephanie
15 days ago
Logging predictions, huh? I hope they have plenty of storage space, 'cause my code tends to make some pretty wild guesses sometimes.
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Felix
21 days ago
Hmm, I'd say fairness. Keeping track of the predictions helps ensure the AI system is being fair and unbiased in its decision-making. Transparency is cool too, I guess.
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Stanton
24 days ago
Safety, for sure. Logging predictions helps identify potential risks or issues down the line. Proactive approach, I like it.
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Renea
14 hours ago
A) Fairness
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Albert
4 days ago
A: Safety, for sure. Logging predictions helps identify potential risks or issues down the line.
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Casey
2 months ago
I'm not sure, but I think it could also be A) Fairness. By storing historical predictions, the AI practitioner is ensuring fairness in future access requests.
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Gregg
2 months ago
I think this is about privacy. Storing people's prediction data could be a sensitive issue if not handled properly. Gotta be careful with that.
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Leota
9 days ago
B: I agree, it's important to be transparent about how the data is being used and stored.
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Bo
12 days ago
A: I think it's more about transparency. Keeping a record of predictions can help ensure accountability.
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Malika
13 days ago
Transparency is also important in this case, so people know how their data is being used and stored.
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Alaine
15 days ago
I agree, privacy is definitely a key concern when it comes to storing sensitive data like predictions.
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Dyan
2 months ago
I agree with Fidelia. It's important to be transparent about how AI predictions are used.
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Fidelia
2 months ago
I think it's D) Transparency.
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Fletcher
2 months ago
Definitely transparency. Logging and storing historical predictions allows for future access and accountability. That's key for ethical AI principles.
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