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IAPP Exam AIGP Topic 1 Question 7 Discussion

Actual exam question for IAPP's AIGP exam
Question #: 7
Topic #: 1
[All AIGP Questions]

CASE STUDY

Please use the following answer the next question:

A local police department in the United States procured an Al system to monitor and analyze social media feeds, online marketplaces and other sources of public information to detect evidence of illegal activities (e.g., sale of drugs or stolen goods). The Al system works by surveilling the public sites in order to identify individuals that are likely to have committed a crime. It cross-references the individuals against data maintained by law enforcement and then assigns a percentage score of the likelihood of criminal activity based on certain factors like previous criminal history, location, time, race and gender.

The police department retained a third-party consultant assist in the procurement process, specifically to evaluate two finalists. Each of the vendors provided information about their system's accuracy rates, the diversity of their training data and how their system works. The consultant determined that the first vendor's system has a higher accuracy rate and based on this information, recommended this vendor to the police department.

The police department chose the first vendor and implemented its Al system. As part of the implementation, the department and consultant created a usage policy for the system, which includes training police officers on how the system works and how to incorporate it into their investigation process.

The police department has now been using the Al system for a year. An internal review has found that every time the system scored a likelihood of criminal activity at or above 90%, the police investigation subsequently confirmed that the individual had, in fact, committed a crime. Based on these results, the police department wants to forego investigations for cases where the Al system gives a score of at least 90% and proceed directly with an arrest.

During the procurement process, what is the most likely reason that the third-party consultant asked each vendor for information about the diversity of their datasets?

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Suggested Answer: B

The third-party consultant asked each vendor for information about the diversity of their datasets to assist in ensuring the fairness of the AI system. Diverse datasets help prevent biases and ensure that the AI system performs equitably across different demographic groups. This is crucial for a law enforcement application, where fairness and avoiding discriminatory practices are of paramount importance. Ensuring diversity in training data helps in building a more just and unbiased AI system. Reference: AIGP Body of Knowledge on Ethical AI and Fairness.


Contribute your Thoughts:

Denise
3 months ago
Just let the robots do the arresting, what could go wrong? I'm sure this will end well for everyone involved.
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Salley
3 months ago
90% accuracy sounds too good to be true. I wonder if the consultant did a deep dive on the methodology, or just took the vendors' word for it.
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Tonette
2 months ago
The consultant likely wanted to evaluate reliability.
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Blair
3 months ago
It helps ensure fairness in the system.
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Xuan
3 months ago
Vendor diversity is important for accuracy.
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Deonna
4 months ago
Yes, having diverse training data can help prevent bias in the Al system.
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Noel
4 months ago
I believe it's also to make sure the system is reliable and accurate.
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Rosann
4 months ago
I agree with Art. It's important for the system to be unbiased.
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Chaya
4 months ago
I'd be a bit concerned about the high accuracy rate. Are they sure the system isn't just profiling certain demographics?
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Micheal
3 months ago
The accuracy rate may be high, but it's crucial to address any potential biases in the system.
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Weldon
3 months ago
The consultant likely asked about diversity to ensure the system is not unfairly targeting specific groups.
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Leota
4 months ago
The diversity of the training data could impact the accuracy and fairness of the system.
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Stephaine
4 months ago
It's important to consider bias in the data used for training the system.
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Chau
4 months ago
The diversity of the training data is crucial to ensure the AI system doesn't discriminate against certain groups. Good catch by the consultant!
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Lisha
3 months ago
Agreed, the consultant made a smart move by considering that aspect.
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Virgina
3 months ago
Yes, it's important to have diverse training data to avoid bias.
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Art
5 months ago
I think the consultant asked about dataset diversity to ensure fairness.
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