Free Isaca AAISM Actual Exam Questions - Question 9 Discussion
applications. Which of the following should be given the HIGHEST priority in the system’s design to
ensure ethical decision-making and prevent bias?
Good point about objective metrics not being bias-free inherently. I’d say B is key since letting customers appeal decisions adds transparency and helps catch potential errors or biases the system missed. B
Maybe C makes more sense since having human experts oversee decisions can catch biases that the AI might miss, adding a layer of ethical judgment beyond just data metrics.
It’s D because using only objective financial metrics limits the chance of introducing biased or subjective factors, which is crucial for fairness in credit assessments. Human judgment can still bring bias in.
Good point about humans catching AI errors, but I think B stands out more here because allowing customers to appeal directly addresses fairness and bias from the user side. Even if the system is well-designed, errors or biases can slip through, so giving people a way to challenge decisions feels crucial. Plus, appeals can reveal hidden issues the model might miss. So I’d go with B on this one.
Option A might be risky if new data reinforces existing biases instead of correcting them. Shouldn't the focus be more on monitoring and mitigating bias rather than just updating for accuracy?
C/D? I think having humans in the loop (C) helps catch any AI mistakes or biases before final decisions. Just using objective metrics (D) might miss important context or hidden biases in the data.
Option D sounds like a trap since financial metrics alone can still carry bias. I think B’s better since allowing appeals helps fix errors and unfairness in decisions.