Explanation:
The correct answer is B.
By analyzing and understanding the source of the age bias, InsureMax can take informed steps to recalibrate the AI model. This approach ensures that policy pricing is fair and equitable across different age groups, aligning with ethical guidelines and fairness standards. Recalibrating the AI model to mitigate bias is a crucial step in maintaining trust and adherence to principles of fairness in AI systems.
A is incorrect because implementing a flat-rate policy does not address the underlying issue of bias in the AI system. While it might seem like a quick fix, it overlooks the importance of a nuanced and accurate risk assessment that is fair and free of bias.
C is incorrect as simply removing age as a factor could oversimplify the risk assessment process and might not result in fair or accurate policy pricing. The goal should be to ensure the AI system assesses risk fairly, not to eliminate relevant factors from the assessment.
D is incorrect because offering discounts is a temporary measure that doesn't solve the problem of bias in the AI system. It is important to address and correct the bias within the AI model to ensure long-term fairness and compliance with ethical standards.
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Q.5712 You are the lead data analyst at "InsureMax," an insurance company utilizing AI for risk assessment and policy pricing. After implementing the AI system, it becomes apparent that policyholders in certain age groups are consistently receiving higher quotes, leading to accusations of age bias. The pattern suggests that the AI model may be inadvertently discriminating against these age groups, potentially violating fair practice standards and ethical guidelines. What action should InsureMax take to address the potential age bias in its AI system, in line with the principles of fairness and harmful bias management in the AI Risk Management Framework?
A
Implement a flat-rate policy for all age groups to immediately eliminate any appearance of age bias.
B
Analyze the AI system’s algorithm to identify and understand the source of the age bias, and recalibrate the model to ensure fair and equitable policy pricing across all age groups.
C
Remove age as a factor in the AI system’s risk assessment algorithm to prevent any possibility of age-related bias in policy pricing.
D
Offer discounts to the affected age groups as a temporary measure while continuing to use the current AI system without modifications.