Question 41

Fairness

The ethical concern corresponding to the discrimination against members of federally protected classes by an AI system is fairness. This issue highlights the need for equitable treatment and non-discrimination in algorithmic decision-making processes.

A) Safety

Safety refers to the protection of individuals from harm or danger. While safety is an important ethical concern in AI, it is not directly related to the issue of discrimination against protected classes. Therefore, this option does not adequately address the ethical implications of biased AI systems.

B) Transparency

Transparency involves the clarity and openness of AI systems, particularly in how decisions are made. Although transparency is crucial for understanding AI operations, the primary concern in this scenario is the fairness of outcomes rather than the visibility of the processes. Thus, this option does not capture the core ethical issue.

C) Privacy

Privacy pertains to the protection of personal information and data. While privacy is a significant ethical concern in the realm of AI, it does not specifically address the discrimination faced by certain groups. Therefore, this option is not relevant to the issue of fairness in AI outcomes.

D) Fairness

Fairness directly addresses the ethical implications of biased treatment that occurs when AI systems discriminate against certain federally protected classes. This concern calls for accountability and the rectification of biases to ensure equitable treatment for all individuals, making it the most relevant option in this context.

Conclusion

The correct answer, fairness, is fundamentally tied to the ethical obligations of AI systems to avoid discrimination. All other options—safety, transparency, and privacy—fail to address the core issue of equitable treatment, which is critical when considering the impact of AI on marginalized groups. Hence, fairness is the paramount concern in the scenario presented.