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You're a software engineering student working at a tech startup during your sum...

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You're a software engineering student working at a tech startup during your summer internship. Your team is developing an AI-powered job recommendation system for college students. While you've memorized the ACM Code of Ethics principles, you're discovering that real-world ethical dilemmas are more complex than the code directly addresses.

Current Situation:

Your job recommendation AI has been trained on historical hiring data and consistently recommends higher-paying tech jobs to male students and lower-paying service jobs to female students with identical qualifications. Your supervisor says this "reflects market realities" and the ACM Code doesn't explicitly forbid using historical data patterns.

The Challenge:

The ACM Code provides general principles like "avoid harm" and "be fair," but it doesn't tell you specifically how to handle this complex situation. You need a systematic way to think through the ethical implications and make a reasoned decision.

Your teammate argues: "The ACM Code says 'be fair' and we're being fair by treating all students' data the same way. We don't need to overthink this."

What limitation of professional codes does this reveal?

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