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CSS 325 Ethics - Finals Mock Exam Review - UOPX 2025

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CSS 325 Ethics - Finals Mock Exam Review - UOPX 2025CSS 325 Ethics - Finals Mock Exam Review - UOPX 2025CSS 325 Ethics - Finals Mock Exam Review - UOPX 2025

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Subido en
28 de mayo de 2025
Número de páginas
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Escrito en
2024/2025
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CSS 325 Ethics in Computer Science

Finals Mock Exam Review

(Questions & Solutions)

2025




©2025

, Question 1:
A computer scientist is evaluating the ethical justification for a new data-
mining project. Which ethical theory suggests that the project should be
implemented if it maximizes overall happiness, even if some individuals’
privacy is compromised?
- A. Deontological Ethics
- B. Utilitarianism
- C. Virtue Ethics
- D. Rights-Based Ethics

ANS: B. Utilitarianism
Rationale: Utilitarianism focuses on maximizing overall happiness or
welfare. In this context, if the benefits (e.g., improved services, public
good) outweigh the harms (e.g., some privacy loss), utilitarianism may
justify the project.

---

Question 2:
A technology firm is developing an AI algorithm for credit scoring. Which
ethical concern is most critical regarding algorithmic decision making?
- A. Ensuring transparency and explainability
- B. Maximizing profit margins
- C. Reducing computational complexity
- D. Achieving higher processing speeds

ANS: A. Ensuring transparency and explainability
Rationale: Ethical AI requires that decisions (especially those affecting
individuals’ financial opportunities) are transparent and explainable, so
that users can understand and trust the process.

---


©2025

, Question 3:
A cybersecurity researcher discovers a vulnerability in a popular software
product. The researcher is faced with an ethical dilemma between
responsible disclosure and immediate public release. Which of the
following actions best aligns with responsible disclosure practices?
- A. Immediately publishing all details to alert users
- B. Reporting the vulnerability privately to the vendor and allowing
them time to patch
- C. Keeping the information confidential for personal gain
- D. Sharing the vulnerability only on social media

ANS: B. Reporting the vulnerability privately to the vendor and
allowing them time to patch
Rationale: Responsible disclosure involves informing the vendor
privately to provide an opportunity to patch the vulnerability before
public release, thereby protecting users while upholding ethical
responsibilities.

---

Question 4:
In the realm of intellectual property law, which concept ensures that
original computer programs are protected from unauthorized copying or
distribution?
- A. Trademark
- B. Copyright
- C. Patent
- D. Trade secret

ANS: B. Copyright
Rationale: Copyright law protects original works of authorship—
including computer programs—by granting the owner exclusivity in
reproducing and distributing the work.

---
©2025

, Question 5:
A software engineer working for a major tech company is considering
whistleblowing after discovering unethical practices related to data
manipulation. Which ethical framework primarily supports the argument
for whistleblowing based on duty and adherence to moral principles?
- A. Utilitarianism
- B. Deontological Ethics
- C. Egoism
- D. Cultural Relativism

ANS: B. Deontological Ethics
Rationale: Deontological ethics emphasizes duty and adherence to
moral rules. A whistleblower acting on deontological principles would
report unethical practices regardless of potential negative consequences
to maximize moral integrity.

---

Question 6:
In discussion of algorithmic fairness, a data scientist is tasked with
minimizing bias in the training data. Which strategy is most effective in
mitigating bias that could lead to discriminatory decisions?
- A. Increasing the volume of data without quality control
- B. Using diverse, representative data samples and fairness-aware
algorithms
- C. Relying only on historical data regardless of its biases
- D. Disregarding input features that seem sensitive

ANS: B. Using diverse, representative data samples and fairness-
aware algorithms
Rationale: Mitigating bias involves ensuring that training data reflects
the diversity of the population and using algorithms designed to detect
and correct bias, thus leading to fairer outcomes.


©2025
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