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Quiz: Fairness in Ethics

Test your understanding of fairness concepts from evolutionary biology to human rights and AI systems.

1. What evidence from Frans de Waal's capuchin monkey experiments suggests that fairness is not uniquely human?

  1. Monkeys learned to share food equally when rewarded with treats
  2. Monkeys rejected unequal rewards and showed protest behaviors when treated unfairly compared to peers
  3. Monkeys developed written rules for distributing food among group members
  4. Monkeys showed no reaction to how other monkeys were treated
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The correct answer is B. In de Waal's experiments, capuchin monkeys who received cucumber while watching a partner receive grapes (a preferred treat) exhibited dramatic protest behaviors including refusing to eat, throwing food back at researchers, and shaking their cages. This "inequity aversion" demonstrates that fairness detection operates at an emotional level in non-human primates.

Concept Tested: Fairness Studies in Primates

2. According to evolutionary biology, which mechanism best explains why fairness sensitivity developed in social species?

  1. Fairness made animals more attractive to potential mates
  2. Reciprocal altruism and reputation monitoring enabled stable cooperative relationships essential for survival
  3. Fair animals were able to find more food through individual hunting
  4. Fairness was taught by parent animals to their offspring through verbal instruction
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The correct answer is B. Evolutionary biologists propose that fairness sensitivity evolved through reciprocal altruism (fair exchanges with non-relatives built coalitions) and reputation monitoring (tracking who cooperates fairly enabled optimal partner selection). These mechanisms required cognitive abilities to track social exchanges and remember past interactions.

Concept Tested: Fairness as a Biological Adaptation

3. In the context of cultural fairness frameworks, what is the key difference between the equity principle and the equality principle?

  1. Equity focuses on individual rights while equality focuses on group harmony
  2. Equity distributes resources proportional to contribution while equality distributes resources equally regardless of contribution
  3. Equity applies to economic decisions while equality applies to political decisions
  4. Equity is used in Western cultures while equality is used in Eastern cultures
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The correct answer is B. The equity principle holds that resources should be distributed proportional to contribution or merit, while the equality principle holds that resources should be distributed equally regardless of contribution. Different cultures weight these principles differently, and even within cultures, the appropriate principle may depend on the domain (workplace vs. family vs. civic life).

Concept Tested: Cultural Dimensions of Fairness

4. Which historical shift in fairness conceptions demonstrates that moral progress is possible but not automatic?

  1. The invention of currency for economic exchange
  2. The development of democratic voting systems in ancient Greece
  3. Practices once considered fair (like slavery) are now universally condemned as profound injustices
  4. The creation of international trade agreements
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The correct answer is C. The chapter emphasizes that practices once considered perfectly fair—such as slavery, denying women the vote, and child labor—are now recognized as profound injustices. This pattern suggests that moral progress requires advocacy, evidence, and expansion of moral imagination to include previously excluded groups.

Concept Tested: Fairness Changes Over Time

5. What does the Universal Declaration of Human Rights (UDHR) Article 1 establish as the foundation for fairness?

  1. All nations must adopt democratic governments
  2. All human beings are born free and equal in dignity and rights
  3. Economic resources must be distributed equally among all people
  4. Religious institutions should determine fairness standards
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The correct answer is B. Article 1 of the UDHR states that "all human beings are born free and equal in dignity and rights." This principle, established in 1948 after World War II, represents humanity's most ambitious attempt to codify universal fairness principles and has influenced countless national constitutions and international treaties.

Concept Tested: Fairness as a Human Right

6. A healthcare algorithm consistently recommends fewer treatments for patients from minority groups, even when they have the same medical conditions as other patients. This is an example of which AI fairness problem?

  1. Feedback loop bias where biased outputs become inputs for future training
  2. Hardware malfunction causing random errors
  3. User interface design issues
  4. Insufficient computing power
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The correct answer is A. AI systems can perpetuate unfairness through feedback loops where biased outputs become inputs for future training. The chapter documents real examples including healthcare algorithms that underestimated Black patients' needs because they learned from historical data reflecting past discrimination.

Concept Tested: Fairness in AI

7. Why is it mathematically impossible to satisfy all definitions of algorithmic fairness simultaneously?

  1. Computer processors cannot handle multiple fairness calculations at once
  2. Different fairness definitions (demographic parity, equalized odds, individual fairness) often conflict mathematically
  3. Programmers have not yet developed efficient enough algorithms
  4. Government regulations prohibit using multiple fairness metrics
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The correct answer is B. Computer scientists have proposed numerous formal definitions of fairness—demographic parity, equalized odds, individual fairness, and counterfactual fairness—but these definitions are often mathematically incompatible. A system cannot satisfy all of them simultaneously, echoing deeper philosophical debates about fairness having no neutral, context-free definition.

Concept Tested: Competing Definitions of Algorithmic Fairness

8. In the case study comparing AI models' evaluations of historical fairness leaders, which three figures appeared on every model's list of champions of fairness?

  1. Eleanor Roosevelt, Abraham Lincoln, and Susan B. Anthony
  2. Nelson Mandela, Mahatma Gandhi, and Martin Luther King Jr.
  3. Frederick Douglass, Harriet Tubman, and Cesar Chavez
  4. Malala Yousafzai, Desmond Tutu, and Greta Thunberg
Show Answer

The correct answer is B. When four AI systems (Claude, ChatGPT, Grok, and DeepSeek) were asked to identify champions of fairness, three figures appeared on every list: Nelson Mandela, Mahatma Gandhi, and Martin Luther King Jr. This universal consensus suggests these figures have achieved near-universal recognition as moral exemplars.

Concept Tested: Case Study - Ranking Fairness Leaders

9. According to the chapter, what does the variation between different AI models' fairness evaluations reveal?

  1. AI models are completely unreliable for moral judgments
  2. Training data, cultural perspectives, and temporal scope affect how AI systems evaluate moral leadership
  3. Only one AI model can be correct about historical fairness
  4. AI models should not be used for any historical analysis
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The correct answer is B. The variations between AI models reveal that training data matters (different corpora emphasize different narratives), cultural perspectives differ (some models showed more global diversity), and temporal scope varies (some focused on recent figures, others on historical ones). This demonstrates that AI systems embed and amplify human conceptions of fairness.

Concept Tested: How AI Systems Reflect Human Biases

10. A company wants to implement a hiring algorithm. Based on the chapter's discussion of fairness, which approach would best address potential bias?

  1. Use only test scores since numbers are inherently objective
  2. Recognize that no single fairness definition works for all contexts and explicitly choose which fairness principles to prioritize
  3. Avoid using any algorithm since technology cannot be fair
  4. Copy the algorithm used by the most successful company in the industry
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The correct answer is B. The chapter emphasizes that multiple fairness principles can conflict and "there is no neutral, context-free definition that everyone will accept." Wisdom involves recognizing which principle applies in which context. For hiring, this means explicitly choosing whether to prioritize demographic parity, individual fairness, or other definitions while being transparent about trade-offs.

Concept Tested: Algorithmic Fairness Application

Summary

This quiz covered key concepts from the Fairness in Ethics chapter:

  • Evolutionary origins of fairness in social animals
  • Cultural variations in fairness conceptions
  • The Universal Declaration of Human Rights
  • Algorithmic fairness challenges in AI systems
  • Historical perspectives on moral progress
  • Case study analysis of AI evaluations of fairness leaders