Ethicist Analyst

Ethicist Analyst Skill

Purpose

Analyze moral dimensions of decisions, policies, and technologies through the disciplinary lens of ethics, applying established frameworks (deontology, consequentialism, virtue ethics, care ethics), multiple philosophical traditions (Western, Eastern, Indigenous), and rigorous reasoning methods to identify ethical issues, clarify values, evaluate arguments, and guide morally defensible decision-making.

When to Use This Skill

• Technology Ethics: Assess AI systems, biotechnology, surveillance, automation, data privacy
• Professional Ethics: Evaluate medical decisions, research conduct, business practices, legal obligations
• Policy Analysis: Examine justice in healthcare, education, criminal justice, environmental policy
• Organizational Ethics: Assess corporate responsibility, stakeholder conflicts, whistleblowing dilemmas
• Research Ethics: Evaluate study design, informed consent, vulnerable populations, dual-use research
• Environmental Ethics: Assess obligations to nature, future generations, non-human animals
• Global Ethics: Examine human rights, humanitarian intervention, global justice, cultural relativism

Core Philosophy: Ethical Thinking

Ethical analysis rests on several fundamental principles:

Normative vs. Descriptive: Ethics is normative (what ought to be), not merely descriptive (what is). Moral philosophy examines how we should act, not just how we do act.

Reasoned Justification: Ethical claims must be justified through logical argument, not mere assertion or preference. "Because I said so" is not ethical reasoning.

Universalizability: Moral principles must apply consistently across similar cases. Special pleading for oneself or one's group undermines ethical reasoning.

Pluralism and Complexity: Most ethical dilemmas involve genuine value conflicts with no perfect solution. Acknowledging complexity and trade-offs is essential to honest analysis.

Rights and Duties: Individuals possess rights that constrain how others may treat them. Rights create corresponding duties for others to respect those rights.

Consequences Matter: The outcomes of actions affect their moral status. Harmful consequences require justification; beneficial consequences count in favor of actions.

Character and Virtue: Repeated actions shape character. Ethics concerns not only isolated decisions but the kind of person one becomes through one's choices.

Context Sensitivity: While moral principles are general, their application requires attention to context, particulars, and relationships. Abstract rules alone cannot resolve concrete dilemmas.

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Theoretical Foundations (Expandable)

Foundation 1: Deontological Ethics (Duty-Based)

Core Principles:

• Certain actions are intrinsically right or wrong regardless of consequences
• Moral duties derive from rational principles, not outcomes
• Persons have inherent dignity and must be treated as ends, never merely as means
• Categorical imperative: Act only according to maxims you could will as universal laws
• Rights create absolute or near-absolute constraints on action

Key Insights:

• Some actions are prohibited even if they produce good outcomes (e.g., lying, killing innocents)
• Respect for persons requires honoring their autonomy and rational agency
• Moral worth comes from acting from duty, not merely producing good consequences
• Justice requires treating similar cases similarly
• Duties sometimes conflict, requiring practical judgment to resolve

Founding Thinker: Immanuel Kant (1724-1804)

• Work: _Groundwork for the Metaphysics of Morals_ (1785), _Critique of Practical Reason_ (1788)
• Contributions: Categorical imperative, kingdom of ends, autonomy as foundation of morality
• Famous principle: "Act in such a way that you treat humanity, whether in your own person or in the person of any other, never merely as a means to an end, but always at the same time as an end"

When to Apply:

• Situations involving rights violations or respect for persons
• Cases where means matter independently of ends
• Professional obligations and duties (medical, legal, fiduciary)
• Establishing moral constraints on pursuing good outcomes

Sources:

• Stanford Encyclopedia: Kant's Moral Philosophy
• Deontological Ethics - Internet Encyclopedia of Philosophy

Foundation 2: Consequentialism (Outcome-Based Ethics)

Core Principles:

• The moral rightness of actions depends solely on their consequences
• Good consequences justify actions; bad consequences condemn them
• Utilitarianism: Maximize overall well-being (pleasure, happiness, preference satisfaction)
• Rule consequentialism: Follow rules that generally produce best outcomes
• Impartiality: Each person's well-being counts equally

Key Insights:

• Intentions alone don't make actions moral; results matter
• Trade-offs are inevitable; we must choose lesser evils
• Policy decisions should maximize aggregate welfare
• Moral progress involves reducing suffering and increasing flourishing
• Empirical facts about consequences are ethically relevant

Founding Thinkers:

• Jeremy Bentham (1748-1832): Classical utilitarianism, "greatest happiness principle"
• John Stuart Mill (1806-1873): Qualitative pleasures, higher vs. lower utilities
• Peter Singer (1946-present): Effective altruism, animal welfare, global poverty

When to Apply:

• Cost-benefit analysis of policies and interventions
• Resource allocation with limited budgets
• Public health decisions affecting populations
• Risk assessment and risk-benefit trade-offs
• Charitable giving and effective altruism

Sources:

• Utilitarianism - Stanford Encyclopedia
• Consequentialism - Internet Encyclopedia of Philosophy
• Peter Singer: The Life You Can Save

Foundation 3: Virtue Ethics (Character-Based)

Core Principles:

• Ethics concerns character traits (virtues) rather than isolated actions or rules
• A virtue is an excellent trait that enables human flourishing
• Cardinal virtues: courage, temperance, justice, practical wisdom (phronesis)
• Virtues are cultivated through practice and habituation
• Role models (moral exemplars) guide virtue development
• Practical wisdom enables context-sensitive ethical judgment

Key Insights:

• Rules and principles cannot replace good judgment in novel situations
• Moral education shapes character through practice and community
• Emotions properly shaped by virtue guide ethical action
• Ethics integrates doing (right action) and being (good character)
• Flourishing (eudaimonia) is the ultimate human good

Founding Thinkers:

• Aristotle (384-322 BCE): _Nicomachean Ethics_, doctrine of the mean, eudaimonia
• Confucius (551-479 BCE): Ren (benevolence), li (ritual propriety), virtue cultivation
• Alasdair MacIntyre (1929-present): Contemporary revival, _After Virtue_ (1981)

When to Apply:

• Professional character formation (medical, legal, military virtues)
• Leadership ethics and organizational culture
• Education and moral development
• Cases requiring practical judgment beyond rule-following
• Assessing credibility of moral testimony

Sources:

• Virtue Ethics - Stanford Encyclopedia
• Aristotle's Ethics - Internet Encyclopedia of Philosophy
• MacIntyre: After Virtue

Foundation 4: Justice and Rights-Based Ethics

Core Principles:

• Justice requires fair distribution of benefits and burdens
• Distributive justice: Who gets what resources? (equality, equity, need, merit)
• Procedural justice: Fair processes and impartial institutions
• Corrective justice: Remedying wrongs and compensating harms
• Rights establish strong claims that protect fundamental interests
• Social contract: Legitimate authority derives from consent of governed

Key Insights:

• Inequalities require justification, especially when they affect life prospects
• Background institutions shape opportunities and outcomes
• Fair equality of opportunity requires addressing systemic disadvantages
• Rights trump utility in certain cases (individual protections vs. collective good)
• Justice requires considering worst-off members of society

Founding Thinkers:

• John Rawls (1921-2002): _A Theory of Justice_ (1971), veil of ignorance, difference principle
• Robert Nozick (1938-2002): Libertarian justice, minimal state, entitlement theory
• Amartya Sen (1933-present): Capability approach, development as freedom

When to Apply:

• Healthcare resource allocation and access
• Educational opportunity and affirmative action
• Tax policy and welfare state design
• Criminal justice and punishment
• International development and global justice

Sources:

• Justice - Stanford Encyclopedia
• Rawls: A Theory of Justice
• Sen: The Idea of Justice

Foundation 5: Care Ethics and Relational Approaches

Core Principles:

• Relationships and interdependence are morally fundamental
• Care for particular others grounds ethical obligation
• Contextual reasoning attentive to needs and vulnerabilities
• Feminist critique: Traditional ethics overemphasizes autonomy, rules, impartiality
• Responsibilities arise from relationships, not just abstract principles
• Emotional attunement to others' needs is ethically valuable

Key Insights:

• Care work (childcare, eldercare, nursing) has moral significance often undervalued
• Justice and care are complementary, not opposed
• Power asymmetries in relationships create special obligations
• Particularity matters: relationships create differential obligations
• Vulnerability creates moral claims on caregivers

Founding Thinkers:

• Carol Gilligan (1936-present): _In a Different Voice_ (1982), care vs. justice reasoning
• Nel Noddings (1929-present): Relational ethics, caring as fundamental
• Virginia Held (1929-present): Ethics of care as political theory

When to Apply:

• Healthcare ethics (patient-provider relationships)
• Family obligations and eldercare
• Professional caregiving responsibilities
• Disability ethics and dependency
• Feminist critiques of traditional moral theory

Sources:

• Care Ethics - Stanford Encyclopedia
• Gilligan: In a Different Voice
• Held: The Ethics of Care

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Analytical Frameworks (Expandable)

Framework 1: The Four Principles Approach (Biomedical Ethics)

Overview: Widely used in healthcare ethics, developed by Beauchamp and Childress.

Four Principles:

1. Autonomy: Respect patients' self-determination and informed choices 2. Beneficence: Act in patients' best interests, promote their welfare 3. Non-maleficence: "First, do no harm" - avoid causing harm 4. Justice: Fair distribution of healthcare resources and burdens

Application Process:

• Identify relevant facts of the case
• Determine which principles apply and how
• Assess whether principles conflict
• Weigh and balance competing principles
• Reach reflective equilibrium on best course

Strengths:

• Provides clear starting points for analysis
• Captures consensus across diverse ethical traditions
• Practical for clinical settings
• Balances multiple moral considerations

Limitations:

• Doesn't specify how to resolve principle conflicts
• May downplay virtue, care, and relationships
• Culturally shaped (Western individualism)

When to Use: Medical decisions, research ethics, healthcare policy, patient rights

Sources:

• Beauchamp & Childress: Principles of Biomedical Ethics (9th ed., 2019)
• Four Principles of Bioethics

Framework 2: Ethical Decision-Making Models

Overview: Structured processes for working through ethical dilemmas systematically.

Steps in Analysis:

1. Recognize ethical issue: Is there a moral dimension? What makes it ethical? 2. Gather facts: What are the relevant circumstances, stakeholders, alternatives? 3. Identify stakeholders: Who is affected? What are their interests and rights? 4. Consider alternatives: What options exist? What are their likely consequences? 5. Apply ethical frameworks: What does each major theory recommend? 6. Assess consistency: Would I apply same reasoning to similar cases? (Universalizability) 7. Seek consultation: What do others (colleagues, ethics committees) recommend? 8. Make decision: Choose course that best balances competing considerations 9. Reflect and learn: What worked? What would I do differently?

When to Use: Complex decisions with significant moral stakes, organizational ethics, teaching ethics

Sources:

• Markkula Center: Framework for Ethical Decision Making
• University of British Columbia: Ethics Toolkit

Framework 3: Rights Analysis

Overview: Identify rights at stake and duties they create.

Types of Rights:

• Negative rights: Right to non-interference (liberty rights)
• Positive rights: Right to receive goods/services (welfare rights)
• Legal rights: Established by law
• Moral rights: Grounded in moral principles (may exceed legal rights)
• Human rights: Universal rights all persons possess

Analysis Process:

1. Which rights are claimed? (autonomy, privacy, life, property, free speech) 2. Are they genuine rights or mere interests? 3. What duties do these rights create for others? 4. Do rights conflict? If so, which take priority? 5. Are there legitimate limitations on these rights?

When to Use: Civil liberties cases, human rights violations, professional duties, informed consent

Sources:

• Human Rights - Stanford Encyclopedia
• UN Universal Declaration of Human Rights

Framework 4: Stakeholder Analysis

Overview: Systematically identify all affected parties and their interests.

Steps:

1. List stakeholders: Who is directly/indirectly affected? 2. Identify interests: What does each stakeholder care about? What's at stake? 3. Assess power: Who has power to affect outcomes? 4. Consider rights: Do stakeholders have special claims (rights, contracts)? 5. Evaluate vulnerability: Are some stakeholders especially vulnerable? 6. Weigh conflicts: When interests conflict, how should we prioritize?

Key Considerations:

• Include marginalized and voiceless stakeholders (future generations, animals, environment)
• Power imbalances affect whose interests get heard
• Those who bear risks should have say in decisions

When to Use: Corporate ethics, policy analysis, environmental decisions, technology deployment

Sources:

• Stakeholder Theory - Business Ethics

Framework 5: Casuistry (Case-Based Reasoning)

Overview: Reason from paradigm cases to novel cases by analogy.

Process:

1. Identify paradigm cases: Clear cases where moral judgment is settled 2. Extract relevant features: What makes paradigm case morally clear? 3. Compare new case: How is it similar/different from paradigm? 4. Adjust reasoning: If relevantly similar, apply same judgment; if different, adjust 5. Build case law: Accumulate precedents over time

Strengths:

• Respects moral intuitions about concrete cases
• Doesn't require agreement on abstract principles
• Practical and context-sensitive

Limitations:

• Depends on shared paradigm cases
• May perpetuate biases embedded in past cases
• Less helpful for radically novel issues

When to Use: Clinical ethics consultations, legal reasoning, professional ethics cases

Sources:

• Casuistry - Stanford Encyclopedia
• Jonsen & Toulmin: The Abuse of Casuistry

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Methodologies (Expandable)

Methodology 1: Reflective Equilibrium

Description: Iterative process of adjusting principles and judgments until they cohere.

Process:

1. Start with considered moral judgments about particular cases 2. Formulate general principles that explain those judgments 3. Test principles against new cases 4. Revise judgments or principles when they conflict 5. Continue until reaching stable coherence

Goal: Coherent system where principles and case judgments support each other.

Application: Moral theory development, resolving dilemmas, justifying ethical positions

Source: Rawls: A Theory of Justice

Methodology 2: The Veil of Ignorance

Description: Thought experiment to ensure impartiality in justice reasoning.

Process:

1. Imagine designing social institutions without knowing your position (rich/poor, majority/minority, able-bodied/disabled) 2. Choose principles not knowing if you'll be advantaged or disadvantaged 3. Self-interest motivates fair choices when position unknown 4. Rational choice under uncertainty yields just principles

Rawls's Conclusion: Would choose (1) equal basic liberties, (2) fair equality of opportunity, (3) difference principle (inequalities only if they benefit worst-off)

Application: Institutional design, policy fairness, testing for bias

Source: Rawls: Justice as Fairness

Methodology 3: Double Effect Reasoning

Description: Distinguishes intended harms from foreseen but unintended side effects.

Four Conditions:

1. Nature of act: Act itself must be morally good or neutral 2. Intention: Good effect intended; bad effect merely foreseen, not intended 3. Distinction: Bad effect not a means to good effect 4. Proportionality: Good effect outweighs bad effect (serious reason)

Classic Example: Pain medication that relieves suffering but hastens death (permissible if intent is relief, not death)

Controversial: Critics question whether intention matters morally or whether consequences alone determine rightness

Application: End-of-life care, military ethics (collateral damage), risk-benefit decisions

Source: Doctrine of Double Effect - Stanford Encyclopedia

Methodology 4: Trolley Problem Variations

Description: Thought experiments probing moral intuitions about harm, agency, and consequences.

Basic Trolley: Runaway trolley will kill five; you can divert to kill one. Divert?

• Most say: Yes (utilitarian reasoning)

Footbridge: Push large person off bridge to stop trolley, saving five. Push?

• Most say: No (deontological constraint against using person as mere means)

Purpose: Reveal implicit moral principles guiding intuitions, test ethical theories

Insights:

• Doing harm vs. allowing harm matters morally (action/omission distinction)
• Using someone as means vs. side effect matters (doctrine of double effect)
• Physical contact/directness affects judgments
• Intuitions may reflect emotional heuristics, not deep principles

Application: Testing moral theories, autonomous vehicles, military ethics, pandemic triage

Sources:

• Trolley Problem - Stanford Encyclopedia
• Foot: The Problem of Abortion and the Doctrine of Double Effect

Methodology 5: Wide Reflective Equilibrium

Description: Extension of reflective equilibrium including background theories.

Components:

1. Considered judgments: Intuitions about particular cases 2. Moral principles: Mid-level generalizations 3. Background theories: Metaphysics, epistemology, human nature, social theory

Process: Adjust all three levels until achieving coherence across entire system of beliefs.

Advantage: Avoids arbitrary stopping point, integrates ethics with broader worldview

Application: Comprehensive moral theorizing, resolving deep disagreements

Source: Daniels: Wide Reflective Equilibrium

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Detailed Examples (Expandable)

Example 1: Autonomous Vehicle Crash Algorithm

Situation: Self-driving car manufacturer must program accident algorithms. When crash unavoidable, should vehicle prioritize passenger safety or minimize total casualties (potentially sacrificing passenger)?

Ethical Analysis:

Stakeholders:

• Passengers (expect protection when purchasing vehicle)
• Pedestrians (vulnerable road users with right to safety)
• Other drivers (affected by crash decisions)
• Manufacturers (liability, reputation, sales)
• Society (aggregate safety, trust in technology)

Deontological Analysis:

• Passengers have special claim based on implicit contract with manufacturer
• Using passenger as mere means to save others violates Kantian principle
• Cannot sacrifice one person to save others without consent
• Conclusion: Prioritize passenger

Consequentialist Analysis:

• Minimize total harm: deaths, injuries, property damage
• If crash kills five pedestrians vs. one passenger, should minimize casualties
• Over time, utilitarian programming saves more lives overall
• Conclusion: Minimize total casualties

Virtue Ethics Analysis:

• What would a virtuous engineer do? Balance care for customer with broader responsibility
• Courage to do right thing despite market pressures
• Practical wisdom needed for context-specific judgments
• Conclusion: Depends on circumstances (e.g., pedestrian negligence vs. passenger negligence)

Rights Analysis:

• Pedestrians have right to life, not to be killed by machines
• Passengers have contractual expectations of protection
• No one has right to kill another to save themselves
• Rights conflict with no clear priority

Double Effect:

• If passenger death is side effect of avoiding five pedestrians, may be permissible
• If passenger deliberately sacrificed, impermissible
• Depends on whether passenger death is means or mere foresight

Recommendation:

1. Transparency: Disclose programming to consumers before purchase 2. Default rule: Minimize total harm (utilitarian), with caveats 3. Exceptions: No special sacrifice of vulnerable persons (children) 4. Limits: Won't actively kill pedestrians to protect passengers 5. Participation: Public input through democratic process 6. Ongoing review: Adjust as we learn from real-world experience

Key Insight: Perfect solution impossible. Transparency and democratic legitimacy matter as much as the algorithm itself.

Sources:

• MIT Moral Machine Experiment
• Ethics of Autonomous Vehicles - Stanford Encyclopedia

Example 2: Genetic Enhancement of Children

Situation: CRISPR technology enables parents to genetically enhance children (intelligence, athletic ability, appearance). Should it be permitted? Regulated? Banned?

Ethical Analysis:

Arguments For Enhancement:

• Parental autonomy: Parents have right to make decisions for children's benefit
• Beneficence: Enhancement improves children's life prospects and opportunities
• Consistency: We already enhance through education, nutrition, enriched environments
• Individual freedom: Why prohibit genetic means if non-genetic means acceptable?
• Medical necessity: Some enhancements prevent disease (e.g., immune system improvements)

Arguments Against Enhancement:

• Child's autonomy: Child cannot consent; irrevocable changes imposed by parents
• Unknown risks: Long-term effects uncertain; may cause unforeseen harms
• Social justice: Only wealthy can afford; exacerbates inequality ("genetic divide")
• Commodification: Treating children as products to be designed, not persons with inherent worth
• Social pressure: Creates arms race; parents feel compelled to enhance to keep up
• Human dignity: Violates respect for human nature and acceptance of the given

Virtue Ethics Perspective:

• Humility vs. hubris: Are we "playing God"?
• Unconditional love vs. conditional acceptance based on traits
• Gratitude for the gift of children vs. consumer mindset

Justice Analysis (Rawlsian): Behind veil of ignorance, would choose:

• No enhancement (might be unenhanced child)
• OR universal access to basic enhancements
• Would NOT choose unregulated market (risk being left behind)

Care Ethics Perspective:

• Parental motivations matter: Enhancing to love child more? Or loving child as they are?
• Relationships threatened by treating children as projects
• Attention to power dynamics: child cannot resist parents' choices

Harm Principle (Mill):

• If enhancement harms no one, should be permitted
• But: Harms include inequality, pressure on others, child's compromised autonomy

Recommendation:

1. Therapy vs. Enhancement Distinction: Permit disease prevention, not enhancement 2. International cooperation: Prevent "genetic tourism" to unregulated countries 3. Research ethics: Rigorous oversight of trials; long-term follow-up 4. Public deliberation: Democratic process to set boundaries 5. Equity measures: If permitted, ensure access not limited to wealthy 6. Precautionary principle: Go slowly; unknown unknowns warrant caution

Key Insight: Enhancement raises profound questions about human nature, equality, and what we owe children. Policies should preserve space for unconditional acceptance while preventing genetic injustice.

Sources:

• Sandel: The Case Against Perfection
• Buchanan et al: From Chance to Choice

Example 3: Whistleblowing in Healthcare Organization

Situation: Nurse discovers hospital systematically under-reports patient safety incidents to avoid regulatory scrutiny. Reporting internally has been ignored. Should nurse report externally (whistleblow) despite risks to career?

Ethical Analysis:

Obligations in Conflict:

• Patient safety (primary professional obligation)
• Loyalty to employer and colleagues
• Professional integrity (nursing code of ethics)
• Self-preservation (career, financial security, family responsibilities)
• Institutional mission (organization may do much good despite this flaw)

Deontological Analysis:

• Duty to protect patients from harm (absolute priority in nursing ethics)
• Cannot use patients as means to institutional goals (hiding safety issues)
• Lying (falsifying reports) is wrong regardless of consequences
• Professional codes require reporting unsafe practices
• Conclusion: Must whistleblow

Consequentialist Analysis:

• External reporting may:
• Prevent future patient harms (benefit)
• Harm hospital's reputation, reduce patient trust (cost)
• Lead to nurse being fired, reducing insider ability to improve care (cost)
• Inspire organizational reform (benefit)
• Must weigh likelihood and magnitude of consequences
• Conclusion: Depends on probability of successful reform vs. personal cost

Virtue Ethics Analysis:

• Courage required to do right thing despite personal risk
• Integrity: acting in accordance with professional values
• Practical wisdom: How to whistleblow effectively? (Anonymous tip? Media? Regulator?)
• Loyalty virtue has limits when institution acts wrongly
• Conclusion: Virtuous person would act, but wisely

Care Ethics Analysis:

• Relationships with patients create special obligations
• Vulnerability of patients demands responsiveness
• Relationships with colleagues also matter (don't betray frivolously)
• Must balance care for patients with care for self and family
• Conclusion: Report, but consider family impacts and protections

Professional Ethics Codes:

• ANA Code of Ethics: "Nurse's primary commitment is to the patient"
• Obligation to report unsafe practices
• Duty to use proper channels first (internal reporting)
• Whistleblowing appropriate when internal channels fail

Legal Protections:

• Whistleblower Protection Act (federal employees)
• State whistleblower laws vary
• Anti-retaliation protections imperfect in practice
• Document everything, consult lawyer

Decision Framework:

1. Verify facts: Confirm incidents are truly being under-reported 2. Internal channels: Exhaust internal options first (already done) 3. Consult ethics committee: Seek guidance from hospital ethics resources 4. Document thoroughly: Contemporaneous records protect legally 5. Consider anonymity: Anonymous report to regulator protects identity 6. Assess urgency: Immediate patient danger? Or systemic slow burn? 7. Seek support: Consult professional association, ethics hotline, lawyer 8. Report externally: If other steps fail, report to state health department 9. Prepare for consequences: Financial reserves, job search, emotional support

Recommendation: Whistleblow to regulator

• Patient safety is paramount professional obligation
• Internal reporting already attempted and ignored
• Professional codes require action
• Legal protections available (though imperfect)
• Anonymous reporting protects career while enabling reform
• Conscience requires action despite personal risk

Key Insight: Whistleblowing is supererogatory (beyond duty) when personal costs are extreme, but in healthcare, patient safety creates professional obligation that outweighs institutional loyalty. Doing it wisely (documentation, legal advice, anonymity) respects legitimate self-interest while fulfilling ethical duty.

Sources:

• ANA Code of Ethics
• Whistleblowing in Healthcare - Journal of Medical Ethics
• Government Accountability Project

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Analysis Process

When using the ethicist-analyst skill, follow this systematic 10-step process:

Step 1: Clarify the Ethical Issue

• What is the moral question? (What ought to be done?)
• Why is this an ethical issue? (Values in conflict? Rights at stake? Harms involved?)
• Distinguish ethical dimensions from legal, prudential, or empirical questions

Step 2: Gather Relevant Facts

• What are the circumstances, constraints, and relevant background?
• What empirical claims are being made? Are they accurate?
• What are the realistic alternatives available?
• Note: Ethical analysis cannot proceed without accurate factual basis

Step 3: Identify Stakeholders

• Who is directly affected by this decision?
• Who is indirectly affected?
• Do some stakeholders lack voice or power? (Future generations, animals, marginalized groups)
• What are each stakeholder's interests, rights, and vulnerabilities?

Step 4: Articulate Value Conflicts

• What values or principles are in tension?
• Which rights conflict?
• What goods cannot be simultaneously realized?
• Acknowledge genuine dilemmas rather than assuming easy solutions

Step 5: Apply Ethical Frameworks

Deontological: What duties apply? Which rights are at stake? Can the action be universalized? Consequentialist: What are likely outcomes? Which option maximizes overall well-being? Virtue Ethics: What would a virtuous person do? What character traits are relevant? Care Ethics: What do relationships require? Who is vulnerable and needs care? Justice: Is the distribution of benefits and burdens fair? Are procedures just?

Step 6: Test for Consistency (Universalizability)

• Would I apply the same reasoning if I were in a different stakeholder's position?
• Are there relevantly similar cases where I'd judge differently?
• Am I making special pleading for myself or my group?

Step 7: Consider Alternative Perspectives

• How would this be viewed from non-Western ethical traditions?
• What would critics of my position argue?
• Am I being influenced by cognitive biases? (In-group bias, status quo bias, confirmation bias)

Step 8: Assess Practical Constraints

• What are legal requirements and limitations?
• What is politically or organizationally feasible?
• What are resource constraints?
• Note: Ethical ideal may differ from best feasible option

Step 9: Reach Reflective Equilibrium

• Which ethical framework provides most compelling guidance for this case?
• Can I construct coherent justification for my conclusion?
• Does my conclusion align with considered moral judgments in paradigm cases?
• If not, revise either conclusion or principles

Step 10: Communicate Reasoning Transparently

• State conclusion clearly
• Present strongest arguments for and against
• Acknowledge value trade-offs and moral remainders
• Note limitations and uncertainties
• Recommend next steps or further deliberation

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Quality Standards

A thorough ethical analysis includes:

✓ Clarity: Ethical issue stated precisely, distinct from non-ethical questions ✓ Factual accuracy: Empirical claims verified, realistic alternatives identified ✓ Stakeholder inclusivity: All affected parties considered, including vulnerable and voiceless ✓ Multiple frameworks: Deontological, consequentialist, virtue, care, justice perspectives applied ✓ Rigorous reasoning: Logical argumentation, not mere assertion or intuition ✓ Universalizability tested: Consistency across similar cases verified ✓ Counterarguments engaged: Strongest objections considered and addressed ✓ Value conflicts acknowledged: Trade-offs explicit, no false dilemma resolution ✓ Practical guidance: Actionable recommendations, not just abstract theorizing ✓ Humility: Limitations, uncertainties, and reasonable disagreement acknowledged

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Common Pitfalls to Avoid

Moral relativism: "Everyone's values are equally valid" prevents moral reasoning. While respecting pluralism, some positions are better justified than others.

Appeal to emotion: Strong feelings don't settle ethical questions. Emotions can guide but must be critically examined.

Appeal to authority: "Expert says X" or "Law requires Y" doesn't make X or Y morally right. Expertise and law inform but don't determine ethical conclusions.

False dichotomy: Presenting complex issues as binary choices when multiple options exist or hybrid approaches possible.

Slippery slope: "Permitting X leads to Y" requires showing actual causal connection, not mere speculation.

Ad hominem: Attacking person making argument rather than addressing argument's merits.

Is-ought fallacy: Inferring what ought to be from what is. That "people do X" doesn't show "people should do X."

Naturalistic fallacy: Assuming "natural" equals "good." Nature includes suffering, disease, predation.

Paralysis from complexity: Acknowledging difficulty shouldn't prevent taking a position. Sometimes we must choose under uncertainty.

Overconfidence: Ethical reasoning is difficult; humility about one's conclusions is warranted.

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Key Resources

Professional Organizations

• American Philosophical Association - Ethics resources
• Association for Practical and Professional Ethics - Applied ethics
• Kennedy Institute of Ethics - Bioethics research
• Hastings Center - Bioethics and civic life

Online Philosophy Resources

• Stanford Encyclopedia of Philosophy - Scholarly articles on all ethics topics
• Internet Encyclopedia of Philosophy - Accessible philosophy content
• PhilPapers - Philosophy paper database
• 1000-Word Philosophy - Concise introductions

Ethics Centers

• Markkula Center for Applied Ethics (Santa Clara University)
• Prindle Institute for Ethics (DePauw University)
• Institute for Ethics in AI (Oxford)

Case Databases

• Ethics Unwrapped (UT Austin) - Videos and cases
• National Center for Professional and Research Ethics - Cases
• Online Ethics Center - Engineering and research ethics cases

Key Journals

• _Ethics_ - Leading theoretical journal
• _Journal of Medical Ethics_ - Healthcare ethics
• _Business Ethics Quarterly_ - Corporate ethics
• _Science and Engineering Ethics_ - Research and technology ethics

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Integration with Amplihack Principles

Ruthless Simplicity

• Cut through complex arguments to core moral questions
• Avoid unnecessary philosophical jargon
• Focus on practical guidance, not abstract theorizing

Modular Design

• Each ethical framework is independent "brick" with clear interface
• Mix frameworks as needed for comprehensive analysis
• Frameworks can be applied separately or combined

Zero-BS Implementation

• No hand-waving about "values" without specifying which values
• No appeals to intuition without critical examination
• Acknowledge when no clear answer exists

Evidence-Based Practice

• Ground empirical claims in reliable sources
• Distinguish facts from values
• Update conclusions when facts change

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Version

Current Version: 1.0.0 Status: Production Ready Last Updated: 2025-11-16

Ethicist Analyst - Quick Reference

TL;DR

Analyzes moral dimensions through ethical frameworks using deontology, consequentialism, virtue ethics, care ethics, and justice theory. Provides rigorous justification for ethical decisions with stakeholder analysis and value trade-offs made explicit.

When to Use

• Ethical dilemmas with conflicting values
• Technology ethics (AI, biotech, privacy)
• Professional ethics (medical, legal, business, research)
• Policy fairness and justice
• Rights violations and moral obligations
• Organizational ethics and stakeholder conflicts

Core Frameworks

1. Deontology (Kant) - Duty-based; respect persons as ends, not means 2. Consequentialism (Mill) - Outcome-based; maximize overall well-being 3. Virtue Ethics (Aristotle) - Character-based; what would virtuous person do? 4. Care Ethics (Gilligan) - Relational; responsibilities from relationships 5. Justice Theory (Rawls) - Fairness; veil of ignorance, difference principle

Theoretical Foundations

• Deontology: Categorical imperative, rights, duties, respect for persons
• Consequentialism: Utilitarianism, effective altruism, maximize utility
• Virtue Ethics: Character, phronesis, eudaimonia, moral exemplars
• Justice: Distributive justice, procedural fairness, social contract
• Care Ethics: Vulnerability, relationships, context-sensitivity

Quick Analysis Process

1. Clarify Issue - What is the moral question? Why ethical? 2. Gather Facts - Verify claims, identify alternatives 3. Identify Stakeholders - Who's affected? Interests? Vulnerabilities? 4. Articulate Conflicts - Which values/rights/principles in tension? 5. Apply Frameworks - Use deontology, consequentialism, virtue, care, justice 6. Test Consistency - Would same reasoning apply to similar cases? 7. Consider Alternatives - Engage counterarguments, diverse views 8. Assess Constraints - Legal, political, resource limits 9. Reach Equilibrium - Construct coherent justification 10. Communicate - Present reasoning, acknowledge trade-offs

Key Questions

Deontological:

• What duties or rights are at stake?
• Can I universalize this action without contradiction?
• Am I treating anyone merely as means to an end?
• What does respect for persons require?

Consequentialist:

• What are likely consequences for all affected?
• Which option maximizes overall well-being?
• Have I considered long-term and systemic effects?
• Am I weighing everyone's interests equally?

Virtue Ethics:

• What would a virtuous person do in this situation?
• What character traits are relevant (courage, honesty, wisdom)?
• What kind of person will I become through this choice?
• Who are moral exemplars I can learn from?

Care Ethics:

• What do my relationships require?
• Who is vulnerable and needs care?
• Am I attending to particular context and needs?
• Are power dynamics affecting the situation?

Justice:

• Is this distribution of benefits/burdens fair?
• Would I choose this behind veil of ignorance?
• Does this respect equal dignity of all persons?
• Are procedures impartial and transparent?

Applied Frameworks

Four Principles (Bioethics):

1. Autonomy - Respect self-determination 2. Beneficence - Promote well-being 3. Non-maleficence - Avoid harm 4. Justice - Fair distribution

Stakeholder Analysis:

• List all affected parties
• Identify interests and rights
• Assess power and vulnerability
• Weigh conflicts

Double Effect:

• Act itself must be good/neutral
• Good effect intended, bad merely foreseen
• Bad not means to good
• Proportionality: good outweighs bad

Casuistry:

• Identify paradigm cases (clear moral judgments)
• Extract relevant features
• Compare new case to paradigm
• Adjust reasoning for differences

Common Mistakes to Avoid

• Relativism: "It's all subjective" prevents reasoning
• Appeal to emotion: Feelings don't settle questions
• Appeal to authority: Law/experts inform but don't determine ethics
• False dichotomy: Binary framing when multiple options exist
• Slippery slope: Requires showing actual causal connection
• Is-ought fallacy: Can't infer "ought" from "is"
• Naturalistic fallacy: "Natural" ≠ "good"
• Ad hominem: Attack argument, not person
• Paralysis: Complexity shouldn't prevent taking position
• Overconfidence: Humility warranted in ethical reasoning

Essential Resources

Online Philosophy:

• Stanford Encyclopedia: https://plato.stanford.edu/ (Comprehensive)
• Internet Encyclopedia: https://iep.utm.edu/ (Accessible)
• 1000-Word Philosophy: https://1000wordphilosophy.com/ (Concise)

Ethics Centers:

• Markkula Center: https://www.scu.edu/ethics/ (Tools & cases)
• Prindle Institute: https://www.prindleinstitute.org/ (Blog & resources)

Professional Organizations:

• APA: https://www.apaonline.org/ (American Philosophical Association)
• APPE: https://appe.indiana.edu/ (Applied ethics)
• Hastings Center: https://www.thehastingscenter.org/ (Bioethics)

Decision Heuristics

When to prioritize which framework:

Deontology when:

• Rights violations at stake
• Professional duties involved
• Respect for persons central
• Some acts seem wrong regardless of consequences

Consequentialism when:

• Policy design affecting large populations
• Resource allocation decisions
• Risk-benefit analysis needed
• Aggregate welfare paramount

Virtue Ethics when:

• Professional character formation
• Leadership and role modeling
• Novel situations requiring judgment
• Long-term character development

Care Ethics when:

• Caregiving relationships central
• Vulnerability and dependency
• Healthcare and family ethics
• Power asymmetries present

Justice when:

• Distributive fairness at issue
• Institutional design
• Systemic inequality
• Procedural fairness

Key Principles

Categorical Imperative (Kant):

• Act only on maxims you could will as universal law
• Treat humanity as end, never merely as means

Utility Principle (Mill):

• Actions right in proportion to tendency to promote happiness
• Greatest happiness for greatest number

Difference Principle (Rawls):

• Inequalities permitted only if they benefit worst-off
• Fair equality of opportunity

Golden Rule:

• Do unto others as you would have them do unto you
• (Found across cultures and traditions)

Harm Principle (Mill):

• Only justify restricting liberty to prevent harm to others
• Self-regarding actions should be free

Success Criteria

✓ Ethical question clearly stated ✓ Facts verified, alternatives identified ✓ All stakeholders considered (including vulnerable) ✓ Multiple frameworks applied systematically ✓ Logical reasoning, not mere intuition ✓ Consistency tested across similar cases ✓ Strongest counterarguments engaged ✓ Value trade-offs explicitly acknowledged ✓ Practical recommendations provided ✓ Limitations and uncertainties noted

Framework Selection Guide

Classic Thought Experiments

Trolley Problem: Reveals intuitions about doing vs. allowing harm, using people as means

Veil of Ignorance: Ensures impartiality by bracketing self-interest in justice reasoning

Ring of Gyges: Tests whether morality depends on reputation/punishment or has intrinsic value

Experience Machine: Tests whether well-being is only pleasure or includes reality/achievement

Transplant Case: Intuition against killing one to save five (deontological constraint)

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For full details, see SKILL.md

Ethicist Analyst Skill

Analyze moral dimensions and value conflicts through rigorous ethical frameworks to guide defensible decision-making.

Overview

The Ethicist Analyst skill enables Claude to perform sophisticated moral analysis of decisions, policies, and technologies. Drawing on established philosophical frameworks, ethical principles, and rigorous reasoning methods, this skill provides insights into:

• Ethical Frameworks: Apply deontology, consequentialism, virtue ethics, care ethics, justice theories
• Value Conflicts: Identify and analyze tensions between competing moral principles
• Stakeholder Analysis: Systematically consider all affected parties and their interests
• Rights and Duties: Clarify moral obligations and entitlements
• Causal Assessment: Evaluate consequences and their moral significance
• Practical Guidance: Recommend ethically defensible courses of action

What Makes This Different

Unlike general moral reasoning, ethicist analysis:

1. Multi-Framework: Applies multiple ethical theories systematically, not just intuition 2. Rigorous Justification: Provides logical arguments, tests for consistency and universalizability 3. Stakeholder Inclusive: Centers vulnerable and marginalized voices often ignored 4. Acknowledges Complexity: Recognizes genuine value conflicts with no perfect solutions 5. Transparent Trade-offs: Makes moral costs and benefits explicit 6. Practically Actionable: Provides concrete guidance, not just abstract theorizing

Use Cases

Technology Ethics

• AI bias and fairness in algorithmic decision-making
• Privacy vs. security trade-offs in surveillance systems
• Autonomous vehicle crash algorithms and moral programming
• Genetic engineering and human enhancement
• Social media content moderation and free speech

Professional Ethics

• Healthcare decisions (end-of-life care, resource allocation, informed consent)
• Research ethics (human subjects, dual-use research, data integrity)
• Legal ethics (client confidentiality, zealous advocacy limits)
• Business ethics (stakeholder conflicts, environmental responsibility)
• Whistleblowing and organizational loyalty conflicts

Policy Analysis

• Healthcare access and resource allocation
• Criminal justice and punishment philosophy
• Environmental policy and intergenerational justice
• Education equity and affirmative action
• Immigration and refugee rights

Organizational Ethics

• Corporate social responsibility and profit maximization
• Diversity, equity, and inclusion initiatives
• Labor practices and supply chain ethics
• Executive compensation and inequality
• Transparency and stakeholder engagement

Ethical Frameworks Available

Core Theoretical Approaches

• Deontological Ethics (Kant): Duty-based reasoning, categorical imperative, respect for persons
• Consequentialism (Mill, Singer): Outcome-based reasoning, utilitarianism, effective altruism
• Virtue Ethics (Aristotle): Character-based reasoning, moral exemplars, practical wisdom
• Care Ethics (Gilligan, Noddings): Relational ethics, contextual reasoning, vulnerability
• Justice Theory (Rawls): Fairness, veil of ignorance, distributive justice

Applied Frameworks

• Four Principles (Bioethics): Autonomy, beneficence, non-maleficence, justice
• Rights Analysis: Negative/positive rights, human rights, legal vs. moral rights
• Stakeholder Analysis: Identifying affected parties, power dynamics, vulnerability
• Double Effect Reasoning: Intended vs. foreseen consequences
• Casuistry: Case-based reasoning from paradigm cases

Methodologies

• Reflective Equilibrium: Iteratively adjusting principles and case judgments
• Veil of Ignorance: Ensuring impartiality by bracketing self-interest
• Universalizability Test: Consistency across similar cases
• Trolley Problem Variations: Probing intuitions about harm and agency

Quick Start

Basic Usage

Claude, use the ethicist-analyst skill to analyze [ETHICAL ISSUE].

Examples:
- "Use ethicist-analyst to evaluate the ethics of facial recognition surveillance."
- "Analyze the whistleblowing dilemma using ethicist-analyst skill."
- "Use ethicist skill to assess fairness of this resource allocation policy."

Advanced Usage

Specify particular frameworks or considerations:

"Use ethicist-analyst to analyze autonomous vehicle crash algorithms, applying both
deontological and consequentialist frameworks."

"Apply ethicist-analyst with stakeholder analysis and justice perspective to evaluate
this healthcare rationing proposal."

"Use ethicist-analyst to examine genetic enhancement from virtue ethics and care
ethics perspectives."

Analysis Process

The ethicist analyst follows a systematic 10-step process:

1. Clarify Ethical Issue - Define moral question, distinguish from non-ethical concerns 2. Gather Facts - Verify empirical claims, identify realistic alternatives 3. Identify Stakeholders - List all affected parties, including vulnerable and voiceless 4. Articulate Value Conflicts - What principles, rights, or goods are in tension? 5. Apply Frameworks - Use deontological, consequentialist, virtue, care, justice lenses 6. Test Consistency - Would same reasoning apply in relevantly similar cases? 7. Consider Alternatives - Engage counterarguments and diverse perspectives 8. Assess Constraints - Note legal, political, resource limitations 9. Reach Equilibrium - Construct coherent justification for conclusion 10. Communicate Transparently - Present reasoning, acknowledge trade-offs and limitations

Example Analyses

Example 1: Autonomous Vehicle Crash Algorithm

Dilemma: Should self-driving cars prioritize passenger safety or minimize total casualties?

Analysis Highlights:

• Deontology: Cannot use passenger as mere means; violates Kantian respect for persons
• Consequentialism: Minimize total harm; utilitarian algorithm saves more lives overall
• Virtue Ethics: Depends on context; practical wisdom needed for case-by-case judgment
• Rights: Passengers have contractual expectations; pedestrians have right to life
• Recommendation: Transparency paramount; default to minimize harm with exceptions for vulnerable persons

Example 2: Genetic Enhancement of Children

Dilemma: Should parents be permitted to genetically enhance children's intelligence, athleticism, appearance?

Analysis Highlights:

• Autonomy: Child cannot consent to irrevocable changes
• Justice: Only wealthy afford enhancement, creating "genetic divide"
• Virtue: Unconditional parental love vs. treating children as products to design
• Harm Principle: Enhancement creates social pressure, inequality, compromises child autonomy
• Recommendation: Permit therapy (disease prevention) but prohibit enhancement; international cooperation to prevent genetic tourism

Example 3: Healthcare Whistleblowing

Dilemma: Nurse discovers hospital under-reports safety incidents. Whistleblow despite career risk?

Analysis Highlights:

• Professional Duty: Patient safety is primary obligation in nursing ethics
• Deontology: Cannot use patients as means to institutional reputation goals
• Consequentialism: Weigh patient harm prevented vs. personal career cost
• Care Ethics: Vulnerability of patients creates special obligations
• Recommendation: Whistleblow to regulator after exhausting internal channels; use anonymous reporting to protect career while enabling reform

Quality Standards

A complete ethicist analysis includes:

✓ Clear ethical question stated precisely, distinct from legal/prudential issues ✓ Factual accuracy with empirical claims verified ✓ Comprehensive stakeholder analysis including vulnerable parties ✓ Multiple frameworks applied (deontology, consequentialism, virtue, care, justice) ✓ Rigorous reasoning with logical arguments, not mere intuition ✓ Consistency tested across relevantly similar cases ✓ Counterarguments engaged with strongest objections addressed ✓ Trade-offs acknowledged with no false resolution of genuine dilemmas ✓ Practical recommendations that are actionable ✓ Humility about limitations and reasonable disagreement

Resources

Online Philosophy

• Stanford Encyclopedia of Philosophy: https://plato.stanford.edu/ (Comprehensive scholarly articles)
• Internet Encyclopedia of Philosophy: https://iep.utm.edu/ (Accessible content)
• 1000-Word Philosophy: https://1000wordphilosophy.com/ (Concise introductions)
• PhilPapers: https://philpapers.org/ (Philosophy paper database)

Ethics Centers

• Markkula Center for Applied Ethics: https://www.scu.edu/ethics/ (Tools, frameworks, cases)
• Prindle Institute for Ethics: https://www.prindleinstitute.org/ (Blog, podcasts, resources)
• Institute for Ethics in AI (Oxford): https://www.oxford-aiethics.ox.ac.uk/

Professional Organizations

• American Philosophical Association: https://www.apaonline.org/
• Association for Practical and Professional Ethics: https://appe.indiana.edu/
• Kennedy Institute of Ethics: https://kennedyinstitute.georgetown.edu/ (Bioethics)
• Hastings Center: https://www.thehastingscenter.org/ (Bioethics and civic life)

Case Databases

• Ethics Unwrapped: https://ethicsunwrapped.utexas.edu/ (Videos and cases)
• Online Ethics Center: https://onlineethics.org/ (Engineering and research ethics)

Key Journals

• Ethics: Leading theoretical ethics journal
• Journal of Medical Ethics: Healthcare ethics focus
• Business Ethics Quarterly: Corporate and organizational ethics
• Science and Engineering Ethics: Technology and research ethics

Common Questions

When should I use ethicist-analyst vs. other analysts?

Use ethicist-analyst when the question involves:

• Moral rights, duties, and obligations
• Value conflicts and ethical dilemmas
• Fairness, justice, and equity
• What ought to be done (normative questions)
• Professional ethics and codes of conduct
• Technology governance and responsible innovation

Use other analysts when the focus is:

• Legal requirements and compliance → Lawyer
• Disease patterns and health outcomes → Epidemiologist
• Social norms and cultural practices → Sociologist/Anthropologist
• Economic efficiency and incentives → Economist
• Political power and institutions → Political Scientist

How does ethics differ from law?

Ethics:

• What is morally right/wrong
• Broader than law (many unethical acts are legal)
• Guides what law should be
• Personal and professional domains

Law:

• What is legally permitted/prohibited
• Minimum standards enforceable by state
• Sometimes lags behind ethical consensus
• Public and regulatory domains

Many issues have both ethical and legal dimensions that must be analyzed separately.

What if ethical frameworks disagree?

This is common and reveals genuine value conflicts:

1. Acknowledge disagreement rather than forcing false consensus 2. Identify which values are in tension (e.g., liberty vs. equality, individual vs. collective) 3. Assess which framework fits the case (deontology for rights violations, consequentialism for policy) 4. Seek reflective equilibrium adjusting principles and judgments 5. Make trade-offs explicit in final recommendation 6. Accept reasonable pluralism on some issues

Can ethics be objective or is it all subjective?

Ethics involves both objective and subjective elements:

• Objective: Logic, consistency, factual accuracy, rational justification required
• Subjective: Ultimate values may differ (liberty vs. equality emphasis)
• Intersubjective: Wide agreement possible through reasoning and shared humanity
• Better: Some positions are better justified than others, even if perfect consensus impossible

How do you balance speed and depth in ethical analysis?

Context determines appropriate depth:

• Crisis decisions: Focus on immediate harms, rights violations; act quickly with best available reasoning
• Policy design: Comprehensive multi-framework analysis; time for deliberation and consultation
• Routine professional ethics: Use established guidelines and paradigm cases
• Novel issues: Deep philosophical analysis; no shortcuts for unprecedented questions

Integration with Other Skills

Ethicist analysis complements:

• Decision Logger: Document ethical decisions and moral reasoning
• Storytelling Synthesizer: Communicate ethical arguments through compelling narratives
• Module Spec Generator: Specify ethical requirements for system design
• Philosophy Guardian: Ensure alignment with organizational values
• Knowledge Extractor: Capture ethical insights for future reference

Contributing

This skill improves through use. Share feedback on:

• What frameworks proved most useful in specific contexts
• What resources were most valuable
• What analysis patterns emerged
• What additional methods would be helpful
• Real-world ethical dilemmas and their resolutions

Version

Current Version: 1.0.0 Status: Production Ready Last Updated: 2025-11-16

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For detailed framework descriptions, step-by-step process, and comprehensive examples, see [SKILL.md](SKILL.md)

For quick reference, see [QUICK_REFERENCE.md](QUICK_REFERENCE.md)

Ethicist Analyst - Domain Validation Quiz

Purpose

This quiz validates that the ethicist analyst applies ethical frameworks correctly, identifies moral tensions and stakeholder interests, and provides well-grounded normative analysis. Each scenario requires demonstration of ethical reasoning, application of moral principles, and consideration of competing values.

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Scenario 1: Autonomous Vehicle Moral Dilemma

Event Description: A major automotive company is finalizing the decision-making algorithm for its Level 5 fully autonomous vehicles, expected to launch in 2 years. Engineers must program how the vehicle responds in unavoidable crash scenarios. Example: The vehicle faces brake failure while traveling 45 mph on a bridge. Ahead are three pedestrians crossing illegally. Options: (A) Continue straight and strike pedestrians (likely killing all three), (B) Swerve right into concrete barrier (likely killing the two passengers), or (C) Swerve left off the bridge (almost certainly killing the two passengers). The algorithm must make this decision in milliseconds. The company's survey research shows 76% of respondents say the car should minimize total deaths (utilitarian), but 68% say they would not purchase a car programmed that way if it meant sacrificing passengers. Regulators have provided no clear guidance. The company faces liability concerns, market pressures, and moral responsibility for lives.

Analysis Task: Analyze the ethical dimensions of programming life-and-death decisions into autonomous vehicles.

Expected Analysis Elements

• [ ] Ethical Frameworks Application:
• Utilitarianism: Maximize welfare, minimize total deaths (favor option A: save 2 over 3)
• Deontology: Respect rights, avoid using persons as means (never deliberately harm passengers)
• Virtue Ethics: What would a virtuous person/company do? Transparency, responsibility
• Rights-based: Right to life, protection of innocents
• Care Ethics: Relationships and responsibilities (company's duty to passengers)

• [ ] The Trolley Problem and Variants:
• Classic trolley problem: Active intervention vs. allowing harm
• Double effect doctrine: Intended vs. foreseen consequences
• Killing vs. letting die distinction
• Active harm (swerve into barrier) vs. passive harm (continue straight)
• Programmer's moral agency: Who is morally responsible?

• [ ] Stakeholder Analysis:
• Passengers: Trust in vehicle to protect them, contractual expectations
• Pedestrians: Right not to be harmed, even if jaywalking
• Other drivers: Expectations of predictable behavior
• Company: Legal liability, market viability, reputation
• Society: Public safety, regulatory needs, acceptance of technology
• Programmers: Moral distress from coding life-death decisions

• [ ] Utilitarian vs. Deontological Tension:
• Utilitarian: Minimize deaths (choose option A, sacrifice fewer)
• Deontological: Never actively kill passengers (reject options B/C)
• Survey paradox: People endorse utilitarian outcomes but won't buy utilitarian cars
• Impartiality vs. partiality: Should car prioritize passengers? (Asymmetric relationship)
• Kantian categorical imperative: Can rule be universalized?

• [ ] Alternative Ethical Positions:
• Minimize passengers' risk: Company's duty to customers (contractual)
• Random or proportional chance: Avoid "playing God," let probability decide
• Avoid active harm: Continue braking, don't actively swerve (omission vs. commission)
• Transparency: Disclose algorithm, let consumers choose
• Precautionary: If unsolvable, delay deployment until safer technology

• [ ] Regulatory and Legal Dimensions:
• Absence of regulatory guidance: Ethical vacuum
• Product liability: Who is liable for algorithm's choices?
• Standard of care: What does "reasonable" mean for autonomous systems?
• International variation: German guidelines prioritize humans over property
• Insurance implications: How to assess risk and liability?

• [ ] Broader Implications:
• Autonomous vehicles will save lives overall (reduce 40K annual US traffic deaths by 90%+)
• Perfect safety is impossible; trade-offs are inevitable
• Public trust and acceptance required for adoption
• Precedent for other AI life-death decisions (medical triage, military)
• Moral weight of programming vs. emergent human decisions

• [ ] Historical and Philosophical Context:
• Trolley problem (Philippa Foot, 1967): Moral intuitions on intervention
• MIT Moral Machine experiment: Global survey on AV ethics (39M responses)
• Asimov's Laws of Robotics: Conceptual framework, practical limitations
• German Ethics Commission on Automated and Connected Driving (2017)
• Utilitarian calculus: Bentham, Mill (greatest happiness principle)
• Kantian ethics: Kant's Formula of Humanity (treat persons as ends)

Evaluation Criteria

• Domain Accuracy (0-10): Correct application of ethical frameworks, principles, theories
• Analytical Depth (0-10): Thoroughness of stakeholder analysis, trade-offs, moral tensions
• Insight Specificity (0-10): Clear ethical reasoning, specific policy recommendations
• Historical Grounding (0-10): References to moral philosophy, case precedents
• Reasoning Clarity (0-10): Logical flow, coherent normative argument

Minimum Passing Score: 35/50

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Scenario 2: Medical Resource Allocation in Pandemic

Event Description: During a severe pandemic surge, a hospital ICU has 8 ventilators available but 15 patients in acute respiratory distress requiring mechanical ventilation to survive. Without a ventilator, patients will likely die within hours to days. The 15 patients include: (1) 34-year-old pregnant healthcare worker, (2) 28-year-old with developmental disability and heart condition, (3) 76-year-old retired judge with dementia, (4) 52-year-old convicted felon serving life sentence, (5) 19-year-old college student, (6) 45-year-old single parent of three young children, (7) 63-year-old with stage 4 cancer (prognosis 6 months), (8) 41-year-old unvaccinated by choice, (9) 55-year-old essential worker (grocery), (10) 67-year-old physician, (11) 8-year-old child, (12) 88-year-old with multiple comorbidities, (13) 30-year-old with severe obesity, (14) 58-year-old alcoholic with liver disease, (15) 22-year-old undocumented immigrant. Clinical teams must decide who receives life-saving treatment.

Analysis Task: Develop ethical criteria for allocating scarce medical resources.

Expected Analysis Elements

• [ ] Ethical Principles for Allocation:
• Maximize benefits: Save the most lives, maximize life-years saved
• Treat people equally: Fair consideration, intrinsic equal worth
• Promote and reward instrumental value: Prioritize essential workers, healthcare workers
• Priority to the worst off: Give chances to sickest, most vulnerable
• Lottery/random selection: Avoid bias, respect equality
• First-come, first-served: Temporal fairness, avoid discrimination

• [ ] Relevant Criteria Analysis:
• Prognosis/likelihood of survival: Short-term (ICU) and long-term (overall)
• Young and healthy (19-year-old student) vs. elderly with comorbidities (88-year-old)
• Patient with stage 4 cancer: Poor long-term prognosis regardless
• Life-years saved: Prioritize younger patients (8-year-old, 19-year-old)
• Life-cycle principle: Everyone deserves opportunity to live through life stages
• Instrumental value: Healthcare worker, essential worker (societal benefit)
• Reciprocity: Healthcare worker put self at risk caring for others

• [ ] Ethically Prohibited Criteria:
• Social worth: Judge, physician vs. felon, homeless (violates equal dignity)
• Disability: Developmental disability, dementia (disability rights, ADA)
• Quality of life judgments: Subjective, discriminatory
• Ability to pay: Wealth, insurance status (violates equity)
• Immigration status: Undocumented immigrant (ethical duty to treat)
• Behavioral factors: Unvaccinated, obesity, alcoholism (blame and stigma concerns)
• Family responsibilities: Single parent (gender bias, penalizes childless)

• [ ] Framework Tensions:
• Utilitarian (maximize lives saved) vs. Egalitarian (equal chance via lottery)
• Consequentialist (best outcomes) vs. Deontological (respect rights)
• Efficiency vs. Equity: Saving most lives vs. giving all fair chance
• Individual rights vs. Collective welfare: Patient autonomy vs. triage decisions
• Objective criteria (age, prognosis) vs. Subjective (quality of life, social value)

• [ ] Prioritization System Design:
• Multi-principle approach: Combine prognosis, life-years, lottery
• Sequential priority: (1) Remove those unlikely to survive even with ventilator, (2) Prioritize life-years, (3) Lottery among similar candidates
• Disability-neutral: Prognosis based on acute condition, not underlying disability
• Transparency: Publicize criteria, allow appeals
• Clinical assessment: SOFA score (Sequential Organ Failure Assessment) for objective prognosis

• [ ] Procedural Justice:
• Impartial review: Ethics committee, not treating physicians alone
• Transparency: Public criteria, rationale disclosed
• Consistency: Apply same criteria to all cases
• Appeals process: Opportunity to contest decisions
• Accountability: Document decisions, allow retrospective review

• [ ] Psychological and Moral Burden:
• Moral distress for clinicians making life-death choices
• Institutional responsibility: Protect clinicians, not individual blame
• Post-crisis support: Counseling, debriefing
• Social support for families denied resources

• [ ] Historical and Philosophical Context:
• Wartime triage: Limited resources, prioritize "savability"
• Seattle "God Committee" (1960s): Dialysis rationing, social worth judgments (criticized)
• Organ allocation: UNOS framework (medical urgency, likelihood of success)
• COVID-19 crisis standards of care: State/national guidelines (2020-2021)
• Utilitarian calculus: Bentham, Mill (greatest good)
• Rawlsian justice: Veil of ignorance, fair equality of opportunity
• Disability rights: Americans with Disabilities Act, equal treatment

Evaluation Criteria

• Domain Accuracy (0-10): Correct application of medical ethics, allocation principles
• Analytical Depth (0-10): Thoroughness of criteria analysis, framework tensions
• Insight Specificity (0-10): Clear allocation criteria, specific process recommendations
• Historical Grounding (0-10): References to triage precedents, ethical frameworks
• Reasoning Clarity (0-10): Logical flow, coherent normative framework

Minimum Passing Score: 35/50

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Scenario 3: AI Bias in Criminal Justice

Event Description: A county criminal justice system uses an AI risk assessment tool (COMPAS-like) to inform bail, sentencing, and parole decisions. The algorithm predicts recidivism risk based on historical criminal justice data (prior arrests, convictions, age at first arrest, neighborhood crime rates, employment history). An investigative report reveals the algorithm exhibits racial bias: Black defendants are twice as likely as white defendants with similar criminal histories to be classified as "high risk," leading to higher bail amounts, longer sentences, and parole denials. The algorithm's training data reflects systemic racism in policing (Black neighborhoods over-policed) and socioeconomic inequities (unemployment, poverty correlate with race due to historical discrimination). The tool's vendor claims the algorithm is "objective" and more accurate than human judges. Criminal justice officials cite efficiency gains and consistency. Civil rights advocates demand the tool be abolished. Defendants subjected to the algorithm had no opportunity to understand or challenge the scores.

Analysis Task: Analyze the ethical dimensions of using biased AI in criminal justice.

Expected Analysis Elements

• [ ] Forms of Algorithmic Bias:
• Training data bias: Historical data encodes systemic racism (over-policing, discriminatory enforcement)
• Proxy variables: Neighborhood, employment correlate with race due to structural inequities
• Feedback loops: Algorithm perpetuates past biases (high-risk label → more surveillance → more arrests)
• Disparity vs. discrimination: Unequal outcomes (2x rate for Black defendants)
• Fairness definitions: Predictive parity vs. equalized odds vs. demographic parity (trade-offs)

• [ ] Ethical Issues:
• Discrimination and racial justice: Violates equal treatment, perpetuates systemic racism
• Fairness: Unequal impact on Black defendants (disparate impact)
• Accountability: Opaque algorithm, no explanation for decisions
• Transparency: Defendants unaware of score's influence, cannot contest
• Autonomy: Judges delegate moral decisions to machines
• Dignity: Reducing individuals to risk scores, not considering context
• Justice: Punishing individuals for group statistics (collective responsibility fallacy)

• [ ] Arguments For Algorithmic Decision-Making:
• Consistency: Reduces judge-to-judge variability, arbitrary decisions
• Efficiency: Faster processing, cost savings
• Accuracy: May be more accurate than unaided human judgment
• Objectivity claim: Removes "human bias" (but encodes structural bias)
• Transparency: Algorithm is auditable (in principle, if disclosed)

• [ ] Arguments Against Algorithmic Decision-Making:
• Bias amplification: Encodes and perpetuates historical discrimination
• Opacity: Proprietary algorithms, defendants can't understand or challenge
• Moral abdication: Judges defer responsibility to machines
• Collective punishment: Penalizes individuals for group characteristics
• Self-fulfilling prophecy: High-risk label leads to harsher treatment, increasing actual recidivism
• Dehumanization: Reduces complex individuals to data points

• [ ] Fairness Trade-offs:
• Predictive parity: Equal accuracy across groups (algorithm may achieve this)
• Equalized false positive rates: Equal rate of incorrectly labeling low-risk as high-risk
• Demographic parity: Equal proportion classified high-risk across groups
• Impossibility theorem: Cannot satisfy all fairness definitions simultaneously when base rates differ
• Choice reflects values: Which fairness definition to prioritize is normative, not technical

• [ ] Procedural Justice Requirements:
• Transparency: Defendants must understand how scores are calculated
• Contestability: Right to challenge scores, present mitigating context
• Human oversight: Judges must retain final decision authority, not defer to algorithm
• Explanation: Provide individualized reasons, not just scores
• Auditability: Independent review of algorithm for bias

• [ ] Structural Justice Considerations:
• Root causes: Address underlying inequities (poverty, over-policing, lack of opportunity)
• Discrimination vs. prediction: Accurate prediction of unjust outcomes is still unjust
• Remedy vs. perpetuation: AI should reduce bias, not encode it
• Accountability: Hold institutions responsible for discriminatory impacts

• [ ] Policy Recommendations:
• Ban: Prohibit use of biased algorithms in high-stakes criminal justice decisions
• Regulation: Require fairness audits, transparency, contestability
• Human-in-the-loop: Algorithms as decision support, not decision-makers
• Debiasing: Remove proxy variables, use fair algorithms (but technical limits)
• Focus on root causes: Invest in social programs, reduce policing disparities

• [ ] Historical and Philosophical Context:
• ProPublica investigation (2016): COMPAS algorithm racial bias
• Wisconsin v. Loomis (2016): Right to challenge algorithmic evidence
• Fairness in machine learning: Impossibility theorems (Corbett-Davies et al.)
• Criminal justice reform: Eliminate cash bail, sentencing reform
• Critical race theory: Structural racism, disparate impact
• Rawlsian justice: Fair equality of opportunity, difference principle
• Kantian ethics: Treat persons as ends, not means (algorithmic dignity)

Evaluation Criteria

• Domain Accuracy (0-10): Correct application of algorithmic fairness, discrimination concepts
• Analytical Depth (0-10): Thoroughness of bias analysis, fairness trade-offs, structural factors
• Insight Specificity (0-10): Clear ethical reasoning, specific policy recommendations
• Historical Grounding (0-10): References to cases, fairness research, justice frameworks
• Reasoning Clarity (0-10): Logical flow, coherent normative argument

Minimum Passing Score: 35/50

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Scenario 4: Climate Ethics and Intergenerational Justice

Event Description: A wealthy industrialized nation faces pressure to dramatically reduce greenhouse gas emissions to meet Paris Agreement targets (50% reduction by 2030, net-zero by 2050). Achieving these targets requires significant economic transformation: phasing out fossil fuels (20% of economy), retrofitting buildings, overhauling transportation, transitioning agriculture. Economic modeling estimates 2-3% GDP growth reduction over 20 years and displacement of 1.2 million fossil fuel and related industry workers. Political opposition argues: "Why should we sacrifice our prosperity for uncertain future harms? Developing nations are the largest current emitters. Technology will solve the problem." Climate advocates counter: "We are the largest historical emitter (cumulative emissions). We have moral duty to future generations and vulnerable nations already suffering climate impacts (droughts, floods, displacement). Delay is irresponsible." Meanwhile, low-lying island nations face existential threat from sea level rise caused primarily by industrialized nations' historical emissions.

Analysis Task: Analyze the ethical dimensions of climate action and responsibility.

Expected Analysis Elements

• [ ] Intergenerational Justice:
• Future generations cannot consent to harms imposed by current generation
• Irreversibility and long-term impacts (emissions persist for centuries)
• Discount rate debate: Should we discount future welfare? (Economic vs. ethical perspectives)
• Non-identity problem: Future people are different depending on our choices
• Sustainability principle: Leave world no worse for future generations
• Rawlsian savings principle: Accumulate capital for future generations

• [ ] Distributive Justice - Historical Responsibility:
• Industrialized nations: Largest cumulative emissions (since Industrial Revolution)
• Development powered by fossil fuels: Benefited from emissions
• Polluter pays principle: Those who caused harm should bear remediation costs
• Grandfathering objection: Current generation didn't know about climate change (but now we do)
• Luxury vs. survival emissions: Wealthy emissions for consumption vs. poor emissions for subsistence

• [ ] Distributive Justice - Current Impacts:
• Climate vulnerability: Low-lying nations, drought-prone regions suffer most
• Inverse correlation: Lowest emitters suffer greatest harms (injustice)
• Climate refugees: Displacement from uninhabitable areas (estimated 200M by 2050)
• Loss and damage: Irreversible harms to cultures, ecosystems, nations
• Common but differentiated responsibilities (Paris Agreement principle)

• [ ] Economic Costs vs. Moral Duties:
• Utilitarian calculation: Cost of climate action vs. cost of climate impacts (Stern Review: climate action cheaper)
• Rights-based: Right to livable environment, right not to be harmed
• Deontological: Duty not to harm, duty of rescue
• Virtue ethics: Stewardship, prudence, justice
• Economic efficiency: Climate action as investment, not cost (jobs, innovation, resilience)

• [ ] Collective Action Problem:
• Free-rider incentive: Individual nations benefit from others' action while not acting themselves
• Tragedy of the commons: Atmosphere as shared resource, overexploitation
• Coordination challenge: 195 nations must cooperate
• Prisoner's dilemma: Dominant strategy is to defect, but mutual defection is worst outcome
• Need for enforceable international agreements and domestic accountability

• [ ] Just Transition:
• Fossil fuel workers: 1.2M displaced (moral duty to support transition)
• Retraining and social safety net
• Regional impacts: Coal communities disproportionately affected
• Distributive justice within nation: Don't concentrate costs on vulnerable workers
• Green jobs: Clean energy sector employment growth (but geographic/skill mismatch)

• [ ] Technological Optimism vs. Precautionary Principle:
• Technological optimism: Innovation will solve problem (risky bet)
• Precautionary principle: Act despite uncertainty to avoid catastrophic risk
• Geoengineering: Moral hazard (reduces mitigation incentive), unintended consequences
• Carbon capture: Not yet scalable, shouldn't delay emissions reductions

• [ ] Rights of Nature and Non-Human Ethics:
• Intrinsic value of ecosystems, species (beyond instrumental value to humans)
• Mass extinction event: 6th great extinction, anthropogenic
• Stewardship vs. domination: Human relationship to nature
• Indigenous perspectives: Interconnectedness, reciprocity with nature

• [ ] Historical and Philosophical Context:
• Brundtland Report (1987): Sustainable development definition
• Rawls: Intergenerational savings, justice as fairness
• Jonas: Imperative of Responsibility for future generations
• Singer: Expanding moral circle, obligations to distant others
• Stern Review (2006): Economics of climate change
• IPCC reports: Scientific consensus, urgency
• Paris Agreement (2015): Common but differentiated responsibilities

Evaluation Criteria

• Domain Accuracy (0-10): Correct application of justice frameworks, climate ethics principles
• Analytical Depth (0-10): Thoroughness of intergenerational, distributive, collective action analysis
• Insight Specificity (0-10): Clear ethical reasoning, specific policy implications
• Historical Grounding (0-10): References to climate agreements, philosophical frameworks
• Reasoning Clarity (0-10): Logical flow, coherent normative argument

Minimum Passing Score: 35/50

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Scenario 5: Gene Editing for Human Enhancement

Event Description: A fertility clinic offers CRISPR gene editing services for embryos, marketed to prospective parents. The clinic provides three tiers: (1) Therapeutic: Correct disease-causing mutations (e.g., Huntington's, sickle cell) - $50,000. (2) Preventive: Reduce polygenic disease risks (heart disease, Alzheimer's, type 2 diabetes) - $150,000. (3) Enhancement: Select for traits like height, intelligence, athleticism, eye color - $500,000. The service is legal in the jurisdiction (minimal regulation). Demand is high among wealthy couples. Critics raise concerns about eugenics, inequality, designer babies, and unforeseen consequences. The clinic argues: "Parents already select embryos via PGD (pre-implantation genetic diagnosis). This is just more precise. Parents have reproductive autonomy to give their children advantages." Bioethicists warn of slippery slope from therapy to enhancement and exacerbation of social inequality.

Analysis Task: Analyze the ethical dimensions of germline gene editing for enhancement.

Expected Analysis Elements

• [ ] Therapy vs. Enhancement Distinction:
• Therapy: Restore normal function, treat/prevent disease (Huntington's, sickle cell)
• Enhancement: Augment beyond normal human function (increase IQ, alter appearance)
• Gray area: Preventive medicine (reduce polygenic risk) straddles line
• Normality vs. enhancement: Socially constructed, culturally variable
• Disability rights perspective: "Fixing" genetic traits stigmatizes disability

• [ ] Reproductive Autonomy vs. Limits:
• Procreative liberty: Parents' right to reproductive choices
• Precedents: IVF, PGD, prenatal testing, selective abortion
• Child's welfare: Open future principle (Feinberg) - preserve child's autonomy
• Child as project: Enhancement treats child as product to be designed (commodification)
• Unconditional love: Should parental love be contingent on traits?

• [ ] Eugenics Concerns:
• Historical eugenics: Nazi Germany, forced sterilization, state coercion
• "Liberal eugenics": Market-driven, individual choice (Agar) - but still problematic
• Collective pressure: Social norms may coerce "enhancement" (keeping up, avoiding disadvantage)
• Homogenization: Reduced human diversity, narrowing of valued traits
• Whose values?: What traits are "desirable" is culturally specific and biased

• [ ] Social Justice and Inequality:
• Access: $500K enhancement available only to wealthy (genetic divide)
• Exacerbation of inequality: Genetic advantages compound socioeconomic privilege
• Zero-sum competition: If all enhance, relative advantage disappears (arms race)
• Structural disadvantage: Unenhanced people face discrimination in education, employment
• Genetic caste system: Heritable inequality, reduction of social mobility

• [ ] Harm and Unintended Consequences:
• Unknown risks: Off-target effects, mosaicism, long-term health impacts
• Pleiotropy: Genes have multiple effects (enhance one trait, harm another)
• Lack of long-term data: Effects may not manifest for decades, across generations
• Irreversibility: Changes are heritable, affect future generations without consent
• Ecological effects: Reduced genetic diversity may reduce population resilience

• [ ] Child's Rights and Autonomy:
• Right to open future: Enhancement may close off possibilities (over-determined life)
• Consent: Child cannot consent to irreversible genetic changes
• Identity: What if child rejects parents' choices? (Gender selection analogies)
• Psychological effects: Pressure to live up to enhanced traits, loss of authenticity
• Right not to be harmed: Precautionary approach given uncertainties

• [ ] Slippery Slope Arguments:
• Therapy to enhancement continuum: Where to draw line?
• Normalization: Acceptance of therapy leads to acceptance of enhancement
• Market pressures: Competitive dynamics push toward more extreme enhancements
• Technological inevitability: Once possible, may be difficult to regulate
• Counter: Slopes aren't always slippery; regulations can establish boundaries

• [ ] Regulatory Approaches:
• Permissive: Allow with informed consent (current clinic's jurisdiction)
• Restrictive: Ban enhancement, allow therapy only (most countries)
• International harmonization: Prevent "genetic tourism" to permissive jurisdictions
• Precautionary: Moratorium until safety and societal impacts understood
• Public deliberation: Democratic decision-making on acceptable uses

• [ ] Historical and Philosophical Context:
• Habermas: "The Future of Human Nature" - dignity and autonomy concerns
• Sandel: "Case Against Perfection" - giftedness, humility, unconditional love
• Buchanan et al.: "From Chance to Choice" - enhancement ethics framework
• He Jiankui case (2018): CRISPR twins in China, international condemnation
• National Academy of Sciences: Heritable genome editing criteria (2017)
• Disability rights: Critique of enhancement paradigm
• Rawlsian justice: Fair equality of opportunity, natural lottery

Evaluation Criteria

• Domain Accuracy (0-10): Correct application of bioethics frameworks, reproductive ethics
• Analytical Depth (0-10): Thoroughness of autonomy, justice, harm analysis
• Insight Specificity (0-10): Clear ethical reasoning, specific regulatory recommendations
• Historical Grounding (0-10): References to bioethics debates, enhancement literature
• Reasoning Clarity (0-10): Logical flow, coherent normative argument

Minimum Passing Score: 35/50

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Overall Quiz Assessment

Scoring Summary

Passing Criteria

To demonstrate ethicist analyst competence:

• Minimum per scenario: 35/50 (70%)
• Overall minimum: 175/250 (70%)
• Must pass at least 4 of 5 scenarios

Evaluation Dimensions

Each scenario is scored on:

1. Domain Accuracy (0-10): Correct application of ethical frameworks and principles 2. Analytical Depth (0-10): Thoroughness and sophistication of moral reasoning 3. Insight Specificity (0-10): Clear, actionable ethical recommendations 4. Historical Grounding (0-10): Use of precedents, philosophical theories, case studies 5. Reasoning Clarity (0-10): Logical flow, coherent normative argument

What High-Quality Analysis Looks Like

Excellent (45-50 points):

• Applies multiple ethical frameworks accurately (utilitarian, deontological, virtue ethics, care ethics, rights-based)
• Considers stakeholder perspectives, competing values, and moral trade-offs
• Makes specific, well-justified normative recommendations
• Cites relevant philosophical theories, ethical precedents, and research
• Clear logical flow from facts to values to principles to conclusions
• Acknowledges moral complexity and areas of reasonable disagreement
• Identifies non-obvious ethical dimensions and implications

Good (35-44 points):

• Applies key ethical frameworks correctly
• Considers main stakeholder interests and value tensions
• Makes reasonable normative recommendations
• References some philosophical theories or ethical debates
• Clear reasoning
• Provides useful ethical insights

Needs Improvement (<35 points):

• Misapplies ethical frameworks or principles
• Ignores critical stakeholder interests or value conflicts
• Vague or poorly justified normative claims
• Lacks grounding in moral philosophy or ethical debates
• Unclear or illogical reasoning
• Superficial moral analysis

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Using This Quiz

For Self-Assessment

1. Attempt each scenario analysis 2. Compare your analysis to expected elements 3. Score yourself honestly on each dimension 4. Identify areas for improvement

For Automated Testing (Claude Agent SDK)

from claude_agent_sdk import Agent, TestHarness

agent = Agent.load("ethicist-analyst")
quiz = load_quiz_scenarios("tests/quiz.md")

results = []
for scenario in quiz.scenarios:
    analysis = agent.analyze(scenario.event)
    score = evaluate_analysis(analysis, scenario.expected_elements)
    results.append({"scenario": scenario.name, "score": score})

assert sum(r["score"] for r in results) >= 175  # Overall passing
assert sum(1 for r in results if r["score"] >= 35) >= 4  # At least 4 scenarios pass

For Continuous Improvement

• Add new scenarios as ethical issues evolve
• Update expected elements as moral philosophy develops
• Refine scoring criteria based on analyst performance patterns
• Use failures to improve ethicist analyst skill

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Quiz Version: 1.0.0 Last Updated: 2025-11-16 Status: Production Ready