By the end of this module, learners will be able to:

1. Identify and summarize the relevant factual elements in an ethically complex recruitment scenario involving artificial intelligence (AI) tools.
2. Differentiate between empirical facts, normative claims, and assumptions when analyzing moral problems in hiring and job application contexts.
3. Recognize and describe key ethical issues raised by AI recruitment systems, including bias, transparency, privacy, accountability, and fairness.
4. Analyze cases of AI-assisted hiring from multiple moral perspectives, including utilitarianism, deontology, virtue ethics, feminist ethics of care, and moral psychology (Haidt’s moral foundations).
5. Formulate clear moral questions that accurately capture the central ethical dilemma without presupposing a conclusion.
6. Apply critical moral reasoning to evaluate competing moral principles such as fairness versus efficiency, honesty versus survival, and transparency versus proprietary rights.
7. Construct sound moral arguments supported by empirical evidence, valid reasoning, and explicit moral premises.
8. Develop counterarguments and assess opposing perspectives with intellectual honesty and analytical rigor.
9. Articulate a reflective equilibrium, demonstrating the ability to revise moral judgments in light of new evidence and theoretical reflection.
10. Communicate ethical analyses in structured written or oral form, integrating theoretical frameworks with real-world corporate and applicant perspectives.

 

Case Study 1: The Algorithm’s Choice (Corporate Perspective)

Background

Noventa Analytics, a mid-sized data consulting firm, recently adopted HireSmart, an AI-powered recruitment system designed to streamline candidate selection. The tool promises to analyze resumes, social media activity, and recorded video interviews to predict “long-term cultural fit” and job performance. With a new opening for a Senior Data Strategist, the HR department relies heavily on this system to narrow hundreds of applicants down to five.

 

Case Details

The AI tool identifies three top candidates—two men and one woman. However, a manual review by a hiring manager reveals an unsettling trend. The rejected candidates include several highly

 

qualified women and older applicants with over twenty years of relevant experience. The algorithm appears to favor candidates from certain universities and zip codes correlated with high-income, predominantly white areas.

When questioned, HireSmart’s vendor attributes this to “data optimization” and assures Noventa that “diversity filters” are already active. The HR director faces a dilemma. The AI model cannot explain why it chose certain applicants over others—the company’s contract explicitly forbids inspecting the proprietary algorithm. Yet rejecting the tool’s recommendations risks delays, higher costs, and accusations of bias if human judgment re-enters the process.

Should the HR director trust the AI’s shortlist, despite unexplained correlations, or override the system and risk undermining the company’s efficiency metrics? Would that decision expose Noventa to liability for bias either way?

 

Key Ethical Tensions

• Fairness Efficiency: Should speed and cost justify using opaque systems?
• Accountability: Who is morally and legally responsible for algorithmic discrimination— the employer or the software vendor?
• Transparency Proprietary Rights: Should businesses have the right to audit tools that affect human livelihoods?

 

Exercise

Analyze this case through utilitarian, deontological, and virtue ethics lenses.

• What outcome maximizes overall welfare?
• What duties does Noventa owe to applicants?
• What character traits should guide a morally responsible recruiter?

Case Study 2: The AI Advantage (Applicant Perspective)

Background

Leah Chen, a recent computer science graduate, is searching for her first full-time position. After months of rejection, she begins using ApplyGenie, a generative AI platform that automates resume tailoring, crafts bespoke cover letters, and even generates deepfake video interviews using her likeness and voice for asynchronous interview platforms. The AI’s synthetic version of Leah is perfectly articulate, never anxious, and always smiles at the right moments.

 

Case Details

Soon after using ApplyGenie, Leah receives multiple interview invitations. One hiring manager compliments her “excellent communication skills” based on her recorded video interview. The problem is that Leah never actually spoke those words—the AI did.

 

Leah reasons that companies themselves use biased algorithms to screen candidates and that her use of ApplyGenie merely “levels the playing field.” Yet she knows her digital self doesn’t reflect her true voice or demeanor. If hired, her performance during live team meetings could quickly reveal the deception.

Leah struggles to justify her actions. Is she simply adapting to a rigged system, or engaging in a form of professional fraud? Meanwhile, employers increasingly deploy software to detect “AI- assisted dishonesty,” potentially blacklisting her name permanently if discovered.

 

Key Ethical Tensions

• Authenticity Survival: Does self-representation through AI constitute dishonesty when the hiring system is already automated and impersonal?
• Fairness Compliance: Is using AI tools an ethical response to biased hiring, or a deeper erosion of trust?
• Responsibility and Reciprocity: Should the same standards apply to job seekers as to employers using AI?

 

Exercise

Evaluate Leah’s actions using Kantian ethics, feminist ethics of care, and moral psychology (Haidt’s framework).

• Does her intent matter more than the deception?
• How might empathy and relational ethics alter our judgment?
• Which moral intuitions—care, fairness, loyalty, authority, purity—shape your response?

 

Instructions for Evaluating the Case Studies

Step 1: Identify the Relevant Facts

1. Read the case carefully, highlighting only empirically verifiable information.
2. List the observable or documented events without interpreting motives or assigning
   • Example: “The AI rejected older applicants above age 55,” or “Leah used an AI tool to simulate her own voice.”
3. Separate facts from assumptions, opinions, and moral claims.
   • A fact can be verified; a moral claim
4. Record any uncertainties or missing information that might influence moral interpretation (e.g., Did the company disclose AI use to applicants? Did Leah’s deepfake misrepresent her skills or only her tone?).

 

Step 2: Identify the Moral Stakeholders

1. Determine all parties affected by the
   • In Case 1: the HR director, rejected applicants, corporate leadership, the AI vendor, future employees.
   • In Case 2: Leah, her prospective employer, other applicants, AI developers, future
2. Assess what each stakeholder values or stands to gain or lose.
   • Use categories such as fairness, autonomy, privacy, honesty, or professional
3. Note any power imbalances (e.g., corporation applicant, algorithm vs. human decision- maker).

 

Step 3: Define the Central Moral Question

1. Formulate a clear ethical question that captures the dilemma without presupposing an
   • Example:
     • “Is it morally permissible for a company to rely on an opaque AI hiring tool that produces unequal outcomes?”
     • “Is Leah justified in using AI-generated materials to overcome algorithmic bias?”

2. Phrase the question so that it invites competing Avoid “yes/no” phrasing in favor of “should” or “is it ethical that…” formulations.

 

Step 4: Analyze Competing Moral Principles

1. Identify at least two moral principles that are in conflict (e.g., fairness efficiency, honesty vs. survival).
2. Clearly define each principle:
   • Fairness means treating similar cases alike and avoiding arbitrary
   • Efficiency means maximizing outcomes with minimal
3. Explain why the conflict cannot be easily resolved—this tension creates the moral ambiguity that makes the case worth studying.

 

Step 5: Apply Ethical Frameworks

Evaluate the case through multiple theoretical lenses to surface contrasting moral conclusions. Use evidence and reasoning, not intuition alone.

 

a)  Utilitarianism

• Ask: Which action produces the greatest overall good for the greatest number?
• Consider both short- and long-term
• Quantify or at least describe who benefits and who is

 

b)  Deontological (Kantian) Ethics

• Ask: Does this action respect persons as ends in themselves rather than as means?
• Identify relevant duties (e.g., duty to truthfulness, fairness, or respect for autonomy).
• Apply the categorical imperative: Would it be morally acceptable if everyone acted the same way?

 

c)  Virtue Ethics

• Ask: What kind of person or organization does this action reveal?
• Identify virtues or vices displayed (e.g., integrity, prudence, compassion, courage).
• Consider how a virtuous actor would balance honesty and

 

d)  Feminist Ethics of Care

• Ask: How do relationships, empathy, and care obligations influence the right action?
• Consider how impersonal AI systems may erode relational ethics or moral attention to the

 

e)  Moral Psychology (Haidt’s Framework)

• Identify which moral intuitions (care, fairness, loyalty, authority, sanctity) dominate your own reaction.
• Reflect on whether those intuitions lead to a bias or blind

 

Step 6: Construct a Moral Argument

1. State your conclusion explicitly as a moral claim:
   • Example: “It is morally wrong for Noventa Analytics to use an opaque AI tool for ”
2. Justify your conclusion using structured reasoning:
   • Premise 1: Define the relevant moral principle or
   • Premise 2: Show how the facts satisfy or violate that
   • Conclusion: Derive a prescriptive statement
3. A sound argument links verifiable facts to moral principles without Avoid

 

fallacies such as appeal to emotion, false equivalence, or slippery slope.

 

Step 7: Consider Counterarguments

1. Identify at least one strong opposing position and present it
   • Example: “Supporters might argue that AI increases objectivity and reduces human ”
2. Explain why that position is partially valid before offering a reasoned
3. This demonstrates intellectual honesty and strengthens critical moral

 

Step 8: Reach a Reflective Equilibrium

1. Revisit your initial intuition after completing your
2. Ask: Have my moral principles or conclusions shifted as a result of evidence and argument?
3. Articulate your final judgment with humility, noting remaining

 

Step 9: Synthesize and Communicate

Write or discuss your findings in this format:

1. Facts Summary (≤150 words)
2. Central Moral Question (1 sentence)
3. Stakeholders and Values (short list)
4. Ethical Analysis (apply at least two frameworks)
5. Final Moral Argument and Counterpoint
6. Conclusion (reflective, balanced judgment)