| Course | IOP 455 Professional Ethics (IOP/455) |
|---|---|
| Week | 3 |
| Paper type | Assessment and selection ethics paper |
| Length | about 1,025 words, 4 double-spaced pages plus title page and references |
| Format | APA 7 student paper |
| School | University of Phoenix |
| Program | BS in Psychology |
| Updated | October 2026 |
Free sample paper for IOP 455 Week 3
The Vendor Promised AI Would Read Their Faces: Ethics in Selecting Nurses With New Tools
[Student Name]
University of Phoenix
IOP/455: Professional Ethics
Week 3 Assignment
[Instructor Name]
[Date]
The hospital system, vendor and staff are composites written for a model paper; professional standards and research come from the sources listed.
Assessments shape who gets hired and promoted, so their ethical use matters as much as their technical quality. New technologies add speed and scale but also new risks. This paper examines two assessment proposals at the Tucson hospital system and the ethical reasoning that guides a response.
Two Proposals
The hospital system must hire two hundred nurses this year. A vendor offers an AI video interview platform: applicants record answers on their phones, and the software scores "empathy," "honesty" and "culture fit" from facial expressions, voice tone and word choice. The vendor cites a reduction in time to hire at other companies and high satisfaction among recruiters, but provides no study showing that its scores predict nursing performance, and it declines to explain how scores are computed, citing trade secrets. Separately, a nursing director asks Dr. Naomi Reyes for personality test results from last year's leadership development course to help decide promotions to charge nurse. Participants were told results were for their own development and would not be shared with managers.
Validity and Fairness as Ethical Duties
The Society for Industrial and Organizational Psychology (2018) set out principles for developing, validating and using personnel selection procedures. The principles call for evidence that scores relate to job requirements or performance, for analysis of fairness and potential bias across groups, for documentation that allows others to evaluate a procedure and for users to understand what a procedure measures and its limitations. Using a procedure without such evidence risks harming applicants who are screened out for reasons unrelated to the job.
Measured against these principles, the vendor's tool falls short. There is no validation evidence for nursing, no data on group differences and no transparency about how scores are produced. Naomi cannot judge whether it measures anything related to nursing.
Concerns About AI Hiring Tools
Tippins et al. (2021) described scientific, legal and ethical concerns raised by AI-based selection tools. Scientifically, many tools lack evidence of reliability and validity, and the features they use may be unrelated to job performance. Legally, they may produce adverse impact that is hard to detect without access to the algorithm. Ethically, they raise issues of transparency, applicant privacy, consent to data collection and the ability to explain decisions. The authors called on developers to meet the same professional standards as traditional assessments and on users to demand evidence.
For the hospital, these concerns are concrete. Video analysis might score applicants differently based on accent, disability affecting facial movement, camera quality or skin tone, and the vendor cannot show otherwise.
The software promised to see empathy in a nurse's face; the research says faces do not carry that message reliably.
Can Faces Reveal Emotions?
Barrett et al. (2019) reviewed research on whether specific emotions can be inferred from facial movements. They concluded that people do frown, smile or scowl when angry, happy or sad more often than chance, but the relationship is weak and varies widely across people, situations and cultures. People often feel emotions without the expected expression and make the expressions without the emotion. Inferring a person's emotional state, let alone a trait like empathy, from facial movements alone is not supported by the evidence.
The vendor's claim that it can score empathy from faces therefore rests on an assumption the research does not support.
Reusing Development Data
The nursing director's request raises a different issue: secondary use of data. The leadership course participants completed personality measures under a clear promise that results were for their development only. Using them for promotion decisions would break that promise, violate the conditions of consent and could discourage employees from participating honestly in future development programs. Personality measures used for development may also lack validation evidence for predicting charge nurse performance.
Responsible Alternatives
For nurse hiring, Naomi proposes a structured interview based on a job analysis of nursing roles, with questions about patient care scenarios scored by trained interviewers, and a situational judgment test that has been validated for nursing. She will monitor selection rates by group. If leadership remains interested in video interviews, Naomi suggests a pilot in which a vendor's scores are collected but not used, then compared with later performance and examined for group differences before any decision.
For charge nurse promotions, Naomi offers to develop an assessment for that purpose, for example a scored scenario interview plus a charge nurse simulation, with participants informed in advance how results will be used. She declines to release the development results and explains why.
Questions to Ask Any Vendor
Naomi drafts a short list of questions the system will put to any assessment vendor in the future. What exactly does the tool measure, and how was that defined? What evidence links scores to performance in jobs like ours, and in samples like our applicants? How do scores differ across racial, ethnic, gender, age and disability groups? What data are collected from applicants, how long are they kept and who can see them? Can a rejected applicant be told what drove the decision? Can our own psychologists review the scoring method? A vendor unable to answer should not be scoring the hospital's future nurses.
Applicants' Side of the Process
Applicants deserve to know how they will be assessed and to give informed consent to recorded interviews and data use. They also need a way to request accommodations, such as a live interview for a candidate whose facial movements are affected by a disability.
Weighing the Pressures
The pull toward the vendor's tool is understandable: hiring two hundred nurses strains recruiters, and the tool promises speed. Naomi's response acknowledges this by proposing efficient, validated alternatives rather than simply saying no.
Conclusion
Two proposals at the hospital system show different ethical risks in assessment: a tool with no validation evidence and an unsupported premise about faces, and a plan to use data beyond the purpose for which it was collected. Professional validation principles, concerns about AI hiring tools and research on facial expressions guide Naomi's response, which protects applicants and employees while offering the organization responsible ways to meet its needs.
References
Barrett, L. F., Adolphs, R., Marsella, S., Martinez, A. M., & Pollak, S. D. (2019). Emotional expressions reconsidered: Challenges to inferring emotion from human facial movements. Psychological Science in the Public Interest, 20(1), 1-68. https://doi.org/10.1177/1529100619832930
Society for Industrial and Organizational Psychology. (2018). Principles for the validation and use of personnel selection procedures (5th ed.). Industrial and Organizational Psychology, 11(S1), 1-97. https://doi.org/10.1017/iop.2018.195
Tippins, N. T., Oswald, F. L., & McPhail, S. M. (2021). Scientific, legal, and ethical concerns about AI-based personnel selection tools: A call to action. Personnel Assessment and Decisions, 7(2), Article 1. https://doi.org/10.25035/pad.2021.02.001
What the IOP 455 Week 3 instructions ask
The third IOP 455 paper usually addresses ethical issues in employee assessment and selection. Students typically discuss validity and fairness as ethical obligations, informed consent and confidentiality of test data, the use of assessments beyond their original purpose, applicant privacy and transparency and the evaluation of new technologies such as automated or AI-based tools. Some versions ask students to review a specific test or vendor claim. Ground ethical judgments in professional principles and evidence, explain how each choice affects applicants and employees and propose responsible alternatives rather than simply rejecting innovation. Cite the course text, professional standards and published studies in APA format, and phrase concerns as questions a vendor would have to answer.
How this IOP 455 Week 3 example is built
Our worked paper follows Dr. Naomi Reyes as she reviews two proposals. A vendor's video interview system claims to score nurse applicants' empathy and honesty from facial expressions and word choice, but offers no validation study for nursing and will not disclose how its scores are produced. The field's principles for validating selection procedures require evidence that scores predict job performance and work fairly across groups. A call to action on AI hiring tools describes the scientific, legal and ethical concerns such systems raise. A review of research on facial expressions shows that emotions cannot be reliably read from faces. Naomi also declines to release personality results collected under a promise of developmental use only.
IOP 455 Week 3 grading rubric: where the points go
Assessment ethics papers are evaluated on accurate use of professional standards, evidence-based critique and fair treatment of stakeholders. Instructors look for validity and fairness to be framed as ethical as well as technical requirements, for consent and secondary use of data to be addressed and for vendor claims to be tested against research. Credit goes to proposing responsible alternatives, to considering applicants' perspectives and to recognizing legal risks without confusing them with ethical duties. Clear APA style is expected, and the most persuasive papers also acknowledge the pressures that make unvalidated tools attractive, such as hiring volume, recruiter workload and cost.
IOP 455 Week 3 help: mistakes to avoid
A frequent weakness is accepting vendor claims at face value or rejecting all new technology without examining evidence. Ask what the tool measures, how it was validated and for whom. Another is overlooking the secondary use of data, such as applying results gathered for development to promotion decisions without consent. Students also treat fairness only as a legal question, missing professional obligations to monitor group differences and explain decisions. Some papers name concerns without proposing what to do instead. Test each claim against published evidence, apply professional principles to each use of data and recommend a responsible path. A tutor can help you turn vague concerns into specific questions for a vendor.
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IOP 455 Week 3 questions, answered
What does IOP 455 Week 3 usually cover?
It usually covers ethical issues in testing and selection, including validity, fairness, consent, confidentiality and new technologies.
Where can I find a free IOP 455 Week 3 sample paper?
The IOP 455 Week 3 paper on an AI interview tool and reused personality data is above, free.
Why is validity an ethical issue in selection?
Because decisions based on invalid scores can unfairly deny people jobs or promotions without a sound reason.
Can AI read emotions from faces?
Research shows that facial movements do not reliably reveal specific emotions across people and situations.
Can development assessments be used for promotion decisions?
Not without clear consent; using data beyond its stated purpose breaks the conditions under which it was collected.
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