Specialty · Specialty exam
AI for Hiring & HR
Verifies whether candidates exercise responsible human judgment while maintaining legal compliance and fairness when using AI in job postings, resume screening, interviews, evaluations, employee data, and performance management.
Daily practice · Free
10 questions · 25 min · No sign-up needed
Specialty exam · Proctored
35 questions · 60 min · Raw score of 75 or more · $3.99 / one attempt
Specialty exam detailsExam overview
- Questions
- 35
- Time
- 60 min
- Pass mark
- 75 pts
- Recommended experience
- White Belt (AI Basics) level and practical experience in hiring and human resources
Every question has five choices and is marked on an OMR answer sheet. Multiple-choice and true-or-false questions ask for the right combination from a box; ordering and matching questions ask for the right arrangement. Judgment questions (L3) are worth 3 points and all others 2; the raw score is converted to a 100-point scale and graded 1 to 9.
Exam domains
1. Job Postings and Resume Screening Inputs20%
2. Evaluations, Interviews, and Automated Decisions25%
3. Applicant and Employee Data20%
4. HR Operations and Performance Management15%
5. Fairness Auditing and Governance20%
Weights follow the Specialty exam. Practice and mock exams may mix domains differently.
What this exam verifies
- Evaluate input data and discrimination risks when using AI for job postings and resume screening
- Apply automated decision-making regulations and human review to determinations based on AI evaluations and interview results
- Determine the legal grounds for collecting, using, and entrusting applicant and employee personal data
- Design recordkeeping and accountability procedures when introducing AI into HR operations and performance management
- Oversee hiring and HR AI systems using fairness metrics and governance frameworks
Who it is for
- HR professionals using or introducing AI tools into hiring and human resources operations
- HR leaders selecting recruiting platforms and HR software solutions
- People managers making final decisions based on AI interview and evaluation results
Does not cover representation in labor litigation, legal counsel on individual cases, or HR software development.
Domain details
Domain 1. Job Postings and Resume Screening Inputs
- Knowledge: Discriminatory language in job postings, Restrictions on requesting personal information under the Fair Hiring Procedure Act, Input data fields used in AI resume screening, Indirect discrimination arising from proxy variables
- Skills: Identifying discriminatory elements in AI-generated job postings and screening criteria, Selecting fields that must be excluded from resume screening inputs
Domain 2. Evaluations, Interviews, and Automated Decisions
- Knowledge: Automated decisions and data subject rights under the Personal Information Protection Act, Explainability of AI interview and assessment tools, High-impact areas (employment) under the Framework Act on Artificial Intelligence, Meaningful human review, Reasonable accommodation in AI interviews under the Act on the Prohibition of Discrimination against Persons with Disabilities
- Skills: Distinguishing fully automated decisions from decisions involving human review, Designing procedures to handle requests for refusal or explanation
Domain 3. Applicant and Employee Data
- Knowledge: Legal bases for collection and use, and unauthorized use beyond stated purposes, Sensitive information and unique identification information, Outsourcing of data processing versus third-party data provision, Retention periods and secure destruction
- Skills: Determining which HR data is permissible to feed into AI tools, Reviewing data usage terms in vendor contracts
Domain 4. HR Operations and Performance Management
- Knowledge: Drafting performance reviews and assisting with feedback formulation, Legal and ethical limits on employee monitoring and surveillance, HR recordkeeping and audit trails, Prohibitions against discrimination based on age and disability, Matters subject to Labor-Management Council consultation under the Act on the Promotion of Worker Participation and Cooperation
- Skills: Reviewing AI-drafted performance evaluations against facts and documented evidence, Verifying notification and consultation procedures prior to introducing monitoring systems
Domain 5. Fairness Auditing and Governance
- Knowledge: Outcome disparity metrics across demographic groups, Bias audit cadence and sampling methods, Re-evaluation procedures upon modifications (model retraining or input variable changes), Requesting vendor verification and validation reports, NIST AI RMF and accountability frameworks
- Skills: Interpreting fairness audit results and determining corrective actions, Establishing operational rules for hiring AI and assigning accountable leaders
Official documentation
국가법령정보센터
Specialty Course · AI for Hiring & HR
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