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1890 learning items

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Quiz

NIST AI Risk Management Framework (NIST AI RMF 1.0)

Unofficial AIGP practice on the NIST AI Risk Management Framework 1.0, its four core functions, and the characteristics of trustworthy AI. Basic familiarity with model development and organizational risk assessment is useful. Questions test function selection, subcategory interpretation, context and proxy validity, bias sources, mixed-method evaluation and documented risk treatment. Additional scenarios examine voluntary guidance, profiles, measurement limits and independent review. The set encourages contextual judgment rather than treating the framework as a linear checklist. Aligned to the NIST framework and Playbook indicator in AIGP Body of Knowledge v2.1, competency II.D. NIST states that a framework revision is in progress; this set explicitly concerns version 1.0. It does not confer certification or establish legal compliance.

ai-governance

Oct 22, 2026

15 questions

Quiz

Privacy-Enhancing Technologies (PETs) & Data De-Identification

Unofficial AIGP practice on privacy-enhancing technologies and responsible use of de-identified data. This set connects technical safeguards with the governance decisions needed before training, sharing or releasing data and models. Topics include pseudonymization and identifiability, equivalence-class disclosure risks, differential privacy parameters and accounting, federated learning, secure aggregation, cryptographic computation and synthetic-data evaluation. Scenarios distinguish protections for data in transit, computation and released outputs, and examine why combining safeguards still requires a documented threat model. Basic familiarity with model training and personal-data concepts is useful. Practise evaluating privacy claims, recognizing residual risks and choosing evidence for approval. These questions support the data-governance and training/testing competencies in the IAPP AIGP Body of Knowledge version 2.1; they are independent study material and do not replace current legislation, regulatory guidance or the official syllabus.

ai-governance

Oct 22, 2026

15 questions

Quiz

Explainability & Interpretability Methods: SHAP, LIME & Counterfactuals

Unofficial AIGP practice on intrinsic and post-hoc interpretability, SHAP, LIME, counterfactuals, global/local summaries and PDP/ICE limitations. Adds scenarios on causal claims, explanation stability, reference populations, realistic feature combinations and audience needs. Aligned chiefly with IAPP BoK v2.1 III.B, with III.C assurance and relevant II.A transparency context. Basic classification knowledge is useful. Explanations are evaluated for fidelity and usefulness; transparency does not itself prove fairness or causation.

ai-governance

Oct 22, 2026

15 questions

Quiz

Specific Transparency Risk Systems (Article 50)

Unofficial AIGP practice on Article 50 transparency responsibilities, supporting the transparency and operator-role indicators in IAPP BoK 2.1, II.C. Practise direct-interaction disclosure, machine-readable synthetic-content marking, deployer disclosure for deepfakes and public-interest text, emotion-recognition and biometric-categorisation notices, artistic accommodation and purpose-specific crime-related exceptions. A realistic voice-agent scenario tests disclosure where AI interaction is not obvious. Distinguish provider design duties from deployer publication or notice duties, and read exceptions with the clear, timely and accessible information requirement. Basic familiarity with provider/deployer roles and synthetic media is useful. Disclosure does not itself make a prohibited use lawful. The set reflects the Commission’s current consolidated text and provides focused practice rather than official IAPP questions or a complete account of every transparency or transition requirement.

ai-governance

Oct 22, 2026

15 questions

Quiz

Vendor Audits, Certification Verification & Third-Party Attestation

Unofficial AIGP practice on evaluating vendor assurance evidence. The set relates to competency IV.B on assessing selected AI systems and vendor terms, with IV.C on ongoing operational assessment and supporting legal/framework knowledge from Domain II. Questions distinguish internal, customer and independent audits; examine certificate status, scope and accreditation; and test how to read assurance criteria, evidence, exceptions and limitations. ISO/IEC 42001 is treated as a management-system standard, while EU conformity assessment and CE marking are examined under their own procedures and application schedule. Employment examples consider the scoped audit and independence requirements of NYC Local Law 144. Other items address confidentiality-preserving audit methods, changing systems, log integrity and unsupported claims of universal fairness. A report or certificate is evidence to interpret, rather than a substitute for deployment-specific due diligence. Basic familiarity with vendor procurement, AI risks and assurance terminology is helpful. Practise asking whether the assessed entity, service, version, population and period match the proposed use, and whether residual gaps need further evidence or controls. This is focused independent practice, not an IAPP-endorsed product or comprehensive legal compliance checklist.

ai-governance

Oct 22, 2026

15 questions

Quiz

Conformity Assessments, CE Marking & Governance/Penalties

Unofficial AIGP practice on EU AI Act conformity assessment, provider responsibilities and enforcement. Prior familiarity with high-risk classification and the distinction between providers and deployers is useful. Practise selecting assessment routes, evaluating changes to intended purpose, distinguishing market-placement duties from CE marking, and applying administrative penalty rules with enterprise-size qualifications. The questions also distinguish Commission-level oversight from national responsibilities. Relevant to the conformity, recordkeeping and enforcement indicators in AIGP Body of Knowledge v2.1, competency II.C. Legal questions use the current Commission-hosted text checked in November 2026. High-risk scenarios state when the relevant obligations are assumed to apply; phased applicability and sectoral product rules still require separate checking. This is topic practice, not an official exam or a complete legal compliance checklist.

ai-governance

Oct 22, 2026

15 questions

Quiz

Data Bias Detection & Pre-Processing Mitigation Techniques

Unofficial AIGP practice on diagnosing data bias and choosing preprocessing responses. Questions distinguish systemic, computational and statistical, and human-cognitive sources of bias, then examine proxy information, annotation practices and pooled-model assumptions. Work through resampling, reweighing and feature transformations while checking what each method can and cannot establish. Employment examples distinguish a selection-rate warning from a legal finding and consider why demographic interventions need contextual legal review. EU AI Act questions separate bias examination from appropriate mitigation. Basic understanding of training data, classification and percentages is helpful. The set encourages explicit fairness objectives, independent validation and documentation of trade-offs rather than assuming one technique guarantees fairness. It supports selected IAPP data-governance competencies with related principles and legal context. This is independent study material, not official IAPP questions or a complete certification exam.

ai-governance

Oct 22, 2026

15 questions

Quiz

Generative AI Red Teaming: Jailbreaking, Prompt Injections & Hallucination Audits

Unofficial AIGP practice on direct and indirect prompt injection, persona and multilingual bypasses, hallucination audits, RAG limitations and layered tool-access controls. Includes risk-based red-team planning, reporting and release decisions. Aligned chiefly with IAPP BoK v2.1 III.B and III.C. Distinguishes voluntary NIST guidance from scoped EU AI Act obligations. Basic generative AI and retrieval concepts are helpful; this is a focused study aid, not an official exam.

ai-governance

Oct 22, 2026

15 questions

Quiz

General-Purpose AI (GPAI) & Systemic Risk Models

Unofficial AIGP practice on general-purpose AI models and systemic-risk responsibilities, supporting the GPAI and role-specific requirements in IAPP BoK 2.1, II.C. Distinguish the statutory model definition from systemic-risk classification, training-compute presumptions from Commission designation, and model-provider duties from downstream system-provider duties. Practice covers documentation, copyright policy, training-content summaries, conditional open-source exceptions, adversarial evaluation, incident reporting and cybersecurity. Basic familiarity with AI models and applications is useful. The set also distinguishes codes of practice as compliance tools from the presumption associated with covered harmonised standards. Read the questions with applicable transition provisions and current Commission guidance; an indicative guidance criterion should not be mistaken for statutory text. This focused resource is independently authored practice and is not an official IAPP exam or a complete legal compliance assessment.

ai-governance

Oct 22, 2026

15 questions

Quiz

Contractual Protections, SLAs & Shared Responsibility Allocation

Unofficial AIGP topic practice on evaluating AI vendor agreements and allocating operational responsibilities. The set supports competency IV.B of the IAPP AIGP Body of Knowledge, version 2.1, with related deployment controls in IV.C. Review scenarios distinguish confidentiality, retention and training restrictions; examine indemnity conditions and liability limits; and assess service quality, change notice, audit evidence, incident escalation and exit arrangements. Questions emphasize the difference between a term worth negotiating and a universally required clause. EU AI Act examples address downstream provider roles and supplier cooperation agreements. Read these alongside the current legal text and application schedule: an agreement can assign practical tasks and remedies but cannot simply erase statutory responsibilities. Other scenarios focus on evidence, measurement and coordination between procurement, legal, security and system owners. Familiarity with SaaS procurement and basic AI deployment is useful. Practise identifying missing protections and choosing terms that address a stated risk. This focused set is not a complete syllabus, legal advice or an official IAPP examination product.

ai-governance

Oct 22, 2026

15 questions

Quiz

Mandatory High-Risk Requirements: Articles 9–15

Unofficial AIGP practice on the EU AI Act requirements for high-risk AI systems, supporting IAPP BoK 2.1 competency II.C. The questions cover lifecycle risk management, purpose-fit datasets and bias safeguards, technical documentation, automatic logging, deployer-facing instructions, human oversight and security resilience. Applied items examine automation bias in clinical workflows and defenses against poisoned retraining data. Review the distinction between system design requirements and the operational duties assigned to providers and deployers. Basic AI lifecycle and data-governance knowledge is helpful. This review uses the Commission’s July 2026 consolidated text, including Article 4a’s replacement of former Article 10(5). The requirements should be read with the applicable transition provisions; the set is focused practice rather than a complete compliance checklist or official IAPP examination.

ai-governance

Oct 22, 2026

15 questions

Quiz

Vendor & Third-Party AI Due Diligence (COTS & Foundation APIs)

This unofficial AIGP practice set examines evidence needed when selecting commercial AI software, embedded AI features and foundation-model APIs. It extends conventional supplier checks with training-data rights and quality, model limitations, benchmark validity, safety evaluation and performance in the organization’s actual use case. Questions distinguish scoped control-assurance reports, AI management-system certification, product conformity evidence and algorithmic bias audits. They explore responsibilities retained by an enterprise using a hosted API, risks from moving model versions, and the practical tradeoffs of self-hosting open weights. A healthcare procurement scenario tests whether marketing accuracy claims are supported by suitable clinical evidence. Basic familiarity with supplier risk, AI model evaluation and deployment architectures is useful. The set supports vendor-assessment and deployment competencies in IAPP AIGP Body of Knowledge version 2.1. Certifications and reports provide evidence within a defined scope; none alone guarantees legal compliance, privacy or safe outcomes. Legal and regulatory requirements depend on the use, jurisdiction and applicable dates. These are original practice questions, not official IAPP exam items or an endorsement of any provider.

ai-governance

Oct 22, 2026

15 questions