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1890 learning items

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Quiz

High-Risk AI Systems Classification: Annex I & Annex III

Unofficial AIGP practice on EU AI Act high-risk classification, aligned to the risk-classification competency in IAPP BoK 2.1, II.C. Practise the product-related and Annex III routes, cumulative product criteria, employment and essential-services examples, critical infrastructure, and the limits of the procedural derogation. Questions distinguish profiling and material influence from administrative support, and examine the provider’s documentation and registration duties. Basic familiarity with provider/deployer roles is useful. Read intended uses and exceptions together rather than treating whole industries as high-risk. The review uses the Commission’s consolidated July 2026 text; classification provisions and their applicability dates are separate issues. This focused set does not cover every Annex III use or replace official legislation or IAPP preparation materials.

ai-governance

Oct 22, 2026

15 questions

Quiz

Conducting Fundamental Rights Impact Assessments (FRIA) & DPIAs for AI

This unofficial AIGP practice set compares fundamental rights impact assessments under the EU AI Act with data protection impact assessments under GDPR. It examines who is covered, which AI uses trigger a FRIA, and why likely high-risk personal-data processing can require a separate DPIA. Questions address assessment contents, affected groups, human oversight, complaint arrangements, authority notification, workplace information, and updating findings when a system or its context changes. Banking, insurance and healthcare scenarios distinguish practical mitigation choices from statutory requirements. Charter references separate the right to an effective remedy from good administration. Basic familiarity with controllers, deployers, high-risk AI classification and GDPR is useful. The material supports IAPP AIGP Body of Knowledge version 2.1 competencies concerning impact assessments and applicable legal requirements. The Commission’s consolidated AI Act text checked in November 2026 schedules Annex III high-risk duties from 2 December 2027; particular commencement and transition rules must be checked before asserting a present obligation. GDPR duties are assessed independently. These original questions are unofficial practice and do not replace jurisdiction-specific legal analysis.

ai-governance

Oct 22, 2026

16 questions

Quiz

Data Quality, Completeness & Representativeness

Unofficial AIGP practice on deciding whether data are fit for an AI system’s intended purpose. Questions address quality dimensions, population coverage, missing values, historical measurement processes, synthetic data and changes over time. Scenarios require separating a plausible risk from a demonstrated result. They examine why aggregate performance, a large row count or a completed field cannot alone establish trustworthy data. Governance questions connect provenance, acceptance criteria, ongoing review and purpose-limited handling of sensitive audit information. Basic familiarity with training, validation, testing and simple performance metrics is useful. EU AI Act references use the amended data-governance framework, including Article 4a safeguards for exceptional bias-related sensitive-data processing. This focused set supports selected IAPP data-governance and maintenance competencies. It is independent practice and does not claim complete exam coverage.

ai-governance

Oct 22, 2026

15 questions

Quiz

Conducting Algorithmic Impact Assessments (AIA)

This unofficial AIGP practice set focuses on assessing the effects of automated decisions on people and communities. It covers purpose and context, affected groups, decision severity and reversibility, system characteristics, stakeholder engagement, quantitative evidence and qualitative rights analysis. Public-service and workplace scenarios ask learners to connect assessment findings with safeguards, deployment authorization, communication and lifecycle review. Canadian federal AIA examples distinguish the questionnaire’s impact levels and publication requirements from general enterprise practices. The set also shows how assessment findings can inform the four NIST AI Risk Management Framework functions without treating a voluntary framework as binding law. Basic familiarity with AI system lifecycles, risk evaluation and organizational accountability is helpful. The questions support impact-assessment competencies in IAPP AIGP Body of Knowledge version 2.1, especially assessment of a selected system before deployment. They are original study material and do not reproduce official IAPP items. An assessment is a decision-support and accountability process; it does not itself establish legal compliance or authorize risks that applicable law prohibits.

ai-governance

Oct 22, 2026

15 questions

Quiz

Security Testing: Adversarial Attacks, Poisoning & Model Inversion

Unofficial AIGP practice on adversarial ML threat models, evasion, poisoning and backdoors, membership inference, inversion and model extraction. Covers differential privacy and defense limitations, plus security-validation and release-evidence scenarios. Aligned chiefly with IAPP BoK v2.1 III.B and III.C; assumes basic model-training and API concepts. Uses NIST attack terminology and distinguishes risk mitigation from guaranteed protection or automatic legal conclusions.

ai-governance

Oct 22, 2026

15 questions

Quiz

Mitigating Automation Bias, Deskilling & Operator Complacency

This unofficial AIGP practice set explores automation bias, reduced vigilance and the risk of losing independent professional skills when AI becomes a routine decision aid. It distinguishes overreliance on recommendations from model bias or malicious data manipulation. Questions examine independent preliminary judgments, evidence checks, alert quality, realistic workloads, safe synthetic exercises, protected unassisted practice and feedback-label quality. Learners evaluate warning indicators such as declining override rates without assuming that a single metric proves complacency. The exercises also address the limits and usability costs of cognitive forcing designs. Familiarity with human oversight workflows and basic AI risk terminology is useful. The set supports workforce-readiness, user-training and monitoring competencies in IAPP AIGP Body of Knowledge version 2.1. EU AI Act references distinguish provider design requirements from deployer staffing and support responsibilities; current applicability rules still need to be checked for each use case. The material is original, unofficial practice and does not certify operator competence or replace task-specific testing.

ai-governance

Oct 22, 2026

15 questions

Quiz

Designing Human Oversight Workflows: HITL, HOTL & Escalation Triggers

This unofficial AIGP practice set examines how organizations turn human oversight policies into workable decision and escalation processes. It covers human approval gates, supervisory monitoring, risk-based referral rules, evidence-focused review interfaces, safe interruption and service-failure contingencies. Scenarios ask learners to judge whether a reviewer has sufficient information, time, authority and support to challenge an AI recommendation. Questions also examine oversight indicators and why agreement rates or fast reviews require contextual investigation rather than automatic conclusions about quality. Basic familiarity with AI risk management and the distinction between providers and deployers is useful. The material supports the deployment, workforce-readiness and operational-governance competencies in the IAPP AIGP Body of Knowledge, version 2.1. EU AI Act questions distinguish system-design requirements from deployer responsibilities; legal applicability and transition dates must be checked for the particular system. These are original study questions, not official IAPP examination items.

ai-governance

Oct 22, 2026

15 questions

Quiz

Robustness, Out-of-Distribution (OOD) Testing & Stress Testing

Unofficial AIGP practice on robustness, out-of-distribution evaluation, corruption and boundary tests, calibration and assumption-dependent uncertainty estimates. Includes safe fallback and release-evidence scenarios. Aligned chiefly with IAPP BoK v2.1 III.B and III.C; basic classification concepts are helpful. Distinguishes technical evidence and its limits from EU AI Act requirements and voluntary standards. It is a focused study aid, not an official exam.

ai-governance

Oct 22, 2026

15 questions

Quiz

Data Sourcing, Scraping Ethics & Licensing Verification

Unofficial AIGP practice on assessing whether proposed training data can be collected and used for an intended AI project. Work through commercial-use restrictions, open licences, public web access, supplier due diligence and the difference between technical availability and legal permission. Scenarios distinguish copyright, contract and privacy questions. The set covers the EU general text-and-data-mining exception, GPAI copyright-policy and training-content summary duties, and selected United States authorities with their jurisdictional limits. It also examines why synthetic data and model outputs may retain contractual restrictions. Basic knowledge of data pipelines and licensing terminology is helpful. Use this set to practise identifying assumptions, gathering evidence and escalating unresolved rights questions. It supports selected IAPP data-governance competencies and related legal topics, without claiming that AI-training copyright questions have one universal answer. This is independent practice, not official IAPP material or legal advice for a particular project.

ai-governance

Oct 22, 2026

15 questions

Quiz

Unacceptable Risk: Prohibited AI Practices (Article 5)

Unofficial AIGP practice on prohibited AI practices and their statutory boundaries. Questions cover harmful manipulation, exploitation of vulnerabilities, qualifying social scoring, profile-based criminal-risk predictions, untargeted facial scraping, workplace and education emotion inference, sensitive biometric categorisation and real-time public-space biometric identification by law enforcement. Scenarios focus on the elements that make a practice prohibited, the narrow exceptions and the distinction between a prohibited use and other regulated uses of the same technology. Consent, conformity assessment or a commercial setting does not automatically settle legality. Customer emotion analysis requires attention to worker safeguards, transparency, high-risk classification and data protection. The material follows the Commission’s text based on the 27 July 2026 consolidated AI Act. It distinguishes the original prohibitions applicable since February 2025 from the added intimate-content and child-abuse-material provisions applying from 2 December 2026. Familiarity with AI uses and EU risk categories is helpful. This focused set supports IAPP AIGP BoK v2.1 Domain II.C; it is unofficial practice rather than a complete compliance checklist.

ai-governance

Oct 22, 2026

16 questions

Quiz

Model Performance Validation: Disaggregated Metrics & Parity Audits

Unofficial AIGP topic practice on classification metrics, subgroup and intersectional evaluation, fairness trade-offs and evidence-based release decisions. Includes numerical and governance scenarios aligned chiefly with IAPP BoK v2.1 III.B, with III.C release assurance. Basic binary-classification knowledge is useful. Legal screening ratios and voluntary frameworks are distinguished from compliance conclusions; this is a focused study aid, not an official exam or a guarantee of compliance.

ai-governance

Oct 22, 2026

15 questions

Quiz

Responsible Design Principles: Value-Sensitive Design & Human Centricity

Unofficial AIGP practice on bringing human values into AI design. Explore value-sensitive design, the perspectives of affected nonusers, participatory engagement and the translation of ethical trade-offs into design decisions. Interface scenarios examine transparency, contestability, automation bias and clinical decision support. Questions distinguish voluntary design approaches from the specific conditions and roles in EU AI Act provisions. Useful preparation includes basic AI terminology and familiarity with risk-based governance. Use this focused set to practise reasoning about whose interests are represented, what evidence supports an interface claim and how oversight works in practice. It supports selected IAPP development-governance competencies, with related principles and legal context. It is independent practice material, not official IAPP content or a complete exam simulation.

ai-governance

Oct 22, 2026

15 questions