IAPP Updated AIGP Exam Questions and Answers by ray

The correct answer is D. Transparency obligations under data protection laws, such as GDPR and most AI governance frameworks, require that users whose data is being processed be directly informed.

From the AIGP ILT Guide (Privacy Module):

“The user privacy notice must be updated to explain the nature of automated processing, the logic involved, and the significance and consequences for the data subject.”

Also, per AI Governance in Practice Report 2024 (Part III):

“Transparency obligations apply throughout the lifecycle of AI… Individuals must be informed about automated decision-making and profiling that may impact them.”

Unlike internal policies or general privacy notices, the user privacy notice provides direct transparency to the individual data subjects affected by AI processing.

===========

Machine learning (ML) is a subset of artificial intelligence (AI) where systems use data to learn and improve over time without being explicitly programmed. Option B accurately describes machine learning by stating that systems can automatically improve from experience through predictive patterns. This aligns with the fundamental concept of ML where algorithms analyze data, recognize patterns, and make decisions with minimal human intervention. Reference: AIGP BODY OF KNOWLEDGE, which covers the basics of AI and machine learning concepts.

An AI model is best defined as a program that has been trained on a set of data to find patterns within that data. This definition captures the essence of machine learning, where the model learns from the data to make predictions or decisions. Reference: AIGP BODY OF KNOWLEDGE, which provides a detailed explanation of AI models and their training processes​​.

The correct answer is E – Superintelligence.

While the other options (Autonomy, Automation, Adaptability, Speed and Scale) are commonly cited as real-world characteristics that affect governance today, superintelligence remains a theoretical concept.

From the AIGP ILT Guide and AI Governance in Practice Report 2024:

“Core AI characteristics—such as automation, adaptability, speed, and autonomy—require active governance due to their impact on decision-making, legal liability, and risk.”

However, superintelligence is speculative and not a current feature of AI systems under governance frameworks like the EU AI Act or NIST RMF.

Thus, it's not a current characteristic requiring governance in real-world enterprise settings.