Question 1

What is the primary goal of Responsible AI?

Accepted Answer

Responsible AI aims for AI systems that are safe, fair, transparent, and accountable. It goes beyond mere compliance: it's a holistic approach that integrates technical, ethical, legal, and social aspects to develop AI that creates value for all stakeholders.

Question 2

Which of the following is NOT a core principle of Responsible AI according to commonly used frameworks?

Accepted Answer

The core principles of Responsible AI are: Fairness, Transparency, Accountability, Privacy, Safety, and Human-centricity. Profit maximization is not a core principle of Responsible AI, although responsible AI can create business value through trust and sustainable implementation.

Question 3

What is 'AI bias' in the context of Responsible AI?

Accepted Answer

AI bias refers to systematic and unfair discrimination or prejudice in AI decisions. This can arise from biased training data, algorithmic choices, or implementation. Bias can lead to discrimination based on gender, ethnicity, age, or other characteristics, which is both ethically and legally problematic.

Question 4

What is the difference between 'explainability' and 'interpretability' in AI?

Accepted Answer

Explainability refers to the ability to explain why an AI system made a specific decision (post-hoc). Interpretability means the model itself is inherently understandable (e.g., decision trees). Both are important for transparency, but interpretability is often more difficult with complex models like deep neural networks.

Question 5

What is 'human-in-the-loop' (HITL) in Responsible AI?

Accepted Answer

Human-in-the-loop (HITL) means there is meaningful human intervention in AI decisions, especially in high-risk applications. Humans can review, correct, or override AI outcomes. This is crucial for accountability and preventing automated discrimination, and is required by the EU AI Act for high-risk systems.

Question 6

What is the 'privacy by design' principle in Responsible AI?

Accepted Answer

Privacy by design means that privacy considerations are built into the design and architecture of AI systems from the very beginning, not added afterwards. This includes techniques such as data minimization, pseudonymization, encryption, and privacy-preserving AI (such as federated learning). It is a GDPR requirement.

Question 7

What is an 'AI Impact Assessment' (AIIA)?

Accepted Answer

An AI Impact Assessment (AIIA) is a systematic evaluation of the potential risks, ethical implications, privacy impact, and broader societal effects of an AI system. It helps organizations proactively identify and mitigate problems. Similar to DPIA (Data Protection Impact Assessment) but broader: it also includes bias, fairness, transparency, and societal impact.

Question 8

What is 'AI governance' in the context of Responsible AI?

Accepted Answer

AI governance is a comprehensive framework of policies, processes, roles, and responsibilities that ensures AI systems are developed and used ethically, safely, compliantly, and aligned with organizational goals. It includes risk management, oversight, monitoring, auditing, and clear accountability structures. Good AI governance is essential for Responsible AI.

Responsible AI Quiz