AI Accountability Failures: What Can Go Wrong | QuizBy Eyal Doron / December 6, 2025 / 1 minute of reading AI Accountability Failures: What Can Go Wrong | Quiz 1 / 7 1. What is the purpose of a RACI matrix in AI accountability? 1. To calculate the return on investment for AI governance programs 2. To assess the technical capabilities of AI team members 3. To rank AI systems by their risk level for compliance purposes 4. To document who is responsible accountable consulted and informed for each AI decision Correct! WHY: A RACI matrix documents who is Responsible Accountable Consulted and Informed for each aspect of the AI system lifecycle preventing ambiguity. CONTEXT: This structured approach unites cross-functional teams under shared responsibility instead of allowing siloed thinking. REMEMBER: RACI prevents the everyone and therefore no one is responsible trap. 2 / 7 2. What percentage of AI incidents trace to unclear roles and responsibilities according to the article? 1. 30 percent 2. 90 percent 3. 50 percent 4. 70 percent Correct! WHY: This statistic from Forrester demonstrates that the majority of AI incidents stem from governance failures not technical failures. CONTEXT: When 70 percent of incidents trace to unclear roles it shows that accountability structures matter more than technical sophistication. REMEMBER: Seventy percent of AI incidents are accountability failures not technical failures. 3 / 7 3. What quick win does the article recommend for improving AI accountability? 1. Create an AI ethics committee with monthly meetings 2. Purchase AI governance software from a major vendor 3. Define the accountable owner and required documentation for your two highest-risk AI systems 4. Hire a dedicated AI ethics officer for your organization Correct! WHY: Defining accountable owners and documentation requirements for high-risk systems is an immediate actionable step that addresses the most critical accountability gaps. CONTEXT: This focuses resources on the systems where accountability failures would cause the most harm. REMEMBER: Start with your two highest-risk AI systems this month. 4 / 7 4. What is the maximum EU AI Act penalty for accountability failures mentioned in the article? 1. 100 million euros or 10 percent of global revenue 2. 35 million euros or 4 percent of global revenue 3. 10 million euros or 1 percent of global revenue 4. 5 million euros or 0.5 percent of global revenue Correct! WHY: The EU AI Act establishes significant financial penalties to enforce accountability requirements for high-risk AI systems. CONTEXT: This reflects the regulatory trend toward codifying accountability expectations with real financial consequences. REMEMBER: 35 million euros or 4 percent of revenue represents substantial organizational risk. 5 / 7 5. According to the article what three things does accountability require? 1. Compliance certifications and audit reports and insurance coverage 2. AI training data and model architecture and deployment infrastructure 3. Clear ownership and documentation of decisions and ability to explain outcomes 4. Technical expertise and budget allocation and executive sponsorship Correct! WHY: These three elements form the foundation of accountability because without any one of them responsibility cannot be established or enforced. CONTEXT: Clear ownership identifies who is responsible while documentation enables reconstruction and explainability allows justification. REMEMBER: Missing any one creates accountability gaps. 6 / 7 6. When a company says the AI did it in response to AI-caused harm what does this represent? 1. A valid legal defense in most jurisdictions 2. An accountability failure that deflects responsibility to the algorithm 3. A technical explanation for model behavior 4. An accurate description of autonomous AI decision-making Correct! WHY: Saying the AI did it is an accountability failure because it deflects responsibility to a tool rather than the humans who chose to deploy it. CONTEXT: Just as we do not say the spreadsheet did it when financial decisions go wrong we cannot blame AI for decisions humans enabled. REMEMBER: AI is a tool and tools cannot be accountable. 7 / 7 7. What is an AI accountability failure? 1. When AI systems fail to produce accurate predictions 2. When AI models exceed their computational budget 3. When machine learning training takes too long 4. When responsibility for AI decisions is diffused or deflected so no one is clearly responsible Correct! WHY: An AI accountability failure occurs when no one can be identified as responsible for AI decisions and their consequences. CONTEXT: This creates accountability gaps where harm goes unaddressed and remediation becomes impossible. REMEMBER: If nobody is accountable then nothing gets fixed. Your score isThe average score is 0% Restart quiz Download PDF Please leave this field empty๐ The AI Security Manager's Newsletter Weekly insights on AI risk management, EU AI Act compliance, and practical security strategies. We donโt spam! Read our privacy policy for more info. Thank you! Please check your inbox to confirm your subscription.
