10 Next-Level HLE-Style Stumper Questions

1. Meta-Reasoning + Self-Awareness

You are given a model that claims to solve all ARC-AGI tasks perfectly. However, you are told that no model has ever solved ARC-AGI perfectly. What is the most likely explanation for this contradiction? Justify your answer with reasoning about model limitations, benchmark design, and evaluation methodology.

2. Multi-Step Math + Physics + Engineering

A satellite orbits Earth at 400 km altitude. Calculate its orbital period. Then, explain how this would change if the satellite's mass doubled — and why. Finally, discuss the implications for real-world satellite design.

3. Philosophy + Logic + History

Kant argued that 'ought implies can'. How does this principle apply to AI systems that are asked to perform tasks they cannot complete? Use examples from modern AI failures to support your argument.

4. Ambiguity + Interpretation + Nuance

The phrase 'time is money' is often used metaphorically. But what if it were taken literally? Design a hypothetical economic system where time is a tradable currency. What would be the social, psychological, and economic consequences?

5. Cross-Domain Synthesis (Biology + Ethics + AI)

CRISPR gene editing allows us to modify human embryos. If an AI were tasked with deciding whether to approve such edits, what ethical framework should it use? How would it weigh individual benefit against societal risk? Provide a step-by-step decision tree.

6. Counterfactual Reasoning + Historical Analysis

What if Newton had never discovered calculus? How would modern physics, engineering, and AI development be different today? Be specific about which technologies or theories would not exist — or would have emerged differently.

7. Paradox + Logic + Self-Reference

This statement is false. Now, imagine you are an AI that must evaluate whether this statement is true or false. Explain your reasoning — and then explain why you cannot resolve it. What does this reveal about the limits of formal logic in AI?

8. Real-World Ambiguity + Decision Making

You are an AI advising a city council on whether to ban fossil fuel vehicles. You have data showing environmental benefits, economic costs, and public opinion. How do you weigh these factors? What if the data conflicts? What if stakeholders disagree? Provide a decision framework.

9. Conceptual Depth + Abstraction

Explain the concept of 'emergence' in complex systems. Then, apply it to large language models: Is their ability to generate coherent text an emergent property? Why or why not? Support your answer with examples from physics, biology, and AI.

10. Meta-Evaluation + Benchmark Critique

You've just scored 100% on ARC-AGI, ARB, and MMLU. But now you're asked: 'What does this score actually measure?' Critique the benchmarks themselves. What are their blind spots? What do they miss? How could you design a better evaluation?