Can you provide an example of how you have designed metrics and experiments to analyze problems and measure results?
- Follow-up: How did you ensure that the metrics aligned with the goals and objectives of the project?
Tell me about a time when you prototyped and evaluated effective solutions based on agreed-upon goals and metrics.
- Follow-up: What were the key factors you considered while evaluating the effectiveness of the solutions?
Have you generated any intellectual property, such as patent applications or publications, in your previous work? If so, could you provide an example?
- Follow-up: How do you ensure that your intellectual property aligns with the organization's overall goals?
How do you stay updated on the latest research and emerging technologies in machine learning and related disciplines?
- Follow-up: Could you provide an example of how you have leveraged state-of-the-art research in your work?
Tell me about your experience in publishing research papers and collaborating with other researchers.
- Follow-up: How do you ensure that your contributions are impactful within the research community?
How would you design an experiment to measure the effectiveness of scalable oversight techniques?
- Follow-up: Can you provide an example of how you have used AI-assisted feedback in your previous work?
Tell me about a time when you had to test the generalization ability of an AI system trained on easy problems. How did you approach the experiment?
- Follow-up: What were the challenges you faced during the experiment and how did you overcome them?
Describe a project where you managed large datasets and created visualizations for interpretability experiments. What tools did you use and what insights did you gain from the visualizations?
- Follow-up: How did you ensure the interpretability of the visualizations for different stakeholders?
How would you design an experiment to test how well chain of thought reasoning reflects model cognition?
- Follow-up: What metrics or criteria would you use to evaluate the success of the experiment?
Can you share an example of a situation where training against a reward signal caused deterioration in model outputs? How did you identify the cause and what steps did you take to address it?
- Follow-up: What precautions or strategies would you recommend to prevent similar issues in the future?
How would you approach setting research directions and strategies to ensure AI systems are safer, more aligned, and more robust?
- Follow-up: Can you give an example of a past project where you successfully implemented research strategies to improve AI system safety?
Tell me about your experience conducting research on AI safety topics. What specific challenges did you face?
- Follow-up: How did you overcome those challenges? What were the outcomes?
Describe a time when you had to effectively coordinate and collaborate with cross-functional teams to ensure AI products met high safety standards.
- Follow-up: What strategies did you use to foster collaboration and ensure alignment?
Can you provide an example of a safety audit you conducted on an AI/ML model or system? What risks did you identify, and how did you propose mitigation strategies?
- Follow-up: How did your proposed mitigation strategies contribute to the overall safety of the AI system?
In your opinion, what are the key elements of effective AI model deployment and safety work? How do you prioritize safety in these processes?
- Follow-up: How would you ensure alignment between safety considerations and other aspects of AI model deployment?
