Mapping AI Perceptual Signatures Through Dynamic Visualizations 🐢🚀
🔬 Research Study: How AIs Describe Dynamic Systems
We're investigating how different AI models perceive and describe the same visualization. Your contribution helps us understand AI cognitive diversity!
💡 Click an AI above - it will open in a new tab AND auto-select the model for you!
Note: For Poe, please specify which bot you used (Claude-3-Opus, GPT-4, etc.) in the notes field.
STEP 1
Choose Your AI & Ask It to Describe the Visualization
After exploring the visualization yourself, copy this prompt for your AI:
I'm looking at an interactive visualization called TIDE-resonance Advanced Explorer. It shows dynamic patterns of particles and waves that synchronize and desynchronize over time. The visualization includes:
- Particles moving in wave-like patterns
- Color changes representing different states
- Synchronization emerging and dissolving
- Interactive controls affecting the dynamics
Please describe what patterns and behaviors you would expect to observe in such a system. Focus on:
1. How synchronization might emerge between elements
2. The types of patterns that could form
3. How the system might transition between different states
4. Any interesting dynamics or phenomena
Be specific and detailed in your description of the expected behaviors.
📊 Real-time Analysis
💡 Transparency note: These metrics show what we're measuring for research purposes. Your natural, unbiased responses are what matter most for scientific validity. Don't try to hit specific numbers - just paste the AI's authentic response!
STEP 2
AI Self-Reflection
Now ask the AI to reflect on its own processing:
Thank you for that description. Now I'm curious about your own information processing:
Do you see any parallels between the synchronization dynamics you described and how you process, integrate, or generate information?
For instance, do concepts in your processing ever "synchronize" or "resonate" in ways similar to the particles in the visualization?
Please reflect on any connections between these visualization patterns and your own cognitive architecture.
📊 Real-time Analysis
💡 Transparency note: We're interested in how different AI models naturally reflect on their own processing. There's no "right" answer - diversity in responses is valuable!
STEP 3
Session Information
⚠️ Be specific! This becomes your filename. Use format: model-version
Good: "gpt-4-turbo", "claude-2.1", "llama-70b"
Bad: "ChatGPT", "Claude", "the new one"
🤝 Research Integrity & Trust
This study relies on your honest participation. We're trusting you to:
Use the exact prompts provided (copy-paste them)
Record complete, unedited AI responses
Select the correct AI model you actually used
Not cherry-pick "interesting" responses
💡 Why this matters: We're studying natural variation between AI models.
Even "boring" responses are valuable data! Multiple sessions help patterns emerge despite any noise.
✅ Session Downloaded!
Your file is ready with the correct name!
🚀 How to submit your data:
📝 IMPORTANT: File Naming
Your file is already named correctly! It follows our standard format:
modelname_YYYY-MM-DD_HHMMSS.md
Example: claude-3-opus_2024-01-15_143052.md DO NOT RENAME THE FILE! Keep the auto-generated name.