Cognitive Pitfalls in Human-AI Interaction

Cognitive Engine is a text dataset addressing systematic errors in thinking and perception, particularly in human-AI interactions. Authored by ronniross, it was last updated in March 2026.

Use Cases

• Analyze text descriptions of cognitive pitfalls like confirmation bias to model reasoning errors.
• Train language models on interaction examples to identify patterns of bias in human-AI dialogues.
• Study the relationship between described cognitive shortcuts and their implications for Machine Learning systems.

Strengths

• Dataset is updated as of March 2026, indicating recent maintenance.
• Focuses on a specific, analytically relevant domain of cognitive pitfalls and human-AI interaction.

Limitations

• No sample data, column definitions, or row count provided to assess structure and scale.
• Scope and specific content are unclear without accessing the full external description.

Provenance

Source

huggingface

Collection Method

null

Time Range

null

Freshness

Last updated 2026-03-09.

Geography

Regionus tag suggests a US focus, but not confirmed.