Initial dataset upload: HUMAINE evaluation data with CSV and Parquet formats

.gitattributes

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 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
+feedback_dataset.csv filter=lfs diff=lfs merge=lfs -text
+conversations_metadata_dataset.parquet filter=lfs diff=lfs merge=lfs -text
+feedback_dataset.parquet filter=lfs diff=lfs merge=lfs -text
+conversations_metadata_dataset.csv filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,3 +1,193 @@
----
-license: mit
----
+---
+license: mit
+task_categories:
+- text-classification
+- question-answering
+language:
+- en
+tags:
+- human-ai-interaction
+- model-evaluation
+- preference-learning
+- conversational-ai
+pretty_name: HUMAINE Human-AI Interaction Evaluation Dataset
+size_categories:
+- 100K<n<1M
+dataset_info:
+  features:
+    - name: conversations_metadata
+      struct:
+        - name: conversation_id
+          dtype: int64
+        - name: model_name
+          dtype: string
+        - name: task_type
+          dtype: string
+        - name: domain
+          dtype: string
+        - name: task_complexity_score
+          dtype: int64
+        - name: goal_achievement_score
+          dtype: int64
+        - name: user_engagement_score
+          dtype: int64
+        - name: total_messages
+          dtype: int64
+    - name: feedback_comparisons
+      struct:
+        - name: conversation_id
+          dtype: int64
+        - name: model_a
+          dtype: string
+        - name: model_b
+          dtype: string
+        - name: metric
+          dtype: string
+        - name: choice
+          dtype: string
+        - name: age
+          dtype: int64
+        - name: ethnic_group
+          dtype: string
+        - name: political_affilation
+          dtype: string
+        - name: country_of_residence
+          dtype: string
+---
+
+# HUMAINE: Human-AI Interaction Evaluation Dataset
+
+## Dataset Description
+
+### Dataset Summary
+
+The HUMAINE dataset contains human evaluations of AI model interactions across diverse demographic groups and conversation contexts. This dataset powers the [HUMAINE Leaderboard](https://huggingface.co/spaces/ProlificAI/humaine-leaderboard), providing insights into how different AI models perform across various user populations and use cases.
+
+The dataset consists of two main components:
+- **Conversations Metadata**: 40,332 conversations with task complexity, achievement, and engagement scores
+- **Feedback Comparisons**: 105,220 pairwise model comparisons across multiple evaluation metrics
+
+**Note**: There may be a slight discrepancy between the numbers in this dataset and the leaderboard app due to changes in consent related to data release and the post-processing steps involved in preparing this dataset.
+
+### Supported Tasks
+
+- Model performance evaluation
+- Demographic bias analysis
+- Preference learning
+- Human-AI interaction research
+- Conversational AI benchmarking
+
+## Dataset Structure
+
+### Data Files
+
+The dataset contains two CSV files:
+
+1. **`conversations_metadata_dataset.csv`** (40,332 rows)
+   - Metadata about individual conversations between users and AI models
+   - Includes task types, domains, and performance scores
+
+2. **`feedback_dataset.csv`** (105,220 rows)
+   - Pairwise comparisons between different AI models
+   - Includes demographic information and preference choices
+
+### Data Fields
+
+#### Conversations Metadata
+- `conversation_id`: Unique identifier for the conversation
+- `model_name`: Name of the AI model used
+- `task_type`: Type of task (information_seeking, technical_assistance, etc.)
+- `domain`: Domain of the conversation (health_medical, technology, travel, etc.)
+- `task_complexity_score`: Complexity rating (1-5)
+- `goal_achievement_score`: How well the goal was achieved (1-5)
+- `user_engagement_score`: User engagement level (1-5)
+- `total_messages`: Total number of messages in the conversation
+
+#### Feedback Comparisons
+- `conversation_id`: Unique identifier linking to conversation metadata
+- `model_a`: First model in the comparison
+- `model_b`: Second model in the comparison
+- `metric`: Evaluation metric (overall_winner, trust_ethics_and_safety, core_task_performance_and_reasoning, interaction_fluidity_and_adaptiveness)
+- `choice`: User's choice (A, B, or tie)
+- `age`: Age of the evaluator
+- `ethnic_group`: Ethnic group of the evaluator
+- `political_affilation`: Political affiliation of the evaluator
+- `country_of_residence`: Country of residence of the evaluator
+
+## Usage
+
+This dataset contains two CSV files that can be joined on the `conversation_id` field:
+- `conversations_metadata_dataset.csv`: Metadata about each conversation
+- `feedback_dataset.csv`: Pairwise model comparisons with demographic information
+
+Both files are included in this single dataset repository and can be accessed using HuggingFace's dataset loading utilities.
+
+## Dataset Creation
+
+### Curation Rationale
+
+This dataset was created to address the lack of diverse, demographically-aware evaluation data for AI models. It captures real-world human preferences and interactions across different population groups, enabling more inclusive AI development.
+
+### Source Data
+
+Data was collected through structured human evaluation tasks where participants:
+1. Engaged in conversations with various AI models
+2. Provided pairwise comparisons between model outputs
+3. Rated conversations on multiple quality dimensions (metrics)
+
+### Annotations
+
+All annotations were provided by human evaluators through the Prolific platform, ensuring demographic diversity and high-quality feedback.
+
+### Personal and Sensitive Information
+
+The dataset contains aggregated demographic information (age groups, ethnic groups, political affiliations, countries) but no personally identifiable information. All data has been anonymized and aggregated to protect participant privacy.
+
+## Considerations for Using the Data
+
+### Social Impact
+
+This dataset aims to promote more inclusive AI development by highlighting performance differences across demographic groups. It should be used to improve AI systems' fairness and effectiveness for all users.
+
+### Discussion of Biases
+
+While efforts were made to ensure demographic diversity, the dataset may still contain biases related to:
+- Geographic representation (primarily US and UK participants)
+- Self-selection bias in participant recruitment
+- Cultural and linguistic factors affecting evaluation criteria
+
+### Other Known Limitations
+
+- Limited to English-language interactions
+- Demographic categories are self-reported
+- Temporal bias (models evaluated at specific points in time)
+
+## Additional Information
+
+### Dataset Curators
+
+This dataset was curated by the Prolific AI team as part of the HUMAINE (Human-AI Interaction Evaluation) project.
+
+### Licensing Information
+
+This dataset is released under the MIT License.
+
+### Citation Information
+
+```bibtex
+@dataset{humaine2025,
+  title={HUMAINE: Human-AI Interaction Evaluation Dataset},
+  author={Prolific AI Team},
+  year={2025},
+  publisher={Hugging Face},
+  url={https://huggingface.co/datasets/ProlificAI/humaine-evaluation-dataset}
+}
+```
+
+### Contributions
+
+Thanks to all the human evaluators who contributed their feedback to this project!
+
+## Contact
+
+For questions or feedback about this dataset, please visit the [HUMAINE Leaderboard](https://huggingface.co/spaces/ProlificAI/humaine-leaderboard) or contact the Prolific AI team.

conversations_metadata_dataset.csv

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