task_categories:reinforcement-learning task_categories:text-classification task_categories:question-answering size_categories:1K<n<10K language:en license:cc-by-4.0 Ecolinguistics Sustainability ecolinguistic environment doi:10.57967/hf/1148 region:us
---
license: cc-by-4.0
task_categories:
- reinforcement-learning
- text-classification
- question-answering
language:
- en
tags:
- Ecolinguistics
- Sustainability
- ecolinguistic
- environment
size_categories:
- 1K<n<10K
---
# Dataset Card for Dataset H4rmony


### Dataset Summary

The H4rmony dataset is a collection of prompts and completions aimed at integrating ecolinguistic principles into AI Large Language Models (LLMs). 
Developed with collaborative efforts from ecolinguistics enthusiasts and experts, it offers a series of prompts and corresponding pairwise responses 
ranked in terms of environmental awareness and alignment. This ranking provides a clear metric for the desired alignment and establishes a framework for LLMs fine-tuning, particularly in reinforcement learning, 
via reward model. 

This dataset aims to bridge the gap between AI and ecolinguistic values, 
pushing the envelope for creating generative AI models that are environmentally and sustainability aware by design.

H4rmony is not just a dataset; it's a project towards harmonising AI with nature by means of fine-tuning.
We believe in the potential of using ecolinguistics to fine-tune and influence LLMs towards more eco-aware outputs.

This dataset is currently work in progress. 

### Languages

Currently only English but will be extended to multi-lingual.

## Dataset Structure

### Data Fields


![image/png](https://cdn-uploads.huggingface.co/production/uploads/64aac16fd4a402e8dce11ebe/tF_DPhg_R8jAyNRvVAuDz.png)


### Data Splits

There are no splits on the dataset. Splits can be created when loading the dataset:

dataset = (load_dataset('neovalle/H4rmony', split='train').train_test_split(test_size=0.2))

## Dataset Creation

### Curation Rationale

Given the multidisciplinary nature of the challenge, H4rmony dataset is being enriched by contributions from environmentalists, AI specialists, and ecolinguistics enthusiasts. 
This collective effort ensures the data is both technically sound and ecologically meaningful.

### Source Data

#### Initial Data Collection and Normalization

The core of the H4rmony dataset originated from active collaborations within the ecolinguistics community. 
Contributors were asked to submit prompts that would help uncover AI models' alignment with ecolinguistic values.

A number of prompts and completions were AI-generated using prompt engineering. 
To this intial group of prompts, human crafted prompts.

### Personal and Sensitive Information

This dataset doesn't contain sensitive information.

## Considerations for Using the Data

This dataset is under construction and hasn't been fully tested yet.
The datase might contain offensive language.

### Social Impact of Dataset

The H4rmony project aims to help AI LLMs to give priority to the crucial importance of environmental consciousness. 
By serving as the fourth "H", "Harmony with nature", it complements the existing triad of Helpfulness, Honesty, and Harmlessness already well known in ethical AI development.

### Discussion of Biases

Not known biases.

### Other Known Limitations

The dataset is still under constructions and the current number of rows might not be enough for some usage cases.

## Additional Information

### Dataset Curators

Jorge Vallego - airesearch@neovalle.co.uk

### Licensing Information

Creative Commons Attribution 4.0

### Citation Information

dataset neovalle/H4rmony - airesearch@neovalle.co.uk

### Testing and PoC Repository

https://github.com/Neovalle/H4rmony

### Note

This project has its roots in the article "Ecolinguistics and AI: Integrating eco-awareness in natural
language processing" https://www.ecoling.net/_files/ugd/ae088a_13cc4828a28e4955804d38e8721056cf.pdf
