---
tags:
- rlfh
- argilla
- human-feedback
---

# Dataset Card for ai-human-trust







This dataset has been created with [Argilla](https://github.com/argilla-io/argilla). As shown in the sections below, this dataset can be loaded into your Argilla server as explained in [Load with Argilla](#load-with-argilla), or used directly with the `datasets` library in [Load with `datasets`](#load-with-datasets).


## Using this dataset with Argilla

To load with Argilla, you'll just need to install Argilla as `pip install argilla --upgrade` and then use the following code:

```python
import argilla as rg

ds = rg.Dataset.from_hub("KpopBarbie/ai-human-trust", settings="auto")
```

This will load the settings and records from the dataset repository and push them to you Argilla server for exploration and annotation.

## Using this dataset with `datasets`

To load the records of this dataset with `datasets`, you'll just need to install `datasets` as `pip install datasets --upgrade` and then use the following code:

```python
from datasets import load_dataset

ds = load_dataset("KpopBarbie/ai-human-trust")
```

This will only load the records of the dataset, but not the Argilla settings.

## Dataset Structure

This dataset repo contains:

* Dataset records in a format compatible with HuggingFace `datasets`. These records will be loaded automatically when using `rg.Dataset.from_hub` and can be loaded independently using the `datasets` library via `load_dataset`.
* The [annotation guidelines](#annotation-guidelines) that have been used for building and curating the dataset, if they've been defined in Argilla.
* A dataset configuration folder conforming to the Argilla dataset format in `.argilla`.

The dataset is created in Argilla with: **fields**, **questions**, **suggestions**, **metadata**, **vectors**, and **guidelines**.

### Fields

The **fields** are the features or text of a dataset's records. For example, the 'text' column of a text classification dataset of the 'prompt' column of an instruction following dataset.

| Field Name | Title | Type | Required |
| ---------- | ----- | ---- | -------- |
| Timestamp | Timestamp | text | False |
| Profession | Profession | text | False |
| Country | Country | text | False |
| AI_Usage_Frequency | AI_Usage_Frequency | text | False |
| AI_Tools_Used | AI_Tools_Used | text | False |
| AI_Usage_Area | AI_Usage_Area | text | False |
| Work_Quality_Impact | Work_Quality_Impact | text | False |
| AI_Desired_Answer | AI_Desired_Answer | text | False |
| AI_tool_training | AI_tool_training | text | False |
| AI_Accuracy | AI_Accuracy | text | False |
| AI_Concerns | AI_Concerns | text | False |
| Biased_Results_Frequency | Biased_Results_Frequency | text | False |
| AI_Failure_Experience | AI_Failure_Experience | text | False |
| Trust_AI_vs_Human | Trust_AI_vs_Human | text | False |
| Trust_Factors | Trust_Factors | text | False |
| Factcheck_Reason | Factcheck_Reason | text | False |
| Factcheck_Impact | Factcheck_Impact | text | False |


### Questions

The **questions** are the questions that will be asked to the annotators. They can be of different types, such as rating, text, label_selection, multi_label_selection, or ranking.

| Question Name | Title | Type | Required | Description | Values/Labels |
| ------------- | ----- | ---- | -------- | ----------- | ------------- |
| label_0 | label_0 | label_selection | True | N/A | ['positive', 'negative', 'neutral'] |


<!-- check length of metadata properties -->

### Metadata

The **metadata** is a dictionary that can be used to provide additional information about the dataset record.
| Metadata Name | Title | Type | Values | Visible for Annotators |
| ------------- | ----- | ---- | ------ | ---------------------- |
 | Age | Age | integer |  -  | True |
 | Productivity_Impact | Productivity_Impact | integer |  -  | True |
 | AI_Reliability | AI_Reliability | integer |  -  | True |
 | Ai_Stakeholder_Task_Trust_Level | Ai_Stakeholder_Task_Trust_Level | integer |  -  | True |
 | Feelings_High_Stakes_AI | Feelings_High_Stakes_AI | integer |  -  | True |
 | Importance_Knowing_AI_vs_Human | Importance_Knowing_AI_vs_Human | integer |  -  | True |





### Data Splits

The dataset contains a single split, which is `train`.

## Dataset Creation

### Curation Rationale

[More Information Needed]

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed]

#### Who are the source language producers?

[More Information Needed]

### Annotations

#### Annotation guidelines

[More Information Needed]

#### Annotation process

[More Information Needed]

#### Who are the annotators?

[More Information Needed]

### Personal and Sensitive Information

[More Information Needed]

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed]

### Discussion of Biases

[More Information Needed]

### Other Known Limitations

[More Information Needed]

## Additional Information

### Dataset Curators

[More Information Needed]

### Licensing Information

[More Information Needed]

### Citation Information

[More Information Needed]

### Contributions

[More Information Needed]