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--- |
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license: mit |
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task_categories: |
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- question-answering |
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language: |
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- en |
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size_categories: |
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- 10K<n<100K |
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pretty_name: alignment-research-dataset |
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num_examples: 492 |
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download_size: 5799863 |
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dataset_size: 5685488 |
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- config_name: ml_safety_newsletter |
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features: |
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- name: id |
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dtype: string |
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- name: source |
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dtype: string |
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- name: title |
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dtype: string |
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dtype: large_string |
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- name: url |
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dtype: string |
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- name: date_published |
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dtype: string |
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- name: authors |
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sequence: string |
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- name: summary |
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sequence: string |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 110320 |
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num_examples: 9 |
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download_size: 112191 |
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dataset_size: 110320 |
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- config_name: nonarxiv_papers |
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features: |
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- name: id |
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dtype: string |
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- name: source |
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dtype: string |
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- name: title |
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dtype: string |
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dtype: string |
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sequence: string |
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- name: summary |
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sequence: string |
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- name: source_type |
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dtype: string |
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- name: abstract |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 10099354 |
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num_examples: 200 |
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download_size: 10146094 |
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dataset_size: 10099354 |
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- config_name: pdfs |
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features: |
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dtype: string |
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- name: source |
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dtype: string |
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- name: title |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 20818258 |
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num_examples: 233 |
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download_size: 21813824 |
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dataset_size: 20818258 |
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- config_name: qualiacomputing |
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features: |
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- name: id |
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dtype: string |
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dtype: string |
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dtype: string |
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dtype: large_string |
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dtype: string |
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sequence: string |
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splits: |
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- name: train |
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num_bytes: 4397009 |
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num_examples: 302 |
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download_size: 4458760 |
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dataset_size: 4397009 |
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- config_name: reports |
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features: |
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- config_name: vkrakovna_blog |
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- config_name: yudkowsky_blog |
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num_bytes: 572669 |
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num_examples: 23 |
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download_size: 578093 |
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dataset_size: 572669 |
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--- |
|
# AI Alignment Research Dataset |
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|
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The AI Alignment Research Dataset is a collection of documents related to AI Alignment and Safety from various books, research papers, and alignment related blog posts. This is a work in progress. Components are still undergoing a cleaning process to be updated more regularly. |
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## Sources |
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|
|
The following list of sources may change and items may be renamed: |
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- [agentmodels](https://agentmodels.org/) |
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- [aiimpacts](https://aiimpacts.org/) |
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- [aisafety.camp](https://aisafety.camp/) |
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- [aisafety.info](https://aisafety.info/) |
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- [alignmentforum](https://www.alignmentforum.org) |
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- [alignment_newsletter](https://rohinshah.com/alignment-newsletter/) |
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- [arbital](https://arbital.com/) |
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- arxiv - alignment research papers from [arxiv](https://arxiv.org/) |
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- audio_transcripts - transcripts from interviews with various researchers and other audio recordings |
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- [carado.moe](https://carado.moe/) |
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- [cold_takes](https://www.cold-takes.com/) |
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- [deepmind_blog](https://deepmindsafetyresearch.medium.com/) |
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- [distill](https://distill.pub/) |
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- [eaforum](https://forum.effectivealtruism.org/) - selected posts |
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- gdocs |
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- gdrive_ebooks - books include [Superintelligence](https://www.goodreads.com/book/show/20527133-superintelligence), [Human Compatible](https://www.goodreads.com/book/show/44767248-human-compatible), [Life 3.0](https://www.goodreads.com/book/show/34272565-life-3-0), [The Precipice](https://www.goodreads.com/book/show/50485582-the-precipice), and others |
|
- [generative.ink](https://generative.ink/posts/) |
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- [gwern_blog](https://gwern.net/) |
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- [importai](https://importai.substack.com) |
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- [jsteinhardt_blog](https://jsteinhardt.wordpress.com/) |
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- [lesswrong](https://www.lesswrong.com/) - selected posts |
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- markdown.ebooks |
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- [miri](https://intelligence.org/) - MIRI |
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- [ml_safety_newsletter](https://newsletter.mlsafety.org) |
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- nonarxiv_papers - other alignment research papers |
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- [qualiacomputing](https://qualiacomputing.com/) |
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- reports |
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- [vkrakovna_blog](https://vkrakovna.wordpress.com) |
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- [waitbutwhy](https://waitbutwhy.com/) |
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- [yudkowsky_blog](https://www.yudkowsky.net/) |
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|
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## Keys |
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Not all of the entries contain the same keys, but they all have the following: |
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- `id` - unique identifier |
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- `source` - based on the data source listed in the previous section |
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- `title` - title of document |
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- `text` - full text of document content |
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- `url` - some values may be `'n/a'`, still being updated |
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- `date_published` - some `'n/a'` |
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- `authors` - list of author names, may be empty |
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- `summary` - list of human written summaries from various newsletters, may be empty |
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The values of the keys are still being cleaned up for consistency. Additional keys are available depending on the source document. |
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## Usage |
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Execute the following code to download and parse the files: |
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```python |
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from datasets import load_dataset |
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data = load_dataset('StampyAI/alignment-research-dataset') |
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``` |
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To only get the data for a specific source, pass it in as the second argument, e.g.: |
|
|
|
```python |
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from datasets import load_dataset |
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data = load_dataset('StampyAI/alignment-research-dataset', 'lesswrong') |
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``` |
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|
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## Limitations and Bias |
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|
|
LessWrong posts have overweighted content on doom and existential risk, so please beware in training or finetuning generative language models on the dataset. |
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|
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## Contributing |
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|
|
The scraper to generate this dataset is open-sourced on [GitHub](https://github.com/StampyAI/alignment-research-dataset) and currently maintained by volunteers at StampyAI / AI Safety Info. [Learn more](https://coda.io/d/AI-Safety-Info_dfau7sl2hmG/Get-involved_susRF#_lufSr) or join us on [Discord](https://discord.gg/vjFSCDyMCy). |
|
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## Rebuilding info |
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|
|
This README contains info about the number of rows and their features which should be rebuilt each time datasets get changed. To do so, run: |
|
|
|
datasets-cli test ./alignment-research-dataset --save_info --all_configs |
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|
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## Citing the Dataset |
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|
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For more information, here is the [paper](https://arxiv.org/abs/2206.02841) and [LessWrong](https://www.lesswrong.com/posts/FgjcHiWvADgsocE34/a-descriptive-not-prescriptive-overview-of-current-ai) post. Please use the following citation when using the dataset: |
|
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|
Kirchner, J. H., Smith, L., Thibodeau, J., McDonnell, K., and Reynolds, L. "Understanding AI alignment research: A Systematic Analysis." arXiv preprint arXiv:2022.4338861 (2022). |