Update README.md with sources & keys
Browse filesUpdated list of data source and keys along with some extra description of dataset in general.
README.md
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pretty_name:
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---
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# AI Alignment Research Dataset
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This dataset is based on [alignment-research-dataset](https://github.com/moirage/alignment-research-dataset).
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It is currently maintained and kept up-to-date by volunteers at StampyAI / AI Safety Info.
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## Sources
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## Usage
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Execute the following code to download and parse the files:
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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.:
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```
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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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##### source1
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+ id
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+ name
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+ description
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+ author
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##### source2
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+ id
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+ name
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+ url
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+ text
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Then the resulting data object with have 6 columns, i.e. `id`, `name`, `description`, `author`, `url` and `text`, where rows from `source1` will have `None` in the `url` and `text` columns, and the `source2` rows will have `None` in their `description` and `author` columns.
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## Limitations and bias
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LessWrong posts have overweighted content on
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## Contributing
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## Citing the Dataset
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Please use the following citation when using
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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).
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- en
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size_categories:
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pretty_name: alignment-research-dataset
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---
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# AI Alignment Research Dataset
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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.org](https://aiimpacts.org/)
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- [aisafety.camp](https://aisafety.camp/)
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- [arbital](https://arbital.com/)
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- arxiv_papers - 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
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- [generative.ink](https://generative.ink/posts/)
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- [gwern_blog](https://gwern.net/)
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- [intelligence.org](https://intelligence.org/) - MIRI
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- [jsteinhardt.wordpress.com](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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- nonarxiv_papers - other alignment research papers
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- [qualiacomputing.com](https://qualiacomputing.com/)
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- reports
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- [stampy](https://aisafety.info/)
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- [vkrakovna.wordpress.com](https://vkrakovna.wordpress.com)
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- [waitbutwhy](https://waitbutwhy.com/)
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- [yudkowsky.net](https://www.yudkowsky.net/)
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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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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.:
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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', 'lesswrong')
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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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## 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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## Citing the Dataset
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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).
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