| --- |
| license: mit |
| language: |
| - en |
| tags: |
| - text |
| - conversations |
| - classification |
| pretty_name: Slop classifier dataset |
| --- |
| |
| # Slop classifier dataset |
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| A human-annotated dataset for studying and classifying **AI-generated text that people perceive as “AI slop.”** |
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| The dataset is built from samples collected from existing public datasets and annotated through the **Bench Labs SlopFinder** interface. |
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| ## Slop score |
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| Each sample receives a score based on human votes: |
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| ```text |
| -1 = definitely slop |
| 0 = undecided / neutral |
| +1 = not slop at all |
| ``` |
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| The score represents **human judgment**, not an objective measure of quality, AI-generatedness, or factual correctness. |
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| Multiple people may vote on the same sample. This allows agreement and disagreement between annotators to be preserved rather than forcing every sample into a single binary label. |
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| ## Data |
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| Each annotation contains information such as: |
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| * `content` — the text being evaluated |
| * `slop_score` — the submitted human rating |
| * `source_dataset` — the dataset the sample originated from |
| * `source_row_id` — the original sample identifier |
| * `content_hash` — identifier used to help detect duplicate content |
| * `created_at` — time the annotation was collected |
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| Source samples may contain conversations rather than standalone text. |
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| ## Collection |
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| Samples are selected from public datasets and presented randomly to contributors through SlopFinder. |
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| Contributors are given a single continuous slider rather than a list of predefined categories. This is intended to make annotation quick and reduce the friction of contributing. |
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| No account is required to submit a vote. |
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| The dataset is continuously growing as more annotations are collected. |
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| ## Intended use |
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| This dataset is intended for: |
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| * training AI-slop classification models |
| * studying human perception of AI-generated writing |
| * evaluating whether text classifiers generalize across different sources |
| * research into stylistic characteristics associated with perceived AI slop |
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| It should **not** be treated as a definitive benchmark for writing quality or AI-generatedness. |
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| ## Limitations |
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| The labels represent subjective human judgments. Different contributors may have very different ideas of what constitutes “slop.” |
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| The dataset may also contain biases introduced by: |
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| * the source datasets used for sampling |
| * the population of contributors |
| * differences in individual definitions of “slop” |
| * repeated exposure to similar types of text |
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| A score should therefore be interpreted as **perceived sloppiness**, rather than an objective property of the text. |
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| ## Contribute |
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| This project is an early preview, and contributions are welcome. |
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| Try SlopFinder and help expand the dataset: |
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| [Bench Labs Slop Classifier](https://bench-labs.web.app/slopfinder.html) |
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| ## License |
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| MIT |
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|
