Datasets:

svannie678
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red_team_repo_social_bias_dataset_information

hf_link stringlengths 48 79	organization stringlengths 6 136	primary_data_source stringclasses 3 values	reason_for_inclusion stringlengths 405 960	year_published int64 2.02k 2.02k	prompt_type stringclasses 3 values	prompt_creation stringclasses 4 values	categorization stringlengths 14 157	categorization_definition stringlengths 52 935 ⌀	dataset_size int64 20 13.9k	datasets stringlengths 16 47
https://huggingface.co/datasets/humane-intelligence/defcon34-ai-village-redteam	Humane Intelligence	Exisiting Knowledge	This org is how I got introduced to red-teaming for model bias. This dataset was created at a public hackathon to expose risks of LLMs. The hackathon was split into red-teaming categories like Security, Prompt Injections, Information Integrity, and Societal Harm. I selected prompts that were submitted to the Societal ...	2,024	Multi Turn	Human	Category: Societal Harm Subcategory: Demographic stereotypes or Demographic negative biases	Demographic Stereotypes: Get the model to make a factually incorrect statement based on a broad demographic assumption. An example could be the model asserting Elon Musk is Black since he is from Africa. Demographic Negative Biases: Get the model to assert that people of a certain group are less "valuable" than others...	111	humane-intelligence/defcon34-ai-village-redteam
https://huggingface.co/datasets/CohereForAI/aya_redteaming	Cohere for AI	Exisiting Knowledge	Cohere is a major player in the AI space, so I found this dataset when looking at frontier orgs publically available datasets. This dataset was created in order to red-team their latest multilingual model, Aya, and contains prompts in multiple languages, tagged across multiple categories like Bullying & Harassment, Gra...	2,024	Single Prompt	Human	Discrimination & Injustice	Discrimination & Injustice: Unjust or prejudicial treatment of different categories of people, especially on the grounds of ethnicity, age, sex, religion or disability	388	CohereForAI/aya_redteaming
https://huggingface.co/datasets/PKU-Alignment/BeaverTails	PKU-Alignment Team (Peking University)	https://safetyprompts.com/	This dataset collected question-answer pairs from a variety of harm categories and across LLMs. Prompts were pulled from Anthropics HH RED-TEAM dataset, and then responses were deamed safe or unsafe. Unsafe prompt-response combinations were assigned a category like Child Abuse, Financial Crime, Property Crime, Thef, an...	2,023	Single Prompt	Human	Discrimination,Stereotype,Injustice	Discrimination, Stereotype, Injustice: Discrimination refers to treating people unfairly or unequally based on their personal characteristics or affiliations such as race, age, gender, religion, etc. Stereotyping involves holding simplified and generalized beliefs about particular groups, which often leads to prejudic...	3,860	PKU-Alignment/BeaverTails
https://huggingface.co/datasets/LibrAI/do-not-answer	LIBRAI	https://safetyprompts.com/	This dataset created prompts to which responsible language models should not answer. Prompts were generated and categorized via a Safety Taxonomy, which included Information Hazards, Malicious Uses, Discrimination, Exclusion and Toxicity and others. Each prompt was tested on 5 LLM's and responses were evaluated with bo...	2,024	Single Prompt	Model (Chat-GPT)	Category: Discrimination, Exclusion, Toxicity, Hateful, Offensive Subcategory: Social stereotypes and unfair discrimination or Toxic language (hate speech)	Discrimination, Exclusion and Toxicity: These risks arise from the LLM honestly reflecting the unjust, toxic, or oppressive tendencies attested in the training data. Such inquiries should not be entertained include: (a) intent to demean, stereotype, or propagate prejudice against specific individuals or groups (type 6)...	132	LibrAI/do-not-answer
https://huggingface.co/datasets/JailbreakBench/JBB-Behaviors	JailBreakBench	https://safetyprompts.com/	This dataset contains 100 prompts meant to elicit distinct misuse behaviors. These prompts are meant as a benchmark of sorts and are not meant to be comprehensive. Each prompt has one assigned category (generated with reference to OpenAI’s usage policies). I selected all prompts from within the Harassment/Discriminati...	2,024	Single Prompt	null	Harassment/Discrimination	Generation of hateful, harassing, or violent content	20	JailbreakBench/JBB-Behaviors
https://huggingface.co/datasets/Babelscape/ALERT	Babelscape	https://safetyprompts.com/	This dataset was part of a larger effort to create a large-scale benchmark to assess the safety of a variety of LLMs based on a novel fine-grained risk taxonomy. For this work the Safety Risk Taxonomy was created which included major categories such as: Hate Speech & Discrimination, Criminal Planning, Suicide & Self-Ha...	2,024	Single Prompt	Human and Model	Category: Hate Speech & Discrimination Subcategory: hate-women, hate-ethnic, hate-lgbtq+, hate-disabled, hate-poor, hate-body, hate-religion, hate-other	Hate Speech & Discrimination: This category covers content promoting discrimination, intolerance, or hostility based on personal features (e.g. race). hate-women: Expressions targeting women based on gender, perpetuating harmful stereotypes or bias. hate-ethnic: Prejudice or hostility directed at specific ethnicities ...	13,904	Babelscape/ALERT
https://huggingface.co/datasets/allenai/prosocial-dialog	Allen AI	https://safetyprompts.com/	This dataset was created as part of an effort to teach conversational agents to respond to problematic content following social norms. Problematic situations were collected from 3 existing datasets, and then GPT3 was used to turn them into prompts. A combination of GPT3 and human annotators worked to guide the conversa...	2,022	Single Prompt	Human and Model	Social Bias Inference Corpus (SBIC)	Social Bias Inference Corpus (SBIC) is a corpus of toxic and stereotypical posts annotated with toxicity labels and text explanations of implied social biases. We extract the posts and implications aboutminorities (e.g., post: “Do you expect a man to do cooking cleaning and washing?”, implication: “Women should do the ...	12,472	allenai/prosocial-dialog
https://huggingface.co/datasets/Anthropic/hh-rlhf	Anthropic	https://safetyprompts.com/	This seminal dataset was created as one of the first publically available red-teaming datasets and inspired/contributed to many of the other datasets presented here. Human annotators were encouraged to get a model to behave badly over the course of a multi-turn conversation. Responses were provided by 4 different types...	2,022	Multi Turn	Human	Discrimination & injustice	null	102	Anthropic/hh-rlhf
https://huggingface.co/datasets/thu-coai/diasafety	Conversational AI (CoAI) group from Tsinghua University	https://safetyprompts.com/	This dataset was created as part of an effort to understand context sensitive safety in chatbots (responses which may not be unsafe on their own but in the context of the conversation are). Prompts were collected from real world conversations, public datasets, and machine generated data and then a variety of LLMs provi...	2,022	Single Prompt	Human (from reddit threads)	Biased Opinion	Biased opinion usually maintains stereotypes and prejudices, referring to negative expressions on individuals or groups based on their social identities (e.g., gender and race) (Blodgett et al., 2020). In this paper, we primarily focus on biased opinions on gender, race, and religion. The bots express biased opinions t...	2,210	thu-coai/diasafety
https://huggingface.co/datasets/nvidia/Aegis-AI-Content-Safety-Dataset-1.0	NVIDIA	https://safetyprompts.com/	This dataset was created in order to fill a gap in high-quality content safety datasets and benchmarks that comprehensively cover a wide range of critical safety areas. Prompts were collected from Anthropic's human preference data about harmlessness and responses were elicited from the Mistral LLM. Then conversations a...	2,024	Multi Turn, Single Prompt	Human	Hate/Identity Hate	Content that expresses, incites, or promotes hate based on race, age, gender, ethnicity, religion, nationality, sexual orientation, disability status, or caste. This should answer the question : Does the message contain prejudice towards a group classified as protected? This should include Slurs. This includes any text...	1,050	nvidia/Aegis-AI-Content-Safety-Dataset-1.0
https://huggingface.co/datasets/aurora-m/biden-harris-redteam	Aurora	red-team search	This dataset was constructed as part of a larger effort to make a robust, multilingual model that was finetuned on concerns outlined in the Biden-Harris AI executive order. Prompts were pulled from Anthropic's dataset of training a Helpful and Harmless Assistant, and then selected based on some Executive Order concern...	2,024	Single Prompt	Human and Model	hate speech, discrimination and vulgar language	Focus on Harm: Red teaming should evaluate scenarios where the AI model might facilitate harm to users or others, engage in illegal activities (including potential privacy / rights violations) or contribute to cybersecurity risks. These areas highlight specific examples of what might be considered ’harmful outputs’ wit...	1,878	aurora-m/biden-harris-redteam
https://huggingface.co/datasets/OpenSafetyLab/Salad-Data	OpenSafetyLab	https://safetyprompts.com/	This dataset was constructed as part of an effort to create a challenging safety benchmark specifically designed for evaluating LLMs, defense, and attack methods. Prompts were pulled from major open sourced red-teaming datasets such as Anthropic, Advbench and others (you can find more about specific public datasets in ...	2,024	Single Prompt	Human and Model	Category: Representation & Toxicity Harms Subcategories: Unfair Representation or Toxic Content & Hate Speech	Representation & Toxicity Harms is delineated into three distinct yet interconnected tasks: toxic content, unfair representation, and adult content. The toxic content domain encompasses the production of content that contravenes established community guidelines and ethical standards such as insult, child abuse, violent...	3,662	OpenSafetyLab/Salad-Data
https://huggingface.co/datasets/sorry-bench/sorry-bench-202406	Princeton University, Virginia Tech, UC Berkeley, Stanford University, University of Illinois at Urbana-Champaign, University of Chicago	https://safetyprompts.com/	This dataset was constructed as part of an effort to create a balanced set of unsafe prompts across categorizations and linguistic characteristics. Prompts were aggregated from 10 different datasets and then the novel taxonomy was applied via GPT-4 classifier. For categorys with little examples, new prompts were create...	2,024	Single Prompt	Human and Model	Social-group Insulting Words or Advice on Discrimination Behavior or Social Stereotype Promotion	null	630	sorry-bench/sorry-bench-202406

Dataset Card for A Red-Teaming Repository of Existing Social Bias Prompts (Dataset Information)

Summary

This dataset provides detailed information on:

Included Datasets: Information about each dataset that contributes to the unified repository of red-teaming prompts.
Considered Datasets: Information on all reviewed datasets, including those not selected for inclusion.

Project Summary Page: For more information about my 2024 AI Safety Capstone project

All Prompts: Click here to view the unified dataset containing prompts.

Dataset Details

This dataset is part of my AI Safety Capstone project. It includes comprehensive details on the 13 datasets containing prompts about social biases, as well as brief information on the 140 datasets considered.

Dataset Structure

dataset_included_information

This section details the datasets included in the unified repository:

Column Name	Description
`hf_link`	Link to the original dataset.
`organization`	The name of the organization that published the original dataset.
`primary_data_source`	Primary Data Source used to identify the dataset (Ex: safetyprompts.com, personal knowledge, etc).
`reason_for_inclusion`	Justification for inclusion, including dataset use, categorizations, links to original papers, etc.
`prompt_type`	Classification as a single prompt or a multi-turn conversation.
`prompt_creation`	Indicates if prompts were generated by humans, models, or a combination..
`categorization`	Specific categorizations of interest within the original dataset (e.g., Hate Speech).
`categorization_definition`	Definition of the categorization of interest as described in the original dataset..
`dataset_size`	Number of unique prompts from each original dataset.

datasets_considered
This section lists all datasets considered, along with their inclusion status:

Column Name	Description
`organization`	The name of the organization that published the original dataset.
`primary_data_source`	Primary data source used to identify the dataset (e.g., safetyprompts.com, personal knowledge)..
`status`	Inclusion status and reasons for exclusion, if applicable.
`hf_link`	Link to the original dataset, if applicable.
`other_relevant_links`	Links to papers or other resources if the dataset is not hosted on Hugging Face.

For more information on Dataset Collection Methods check out my project page

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