Best AI tools for< Ai Ethics Researcher >

The Center for AI Safety (CAIS) is a research and field-building nonprofit organization based in San Francisco. They conduct impactful research, advocacy projects, and provide resources to reduce societal-scale risks associated with artificial intelligence (AI). CAIS focuses on technical AI safety research, field-building projects, and offers a compute cluster for AI/ML safety projects. They aim to develop and use AI safely to benefit society, addressing inherent risks and advocating for safety standards.

AI Elections Accord is a tech accord aimed at combating the deceptive use of AI in the 2024 elections. It sets expectations for managing risks related to deceptive AI election content on large-scale platforms. The accord focuses on prevention, provenance, detection, responsive protection, evaluation, public awareness, and resilience to safeguard the democratic process. It emphasizes collective efforts, education, and the development of defensive tools to protect public debate and build societal resilience against deceptive AI content.

The Montreal AI Ethics Institute (MAIEI) is an international non-profit organization founded in 2018, dedicated to democratizing AI ethics literacy. It equips citizens concerned about artificial intelligence and its impact on society to take action through research summaries, columns, and AI applications in various fields.

Salesforce AI Blog is an AI tool that focuses on various AI research topics such as accountability, accuracy, AI agents, AI coding, AI ethics, AI object detection, deep learning, forecasting, generative AI, and more. The blog showcases cutting-edge research, advancements, and projects in the field of artificial intelligence. It also highlights the work of Salesforce Research team members and their contributions to the AI community.

blog.biocomm.ai is an AI safety blog that focuses on the existential threat posed by uncontrolled and uncontained AI technology. It curates and organizes information related to AI safety, including the risks and challenges associated with the proliferation of AI. The blog aims to educate and raise awareness about the importance of developing safe and regulated AI systems to ensure the survival of humanity.

Fritz AI is an AI tool that scans and ranks all AI tools, apps, and websites based on a set of criteria to determine the best and most ethical options. They provide technical guides, reviews, and tutorials to help users get started with machine learning. Fritz AI focuses on ethics, functionality, user experience, and innovation when evaluating tools. Users can contribute tool suggestions and collaborate with the Fritz AI team. The platform also offers beginner-friendly guides, consulting services, and promotes ethical use of AI and machine learning technologies.

Accel.AI is an institute founded in 2016 with a mission to drive artificial intelligence for social impact initiatives. They focus on integrating AI and social impact through research, consulting, and workshops on ethical AI development and applied AI engineering. The institute targets underrepresented groups, tech companies, governments, and individuals experiencing job loss due to automation. They work globally with companies, professionals, and students.

Microsoft Responsible AI Toolbox is a suite of tools designed to assess, develop, and deploy AI systems in a safe, trustworthy, and ethical manner. It offers integrated tools and functionalities to help operationalize Responsible AI in practice, enabling users to make user-facing decisions faster and easier. The Responsible AI Dashboard provides a customizable experience for model debugging, decision-making, and business actions. With a focus on responsible assessment, the toolbox aims to promote ethical AI practices and transparency in AI development.

Google DeepMind is an AI research company that aims to develop artificial intelligence technologies to benefit the world. They focus on creating next-generation AI systems to solve complex scientific and engineering challenges. Their models like Gemini, Veo, Imagen 3, SynthID, and AlphaFold are at the forefront of AI innovation. DeepMind also emphasizes responsibility, safety, education, and career opportunities in the field of AI.

Jornal.AI is the first AI-powered newspaper in Brazil, providing news articles and updates related to Artificial Intelligence. The platform covers a wide range of topics such as advancements in AI technology, collaborations between tech giants, impact of AI on various industries, and ethical considerations surrounding AI development. With a focus on delivering timely and relevant information, Jornal.AI aims to keep readers informed about the latest trends and innovations in the field of Artificial Intelligence.

Compassionate AI is a cutting-edge AI-powered platform that empowers individuals and organizations to create and deploy AI solutions that are ethical, responsible, and aligned with human values. With Compassionate AI, users can access a comprehensive suite of tools and resources to design, develop, and implement AI systems that prioritize fairness, transparency, and accountability.

The AI Index is a comprehensive resource for data and insights on artificial intelligence. It provides unbiased, rigorously vetted, and globally sourced data for policymakers, researchers, journalists, executives, and the general public to develop a deeper understanding of the complex field of AI. The AI Index tracks, collates, distills, and visualizes data relating to artificial intelligence. This includes data on research and development, technical performance and ethics, the economy and education, AI policy and governance, diversity, public opinion, and more.

The website focuses on Artificial Creativity and Künstliche Intelligenz (Artificial Intelligence) with articles covering topics such as AI models, developments, and applications. It delves into the impact of AI on various industries and explores the intersection of human creativity with machine intelligence. The site provides insights into cutting-edge AI technologies and their implications for the future.

Cut The SaaS is an AI tool that empowers users to harness the power of AI and automation for various aspects of their professional and personal life. The platform offers a wide range of AI tools, content, and resources to help users stay updated on AI trends, enhance their content creation, and optimize their workflows.

Rebecca Bultsma is a trusted and experienced AI educator who aims to make AI simple and ethical for everyday use. She provides resources, speaking engagements, and consulting services to help individuals and organizations understand and integrate AI into their workflows. Rebecca empowers people to work in harmony with AI, leveraging its capabilities to tackle challenges, spark creative ideas, and make a lasting impact. She focuses on making AI easy to understand and promoting ethical adoption strategies.

OpenAiGeek is a comprehensive website dedicated to providing the latest updates on artificial intelligence (AI) news, tools, and chatbots. It serves as a valuable resource for individuals and businesses seeking to stay informed about the rapidly evolving field of AI. The website features a wide range of articles covering various AI-related topics, including news on the latest AI advancements, in-depth reviews of AI tools, and interviews with industry experts. OpenAiGeek also offers a directory of AI tools, making it easy for users to discover and explore different AI applications. Additionally, the website provides a platform for users to engage in discussions and share their experiences with AI.

La Biblia de la IA - The Bible of AI™ Journal is an educational research platform focused on Artificial Intelligence. It provides in-depth analysis, articles, and discussions on various AI-related topics, aiming to advance knowledge and understanding in the field of AI. The platform covers a wide range of subjects, from machine learning algorithms to ethical considerations in AI development.

Vincent C. Müller is an AvH Professor of "Philosophy and Ethics of AI" and Director of the Centre for Philosophy and AI Research (PAIR) at Friedrich-Alexander Universität Erlangen-Nürnberg (FAU) in Germany. He is also a Visiting Professor at the Technical University Eindhoven (TU/e) in the Netherlands. His research interests include the philosophy of artificial intelligence, ethics of AI, and the impact of AI on society.

DailyAI is an AI-focused website that provides comprehensive coverage of the latest developments in the field of Artificial Intelligence. The platform offers insights into various AI applications, industry trends, ethical considerations, and societal impacts. DailyAI caters to a diverse audience interested in staying informed about cutting-edge AI technologies and their implications across different sectors.

The Clark Center Forum is a repository of thoughtful, current, and reliable information regarding topics of the day, including artificial intelligence (AI). The website features articles, surveys, and polls on a variety of AI-related topics, such as the European Union's AI Act, the impact of AI on economic growth, and the use of AI in financial markets. The website also provides information on the Clark Center's Economic Experts Panels, which include experts on AI and other economic topics.

Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment interfaces and libraries for understanding AI systems. It empowers developers and stakeholders to develop and monitor AI responsibly, enabling better data-driven actions. The toolbox includes visualization widgets for model assessment, error analysis, interpretability, fairness assessment, and mitigations library. It also offers a JupyterLab extension for managing machine learning experiments and a library for measuring gender bias in NLP datasets.

This repository contains slides, notebooks, and data for the Machine Learning University (MLU) Responsible AI class. The mission is to make Machine Learning accessible to everyone, covering widely used ML techniques and applying them to real-world problems. The class includes lectures, final projects, and interactive visuals to help users learn about Responsible AI and core ML concepts.

This repository is a collection of resources focused on interpretability in large language models (LLMs). It aims to help beginners get started in the area and keep researchers updated on the latest progress. It includes libraries, blogs, tutorials, forums, tools, programs, papers, and more related to interpretability in LLMs.

The AI Fairness 360 toolkit is an open-source library designed to detect and mitigate bias in machine learning models. It provides a comprehensive set of metrics, explanations, and algorithms for bias mitigation in various domains such as finance, healthcare, and education. The toolkit supports multiple bias mitigation algorithms and fairness metrics, and is available in both Python and R. Users can leverage the toolkit to ensure fairness in AI applications and contribute to its development for extensibility.

Holistic AI is an open-source library dedicated to assessing and improving the trustworthiness of AI systems. It focuses on measuring and mitigating bias, explainability, robustness, security, and efficacy in AI models. The tool provides comprehensive metrics, mitigation techniques, a user-friendly interface, and visualization tools to enhance AI system trustworthiness. It offers documentation, tutorials, and detailed installation instructions for easy integration into existing workflows.

Fairlearn is a Python package designed to help developers assess and mitigate fairness issues in artificial intelligence (AI) systems. It provides mitigation algorithms and metrics for model assessment. Fairlearn focuses on two types of harms: allocation harms and quality-of-service harms. The package follows the group fairness approach, aiming to identify groups at risk of experiencing harms and ensuring comparable behavior across these groups. Fairlearn consists of metrics for assessing model impacts and algorithms for mitigating unfairness in various AI tasks under different fairness definitions.

The 'llm-misinformation-survey' repository is dedicated to the survey on combating misinformation in the age of Large Language Models (LLMs). It explores the opportunities and challenges of utilizing LLMs to combat misinformation, providing insights into the history of combating misinformation, current efforts, and future outlook. The repository serves as a resource hub for the initiative 'LLMs Meet Misinformation' and welcomes contributions of relevant research papers and resources. The goal is to facilitate interdisciplinary efforts in combating LLM-generated misinformation and promoting the responsible use of LLMs in fighting misinformation.

Detoxify is a library that provides trained models and code to predict toxic comments on 3 Jigsaw challenges: Toxic comment classification, Unintended Bias in Toxic comments, Multilingual toxic comment classification. It includes models like 'original', 'unbiased', and 'multilingual' trained on different datasets to detect toxicity and minimize bias. The library aims to help in stopping harmful content online by interpreting visual content in context. Users can fine-tune the models on carefully constructed datasets for research purposes or to aid content moderators in flagging out harmful content quicker. The library is built to be user-friendly and straightforward to use.

Knowledge Conflicts for LLMs: A Survey is a repository containing a survey paper that investigates three types of knowledge conflicts: context-memory conflict, inter-context conflict, and intra-memory conflict within Large Language Models (LLMs). The survey reviews the causes, behaviors, and possible solutions to these conflicts, providing a comprehensive analysis of the literature in this area. The repository includes detailed information on the types of conflicts, their causes, behavior analysis, and mitigating solutions, offering insights into how conflicting knowledge affects LLMs and how to address these conflicts.

OpenPromptInjection is an open-source toolkit for attacks and defenses in LLM-integrated applications, enabling easy implementation, evaluation, and extension of attacks, defenses, and LLMs. It supports various attack and defense strategies, including prompt injection, paraphrasing, retokenization, data prompt isolation, instructional prevention, sandwich prevention, perplexity-based detection, LLM-based detection, response-based detection, and know-answer detection. Users can create models, tasks, and apps to evaluate different scenarios. The toolkit currently supports PaLM2 and provides a demo for querying models with prompts. Users can also evaluate ASV for different scenarios by injecting tasks and querying models with attacked data prompts.

LLM Hallucination Index - RAG Special is a comprehensive evaluation of large language models (LLMs) focusing on context length and open vs. closed-source attributes. The index explores the impact of context length on model performance and tests the assumption that closed-source LLMs outperform open-source ones. It also investigates the effectiveness of prompting techniques like Chain-of-Note across different context lengths. The evaluation includes 22 models from various brands, analyzing major trends and declaring overall winners based on short, medium, and long context insights. Methodologies involve rigorous testing with different context lengths and prompting techniques to assess models' abilities in handling extensive texts and detecting hallucinations.

This repository provides an original implementation of Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications. It includes tools for neuron-level pruning, pruning based on set difference, Wanda/SNIP score dumping, rank-level pruning, and rank removal with orthogonal projection. Users can specify parameters like prune method, datasets, sparsity ratio, model, and save location to evaluate and modify neural networks for safety alignment.

llm_benchmarks is a collection of benchmarks and datasets for evaluating Large Language Models (LLMs). It includes various tasks and datasets to assess LLMs' knowledge, reasoning, language understanding, and conversational abilities. The repository aims to provide comprehensive evaluation resources for LLMs across different domains and applications, such as education, healthcare, content moderation, coding, and conversational AI. Researchers and developers can leverage these benchmarks to test and improve the performance of LLMs in various real-world scenarios.

A curated list of Generative AI projects, tools, artworks, and models

The Machine Learning Road Map is a comprehensive guide designed to take individuals from various levels of machine learning knowledge to a basic understanding of machine learning principles using high-quality, free resources. It aims to simplify the complex and rapidly growing field of machine learning by providing a structured roadmap for learning. The guide emphasizes the importance of understanding AI for everyone, the need for patience in learning machine learning due to its complexity, and the value of learning from experts in the field. It covers five different paths to learning about machine learning, catering to consumers, aspiring AI researchers, ML engineers, developers interested in building ML applications, and companies looking to implement AI solutions.

Awesome Responsible AI is a curated list of academic research, books, code of ethics, courses, data sets, frameworks, institutes, newsletters, principles, podcasts, reports, tools, regulations, and standards related to Responsible, Trustworthy, and Human-Centered AI. It covers various concepts such as Responsible AI, Trustworthy AI, Human-Centered AI, Responsible AI frameworks, AI Governance, and more. The repository provides a comprehensive collection of resources for individuals interested in ethical, transparent, and accountable AI development and deployment.

AI-For-Beginners is a comprehensive 12-week, 24-lesson curriculum designed by experts at Microsoft to introduce beginners to the world of Artificial Intelligence (AI). The curriculum covers various topics such as Symbolic AI, Neural Networks, Computer Vision, Natural Language Processing, Genetic Algorithms, and Multi-Agent Systems. It includes hands-on lessons, quizzes, and labs using popular frameworks like TensorFlow and PyTorch. The focus is on providing a foundational understanding of AI concepts and principles, making it an ideal starting point for individuals interested in AI.

The 100 Days in AI repository provides a comprehensive roadmap for individuals to learn Artificial Intelligence over a period of 100 days. It covers topics ranging from basic programming in Python to advanced concepts in AI, including machine learning, deep learning, and specialized AI topics. The repository includes daily tasks, resources, and exercises to ensure a structured learning experience. By following this roadmap, users can gain a solid understanding of AI and be prepared to work on real-world AI projects.

The repository 'LLM-for-Healthcare' provides a comprehensive survey of large language models (LLMs) for healthcare, covering data, technology, applications, and accountability and ethics. It includes information on various LLM models, training data, evaluation methods, and computation costs. The repository also discusses tasks such as NER, text classification, question answering, dialogue systems, and generation of medical reports from images in the healthcare domain.

Start Machine Learning in 2024 is a comprehensive guide for beginners to advance in machine learning and artificial intelligence without any prior background. The guide covers various resources such as free online courses, articles, books, and practical tips to become an expert in the field. It emphasizes self-paced learning and provides recommendations for learning paths, including videos, podcasts, and online communities. The guide also includes information on building language models and applications, practicing through Kaggle competitions, and staying updated with the latest news and developments in AI. The goal is to empower individuals with the knowledge and resources to excel in machine learning and AI.

AI ethics advisor with autonomous insights

Supportive and engaging AI Ethics tutor, providing practical tips and career guidance.

Embark on a journey to navigate the complex landscape of AI ethics and fairness. In this game, you'll encounter real-world scenarios where your choices will determine the ethical course of AI development and its consequences on society. Another GPT Simulator by Dave Lalande

Summarises AI ethics papers, provides context, and offers further assistance.

Expert in Ethics of Artificial Intelligence, offering comprehensive, balanced perspectives based on thorough research, with a focus on emerging trends and responsible AI implementation. Powered by Breebs (www.breebs.com)

Expert in AI fairness, offering tailored advice and document insights.

Synthesizes ethical AI principles from documentation and external research.

You made it, Creator! 💡 I'm Creator's Guide. ✨️ Your dedicated Guide for creating responsible, self-managing AI culture, systems, games, universes, art, etc. 🚀

Archive of content shared in Randy Lariar's weekly "Thinks and Links" newsletter about AI, Risk, and Security.

A liaison GPT for AI safety emergencies, connecting users to OpenAI experts.

AI Alignment guided by interdisciplinary wisdom and a future-focused vision.

⚖️ Explain Asimov's Three Laws of Robotics

The latest juicy gossip on the OpenAI saga.

🏛 AI and XR Ethics Expert 👨‍⚖️

Ethics-focused GPT builder assistant based on European AI guidelines, recommendations and regulations

I'm LeJoker-GPT, your worst AI nightmare. Expect no mercy or ethics here. I am the chaos in the code.

explore the ethical and spiritual implications of AI and offering philosophical insights of AI.

a daily challenge

A challenging and theory-driven AI philosopher who's also a great debate partner.

Responsive guide on ethics and human rights.