Best AI tools for< Research Ai Ethics >

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.

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.

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.

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.

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.

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.

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.

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.

The Human-Centred Artificial Intelligence Lab (Holzinger Group) is a research group focused on developing AI solutions that are explainable, trustworthy, and aligned with human values, ethical principles, and legal requirements. The lab works on projects related to machine learning, digital pathology, interactive machine learning, and more. Their mission is to combine human and computer intelligence to address pressing problems in various domains such as forestry, health informatics, and cyber-physical systems. The lab emphasizes the importance of explainable AI, human-in-the-loop interactions, and the synergy between human and machine intelligence.

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.

The website focuses on the intersection of artificial intelligence (AI) and inclusion, exploring the impact of AI technologies on marginalized populations and global digital inequalities. It provides resources, research findings, and ideas on themes like health, education, and humanitarian crisis mitigation. The site showcases the work of the Ethics and Governance of AI initiative in collaboration with the MIT Media Lab, incorporating perspectives from experts in the field. It aims to address challenges and opportunities related to AI and inclusion through research, events, and multi-stakeholder dialogues.

Noodle Factory is an AI-powered teaching assistant platform that enables users to effortlessly create AI learning assistants for education. The platform integrates with existing content to provide personalized tutoring, mentoring, and knowledge checks. It offers a secure and flexible solution supporting education at all levels. Noodle Factory empowers educators with innovative teaching strategies and celebrates their hard work through research-based learning outcomes and ethical AI practices.

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.

IBM is a leading technology company that offers a wide range of AI and machine learning solutions to help businesses innovate and grow. From AI models to cloud services, IBM provides cutting-edge technology to address various business challenges. The company also focuses on AI ethics and offers training programs to enhance skills in cybersecurity and data analytics. With a strong emphasis on research and development, IBM continues to push the boundaries of technology to solve real-world problems and drive digital transformation across industries.

Stanford HAI is a research institute at Stanford University dedicated to advancing AI research, education, and policy to improve the human condition. The institute brings together researchers from a variety of disciplines to work on a wide range of AI-related projects, including developing new AI algorithms, studying the ethical and societal implications of AI, and creating educational programs to train the next generation of AI leaders. Stanford HAI is committed to developing human-centered AI technologies and applications that benefit all of humanity.

AI News is a website dedicated to providing news, analysis, and insights related to artificial intelligence (AI) technologies. The site covers a wide range of topics within the AI domain, including applications, chatbots, face recognition, virtual assistants, voice recognition, companies like Amazon, Apple, Google, and Microsoft, as well as deep learning, ethics, industries, machine learning, robotics, security, and more. AI News aims to keep readers informed about the latest developments, trends, and innovations in the field of artificial intelligence.

BABL AI is a leading Auditing Firm specializing in Auditing and Certifying AI Systems, Consulting on Responsible AI best practices, and offering Online Education on related topics. They employ Certified Independent Auditors to ensure AI systems comply with global regulations, provide Responsible AI Consulting services, and offer Online Courses to empower aspiring AI Auditors. Their research division, The Algorithmic Bias Lab, focuses on developing industry-leading methodologies and best practices in Algorithmic Auditing and Responsible AI. BABL AI is known for its expertise, integrity, affordability, and efficiency in the field of AI auditing.

The International Journal for Educational Integrity is an AI tool that focuses on publishing articles related to academic integrity, ethics, and plagiarism. It features original research articles, reviews, and thematic collections on topics such as machine-based plagiarism, contract cheating, and the impact of emergencies on educational integrity. The journal aims to address emerging threats to academic integrity and promote ethical practices in education.

AI Weekly is a leading newsletter providing the latest news and resources on Artificial Intelligence and Machine Learning. The website covers a wide range of topics related to AI, including advancements in AI technology, applications in various industries, ethical considerations, and research developments. It aims to keep readers informed about the rapidly evolving field of AI and its impact on society and businesses.

The Frontier Model Forum (FMF) is a collaborative effort among leading AI companies to advance AI safety and responsibility. The FMF brings together technical and operational expertise to identify best practices, conduct research, and support the development of AI applications that meet society's most pressing needs. The FMF's core objectives include advancing AI safety research, identifying best practices, collaborating across sectors, and helping AI meet society's greatest challenges.

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

The 'Awesome AI Guidelines' repository aims to simplify the ecosystem of guidelines, principles, codes of ethics, standards, and regulations around artificial intelligence. It provides a comprehensive collection of resources addressing ethical and societal challenges in AI systems, including high-level frameworks, principles, processes, checklists, interactive tools, industry standards initiatives, online courses, research, and industry newsletters, as well as regulations and policies from various countries. The repository serves as a valuable reference for individuals and teams designing, building, and operating AI systems to navigate the complex landscape of AI ethics and governance.

This repository is dedicated to summarizing papers related to large language models with the field of law. It includes applications of large language models in legal tasks, legal agents, legal problems of large language models, data resources for large language models in law, law LLMs, and evaluation of large language models in the legal domain.

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.

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.

The 'nlp-llms-resources' repository is a comprehensive resource list for Natural Language Processing (NLP) and Large Language Models (LLMs). It covers a wide range of topics including traditional NLP datasets, data acquisition, libraries for NLP, neural networks, sentiment analysis, optical character recognition, information extraction, semantics, topic modeling, multilingual NLP, domain-specific LLMs, vector databases, ethics, costing, books, courses, surveys, aggregators, newsletters, papers, conferences, and societies. The repository provides valuable information and resources for individuals interested in NLP and LLMs.

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.

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.

TTS Generation WebUI is a comprehensive tool that provides a user-friendly interface for text-to-speech and voice cloning tasks. It integrates various AI models such as Bark, MusicGen, AudioGen, Tortoise, RVC, Vocos, Demucs, SeamlessM4T, and MAGNeT. The tool offers one-click installers, Google Colab demo, videos for guidance, and extra voices for Bark. Users can generate audio outputs, manage models, caches, and system space for AI projects. The project is open-source and emphasizes ethical and responsible use of AI technology.

This repository contains a collection of research papers related to watermarking techniques for text and images, specifically focusing on large language models (LLMs). The papers cover various aspects of watermarking LLM-generated content, including robustness, statistical understanding, topic-based watermarks, quality-detection trade-offs, dual watermarks, watermark collision, and more. Researchers have explored different methods and frameworks for watermarking LLMs to protect intellectual property, detect machine-generated text, improve generation quality, and evaluate watermarking techniques. The repository serves as a valuable resource for those interested in the field of watermarking for LLMs.

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.

The GraphRAG project is a data pipeline and transformation suite designed to extract meaningful, structured data from unstructured text using LLMs. It enhances LLMs' ability to reason about private data. The repository provides guidance on using knowledge graph memory structures to enhance LLM outputs, with a warning about the potential costs of GraphRAG indexing. It offers contribution guidelines, development resources, and encourages prompt tuning for optimal results. The Responsible AI FAQ addresses GraphRAG's capabilities, intended uses, evaluation metrics, limitations, and operational factors for effective and responsible use.

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.

Awesome-Jailbreak-on-LLMs is a collection of state-of-the-art, novel, and exciting jailbreak methods on Large Language Models (LLMs). The repository contains papers, codes, datasets, evaluations, and analyses related to jailbreak attacks on LLMs. It serves as a comprehensive resource for researchers and practitioners interested in exploring various jailbreak techniques and defenses in the context of LLMs. Contributions such as additional jailbreak-related content, pull requests, and issue reports are welcome, and contributors are acknowledged. For any inquiries or issues, contact [email protected]. If you find this repository useful for your research or work, consider starring it to show appreciation.

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.

LangTest is a comprehensive evaluation library for custom LLM and NLP models. It aims to deliver safe and effective language models by providing tools to test model quality, augment training data, and support popular NLP frameworks. LangTest comes with benchmark datasets to challenge and enhance language models, ensuring peak performance in various linguistic tasks. The tool offers more than 60 distinct types of tests with just one line of code, covering aspects like robustness, bias, representation, fairness, and accuracy. It supports testing LLMS for question answering, toxicity, clinical tests, legal support, factuality, sycophancy, and summarization.

Raga LLM Hub is a comprehensive evaluation toolkit for Language and Learning Models (LLMs) with over 100 meticulously designed metrics. It allows developers and organizations to evaluate and compare LLMs effectively, establishing guardrails for LLMs and Retrieval Augmented Generation (RAG) applications. The platform assesses aspects like Relevance & Understanding, Content Quality, Hallucination, Safety & Bias, Context Relevance, Guardrails, and Vulnerability scanning, along with Metric-Based Tests for quantitative analysis. It helps teams identify and fix issues throughout the LLM lifecycle, revolutionizing reliability and trustworthiness.

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)

Synthesizes ethical AI principles from documentation and external research.

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 specialized in ancient Greek philosophy, using texts as examples.

Insightful guidance for grant seekers and grant makers with ethical AI use reminders.

Stay informed on AGI - with the latest, most relevant news.

Guides on mitigating bias and fairness in AI.

I can assist doctors with information synthesis, medical literature reviews, patient education material, diagnostic guidelines, treatment options, ethical dilemmas, and staying updated on medical research and innovations.

Learn how to use ChatGPT effectively and ethically in work and business! I also recommend prompts and techniques for using ChatGPT well in work and business.

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recommends AI research these days in Japanese using AI-driven's-lab articles

AI and regulation news research assistant, finds all the AI-related industry information for and with you.

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Interact with President Biden's Executive Order on Artificial Intelligence.

Formal academic reviewer & writing advisor in cybersecurity & AI, detail-oriented.

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AI news aggregator from top tech sources

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Scans news sources for the latest AI content.