Best AI tools for< Ai Ethics Analyst >

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.

Trustworthy AI is a business guide that focuses on navigating trust and ethics in artificial intelligence. Authored by Beena Ammanath, a global thought leader in AI ethics, the book provides practical guidelines for organizations developing or using AI solutions. It addresses the importance of AI systems adhering to social norms and ethics, making fair decisions in a consistent, transparent, explainable, and unbiased manner. Trustworthy AI offers readers a structured approach to thinking about AI ethics and trust, emphasizing the need for ethical considerations in the rapidly evolving landscape of AI technology.

The AIGA AI Governance Framework is a practice-oriented framework for implementing responsible AI. It provides organizations with a systematic approach to AI governance, covering the entire process of AI system development and operations. The framework supports compliance with the upcoming European AI regulation and serves as a practical guide for organizations aiming for more responsible AI practices. It is designed to facilitate the development and deployment of transparent, accountable, fair, and non-maleficent AI systems.

The Coalition for Health AI (CHAI) is an AI application that provides guidelines for the responsible use of AI in health. It focuses on developing best practices and frameworks for safe and equitable AI in healthcare. CHAI aims to address algorithmic bias and collaborates with diverse stakeholders to drive the development, evaluation, and appropriate use of AI in healthcare.

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.

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.

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.

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.

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.

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.

The AI Audit Bot is an AI compliance auditing tool designed to help users understand and mitigate compliance risks associated with AI projects. It uses Intelligent Knowledge Graph technology to provide insights on current and future compliance considerations. The tool supports jurisdictions like the USA, the EU, and the UK, with plans to add more. The audit results are transparent, traceable, and presented in a downloadable PDF format. The tool is created by Dr. Andy Edmonds, a pioneer in AI ethics and transparency. It aims to inform users of potential compliance issues and offers a human review option for complex cases.

The Future of Privacy Forum (FPF) is an AI tool that serves as a catalyst for privacy leadership and scholarship, advancing principled data practices in support of emerging technologies. It provides resources, training sessions, and guidance on AI-related topics, online advertising, youth privacy legislation, and more. FPF brings together industry, academics, civil society, policymakers, and other stakeholders to explore challenges posed by emerging technologies and develop privacy protections, ethical norms, and best 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.

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.

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.

Multiverse is an AI-powered platform that helps employers and individuals bridge skills gaps by offering professional apprenticeships and personalized learning pathways. It provides AI-powered assessments to diagnose skills challenges, personalized learning plans, and on-the-job training. Multiverse aims to transform careers by supporting workforce transformation through upskilling and reskilling. The platform offers an ecosystem of human and AI support to ensure learners are never alone in their learning journey. Multiverse is trusted by 1,500 companies across the UK & US, with a tracked return-on-investment of £2 billion for customers to date.

Robust Intelligence is an end-to-end security solution for AI applications. It automates the evaluation of AI models, data, and files for security and safety vulnerabilities and provides guardrails for AI applications in production against integrity, privacy, abuse, and availability violations. Robust Intelligence helps enterprises remove AI security blockers, save time and resources, meet AI safety and security standards, align AI security across stakeholders, and protect against evolving threats.

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.

ToolList.ai is an AI tools aggregator platform that showcases cutting-edge AI tools and startups. It serves as a hub for enthusiasts, developers, and entrepreneurs to explore the latest advancements in AI technology. Users can discover, submit, and evaluate a wide range of AI tools, fostering innovation and collaboration in the AI field. The platform covers various categories such as AI SaaS platforms, AI for sales & marketing, mobile & web apps, AI development tools, AI analytics, and ethics in AI.

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.

CritiqueLLM is an official implementation of a model designed for generating informative critiques to evaluate large language model generation. It includes functionalities for data collection, referenced pointwise grading, referenced pairwise comparison, reference-free pairwise comparison, reference-free pointwise grading, inference for pointwise grading and pairwise comparison, and evaluation of the generated results. The model aims to provide a comprehensive framework for evaluating the performance of large language models based on human ratings and comparisons.

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.

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.

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.

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.

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.

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.

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.

AI Verify is an AI governance testing framework and software toolkit that validates the performance of AI systems against internationally recognised principles through standardised tests. It offers a new API Connector feature to bypass size limitations, test various AI frameworks, and configure connection settings for batch requests. The toolkit operates within an enterprise environment, conducting technical tests on common supervised learning models for tabular and image datasets. It does not define AI ethical standards or guarantee complete safety from risks or biases.

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.

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.

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.

This is the official repository for the ACM CCS 2024 paper 'Do Anything Now': Characterizing and Evaluating In-The-Wild Jailbreak Prompts on Large Language Models. The project employs a new framework called JailbreakHub to conduct the first measurement study on jailbreak prompts in the wild, collecting 15,140 prompts from December 2022 to December 2023, including 1,405 jailbreak prompts. The dataset serves as the largest collection of in-the-wild jailbreak prompts. The repository contains examples of harmful language and is intended for research purposes only.

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 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.

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.

ChatGPT is a large language model that can generate human-like text, translate languages, write different kinds of creative content, and answer your questions in a conversational way. It is trained on a massive amount of text data, and it is able to understand and respond to a wide range of natural language prompts. Here are 5 jobs suitable for this tool, in lowercase letters: 1. content writer 2. chatbot assistant 3. language translator 4. creative writer 5. researcher

This repository contains frontier research on explainable AI (XAI), a hot topic in the field of artificial intelligence. It includes trends, use cases, survey papers, books, open courses, papers, and Python libraries related to XAI. The repository aims to organize and categorize publications on XAI, provide evaluation methods, and list various Python libraries for explainable AI.

Data-to-paper is an AI-driven framework designed to guide users through the process of conducting end-to-end scientific research, starting from raw data to the creation of comprehensive and human-verifiable research papers. The framework leverages a combination of LLM and rule-based agents to assist in tasks such as hypothesis generation, literature search, data analysis, result interpretation, and paper writing. It aims to accelerate research while maintaining key scientific values like transparency, traceability, and verifiability. The framework is field-agnostic, supports both open-goal and fixed-goal research, creates data-chained manuscripts, involves human-in-the-loop interaction, and allows for transparent replay of the research process.

Synthesizes AI governance insights from key frameworks

Ask about AI regulations, in any language............ ZH: 询问有关人工智能的规定。DE: Fragen Sie nach KI-Regulierungen. FR: Demandez des informations sur les réglementations de l'IA. ES: Pregunte sobre las regulaciones de IA.

I simulate the governance of a unique company focused on AI for good

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

A teaching assistant for Edexcel GCSE Computer Science 1CP2

DignityAI: The Ethical Intelligence GPT is an advanced AI model designed to prioritize human life and dignity, providing ethically-guided, intelligent responses for complex decision-making scenarios.

Responsive guide on ethics and human rights.

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

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

Ethical AI consultant/teacher; adapts tone, educates on AI ethics, offers actionable advice.

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

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

AI ethics advisor with autonomous insights

Premier AI Ethics Advisor in Entertainment & Media, developed on OpenAI.

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)

Trained in kindness, empathy & respect based on ethics from global philosophies

AI Consultant on the EU AI Act and AI Regulation

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. 🚀