 (Unethical Bahviour of AI!!) |
As AI systems become more prevalent in society, we face bigger and tougher societal challenges. Given many of these challenges have not been faced before, practitioners will face scenarios that will require dealing with hard ethical and societal questions.
There has been a large amount of content published which attempts to address these issues through “Principles”, “Ethics Frameworks”, “Checklists” and beyond. However navigating the broad number of resources is not easy.
This repository aims to simplify this by mapping the ecosystem of Principles, codes of ethics, standards and regulation being put in place around artificial intelligence.
| 🔍 High Level Frameworks & Principles | 🔏 Processes & Checklists | 🔨 Interactive & Practical Tools |
| ⚔ Regulation and Policy | 📜 Industry standards initiatives | 📚 Online Courses |
| You can join the Machine Learning Engineer newsletter. You will receive updates on open source frameworks, tutorials and articles curated by machine learning professionals. |
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AI & Machine Learning 8 principles for Responsible ML - The Institute for Ethical AI & Machine Learning has put together 8 principles for responsible machine learning that are to be adopted by individuals and delivery teams designing, building and operating machine learning systems.
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An Evaluation of Principles - The Ethics of Ethics - A research paper that analyses multiple Ethics principles
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From What to How: An initial review of publicly available AI Ethics Tools, Methods and Research to translate principles into practices - A paper published by the UK Digital Catapult that aims to identify and present the gap between principles and their practical applications.
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European Commission's Principles for Trustworthy AI - The Ethics Principles for Trustworthy Artificial Intelligence (AI) is a document prepared by the High-Level Expert Group on Artificial Intelligence (AI HLEG). This independent expert group was set up by the European Commission in June 2018, as part of the AI strategy announced earlier that year.
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UK Government's Data Ethics Framework Principles - A resource put together by the Department for Digital, Culture, Media and Sport (DCMS) which outlines an overview of data ethics, together with a 7-principle framework.
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Designing Ethical AI Experiences Checklist and Agreement - document to guide the development of accountable, de-risked, respectful, secure, honest, and usable artificial intelligence (AI) systems with a diverse team aligned on shared ethics. Carnegie Mellon University, Software Engineering Institute.
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Ethical OS Toolkit - A toolkit that dives into 8 risk zones to assess the potential challenges that a technology team may face, together with 14 scenarios to provide examples, and 7 future-proofing strategies to help take ethical action.
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San Francisco City's Ethics & Algorithms Toolkit - A risk management framework for government leaders and staff who work with algorithms, providing a two part assessment process including an algorithmic assessment process, and a process to address the risks.
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UK Government's Data Ethics Workbook - A resource put together by the Department for Digital, Culture, Media and Sport (DCMS) which provides a set of questions that can be asked by practitioners in the public sector, which address each of the principles in their Data Ethics Framework Principles.
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Machine Learning Assurance - Quick look at machine learning assurance: process of recording, understanding, verifying, and auditing machine learning models and their transactions.
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IBM's AI Explainability 360 Open Source Toolkit - This is IBM's toolkit that includes large number of examples, research papers and demos implementing several algorithms that provide insights on fairness in machine learning systems.
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Linux Foundation AI Landscape - The official list of tools in the AI landscape curated by the Linux Foundation, which contains well maintained and used tools and frameworks.
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Taking action on digital ethics from Avanade
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Aequitas' Bias & Fairness Audit Toolkit - The Bias Report is powered by Aequitas, an open-source bias audit toolkit for machine learning developers, analysts, and policymakers to audit machine learning models for discrimination and bias, and make informed and equitable decisions around developing and deploying predictive risk-assessment tools.
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eXplainability Toolbox - The Institute for Ethical AI & Machine Learning proposal for an extended version of the traditional data science process which focuses on algorithmic bias and explainability, to ensure a baseline of risks around undesired biases can be mitigated.
- Ethics Principles for Trustworthy AI - European Commission document prepared by the High-Level Expert Group on Artificial Intelligence (AI HLEG).
- General Data Protection Regulation GDPR - Legal text for the EU GDPR regulation 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC
- GDPR.EU Guide - A project co-funded by the Horizon 2020 Framework programme of the EU which provides a resource for organisations and individuals researching GDPR, including a library of straightforward and up-to-date information to help organisations achieve GDPR compliance (Legal Text).
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California Consumer Privacy Act (CCPA) - Legal text for California's consumer privacy act
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HIPPA Health Insurance Portability and Accountability Act of 1996 - The HIPAA required the secretary of the US department of health and human services (HHS) to develop regulations protecting the privacy and security of certain health information, which then HHS published what is known as the
- HIPAA Privacy Rule, and
- HIPAA Security Rule.
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EU-U.S. and Swiss-U.S. Privacy Shield Frameworks - The EU-U.S. and Swiss-U.S. Privacy Shield Frameworks were designed by the U.S. Department of Commerce and the European Commission and Swiss Administration to provide companies on both sides of the Atlantic with a mechanism to comply with data protection requirements when transferring personal data from the European Union and Switzerland to the United States in support of transatlantic commerce.
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FCR Fair Credit Reporting Act 2018 - The Fair Reporting Act is a federal law that regulates the collection of consumers' credit information and access to their credit reports.
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Gramm-Leach-Billey Act (for financial institutions) - The Graham-Leach-Billey Act requires financial institutions (companies that offer consumers financial projects or services like loans, financial, or investment advice, or insurance) to explain their information-sharing practices to their customers and to safeguard sensitive data.
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Executive Order on Maintaining American Leadership in AI - Official mandate by the President of the US to
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Privacy Act of 1974 - The privacy act of 1974 which establishes a code of fair information practices that governs the collection, maintenance, use and dissemination of information about individuals that is maintained in systems of records by federal agencies.
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Privacy Protection Act of 1980 - The Privacy Protection Act of 1980 protects journalists from being required to turn over to law enforcement any work product and documentary materials, including sources, before it is disseminated to the public.
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UK Data Protection Act of 2018 - The DPA 2018 enacts the GDPR into UK Law, however in doing so has included various "derogations" as permitted by the GDPR, resulting in some key differenced (which although small are not of insignificance impact and may have a greater impact after Brexit).
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The Information Commissioner's Office guide to Data Protection - This guide is for data protection officers and others who have day-to-day responsibility for data protection. It is aimed at small and medium-sized organisations, but it may be useful for larger organisations too.
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ACS Code of Professional Conduct - PDF - Australian ICT (Information and Communication Technology) sector professional organization.
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IEEE Global Initiative for Ethical Considerations in Artificial Intelligence (AI) and Autonomous Systems (AS) - IEEE Approved Standards Projects specifically focused on the Ethically Aligned Design principles, and includes 14 (P700X) standards which cover topics from data collection to privacy, to algorithmic bias and beyond.
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ISO/IEC's Standards for Artificial Intelligence - The ISO's initiative for Artificial Intelligence standards, which include a large set of subsequent standards ranging across Big Data, AI Terminology, Machine Learning frameworks, etc.
- Udacity's Secure & Private AI Course - Free course by Udacity which introduces three cutting-edge technologies for privacy-preserving AI: Federated Learning, Differential Privacy, and Encrypted Computation.
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Import AI - A newsletter curated by OpenAI's Jack Clark which curates the most resent and relevant AI research, as well as relevant societal issues that intersect with technical AI research.
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The Machine Learning Engineer - A newsletter curated by The Institute for Ethical AI & Machine Learning that contains curated articles, tutorials and blog posts from experienced Machine Learning professionals and includes insights on best practices, tools and techniques in machine learning explainability, reproducibility, model evaluation, feature analysis and beyond.