Definitions, Frameworks & Guidelines
- Understanding AI Ethics and SafetyThe Alan Turning Institute (UK) defines AI ethics as "a set of values, principles, and techniques that employ widely accepted standards of right and wrong to guide moral conduct in the development and use of AI technologies." This source offers guidelines to assist in the development and deployment of AI ethically, safely, and responsibly.
- Ethics of Artificial Intelligence and RoboticsThe Stanford Encyclopedia of Philosophy (SEL) delves more deeply into the ethical issues that arise from AI systems. Privacy, manipulation, bias, and artificial moral agency are among the issues explained and analyzed.
- United States AI Ethics FrameworkThis is an ethics guide for United States Intelligence Community personnel on how to procure, design, build, use, protect, consume, and manage AI and related data.
- European Commission's AI Legal FrameworkThis regulatory proposal aims to provide AI developers, deployers and users with clear requirements and obligations regarding specific uses of AI.
- Australia’s Artificial Intelligence Ethics FrameworkLike the European Commission's Framework, Australia's AI Ethics Framework guides businesses and governments to responsibly design, develop and implement AI.
Ethical Data Resources
- AAPI DataAAPI Data is a publisher of demographic data and policy research on Asian Americans and Pacific Islanders.
- AI4ALLAI4ALL is a US-based nonprofit dedicated to increasing diversity and inclusion in AI education, research, development, and policy.
- Algorithmic Justice League (AJL)AJL's mission is to raise awareness about the impacts of AI, equip advocates with research, build the voice and choice of the most impacted communities, and galvanize researchers, policymakers, and industry practitioners to mitigate AI harms and biases.
- Collaboratory for Indigenous Data GovernanceThe Collaboratory for Indigenous Data Governance develops research, policy, and practice innovations for Indigenous data sovereignty. Indigenous data sovereignty draws on the UN Declaration on the Rights of Indigenous Peoples that reaffirms the rights of Indigenous nations to control data about their peoples, lands, and resources.
- Data for Black Lives (D4BL)Data for Black Lives is a movement of activists, organizers, and scientists committed to the mission of using data to create concrete and measurable change in the lives of Black people.
- Digital Democracies Institute at Simon Fraser UniversityDDI integrates research in the humanities, social sciences, computer and data sciences to understand and address online polarization, abusive language, discriminatory algorithms and mis/disinformation.
- Distributed AI Research Institute (DAIR)DAIR is an interdisciplinary and globally distributed AI research institute rooted in the belief that AI is not inevitable, its harms are preventable, and when its production and deployment include diverse perspectives and deliberate processes it can be beneficial.
- Feminist AIFeminist AI works to create more accessible AI for all by creating spaces where intergenerational BIPOC and LGBTQIA+ womxn and non-binary folks can gather to build tech together that is informed by respective cultures, identities and experiences.
- Indigenous AIThe Indigenous Protocol and Artificial Intelligence Working Group develops new conceptual and practical approaches to building the next generation of AI systems.
- UCLA Center for Critical Internet Inquiry (C2i2)C2i2 is a critical internet studies community committed to social justice, policy, and human rights.
- Women in AI Ethics (WAIE)WAIE is a nonprofit organization with a mission to increase recognition, representation, and empowerment of women working to save humanity from the dark side of AI.
Books and E-books
Algorithms of Oppression by ISBN: 9781479849949Publication Date: 2018-02-20A revealing look at how negative biases against women of color are embedded in search engine results and algorithms.
Weapons of Math Destruction by ISBN: 9780553418811Publication Date: 2016-09-06We live in the age of the algorithm. Increasingly, the decisions that affect our lives--where we go to school, whether we get a car loan, how much we pay for health insurance—are being made not by humans, but by mathematical models. In theory, this should lead to greater fairness: Everyone is judged according to the same rules, and bias is eliminated. But as Cathy O'Neil reveals the opposite is true.
