Data and Responsible AI Resources
Boost your data readiness and expand your AI knowledge with this diverse curated collection of resources from data and AI experts. Learn ways to critique data, AI and its applications. Our online library has something for the data newcomer to seasoned professional. Start exploring today! If you're looking for work involving DataedX Group, check out our Insights page.
Courses
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LinuxFoundationX: Ethical Principles for Conversational AI
7 weeks | 1 – 2 hr/wk | Self-Paced
Practical Database Design: Implementing Responsible Data Solutions
2.5 hours | Self-Paced
DavidsonX: The Essentials of Data Literacy Online Course
Leading Responsible AI in Organizations
Practical Data Ethics
Practice It: Advanced SQL
National Forum on Education Statistics' Introduction to Data Ethics
Introduction to Auditing AI Systems
Reports & Papers
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Generative AI: Models Opportunities and Risks for Industry and Authorities
Federal Office for Information Security. Generative AI: Models Opportunities and Risks for Industry and Authorities, 2025.
Ten Simple Rules for Building and Maintaining a Responsible Data Science Workflow
Stoudt S, Jernite Y, Marshall B, Marwick B, Sharan M, Whitaker K, et al. (2024) Ten simple rules for building and maintaining a responsible data science workflow. PLoS Comput Biol 20(7): e1012232.
Human-AI Collaboration Patterns in AI-assisted Academic Writing
Nguyen, A., Hong, Y., Dang, B., & Huang, X. (2024). Human-AI collaboration patterns in AI-assisted academic writing. Studies in Higher Education, 49(5), 847–864.
AI Competency Framework for Teachers
Fengchun Miao and Mutlu Cukurova, AI competency framework for teachers, UNESCO, 2024.
AI Competency Framework for Students
Fengchun Miao and Kelly Shiohira, AI competency framework for students, UNESCO, August 8, 2024 (revised February 7, 2025).
Grounded in the vision of students as AI co-creators and responsible citizens, the publication emphasizes critical judgement of AI solutions, awareness of citizenship responsibilities in the AI era, foundational AI knowledge for lifelong learning, and inclusive, sustainable AI design. The UNESCO AI Competency Framework for Students aims to help educators in this integration, outlining 12 competencies across four dimensions:
- A human-centred mindset
- Ethics of AI
- AI techniques and applications
- AI system design
Report of the NEA Task Force on Artificial Intelligence in Education
National Education Association. Report of the NEA Task Force on Artificial Intelligence in Education. July 2024.
Our report and statement cover ideas that are essential to the question of AI in education, namely:
- Students and educators must remain at the center of education
- Evidence-based AI technology must enhance the educational experience
- Ethical development/use of AI technology and strong data protection practices
- Equitable access to and use of AI tools is ensured
- Ongoing education with and about AI: AI literacy and agency
At the heart of all our recommendations is the principle that humans must always be the center of the teaching and learning experience and play a significant role in every consequential education and employment decision.
PwC’s 2024 US Responsible AI Survey
PwC’s 2024 US Responsible AI Survey, 2024.
As we move well into the second year of generative AI’s (GenAI) broad emergence — which propelled AI to the top of corporate agendas — there’s no question it’s becoming integral to business. Companies slow to make AI an intrinsic part of their businesses may find themselves so far behind that it will be difficult to catch up. While it’s still early days, leaders now have a better understanding of how AI affects business strategy. They also are beginning to realize what it takes to build and deploy AI solutions that not only drive productivity and business transformation but also manage risk and preserve the incremental value that these solutions create. The key lesson of these early efforts? As AI continues to advance and redefines the nature of work and innovation, success requires sustained focus and a holistic view of the risks and the opportunities to build AI solutions responsibly.
Artificial Intelligence Index Report
Stanford’s Human-Centered Artificial Intelligence, Artificial Intelligence Index Report, 2025.
No Legal Personhood for AI
Brandeis Marshall, No legal personhood for AI, Patterns, Volume 4, Issue 11, 100861, November 10, 2023.
RECOMMENDATIONS: Enhancing AI Literacy for the United States of America
National Artificial Intelligence Advisory Committee (NAIAC), RECOMMENDATIONS: Enhancing AI Literacy for the United States of America, November 2023.
Recommendation 1: Create a National AI Literacy Campaign that fosters national AI literacy.
Based on the findings in the below “Context” section, a National AI Literacy Campaign should prioritize community college, university, non-traditional students, the workforce, individuals within underrepresented communities, and adults in roles who are most likely to be displaced by AI as aligned with EO 13985. 1 To make this recommendation actionable and executable in the short term, this campaign should both empower communities with adequate access to resources and leverage existing frameworks. This campaign would serve as a global example in AI literacy and allow local leaders in the U.S. to create and execute AI literacy programs to meet the specific needs of their communities.