Criteria for Inclusion in the AIDA Resource List
A. Scientific Quality
- Resource is accurate and based on current AI knowledge.
- Authors are identifiable and credible (researchers, institutions, reputable organizations, companies).
- Methods are rigorous and transparent.
B. Pedagogical Value
- Resource is accessible and suitable for doctoral- / master levels
- Learning goals or outcomes are clearly stated
- Includes explanations, examples, or exercises when relevant.
- Support materials provided (slides, code, datasets).
C. Relevance to the AIDAI AI Curriculum
Resource must meaningfully support at least one of the core topic of AIDA AI Curriculum
AI PhD Curriculum is a specification of the structure and content of a PhD programme. The Curriculum concentrates on the doctoral training parts categorized as AI Core Curriculum modules and AI Special Topic Pillars with specific learning outcomes and related courses.
https://www.i-aida.org/phd-curriculum/
D. Accessibility & Licensing
- The resource must be accessible to the intended academic audience. Open-access resources are preferred. Access conditions must be clearly specified.
- The resource must include clear usage rights (e.g., Creative Commons, open-source licenses, or institutional authorization). Any resource containing personal data must comply with the General Data Protection Regulation (GDPR) and applicable data protection laws.
E. Ethical & Sustainable AI Compliance
Resources must:
- Not promote harmful practices or unsafe deployments
- Follow guidelines on responsible AI, fairness, transparency, and sustainability
- For datasets: no private or sensitive data without consent
AIDAI AI Editor Selection Criteria
- Expertise: Strong background in AI/ML and doctoral-level teaching or supervision.
- Pedagogical Judgment: Can assess clarity, usability, and relevance of educational resources.
- Ethical Awareness: Knowledgeable in responsible AI, privacy, bias, and sustainability.
- Commitment & Reputation: Willing to maintain the repository; trusted and recognized in the field.
- Technical Skills (optional): Familiar with repository management, metadata, and link verification.
Procedure for Conflict of Interest (COI)
- All ADAI AI editors must disclose relationships with contributors, institutions, or resources that could influence judgment.
Liability disclaimer:
- AIDA AI editors should avoid uploading material that is not licensed for public use or may pose legal/ethical risks.
- AI Editors are fully responsible for the AI material that they upload.
- AIDA is not liable for any uploaded AI materia
Submission Policy for Student Contributors
Senior MSc students and PhD candidates may submit educational materials to the AI Educational Resource Repository under the following conditions:
- Eligibility
The contributor must be a Senior MSc (final year) or an enrolled PhD student in AI or a closely related field.
The submitted material must align with the repository’s Criteria for Inclusion.
Supervision and Validation
Submission must be made in consultation with one AIDA AI Editor.
The designated AIDA AI Editor reviews the material prior to upload to ensure:
- Scientific accuracy
- Pedagogical relevance
- Ethical compliance
- Proper licensing and attribution
- Final Approval
The AIDA AI Editor provides a recommendation.
The AI Resource Committee (or its Chair) retains final approval authority if required.
Conflict of Interest
If the AIDA AI Editor has a conflict of interest (e.g., supervisor of the student, co-author, close collaborator), another editor must review the submission.