You do not have permission to edit this page, for the following reason:

Only users who are logged in using ORCID can make a change or add a contribution. Please login here.

Back

Edit a module

With this form, you create a step-by-step module on research integrity or ethics. This can be used to provide instruction on a particular topic. You might want to use it for a tutorial, teaching material, case analysis tool, or an educational game.

Every single module is intended for just one type of user. That sets it apart. It might be that you write an instruction for a group session with a facilitator and participants. You would then need to write two pages, one with the steps for facilitators and one with the steps for participants.

Before you submit, please be aware of our community guidelines.

Do you want your training and project to be featured on the Embassy?

Feel free to contact us to discuss the options.

Module

Instructions for:ParticipantTrainer

Perspective Participant

What are the steps?

The European Union promotes Trustworthy Artificial Intelligence (AI) as the foundation for responsible AI development and deployment, requiring systems to be lawful, ethical, and technically robust. Established by the European Commission, the High-Level Expert Group on AI (HLEG) introduced the ''Ethics Guidelines for Trustworthy AI'' in 2019, defining four foundational ethical principles—Respect for Human Autonomy, Prevention of Harm, Fairness, and Explicability. These principles translate into seven practical requirements: Human Agency & Oversight, Technical Robustness & Safety, Privacy & Data Governance, Transparency, Diversity, Non-Discrimination & Fairness, Societal & Environmental Wellbeing, and Accountability. To operationalize these guidelines across the AI lifecycle, the EC created the Assessment List for Trustworthy AI (ALTAI). Moving beyond "box-ticking" checklists, the Ethics Readiness Levels (ERLs) framework utilizes semi-structured dialogues between technical and ethics experts to measure and advance ethical maturity across five discrete levels (ERL 0 to ERL 4). Applying these ethical frameworks is crucial when evaluating research projects against the regulatory context of the EU AI Act. While Article 2 provides a "safe harbor" research exemption for scientific R&D, real-world testing, pilots in sensitive operational settings (such as healthcare, education, or employment), and commercialization move projects into a "Grey Zone" where high-risk obligations or Article 5 prohibited practices may apply.

Interactive Content

Add another

Instruction Remarks Participant

Perspective Trainer

What are the steps?

Add another

Instruction Remarks Trainer

Related To

Edit Instruction: Instruction:E00715de-6b4a-4dc6-96ae-2f78695636b2

Edit a module