Ethics of AI and Data in Education The Situated ETH-TECH Perspective: a Framework for Practice_Project Deliverable –Work Package II «ETH-TECH Framework»

This document presents the ETH-TECH project framework document outlined in Work Project 2 (WP2) of the ETH-TECH project. The ETH-TECH framework reflects the teaching and research expertise of teams from 4 European countries (Germany, Italy, Romania, Spain). In proposes a culturally sensitive and contextualized approach of the ethical principles developed at EU level. It is grounded on the participatory Awareness Raising sessions that took part in spring 2025 in the 4 countries, involving university teachers and students. For a contextualized ethical approach of AI usage in HE we recommend: (a) a careful analysis of the role of culture in how ethics of AI is understood and how responsibility is negotiated; (b) an in-depth understanding of the national and local socio-economic dynamics, with a focus on existing affordances and structural barriers; (c) an integration of national recommendations in the structure of the specific educational system. The ETH-TECH framework conceptualizes three hierarchical levels of ethical engagement with AI for education: 1. Technological; 2. Institutional; 3. Personal (teacher, student, classroom as regulated interaction of individuals). These levels are interwoven, with the technological level (how AI systems work, how they are regulated and transparent, how personal data is managed) being the opaquest, often working as a “black box”. The three EU principles that the ETH-TECH framework focuses on are: human agency and oversight, transparency, and diversity, non-discrimination and fairness. Each principle is presented through an intuitive definition, a case-study with guiding questions, and practical recommendations for institutions, teachers and students using a problem – action point format. Hosted on the project website (ETH-TECH Framework, https://eth-tech.eu/eth-tech-framework/), this interactive and multimodal resource consists of: >an introductory video, >the consultable Framework document, >and a direct link to all the supporting technical documents. By combining participatory insights, academic expertise, and ethical guidelines, the ETH-TECH Framework provides a shared reference for ethical, inclusive, and transparent approaches to AI in HE. This project deliverable is the result of joint collaboration between all partners. Final document authored by BBU and UNIPD teams (Work Package Leaders).