Scenarios

Can We Teach the Ethics of Technology?

Juliana Raffaghelli & Mariana Ferrarelli (UdeSA, Argentina, ETH-TECH Advisory Board)

The idea of moving from abstract ethical discourse to situated ethical practice was instantiated in seminars and workshops, which might be inspirational for other teachers aiming at exploring the “teachability” of edtech ethics.

The question of whether we can teach the ethics of technology has become increasingly urgent as artificial intelligence, data infrastructures, and platformed educational systems permeate everyday teaching and learning. At first glance, the answer appears simple: of course we can teach it, just as we teach other forms of professional ethics. Yet the reality is far more complicated. Technology ethics does not behave like classical deontological rules, nor like a list of virtues to be cultivated. It is dynamic, uncertain, highly contextual, and deeply entangled with political, economic, and sociotechnical structures. Teaching it demands far more than transferring normative principles from guidelines into classrooms, this is something we have been discussing from the very beginning of the ETH-TECH project.

One of the primary difficulties is that technology evolves faster than curricular structures can adapt. Educators are often asked to teach ethical implications of systems whose functioning is opaque even to their designers. Without some level of technical and data literacy, discussions of fairness, transparency, or accountability risk becoming abstract exercises rather than grounded ethical reasoning. Students cannot meaningfully interrogate a system they cannot see. Thus, teaching the ethics of technology requires not only moral frameworks but also the cultivation of critical technological literacy.

At the same time, ethics cannot be reduced to compliance with predefined checklists. Research consistently shows that when ethical guidelines for AI and data are presented as procedural tasks, they lose their pedagogical power. Students learn what must be performed, not what must be questioned. This is particularly visible in recent transnational analyses of teacher-education syllabi, where ethics—especially digital ethics—appears only marginally and often as a rhetorical gesture rather than as a substantial curricular commitment (Raffaghelli & Negru-Subtirica, 2025). In these contexts, ethics becomes ornamental rather than transformative.

For ethics to be teachable, it must instead be situated within real dilemmas. Students learn by grappling with tensions: between efficiency and equity, between data collection and privacy, between automation and human judgment, between institutional pressure and professional agency.

These tensions are productive; they invite the kind of reflective inquiry through which ethical understanding develops. Teaching the ethics of technology involves making these tensions visible and giving students tools to navigate them.

This means shifting ethics education from doctrine to praxis. Educators do not “deliver” ethical truth; they facilitate encounters with ambiguity, conflict, and responsibility. They help students surface the social and political consequences embedded in technological systems and encourage them to imagine alternatives. In this sense, the ethics of technology is teachable precisely because it refuses closure. It is an ongoing practice of questioning, contextualizing, and negotiating—one that demands curiosity, humility, and a willingness to confront the limits of what technology can or should solve.

So yes, we can teach the ethics of technology. But only when we abandon the illusion that it is a stable body of knowledge. What is teachable is not a set of universal rules, but a capacity for critical engagement: the ability to see technology as situated, value-laden, and open to contestation. Ethics becomes teachable when we acknowledge its complexity and invite students to inhabit it fully.

Using the Scenarios: A Workshop

Here is a case to learn how to adopt the several tools of the ETH-TECH project and also, to engage your students in building new situated ethical scenarios. If you are interested in collaborating with collecting scenarios, we are open! Please send your scenarios and learning designs to support inquiry-based ethical reflection on AI and data in education using the form here.

A dedicated Seminario-Taller on the ethical uses of AI in education, organised by the Universidad de San Andrés (Argentina) and led by Prof. Mariana Ferrarelli, part of the ETH-TECH advisory board.

Supported by Juliana Raffaghelli, ETH-TECH Italy, the workshop invited higher-education teachers, teacher educators, and students to engage in a critical, experiential exploration of ethical dilemmas emerging from AI and data-driven technologies. Using the EU Ethical Guidelines as a shared framework and the ETH-TECH self-reflection instrument as a starting point, participants first mapped their own individual and institutional perceptions of principles such as human agency, transparency, fairness, wellbeing, privacy, robustness, and accountability. They then worked collaboratively to design situated ethical scenarios, articulating concrete tensions within their educational contexts and imagining possible responses and future practices. Through this structured process—combining self-evaluation, conceptual framing, small-group dialogue, and scenario-building—the workshop transformed awareness into reflective action, enabling participants to prototype ethical practices grounded in their own realities.

Check here the Learning Plan co-designed to lead the workshop! (Spanish)

You can browse the resulting scenarios, published below. These scenarios are part of the ETH-TECH scenarios collection, that, as the Art Contest results, can support approaches to teach ethics that are:

situated in practice;

participatory, not prescriptive;

critical, not technocratic;

messy, not polished;

collective, not individualised;

interdisciplinary, not siloed.

Take a look to the published scenarios here.

Also, browse the interactive tool to explore the EU Ethical Guidelines of AI and data in Teaching and Learning here!

Enjoy!