Class Ethics and Regulation

The Ethics and Regulation course unit forms the deontological and normative axis of the master's in Applied Journalism. Its field of action covers journalistic ethics, media regulation and self-regulation models, and the legal framework that governs news activity in the digital age. It operates in the domains where technology reshapes professional practice: digital platforms, artificial intelligence, algorithmic bias, disinformation, transparency and diversity. It intervenes in the formation of journalists' ethical judgement, in rigorous fact verification skills, and in the distinction between journalism and activism. Its relevance within the study cycle is structural: in a master's programme oriented towards digital innovation and emerging technologies, this unit ensures that technical competence rests on social responsibility, credibility and respect for fundamental rights - conditions of legitimacy for professional journalism that the market demands and democracy requires.

Not applicable

Module 1 (M1) - The Challenges of AI Regulation (3 sessions): the emerging regulatory framework for AI; ethical principles applied to news production. Module 2 (M2) - Data Verification, Fact-Checking and Disinformation (4 sessions): methods and tools to counter disinformation; algorithms and information flows; platform transparency and social responsibility - justice and regulation. Module 3 (M3) - Transparency, Diversity and Inclusion (5 sessions): justice and fairness; accuracy and equality in news coverage; journalism vs. activism - ethical boundaries and impacts on credibility; algorithmic bias and its effects on editorial choices. Module 4 (M4) - Applied Ethics in Project Development (3 sessions, 9 hours): guidance on the ethical, legal and deontological dilemmas raised by students' projects; from theory to concrete editorial decisions.

The unit combines theory and practice, with inquiry- and cooperation-based approaches that foster peer learning and self-assessment. Problem-based learning strategies and realistic exercises (Savin-Baden & Major, 2004) develop critical thinking, autonomy and collaborative work, drawing on the professional experience of students and faculty. In M1, interactive lectures and case studies frame AI regulation and applied ethical principles. In M2, students carry out data verification and disinformation detection exercises with professional fact-checking tools. In M3, guided debates confront dilemmas of transparency, diversity, algorithmic bias and the boundaries between journalism and activism (Kim et al., 2006). In M4, project-based learning links the unit to students' projects, with continuous feedback (McLaughlin et al., 2022). Tutorial sessions support coursework and sound editorial decisions.

Diakopoulos, N. (2019). Automating the News: How Algorithms Are Rewriting Journalism. Harvard University Press. Pena, P. (2019). Fábrica de Mentiras: Viagem ao Mundo das Fake News. Objectiva. Regulamento (UE) 2024/1689 do Parlamento Europeu e do Conselho, de 13 de junho de 2024 (Regulamento Inteligência Artificial). Jornal Oficial da União Europeia. Silverman, C. (Ed.) (2020). Verification Handbook: For Disinformation and Media Manipulation (3.ª ed.). European Journalism Centre. Simon, F. M. (2024). Artificial Intelligence in the News: How AI Retools, Rationalizes, and Reshapes Journalism and the Public Arena. Tow Center for Digital Journalism, Columbia University. Tambini, D. (2021). Media Freedom: The Contradictions of Communication in the Age of AI. Polity Press.