When generative AI produces a racially stereotyped image, who is responsible - the developer, the platform, or the designer who delivers it to a client? This question, unanswerable within existing competency models, reveals an ethical rupture that generative AI has introduced into design practice. Unlike general AI literacy or digital ethics frameworks, which treat ethical competence as one component among several, the Ethical Information-Communicative Competence (EICC) model proposed in this paper positions ethical competence as a cross-cutting dimension that permeates all aspects of professional design activity - from information evaluation through communication to technology use and reflection. The paper maps the ethical challenge landscape of AI-driven design, develops EICC around five cross-cutting ethical challenges (bias, provenance, disclosure, intellectual property, and environmental impact) that manifest differently across professional domains, and defines proficiency in terms of ethical reasoning levels (compliance, deliberative, transformative) rather than skill acquisition stages. It further proposes TPACK-Ethical as a pedagogical architecture that integrates ethical knowledge into studio-based instruction, and reveals through gap analysis of the Ukrainian B2 Design standard that ethical competence is systematically absent from current standards. An integrative framework links EICC, TPACK-Ethical, and constructive alignment into a cyclical model for curriculum transformation.
Yuliia V. Yechkalo (Sat,) studied this question.