Abstract:

Generative AI technologies are increasingly embedded in visual communication practices, particularly during early-stage ideation, where designers explore concepts, generate visual alternatives, and frame creative directions. While these systems accelerate creative exploration, they also introduce ethical challenges that often remain implicit or unaddressed at the ideation stage. This paper examines Human–AI co-design in visual communication with a focused investigation of how ethical decision-making can be systematically integrated into AI-assisted ideation workflows.

Guided by the research question How can ethical AI practices be operationalized within AI-assisted ideation processes in visual communication design?, the study adopts a qualitative, conceptual research methodology.

The research combines:
(1) a structured literature review across design research, human–AI interaction, and ethical AI studies, and
(2) an analytical synthesis of documented AI-assisted design practices to identify recurring interaction patterns between designers and generative systems.

These patterns are analyzed through an ethical lens to examine decision points where designers negotiate authorship, originality, cultural representation, and creative control.

The analysis reveals four primary ethical tensions emerging during AI-assisted ideation: reinforcement of cultural and stylistic bias, visual homogenization, unintentional cultural appropriation, and diminished designer agency due to over-reliance on generative outputs. Based on these findings, the paper proposes a micro-framework for ethical AI-assisted ideation, consisting of reflective checkpoints embedded within early creative workflows. These checkpoints prompt designers to critically assess AI-generated content in relation to intent, context, authorship, and cultural sensitivity without disrupting creative momentum.

The study concludes that ethical deliberation, when integrated into ideation rather than applied retrospectively, can function as a generative design practice rather than a constraint. The paper contributes to Human–AI co-design research by offering a practical, education-oriented framework that supports responsible AI use in visual communication. This approach is particularly relevant for design education and professional practice, where AI tools are rapidly adopted but ethical guidance remains underdeveloped.

Keywords:

Human–AI Co-Design, Visual Communication, AI-Assisted Ideation, Ethical AI, Design Education, Creative Workflows, Generative AI.