AI-generated designs are powerful, but they aren't perfect, especially when it comes to their heavy dependence on data. For instance, if an AI tool is trained primarily on Western art, its output may lack a global perspective, leaving out non-Western aesthetics and potentially alienating some users. This is a clear risk in today's globalized world.

So what can designers do?

• Select data sets mindfully, aiming for diversity to train the AI on a wide array of styles and cultural visuals. This proactive step prevents the AI from developing a narrow, biased perspective.
• Use AI as a collaborator rather than a replacement. Human designers can identify nuances and subtleties that AI might overlook, bringing a more well-rounded approach to the final design.