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Between Human and Machine
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Exploring how creatives define authenticity and authorship in an AI-driven world

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MEET THE Designers:
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Shihua (Ariel) Wang

linkedin.com/in/shihua-wang/
SUMMARY

I began by exploring how generative AI is reshaping creativity and challenging our ideas of authorship, originality, and authenticity. Through surveys, interviews, and prototype testing with creatives across fields, I discovered a consistent tension: AI boosts efficiency but often threatens personal voice and ownership. My project investigates how creatives define their ethical boundaries with AI and proposes tools that support more mindful, transparent, and human-first creative practices.

challenge 

Across creatives, agencies, tech developers, and legal experts, I identified a shared gap: AI improves efficiency, but there is no clear framework to help people decide when AI supports their voice and when it threatens authenticity. Creatives fear losing authorship, clients struggle with transparency, and developers face trust barriers. These gaps reveal an opportunity for tools that guide reflection, disclosure, and intentional human-AI collaboration.

Outcome

The project resulted in a reflection-based tool that helps creatives map how much of their process is human-led, AI-assisted, or automated. Paired with guided prompts and a disclosure checklist, it gives users a way to evaluate authorship, identify where AI supports or weakens authenticity, and communicate their choices transparently. This outcome directly addresses stakeholder needs for clarity, trust, and ethical boundaries in AI-assisted creative work.

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