How do you preserve authorship in an AI world?

Cogmos: designing a course for an AI-native generation.

Role

Learning Experience Designer

Context

Columbia University Working Group

Focus

User Research, Product Design, Learning Strategy

Course

AI & Creative Technology

The Challenge

Generative AI is transforming how students create, learn, and solve problems. Our team was tasked with helping design a new AI and Creative Technology course.

Before designing the experience, we needed to understand how students were actually using these tools.

My Role

I conducted research, synthesized findings, and helped translate those insights into course strategy and design principles. I also designed the Cogmos Design Lab logo.

The Insight

Across interviews, portfolio reviews, and online discussions, one pattern emerged repeatedly. Students were producing increasingly polished work while struggling to explain their reasoning.

Output quality was improving faster than authorship.

Students were finding it harder to differentiate themselves in a world of AI.

Key Decisions

Start with behavior
Rather than designing around assumptions, I examined how students were actually incorporating AI into their creative workflows.
Define the core tension
The core challenge wasn't technical literacy with AI, but maintaining ownership, reasoning, and creative voice in AI-assisted work.
Design around durable skills
Instead of organizing the curriculum around specific tools, we focused on perception, reasoning, decision-making, critique, and authorship, the skills that outlast any one tool.

The Visual Design Module

I applied these principles in the Visual Design module, an early part of the course that addresses how generative AI reshapes creative authorship.

Elements → Perception

Students analyze how visual components shape attention and meaning, so they can critically evaluate AI outputs, not just generate them.

↓

Relationships → Structure

Students move from manipulating parts to understanding systems, examining hierarchy and composition so they can intentionally guide AI rather than accept default results.

↓

Constraints → Decision Quality

Projects introduce limitations that require tradeoffs and justification, countering the infinite-generation logic of AI tools.

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Identity → Voice Over Time

Students synthesize structural awareness and decision-making into an emerging creative voice, distinguishing their authorship from algorithmic style.

Across each phase, students articulate their reasoning and identify where AI influenced the outcome. The goal is not to reject generative tools, but to keep students the primary decision-makers in their own creative process.

Outcome

The resulting framework informed both course positioning and instructional design, ensuring the program emphasized long-term cognitive skills rather than short-lived tool proficiency.