Recognition, Authorship & AI Collaboration

Kevin.Nomu@gmail.com
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Recognition, Authorship & AI Collaboration
(05/30/2025)Ethics & Justice
Restoring Recognition
(04/26/2024)

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How Sex, Comparison, and Happiness Interact
(05/18/2024)

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(12/06/2023)

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Morality as a Problem
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Recognition, Authorship & AI Collaboration
Rethinking Creative Interfaces in the Age of Machine Learning By Kevin Langyintuo

Originally written as part of my application to NYU’s Interactive Telecommunications Program (ITP), this essay explores how emerging AI tools are reshaping creative authorship—and why we need new interfaces to meet that shift with intention. Drawing from Recognition Theory and my experience as a designer and researcher, I argue that speed alone isn’t enough: creative tools must preserve agency, authorship, and collaboration.

I propose a layout-native interface for human-AI design collaboration—one that prioritizes iteration, shared context, and visual thinking between creators and machines. From campaign work to generative image workflows, I reflect on the creative friction I’ve experienced and outline how a new kind of tool could help teams work with AI, not just after it.

Rather than treating AI as a threat to creative direction, I view it as an accelerator for intuition—if we design tools that support clarity, authorship, and collaborative flow.

Read the full paper here.

Topics: AI & Creativity, Recognition Theory, Interface Design, Collaboration, Layout Systems, Creative Tools