E.A.R.T.H.: Structuring Creative Evolution through Model Error in Generative AI

TL;DR

This paper introduces the E.A.R.T.H. framework, a five-stage pipeline that leverages model errors to enhance AI-generated creativity through structured error transformation, human feedback, and multi-modal evaluation.

Contribution

It presents a novel structured approach to transform AI errors into creative assets, improving output novelty, relevance, and stylistic quality in generative models.

Findings

Creativity scores increased by 52.5% after refinement.

Final outputs showed a 70.4% improvement in creativity metrics.

Human evaluations rated outputs highly for creativity and clarity.

Abstract

How can AI move beyond imitation toward genuine creativity? This paper proposes the E.A.R.T.H. framework, a five-stage generative pipeline that transforms model-generated errors into creative assets through Error generation, Amplification, Refine selection, Transform, and Harness feedback. Drawing on cognitive science and generative modeling, we posit that "creative potential hides in failure" and operationalize this via structured prompts, semantic scoring, and human-in-the-loop evaluation. Implemented using LLaMA-2-7B-Chat, SBERT, BERTScore, CLIP, BLIP-2, and Stable Diffusion, the pipeline employs a composite reward function based on novelty, surprise, and relevance. At the Refine stage, creativity scores increase by 52.5% (1.179 to 1.898, t = -5.56, p < 0.001), with final outputs reaching 2.010 - a 70.4% improvement. Refined slogans are 48.4% shorter, 40.7% more novel, with only a 4.0% drop in relevance. Cross-modal tests show strong slogan-to-image alignment (CLIPScore: 0.249; BERTScore F1: 0.816). In human evaluations, the generated outputs were consistently rated highly, demonstrating strong creative quality and expressive clarity. Feedback highlights stylistic precision and emotional resonance. These results demonstrate that error-centered, feedback-driven generation enhances creativity, offering a scalable path toward self-evolving, human-aligned creative AI.