Human vs. AI: Creativity in Game Design

Research Overview: Human vs. AI Creativity in Game Design

• Format: Academic Paper (IEEE Standards)
• Core Inquiry: A comparative analysis of creative outputs between human designers and generative AI models within the context of game mechanics and world-building.
• Key Objective: Determining the current boundaries of AI as a co-creative tool and identifying the unique "human-centric" design elements that remain difficult for algorithmic models to replicate.

Abstract & Thesis

The research explores the intersection of procedural generation and human intuition. It investigates whether AI can transcend "recombinational creativity" (mixing existing data) to achieve "transformational creativity" (creating entirely new design paradigms) in game development. The paper analyzes specific design tasks—ranging from level layout to narrative branching—to evaluate the qualitative differences in the resulting player experience.

Comparative Methodology

The study employs a structured framework to compare design outputs based on three primary pillars:

• Structural Coherence: How well the design follows the functional constraints of game logic and player progression.
• Thematic Resonance: The ability of the design to evoke specific emotional responses and maintain narrative consistency.
• Innovation vs. Imitation: Assessing if the AI-generated content offers novel mechanics or merely mimics high-frequency patterns found in its training data.

Key Findings & Insights

• The "Intentionality" Gap: While AI excels at rapid iteration and generating vast amounts of coherent content, it lacks "intentionality"—the ability to break rules for a specific emotional or artistic purpose.
• Co-Creativity Model: The research concludes that the most effective use of AI in modern game design is not as a replacement for the designer, but as a "force multiplier" that handles procedural density, allowing the human designer to focus on high-level systems and emotional anchoring.
• Iterative Design: Highlighting how AI can be utilized to stress-test game balance through rapid prototyping, significantly reducing the pre-production phase of complex system design.