China Social Science Review

No.2, 2024

Cross-Modal AI, Human-Machine Collaboration and Creativity: Rethinking the Technology with Text-to-Image Generation Modals as the Core

(Abstract)

Yang Junlei and Zheng Danlu

In the realm of AI-generated content creation (AIGC), text-to-image generation models primarily depend on two technological processes: text-image correlation and image generation. AIGC applications, including text-to-image models, introduce a novel paradigm of human-machine collaboration into the domain of artistic creation. To harness the assistance of machines, humans must recalibrate their approach, aligning closer to machine-like thinking, while concurrently reevaluating their own cognitive processes. Although current AI generation technologies may not yet endow text-to-image models with autonomous creativity, the future of artistic creation may no longer be characterized by a competition between humans and machines, but rather a contest between permutations of “human + machine” collaborations. Together, humans and machines form a new entity, becoming a wellspring of creativity.