Conditions for True Machine Creativity: A Ten-Requirement Framework Based on Designics

Starting from the science of Designics, the paper proposes ten requirements that true machine creativity must meet (including environmental representation, scope awareness, conflict identification, etc.). It emphasizes that value-oriented scope definition and human-machine symbiosis are inherent components of creativity. The study redefines the standards for machine creativity, focusing on its ability to actively transform reality rather than just generate novel outputs, and discusses the importance of ethics and the protection of human subjectivity.

In recent years, AI's generative capabilities have raised core questions: When can machines truly possess creativity? How to maintain human subjectivity? The paper points out that true creativity is the structural transformation of incomplete situations, not just novelty. Designics is a science that studies intentional changes carrying meaning; its theoretical foundations consist of the Law of Perception (purposeful observation), Law of Conflict (identifying situational tensions), and Law of Ability (implementing interventions and observing).

Based on the Designics framework, the paper proposes ten requirements:

1. Environmental representation (constructing a model of the external world);
2. Scope awareness (selectively focusing on task-related information);
3. Conflict identification (discovering gaps between current status and expectations);
4. Intervention ability (implementing actions for change);
5. Outcome observation (perceiving the results of interventions);
6. Knowledge and environment update (updating models based on results);
7. Scope redefinition (adjusting the scope of perception/intervention);
8. Local-to-global expansion (extending the impact of local changes);
9. Value-oriented scope definition (focusing on priorities based on value judgments);
10. Human-machine symbiosis (realized within a collaborative framework).

The paper demonstrates the feasibility of the requirements through multiple cases: recursive element extraction (identifying structural units from complex data), autonomous mesh generation (automatically creating computational meshes according to physical constraints), and neurophysiological and workload analysis (understanding human cognition to guide machine design). These cases show that Designics requirements are not just theoretical but can be implemented in practical systems.

The paper's analysis of existing systems such as open systems, automatic discovery frameworks, and self-modifying agents finds that although they have strong generative capabilities, they lack true situational understanding and conflict identification, value-oriented scope definition, and deep human-machine collaboration. Their novel outputs are not equivalent to the structural transformation required for creativity.

Proactive AI ethics are an inherent part of machine creativity, not a post-hoc filter. Value orientation and human-machine symbiosis need to shape core mechanisms such as machine perception, conflict identification, and intervention selection. At the same time, human subjectivity must be protected: machines should understand and respect human value goals, seek human input for key decisions, reserve space for human creative judgment, and promote the development of human capabilities.

The philosophical significance of the study lies in redefining the standards for machine creativity (participating in world transformation rather than just generation). Future directions:

1. Implementing the ten requirements in practical systems;
2. Evaluating whether machines meet the requirements;
3. Integrating ethical considerations while maintaining efficiency;
4. Designing interactive interfaces that promote human-machine symbiosis. This study provides a normative framework for AI development and reminds us to pay attention to the essential characteristics of creativity.