Distinctions Between Active Medicine and Proactive Health and Their Philosophical Elevation and Semantic Transformation in the AI Era

Yucong Duan

International Standardization Committee of Networked DIKWP for Artificial Intelligence Evaluation(DIKWP-SC)

World Artificial Consciousness CIC(WAC)

World Conference on Artificial Consciousness(WCAC)

(Email: duanyucong@hotmail.com)

I. Era of Transformation: A Paradigm Shift in Medical Practices

In the 21st century, medical practice remains predominantly symptom-based and reactive. This model struggles to address the challenges posed by complex disease spectrums, global population aging, and the coexistence of chronic and multiple conditions. The rapid development of Artificial Intelligence (AI) offers new tools and perspectives for medicine, yet AI's inherent "black box" issues, information opacity, and lack of interpretability limit its potential.

This report introduces the concept of Active Medicine, emphasizing a shift from mere remedial actions after disease onset to a higher-level integration of health concepts aligned with the "Dao" (the Way). Utilizing semantic mathematics (DIKWP) as a foundation, Active Medicine ensures that AI's decision-making logic achieves interpretability and validation at the semantic level. Consequently, medicine transcends its traditional role as a mere technical adjunct, becoming a central driving force in the evolution of civilization.

II. Background and Challenges: The Era Demanding a Shift from Reactive to Proactive Medicine2.1 Limitations of Reactive Medicine and Its Root Causes

Under the reactive medical model, medical interventions are often delayed, merely compensating for existing damage without the capacity to shape the overall health landscape. This limitation stems from a lack of comprehensive understanding and semantic description methods for the complex systems of life.

2.2 Opportunities and Future Trends in the AI Era

AI's ability to rapidly analyze vast amounts of data and provide predictive and decision-making suggestions offers significant opportunities to optimize diagnostic and treatment processes. However, without addressing AI's semantic understanding and interpretability issues, such optimization remains superficial.

2.3 Black Box Problem and the Semantic Cognition Dilemma in Medicine

The essence of AI's black box problem lies in its inability to explain decision-making processes at the semantic level. Medical decision-making fundamentally involves reasoning within a complex semantic system encompassing disease descriptions, lifestyle factors, and psychological states. Without solutions at the semantic level, AI's potential in medicine remains constrained.

III. Philosophical Foundation: Transformation from "Dao" Theory and the Essence of Medicine3.1 "Dao" and Universal Order: The Ultimate Reference for Medicine

"Dao," as the fundamental law of the universe, symbolizes harmony and order. When medicine originates from the Dao, it can perceive health as harmony with the Dao, elevating diagnostic and therapeutic decisions to the level of cosmic and humanistic perspectives.

3.2 Insights from Laozi's Philosophical Sequence: Dao-De-Ren-Yi-Li

Laozi posited that when the Dao is lost, human civilization descends sequentially to only retaining ritual (Li). In the context of medicine, lacking the guidance of Dao results in reliance solely on mechanical procedures (Li). Active Medicine aims to reverse this descent, returning from Li to Dao.

3.3 Education and Medical Transformation: Ascending from Ritual to Dao

Medical education must leverage philosophy and cognitive science to elevate from technical regulations to a cognitive process that comprehends the essence of life and the universe (Dao).

IV. The Essence and Vision of Active Medicine4.1 Active Medicine vs. Reactive Medicine: From Symptomatic Treatment to Holistic Optimization

Active Medicine is unsatisfied with merely repairing parts; instead, it plans health from a holistic perspective, making medical practice an active intervention that guides humanity towards an ideal harmonious (Dao) state.

4.2 Active Medicine as an Engine for Civilizational Evolution: Enhancing Health Philosophy

When health concepts integrate Dao's philosophical essence, medicine extends from a technical discipline to a civilizational philosophy, guiding society to pursue higher levels of life and cultural values collectively.

4.3 Human-Machine Collaboration and Integration Optimization: Approaching the Realm of Dao Rapidly

With AI and semantic tools aiding, human-machine collaboration can more swiftly process complex information and optimize decisions, bringing medical actions closer to the realm of Dao and transforming the traditional slow and fragmented medical landscape.

V. Innovation in Semantic Mathematics: The Proposal and Concept of DIKWP Semantic Mathematics5.1 The Core Dilemma of AI: The Black Box and Lack of Interpretability in Semantic Machines

AI's core lies in semantic processing, but without mathematical tools to handle semantics, it remains unexplainable.

5.2 Limitations of Mathematical Tools: Difficulty in Precisely Describing Real-World Semantics

Traditional mathematics excels in measurement and logical reasoning but cannot handle metaphors, contexts, and cultural semantic complexities.

5.3 DIKWP Semantic Mathematics: A Semantically Bindable Mathematical Language Structure

The DIKWP framework (Data-Information-Knowledge-Wisdom-Purpose) provides an operable mathematical expression for semantic concepts, enabling precise handling of semantic entities in medicine such as "Yin-Yang balance," "immune balance," and "health maintenance trends."

5.4 Scientific Paradigm Shift from Data-Driven to Semantic-Driven Research

DIKWP facilitates a transition from data statistics to semantic reasoning in scientific research, allowing for deeper modeling of medical phenomena.

VI. Practical Pathways and Case Studies6.1 Construction and Application of Semantic Medical Knowledge Graphs

By semantically annotating diseases, medications, therapies, and population characteristics, a multi-layered knowledge graph is constructed. AI can retrieve optimal treatment plans within this semantic network.

6.2 Design of Human-Machine-Patient Semantic Lossless Interaction Interfaces

Designing semantically driven interaction interfaces allows patients to describe symptoms using semantic options, enabling doctors and AI to communicate under unified semantic standards, reducing misdiagnosis and information bias.

6.3 Semantic Optimization and Iteration of Diagnostic Processes

Health goals are defined as points or trajectories in the semantic space, with AI continuously iterating and optimizing treatment strategies, directly explaining and adjusting the reasons behind changes.

6.4 New Drug Development Semantic Platforms

Using semantic mathematics to encode drug molecules, mechanisms, and metabolic pathways, AI can semantically deduce new molecule designs and formulation combinations, overcoming traditional trial-and-error bottlenecks.

VII. Re-Creating Traditional Medical Wisdom through Integration7.1 Semantic Reconstruction of Traditional Chinese Medicine’s Holistic Perspective

By expressing traditional Chinese medical concepts (such as meridians and Qi-blood) through semantic mathematics, AI can understand Chinese medical philosophy and link it with Western medical data, forming an integrated medical model.

7.2 Complementing and Integrating Western Reductionist Thinking

Combining reductionist experimental data from Western medicine with the holistic semantic models of traditional medicine enables medical decisions to be based on precise biological evidence and broad strategic health trends.

7.3 Semantic Activation of Traditional Medical Texts in the AI Era

Semantic information from classical texts like the "Yellow Emperor's Inner Canon" is digitized, allowing them to interface with modern evidence-based medical data, broadening the scope of clinical decision-making.

VIII. Re-Examining the Enhancement of Civilization and Cross-Disciplinary Significance8.1 Building a Cross-Disciplinary Ecosystem

Integrating philosophy, cognitive science, computer science, medicine, sociology, and economics into a multi-disciplinary semantic-driven new academic ecosystem.

8.2 A New Human Health Paradigm: Beyond Physiological Metrics

Health is no longer just blood pressure and blood sugar levels; it encompasses the semantic mapping of life meaning, cultural values, social relationships, and ecological harmony.

8.3 Social and Economic Impacts: Reshaping Policies and Industries

Active Medicine requires reshaping the industry chain from pharmaceutical companies and medical device manufacturers to insurance and elderly care services. Building a new ecosystem based on semantic standards and explainable decision-making enhances efficiency and fairness.

IX. Deepening Future Prospects and Real-World Challenges9.1 Standardization and Normative Construction

Develop universal DIKWP semantic tagging standards and medical semantic data exchange protocols to facilitate international collaboration and result comparison.

9.2 Privacy and Ethical Issues

Semantic-level decisions may involve deeper privacy concerns, necessitating semantic encryption, zero-knowledge proofs, and scrutiny and correction of semantic ambiguities and biases.

9.3 Educational Reforms and Talent Development

Medical education must incorporate courses in "Medical Semantics," "Philosophical Medicine," and "AI Semantic Algorithms," fostering interdisciplinary talents with philosophical literacy, semantic analysis, and programming skills.

9.4 Exploration of Economic and Industrialization Models

Encourage startups to explore semantic diagnostic platforms, promote pilot projects through government and capital, and ultimately form mature industry clusters and market ecosystems.

X. Extended Case Studies and Scenario Simulations10.1 Comprehensive Management Plans for Elderly Chronic Diseases

Semantic descriptions of elderly patients' physiological, psychological, and social parameters enable AI to find optimal wellness strategies within the semantic space, dynamically adjusting based on feedback to make elderly care smarter and more humane.

10.2 Semantic Decision-Making in Global Pandemic Response

Semantic models integrating geographical and cultural differences, preventive measures, and medical resource allocation information allow AI to quickly generate differentiated epidemic control strategy recommendations, transparently explaining the semantic logic behind each plan.

10.3 Semantic Telemedicine in Remote Areas

Local residents describe symptoms through semantic interfaces, AI provides preliminary semantic diagnostic suggestions, and remote doctors review them, bridging the gap in medical resource distribution.

XI. Prospects for New Academic Paradigms11.1 Establishing a Semantic Mathematics Academic Ecosystem

Create research centers, international conferences, and academic journals dedicated to semantic mathematics, promoting collaboration among mathematicians, AI researchers, philosophers, and medical scientists to enrich both theory and practice.

11.2 Expanding Medical Philosophy and Aesthetic Dimensions

Semantic mathematics can describe non-traditional therapies like art therapy, music therapy, and cultural rituals, infusing treatment processes with humanistic depth and achieving the integration of aesthetics and medicine.

11.3 Beyond Medicine: Integration with Arts, Religion, and Other Fields

Semantic tools extend beyond medicine to art creation, religious symbol interpretation, and social value system assessment, broadening new dimensions for human cognition and communication.

XII. Conclusion

This report comprehensively explores the distinctions between Active Medicine and Proactive Health, emphasizing how Active Medicine, grounded in the philosophical principles of "Dao-De-Ren-Yi-Li," leverages the DIKWP semantic mathematics framework to facilitate the dimensional transformation from conceptual space to semantic space. This transformation is pivotal for the AI-driven integration of traditional and modern medicine, promoting a paradigm shift from reactive responses to proactive management and optimization of health.

Active Medicine revolutionizes medical philosophy and cognitive frameworks, guiding AI to achieve interpretable and ethically aligned decision-making processes in medicine. Proactive Health extends these revolutionary ideas into practical applications, focusing on technological and behavioral interventions to maintain and enhance health continuously.

Together, Active Medicine and Proactive Health synergistically advance medicine towards a higher, more comprehensive, and dynamic health management system, ultimately achieving holistic and harmonious health for individuals and society.

Download the Presentation:

Philosophy of DIKWP AC-MED, December 2024DOI: 10.13140/RG.2.2.21465.63847Yucong Duanhttps://www.researchgate.net/publication/387078912_Philosophy_of_DIKWP_AC-MED

Appendix: Key Concepts and Frameworks

1. DIKWP Framework:

• Data: Raw, objective information.

• Information: Processed data that identifies differences and similarities.

• Knowledge: Integrated information forming a comprehensive understanding.

• Wisdom: Application of knowledge to make informed decisions.

• Purpose: Alignment of actions with defined goals and intentions.

2. Consciousness Bug Theory: A theoretical framework addressing the limitations and challenges of artificial consciousness, emphasizing the need for transparent, interpretable, and ethically aligned AI systems.

3. Semantic Integration: Ensuring that data from traditional and modern medicine can be seamlessly combined without loss of meaning, facilitating effective communication and decision-making.

4. Active Medicine: A revolutionary medical model based on "Dao-De-Ren-Yi-Li" philosophical principles, aiming to redefine health and disease from a holistic and proactive perspective, leveraging dimensional transformation from conceptual to semantic space through the DIKWP framework.

5. Proactive Health: An expanded medical model focused on active intervention and behavior management to maintain continuous health and reverse chronic diseases through controllable stimuli and dynamic health tracking.

This complete English translation maintains the depth and detail of Professor Yucong Duan's original Chinese report, clearly distinguishing between Active Medicine and Proactive Health, and highlighting the pivotal role of the DIKWP framework in integrating AI with traditional and modern medical practices. 

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