World Artificial Consciousness Association (WACA)and the International Artificial Intelligence DIKWP Evaluation Standards Committee (DIKWP-SC)
I. Background of the Organization: World Artificial Consciousness Association (WACA)1. Organizational Positioning
The World Artificial Consciousness Association (WACA) is a high-level international organization that integrates academic research and industry. It not only focuses on traditional weak AI but also devotes itself to exploring higher-level, “quasi-conscious” forms of AI (Strong AI or even Artificial Consciousness). WACA brings together leading experts in multiple disciplines—such as intelligent science, neuroscience, cognitive science, ethics, and computer science—from around the world to build a cross-regional, cross-disciplinary, and cross-industry platform for AI research and applications.
2. Mission of the Association
Advancing “Artificial Consciousness” ResearchActively promoting research in areas such as brain-inspired intelligence, cognitive computing, and neuromorphic chips, driving AI development toward systems with autonomous “intent,” higher cognitive abilities, and advanced deep learning capabilities.
Encouraging Multidisciplinary IntegrationWelcoming experts and institutions from neuroscience, philosophy, ethics, sociology, law, economics, and other fields to expand both the breadth and depth of AI research.
Facilitating AI and Society’s Coordinated DevelopmentCollaborating with governments, enterprises, and NGOs to ensure that AI development aligns with security, sustainability, compliance, and humanistic considerations.
Building a Global Exchange PlatformHosting international conferences, workshops, competitions, and collaborative projects to strengthen academic and industrial interaction globally, and to actively promote international standardization and evaluation systems.
II. Introduction to the DIKWP Model
DIKWP is a comprehensive evaluation model initiated by WACA and promoted by the “International AI DIKWP Standards Committee,” designed to evaluate AI from data input to the final decision-making purpose. The name derives from five key elements:
Data
Covers data acquisition and collection, data governance and quality control, data security, compliance, privacy protection, etc.
Emphasizes the legality, accuracy, diversity of data sources, as well as handling imbalance and bias in data.
Intelligence
Focuses on machine learning algorithms, deep learning models, multimodal fusion, reasoning, and learning efficiency.
Includes advanced technologies such as adversarial defense, online learning, transfer learning, and federated learning.
Knowledge
Involves knowledge acquisition, knowledge representation, knowledge graphs, and knowledge reasoning.
Explores how knowledge is accumulated and transformed from “data,” as well as how to integrate human expert experience or external knowledge bases to enhance algorithm explainability and versatility.
Wisdom
Stresses higher cognition and contextual understanding, holistic decision-making, cross-domain applications, and real-time decision-making.
Balances timeliness, robustness, security, credibility, and human-machine collaboration as comprehensive indicators.
Purpose
Includes ethical and moral considerations, legal and regulatory requirements, sustainable development goals, and social value assessment.
Pays special attention to why an AI makes certain decisions—i.e., the goal-setting and intent design process—and the impact on society, ensuring alignment with shared human interests and core values.
As a novel AI evaluation framework, DIKWP provides academia and industry with a comprehensive lifecycle assessment approach, ensuring security and compliance while facilitating the continuous upgrading and evolution of AI.
III. The International Artificial Intelligence DIKWP Evaluation Standards Committee (DIKWP-SC): Main Responsibilities
To promote the global adoption and standardization of the DIKWP model, WACA has founded the “International Artificial Intelligence DIKWP Evaluation Standards Committee (DIKWP-SC)” The Committee’s main responsibilities include:
Standards and Norms Development
Organizing experts worldwide to study the metrics, classifications, and evaluation methodologies within the DIKWP framework, formulating practical and internationally recognized technical standards and industry guidelines.
Developing specialized sub-standards and use-case specifications for different industries (e.g., healthcare, finance, manufacturing, urban governance).
Evaluation System Enhancement
Compiling a complete set of DIKWP evaluation protocols, including operational manuals and data guidelines, to facilitate implementation by governments, enterprises, and research institutes.
Tracking AI technology frontiers and promptly revising, upgrading, and expanding evaluation metrics and methods to keep pace with technological advances.
Consulting and Training
Providing DIKWP-based consulting services for governments, social organizations, and enterprises, including technical evaluation, system acceptance, risk monitoring, and technical planning.
Offering specialized training and certification to cultivate skilled evaluators and promote international communication in the AI evaluation field.
Scientific Research Collaboration and Outcomes Sharing
Hosting international academic conferences, high-level forums, workshops, and competitions to inspire research and best practices for each DIKWP dimension among global institutions, enterprises, and universities.
Collaborating with standardization bodies (e.g., ISO, IEEE, IETF) to integrate existing standards with the DIKWP model for mutual benefit.
Cross-Disciplinary and Cross-Industry Advancement
Addressing the complexities of AI in regulatory, ethical, and legal contexts by involving experts from law, social sciences, and industry, thereby strengthening the “Purpose” dimension.
Setting up working groups for key areas such as smart healthcare, smart cities, smart industry, and intelligent transportation to define industry-specific standardization and application frameworks.
IV. Core Committee Members (Name and Affiliation Only)
(Listed in the order they appeared in the original data.)
Duan Yucong - World Artificial Consciousness Association (Chairman)
Dou Erxiang - Peking University
Gao Musheng - Shanghai Nichong Burui Intelligent Technology Co., Ltd.
Han Long - Hainan University
Jiang Zuo-wen - Ningbo University
Jiang Binxiang - Shandong University
Li Sheng - Guangxi Normal University
Chen Shiping - Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australia (International Academician)
Weng Jialiang - AIII Artificial Intelligence International Institute
Sajid Anwar - Institute of Management Sciences, Peshawar (Pakistan)
Li Chunguo - Southeast University (International Academician)
Liu Yongmou - Renmin University of China
Yu Lei - Inner Mongolia University
Qiu Jiawen - Kenside (Zhuhai) Co., Ltd.
Huang Qibao - Shangrao Normal University
Song Zhengyang - Shanghai Pudong Development Bank
Sun Qiang - Xi’an University of Technology
Wen Bin - Hainan Normal University
Cheng Hexiang - Southwest University of Political Science and Law
Xu Yongshun - Jiangsu Second Normal University
Zhang Jinsong - Beijing Research Institute of Standardization
Zhou Dexing - The Second Affiliated Hospital of Hainan Medical University
Yao Xifan - South China University of Technology (Committee Chairman)
Xu Caiguo - Ningbo University
Wu Aiqun - Shanghai Aerospace Information Technology Research Institute
Wang Peng - Beijing Academy of Social Sciences
Wang Lei - Hainan University
Wang Jun - Jiangsu Lizhuo Information Technology Co., Ltd.
Wang Jinlong - Tsinghua University Institute
Tong Dawei - CETC Investment
Song Jia - Chinese Academy of Tropical Agricultural Sciences
Shang Delong - Institute of Microelectronics, Chinese Academy of Sciences
Liu Yanfei - Chongqing Police College
Liu Minglei - Mechatronics Association
Li Yingbo - Blue (France)
Han Wei - Eurasian Academy of Sciences (China), Guangdong-Hong Kong-Macao Greater Bay Area Computing Power Economy Research Institute
Gu Yanhui - Huaiyin Institute of Technology
Dong Liang - Tencent HunYuan Model
Chen Liang - Hainan Meteorological Bureau
Che Haoyang - Zeekr Automobile
Fan Huiwen - SK China
Liu Bin - Northeast Petroleum University
Yan Baoping - Nanjing University of the Arts
Wang Changquan - Beijing Vocational College of Labor and Social Security
He Hui - Harbin Institute of Technology
Huang Yong - Guangdong University of Science and Technology
Andrea Baldini - Nanjing University
Peng Junhui - Beijing XiaDi Robotics Technology Co., Ltd.
Xiong Xi - Chengdu University of Information Technology
Liu Hongyang - Kyung Hee University, Advanced Information Technology Research Center (CAlTech), Korea
Liu Chunguo - Shandong Foreign Affairs Vocational University
Liu Yiming - Chinese Academy of Sciences Network Information Center (Affiliated Company)
Chen Guilin - Guangdong Advanced Institute of Science and Technology
Yang Minghao - Hainan Universal Intelligence Technology Co., Ltd.
Zou Jun - Hainan Women and Children’s Medical Center
Pu Yifei - Sichuan University
Wang Xinsheng - Harbin Institute of Technology (Weihai Campus)
Ji Hailiang - (Independent Consultant / No Fixed Institution)
Liu Haiping - Hubei Engineering College
Zhou Xiangyong - The Second Affiliated Hospital of Zhejiang University School of Medicine
Liu Zelong - China-Japan Friendship Hospital
Yan Ziye - Guangzhou Bys Medical Technology Co., Ltd.
Zhang Sheng - The First Affiliated Hospital of Soochow University
Yin Sheng - Zhongnan University of Economics and Law
Guo Jianan - Asian Institute of Technology
Wang Zumin - Dalian University
Hu Chunqiang - Chongqing University
Pan Zhifang - Wenzhou Medical University
Liu Luyi - Leshan Normal University
Xing Hongliang - Shenyang Aerospace University
Cao Quanlai - Changzhou University
Wei Wei - Xi’an University of Technology
Sun Chen - China Electronics Standardization Institute under the Ministry of Industry and Information Technology (MIIT)
Xu Jingheng - Sangfor Technologies / Shenzhen Municipal Key Laboratory of Cloud Security
Li Xiaojun - CEC New Smart City Research Institute Co., Ltd.
Huang Jianqiang - China Telecom Hainan Branch
He Changxu - Shanghai Huacai Group
Zhang QuanGuo - Henan Agricultural University (International Academician)
Liu Jun - Chengdu University of Information Technology
Liu Hongjian - Sino-American Silicon Valley Development Promotion Association Innovation Technology Industrialization Research Institute
Dai Yunhai - Sungkyunkwan University
Zhang Bin - Xinjiang Political Science and Law College Information Network Security Department, Network Information Center
Wang Qiaohua - International Medical University, USA (International Academician)
Sun Qiang - Xi’an University of Technology
Peng Ling - Huanggang Real Estate Registration Center
Li Lizhong - Quanshi International (International Academician)
An Xiaomi - Renmin University of China
Wang Donghai - China Electronics Technology Group
Ren Qilong - BAIC Foton Motor (International Academician)
Zhu Mianmao - Hainan Open University
Liu Zhen - Nagasaki University of Applied Sciences (Japan Engineering Academy Academician)
Dai Jianhua - Hunan Normal University
Xia Qinghua - Zhejiang University
Jiang Kun - Aizu University
Zhang Jicong - Beihang University
Jin Zhuo - Royal Society of Arts & Crafts, UK (International Academician)
Feng Zaiwen - Huazhong Agricultural University
Jiang Linhua - Bolivian Academy of Sciences (International Academician)
Wang He - Guangzhou University Architectural Design Institute (International Academician)
Wang Yongzhi - Xi’an University of Architecture and Technology
Zhang Yingsheng - China Scientific and Technological Information Institute
Qu Xilong - Changsha Normal University
Liao Hong - Hongshang Group (International Academician)
Wu Dongfang - Zhejiang University (International Academician)
Meng Lin - Ritsumeikan University
Wang Huaping - Sun Yat-sen University
Ning Huansheng - University of Science and Technology Beijing (International Academician)
Jiao Li Cheng - Xi’an University of Electronic Science and Technology (International Academician)
Hu Junhong - Beijing Normal University
Cai Hengjin - Wuhan University (International Academician)
Jin Chaohui - Hunan University of Chinese Medicine (International Academician)
He Yigang - Wuhan University (International Academician)
Zhu Wenhua - Asia-Pacific Academy of Sciences (International Academician)
Li Jie - Japan Engineering Academy (International Academician)
Zhao Xiaoliang - Zhejiang University
Ren Chengxiang - University of Science and Technology Beijing
Gong Jiayuan - Hubei Automotive Industry College
V. Future Prospects
Standardization and Deepening International Collaboration
The Committee will establish strategic partnerships with international standardization organizations (ISO, IEEE, IETF), government agencies, industry alliances, and NGOs, striving to integrate DIKWP into policy frameworks worldwide, ultimately forming an authoritative standard with global influence.
Extensive Application Across Multiple Scenarios and Industries
The Committee plans to explore the diverse needs of AI in healthcare, finance, public safety, energy, manufacturing, education, agriculture, and environmental protection. By adapting DIKWP to each scenario, the Committee will develop industry standards and application guidelines that maximize the synergy of AI technologies with real-world use cases.
Talent Cultivation and Technology Accumulation
Through international competitions, forums, workshops, and certification programs, the Committee aims to train professionals in the field of AI evaluation. Supported by academic and industry resources, they will build AI algorithm libraries, benchmarking datasets, and open-source tools to sustain the long-term development of DIKWP evaluation.
Ethics and Social Responsibility
Recognizing the growing impact of AI in areas such as defense, security, finance, and healthcare, the Committee will reinforce the “Purpose” dimension, with particular attention to environmental protection, social justice, sustainability, and ESG topics, ensuring the practice of “Responsible AI.”
Ongoing Technological Upgrades and Model Refinement
Since AI technologies evolve rapidly—large language models, multimodal models, new neural-network chips, etc.—the DIKWP model also requires continual updates to incorporate cutting-edge research and address challenges like adversarial attacks and algorithmic security, ensuring its forward-looking and practical relevance.
Through these strategies, the World Artificial Consciousness Association and its International Artificial Intelligence DIKWP Evaluation Standards Committee (DIKWP-SC) will actively promote “Data–Intelligence–Knowledge–Wisdom–Purpose” as the five pillars of AI evaluation and standardization on a global scale, enhancing the credibility, security, compliance, and sustainability of the AI industry while fostering the coordinated advancement of technology innovation and human welfare.
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