Traditional Invention and Innovation Theory 1946-TRIZ Does Not Adapt to the Digital Era

-Innovative problem-solving methods combining DIKWP model and classic TRIZ

Purpose driven Integration of data, information, knowledge, and wisdom Invention and creation methods: DIKWP-TRIZ

(Chinese people's own original invention and creation methods:DIKWP - TRIZ)

Embracing the Post-Dissertation Publishing Era

Yucong Duan, Shiming Gong

DIKWP-AC Artificial Consciousness Laboratory

AGI-AIGC-GPT Evaluation DIKWP (Global) Laboratory

World Association of Artificial Consciousness

(Email：duanyucong@hotmail.com)

In the academic research of human society, the mechanism centered on the publication of papers has long been regarded as the key measure of academic achievement and research quality. However, with the rapid development of artificial intelligence technology and the explosive growth of digital information, this traditional mechanism is facing unprecedented challenges and subversive changes. This report discusses the possible future direction of change, including the change of academic communication mode, the diversification of evaluation criteria, and the new mode of sharing and disseminating academic achievements.

First of all, the traditional publication of papers may no longer be the only way to display achievements in future academic research. With the development of multimedia and interactive technology, the display of research results can take more abundant and dynamic forms, such as data visualization, interactive demonstration, and even the application of Virtual Reality (VR) and Augmented Reality (AR) technologies, which makes academic communication more intuitive and vivid.

Secondly, the diversification of evaluation criteria will become another major trend in future academic research. With the application of artificial intelligence and big data technology, the evaluation of research impact will not only depend on the number of citations or impact factors of papers, but also include a wider range of indicators, such as discussion on social media, public participation, and applications in interdisciplinary fields. This diversification of evaluation criteria is helpful to reflect the social value and practical influence of research more comprehensively.

Furthermore, the rise of Open Access and Preprint Servers is changing the way of sharing and disseminating academic achievements. The development of these platforms has promoted the instant sharing of academic achievements, accelerated the dissemination and exchange of knowledge, and lowered the threshold for acquiring knowledge. In the future, these platforms may be further developed, combining artificial intelligence technology to realize intelligent recommendation and customized reading, making the dissemination of academic research more efficient and personalized.

In addition, the mode of collaborative research may also change with the development of digital tools and platforms. The application of cloud computing, online collaboration platform and social network will make it more convenient for researchers to cooperate across geographical and disciplinary boundaries. This increase in cross-border cooperation is expected to promote the collision of innovative ideas and accelerate the process of scientific discovery.

Finally, academic integrity and ethical issues will be paid more attention in future academic research. The application of artificial intelligence technology, such as tools to automatically detect plagiarism and forged data, will help maintain the quality and integrity of academic research. At the same time, with the diversification of academic communication methods, how to ensure the accuracy and reliability of research results will also become a new challenge for academic circles in the future.

In a word, with the progress of technology and the change of academic communication mode, the future of academic research will be more open, interactive and diversified. These changes will bring new opportunities to academic circles and promote the creation, sharing and application of knowledge.

在人类社会学术研究中，以论文发表为核心的机制长久以来被视为学术成就和研究质量的关键衡量标准。然而，随着人工智能技术的迅速发展和数字化信息的爆炸式增长，这一传统机制正在面临前所未有的挑战和颠覆性变化。本报告探讨了可能出现的未来变革方向，包括学术沟通方式的变革、评价标准的多元化、以及学术成果分享和传播的新模式。

首先，未来的学术研究可能不再将传统的论文发表作为唯一的成果展示方式。随着多媒体和互动技术的发展，研究成果的展示可以采取更为丰富和动态的形式，如数据可视化、交互式演示、甚至虚拟现实（VR）和增强现实（AR）技术的应用，使得学术交流更为直观和生动。

其次，评价标准的多元化将成为未来学术研究的另一大趋势。随着人工智能和大数据技术的应用，研究影响力的评估将不再仅仅依赖于论文的引用次数或影响因子，而是包括更广泛的指标，如社交媒体上的讨论度、公众参与度、以及跨学科领域的应用等。这种评价标准的多元化有助于更全面地反映研究的社会价值和实际影响。

再者，开放获取（Open Access）和预印本服务器（Preprint Servers）的兴起正在改变学术成果分享和传播的方式。这些平台的发展促进了学术成果的即时共享，加速了知识的传播和交流，同时也降低了获取知识的门槛。未来，这些平台可能会进一步发展，结合人工智能技术实现智能推荐和定制化阅读，使得学术研究的传播更加高效和个性化。

此外，协作研究的模式也可能因为数字化工具和平台的发展而发生变革。云计算、在线协作平台和社交网络的应用，将使得研究者跨越地理和学科界限进行合作变得更加便捷。这种跨界合作的增加有望促进创新思想的碰撞，加速科学发现的过程。

最后，学术诚信和伦理问题在未来学术研究中将更加受到重视。人工智能技术的应用，如自动检测抄袭和伪造数据的工具，将有助于维护学术研究的质量和诚信。同时，随着学术交流方式的多样化，如何确保研究成果的准确性和可靠性也将成为未来学术界需要面对的新挑战。

总之，随着技术的进步和学术交流模式的变化，学术研究的未来将更加开放、互动和多元化。这些变革将为学术界带来新的机遇，促进知识的创造、分享和应用。

Reference

[1] Duan Y. Which characteristic does GPT-4 belong to? An analysis through DIKWP model. DOI: 10.13140/RG.2.2.25042.53447. https://www.researchgate.net/publication/375597900_Which_characteristic_does_GPT-4_belong_to_An_analysis_through_DIKWP_model_GPT-4_shishenmexinggeDIKWP_moxingfenxibaogao. 2023.

[2] Duan Y. DIKWP Processing Report on Five Personality Traits. DOI: 10.13140/RG.2.2.35738.00965. https://www.researchgate.net/publication/375597092_wudaxinggetezhide_DIKWP_chulibaogao_duanyucongYucong_Duan. 2023.

[3] Duan Y. Research on the Application of DIKWP Model in Automatic Classification of Five Personality Traits. DOI: 10.13140/RG.2.2.15605.35047. https://www.researchgate.net/publication/375597087_DIKWP_moxingzaiwudaxinggetezhizidongfenleizhongdeyingyongyanjiu_duanyucongYucong_Duan. 2023.

[4] Duan Y, Gong S. DIKWP-TRIZ method: an innovative problem-solving method that combines the DIKWP model and classic TRIZ. DOI: 10.13140/RG.2.2.12020.53120. https://www.researchgate.net/publication/375380084_DIKWP-TRIZfangfazongheDIKWPmoxinghejingdianTRIZdechuangxinwentijiejuefangfa. 2023.

[5] Duan Y. The Technological Prospects of Natural Language Programming in Large-scale AI Models: Implementation Based on DIKWP. DOI: 10.13140/RG.2.2.19207.57762. https://www.researchgate.net/publication/374585374_The_Technological_Prospects_of_Natural_Language_Programming_in_Large-scale_AI_Models_Implementation_Based_on_DIKWP_duanyucongYucong_Duan. 2023.

[6] Duan Y. The Technological Prospects of Natural Language Programming in Large-scale AI Models: Implementation Based on DIKWP. DOI: 10.13140/RG.2.2.19207.57762. https://www.researchgate.net/publication/374585374_The_Technological_Prospects_of_Natural_Language_Programming_in_Large-scale_AI_Models_Implementation_Based_on_DIKWP_duanyucongYucong_Duan. 2023.

[7] Duan Y. Exploring GPT-4, Bias, and its Association with the DIKWP Model. DOI: 10.13140/RG.2.2.11687.32161. https://www.researchgate.net/publication/374420003_tantaoGPT-4pianjianjiqiyuDIKWPmoxingdeguanlian_Exploring_GPT-4_Bias_and_its_Association_with_the_DIKWP_Model. 2023.

[8] Duan Y. DIKWP language: a semantic bridge connecting humans and AI. DOI: 10.13140/RG.2.2.16464.89602. https://www.researchgate.net/publication/374385889_DIKWP_yuyanlianjierenleiyu_AI_deyuyiqiaoliang. 2023.

[9] Duan Y. The DIKWP artificial consciousness of the DIKWP automaton method displays the corresponding processing process at the level of word and word granularity. DOI: 10.13140/RG.2.2.13773.00483. https://www.researchgate.net/publication/374267176_DIKWP_rengongyishide_DIKWP_zidongjifangshiyiziciliducengjizhanxianduiyingdechuliguocheng. 2023.

[10] Duan Y. Implementation and Application of Artificial wisdom in DIKWP Model: Exploring a Deep Framework from Data to Decision Making. DOI: 10.13140/RG.2.2.33276.51847. https://www.researchgate.net/publication/374266065_rengongzhinengzai_DIKWP_moxingzhongdeshixianyuyingyongtansuocongshujudaojuecedeshendukuangjia_duanyucongYucong_Duan. 2023.

Data can be regarded as a concrete manifestation of the same semantics in our cognition. Often, Data represents the semantic confirmation of the existence of a specific fact or observation, and is recognised as the same object or concept by corresponding to some of the same semantic correspondences contained in the existential nature of the cognitive subject's pre-existing cognitive objects. When dealing with data, we often seek and extract the particular identical semantics that labels that data, and then unify them as an identical concept based on the corresponding identical semantics. For example, when we see a flock of sheep, although each sheep may be slightly different in terms of size, colour, gender, etc., we will classify them into the concept of "sheep" because they share our semantic understanding of the concept of "sheep". The same semantics can be specific, for example, when identifying an arm, we can confirm that a silicone arm is an arm based on the same semantics as a human arm, such as the same number of fingers, the same colour, the same arm shape, etc., or we can determine that the silicone arm is not an arm because it doesn't have the same semantics as a real arm, which is defined by the definition of "can be rotated". It is also possible to determine that the silicone arm is not an arm because it does not have the same semantics as a real arm, such as "rotatable".

Information, on the other hand, corresponds to the expression of different semantics in cognition. Typically, Information refers to the creation of new semantic associations by linking cognitive DIKWP objects with data, information, knowledge, wisdom, or purposes already cognised by the cognising subject through a specific purpose. When processing information, we identify the differences in the DIKWP objects they are cognised with, corresponding to different semantics, and classify the information according to the input data, information, knowledge, wisdom or purpose. For example, in a car park, although all cars can be classified under the notion of 'car', each car's parking location, time of parking, wear and tear, owner, functionality, payment history and experience all represent different semantics in the information. The different semantics of the information are often present in the cognition of the cognitive subject and are often not explicitly expressed. For example, a depressed person may use the term "depressed" to express the decline of his current mood relative to his previous mood, but this "depressed" is not the same as the corresponding information because its contrasting state is not the same as the corresponding information. However, the corresponding information cannot be objectively perceived by the listener because the contrasting state is not known to the listener, and thus becomes the patient's own subjective cognitive information.

Knowledge corresponds to the complete semantics in cognition. Knowledge is the understanding and explanation of the world acquired through observation and learning. In processing knowledge, we abstract at least one concept or schema that corresponds to a complete semantics through observation and learning. For example, we learn that all swans are white through observation, which is a complete knowledge of the concept "all swans are white" that we have gathered through a large amount of information.

Wisdom corresponds to information in the perspective of ethics, social morality, human nature, etc., a kind of extreme values from the culture, human social groups relative to the current era fixed or individual cognitive values. When dealing with Wisdom, we integrate this data, information, knowledge, and wisdom and use them to guide decision-making. For example, when faced with a decision-making problem, we integrate various perspectives such as ethics, morality, and feasibility, not just technology or efficiency.

Purpose can be viewed as a dichotomy (input, output), where both input and output are elements of data, information, knowledge, wisdom, or purpose. Purpose represents our understanding of a phenomenon or problem (input) and the goal we wish to achieve by processing and solving that phenomenon or problem (output). When processing purposes, the AI system processes the inputs according to its predefined goals (outputs), and gradually brings the outputs closer to the predefined goals by learning and adapting.

Yucong Duan, male, currently serves as a member of the Academic Committee of the School  of Computer Science and Technology at Hainan University. He is a professor and doctoral supervisor and is one of the first batch of talents selected into the South China Sea Masters Program of Hainan Province and the leading talents in Hainan Province. He graduated from the Software Research Institute of the Chinese Academy of Sciences in 2006, and has successively worked and visited Tsinghua University, Capital Medical University, POSCO University of Technology in South Korea, National Academy of Sciences of France, Charles University in Prague, Czech Republic, Milan Bicka University in Italy, Missouri State University in the United States, etc. He is currently a member of the Academic Committee of the School of Computer Science and Technology at Hainan University and he is the leader of the DIKWP (Data, Information, Knowledge, Wisdom, Purpose) Innovation Team at Hainan University, Distinguished Researcher at Chongqing Police College, Leader of Hainan Provincial Committee's "Double Hundred Talent" Team, Vice President of Hainan Invention Association, Vice President of Hainan Intellectual Property Association, Vice President of Hainan Low Carbon Economy Development Promotion Association, Vice President of Hainan Agricultural Products Processing Enterprises Association, Director of Network Security and Informatization Association of Hainan Province, Director of Artificial Intelligence Society of Hainan Province, Visiting Fellow, Central Michigan University, Member of the Doctoral Steering Committee of the University of Modena. Since being introduced to Hainan University as a D-class talent in 2012, He has published over 260 papers, included more than 120 SCI citations, and 11 ESI citations, with a citation count of over 4300. He has designed 241 serialized Chinese national and international invention patents (including 15 PCT invention patents) for multiple industries and fields and has been granted 85 Chinese national and international invention patents as the first inventor. Received the third prize for Wu Wenjun's artificial intelligence technology invention in 2020; In 2021, as the Chairman of the Program Committee, independently initiated the first International Conference on Data, Information, Knowledge and Wisdom - IEEE DIKW 2021; Served as the Chairman of the IEEE DIKW 2022 Conference Steering Committee in 2022; Served as the Chairman of the IEEE DIKW 2023 Conference in 2023. He was named the most beautiful technology worker in Hainan Province in 2022 (and was promoted nationwide); In 2022 and 2023, he was consecutively selected for the "Lifetime Scientific Influence Ranking" of the top 2% of global scientists released by Stanford University in the United States. Participated in the development of 2 international standards for IEEE financial knowledge graph and 4 industry knowledge graph standards. Initiated and co hosted the first International Congress on Artificial Consciousness (AC2023) in 2023.

Prof. Yucong Duan

DIKWP-AC Artificial Consciousness Laboratory

AGI-AIGC-GPT Evaluation DIKWP (Global) Laboratory

DIKWP research group, Hainan University

duanyucong@hotmail.com