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)

The Impact of Artificial Consciousness Technology on Future Civilizations

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)

Catalogue

Abstract

1 Introduction

2 Changes in scientific research paradigm under Brain-Machine Interface technology

3 Philosophical issues of continuity of human consciousness

摘要

1 引言

2 脑机接口技术下的科学研究范式变化

3 人类意识连续性的哲学问题

Reference

Abstract

This report discusses the impact of the development of Artificial Consciousness technology on future civilization, paying special attention to the evolution of individual consciousness and global consciousness, as well as the change of scientific research paradigm under Brain-Machine Interface technology. First of all, we review the subversive impact of the development of Brain-Machine Interface technology on scientific research and academic exchange, and then discuss the philosophical problem of the continuity of human consciousness. Then, starting from the paradox of Theseus' ship, we discuss the challenge and possible impact of Artificial Consciousness technology on individual identity and social structure. Finally, we look forward to the global consciousness network that may be brought by Artificial Consciousness technology in the future, as well as the ethical and social challenges faced in this process.

1 Introduction

The rapid development of Artificial Intelligence technology has profoundly changed our way of life and work. With the continuous progress of Artificial Intelligence, human exploration of Artificial Consciousness is also deepening. Artificial Consciousness is regarded as one of the ultimate goals in the field of Artificial Intelligence, in fact, it will now mark the peak of Artificial Intelligence technology. However, the concept of Artificial Consciousness involves not only technological breakthroughs, but also profound thinking about human cognition. This report will explore the possibility of Artificial Consciousness technology and its impact on future civilization.

2 Changes in scientific research paradigm under Brain-Machine Interface technology

The development of Brain-Machine Interface (BMI) technology has brought unprecedented new perspectives and opportunities for scientific research and academic exchanges. This technology enables scientists to study ideas and achievements directly through thinking exchange, and is no longer limited by traditional language or writing forms. The following are the subversive changes brought by Brain-Machine Interface technology to the scientific research paradigm:

Direct thinking communication: Brain-Machine Interface technology enables scientists to study ideas and achievements directly through thinking communication, which is no longer limited by language or writing form. This way of communication improves the efficiency and accuracy of academic communication.

Enhanced cognitive ability: Using Brain-Machine Interface, researchers can expand their cognitive ability and improve their ability to process information and solve problems. This will help to accelerate the process of scientific discovery and promote interdisciplinary integration and innovation.

Virtual laboratory and simulation experiment: Combined with virtual reality technology, Brain-Machine Interface technology can create a highly realistic virtual laboratory, enabling researchers to conduct experiments and explore in a completely controlled environment. At the same time, the simulation experiment can reduce the research cost and risk.

Intuitive perception of data: Brain-Machine Interface technology allows researchers to directly perceive and analyze a large number of data and reveal the relationships and patterns between data.

Personalized learning and knowledge dissemination: According to individual cognitive status and learning habits, Brain-Machine Interface technology can customize the contents and methods of learning and knowledge dissemination, and improve learning efficiency.

Expansion of public participation: Brain-Machine Interface technology enables non-professional researchers and the public to participate in scientific research more directly and promote the popularization and sharing of scientific knowledge.

In addition to the above-mentioned changes in scientific research paradigm, Brain-Machine Interface technology has also had a far-reaching impact on the methodology and ethical framework of scientific research. The following are some aspects of these impacts:

Data privacy and security: With the development of Brain-Machine Interface technology, personal thinking and cognitive data may become available. This brings new challenges to data privacy and security, and it is necessary to establish a strict legal and ethical framework to protect the security and privacy of personal data.

Thinking manipulation and ethical issues: the development of Brain-Machine Interface technology may lead to ethical issues of thinking manipulation. For example, if Brain-Machine Interface is used to modify or control individual thinking or behavior, it will involve many complex issues of individual autonomy and ethics.

Cognitive freedom and responsibility: With the development of Brain-Machine Interface technology, individual's cognitive freedom may be challenged. For example, if the Brain-Machine Interface is used to manipulate the individual's thinking or decision-making process, the individual's autonomy and responsibility may be affected, which may lead to new thinking on moral responsibility and legal responsibility.

Ethical framework of Brain-Machine Interface technology: Facing the ethical challenges that Brain-Machine Interface technology may bring, it is very important to establish an appropriate ethical framework. This framework needs to balance the driving force of scientific and technological development and respect for individual rights. The following are some suggestions for establishing an ethical framework for Brain-Machine Interface technology:

Transparency and informed consent: For the research and application of Brain-Machine Interface technology, it is necessary to ensure that participants fully understand the possible risks and potential impacts, and participate on the basis of informed consent. Transparency and informed consent are the basic principles to protect individual rights and dignity.

Data privacy and security protection: establish strict data privacy and security protection measures to ensure that personal thinking and cognitive data are not abused or leaked. This may involve the application of encryption technology, data anonymity and access control.

Autonomy and individual rights: respect individual autonomy and rights, and do not manipulate or control individual thinking and behavior without consent. Individuals should have the right to decide how to use their thinking and cognitive data, and can withdraw from the research or application of Brain-Machine Interface technology at any time.

Fairness and justice: ensure that the development and application of Brain-Machine Interface technology will not aggravate social inequality or cause unfair impact on certain groups. Measures should be taken to promote the popularization and fair acquisition of technology and avoid the abuse or discriminatory application of technology.

International cooperation and standardization: In the development and application of Brain-Machine Interface technology, strengthen international cooperation and standardization, and establish unified ethical standards and norms. This will help to promote the safety and sustainability of technology and avoid legal and ethical conflicts between different regions.

Long-term impact assessment and supervision: evaluate the long-term impact of Brain-Machine Interface technology and establish an effective supervision mechanism. Discover and solve the possible negative effects of technology in time, and ensure the sustainable development of technology in line with the overall interests of society.

To sum up, establishing the ethical framework of Brain-Machine Interface technology is a key step to protect individual rights and social stability. Only under the appropriate ethical framework can Brain-Machine Interface technology realize its potential value and make positive contributions to the development of human society.

3 Philosophical issues of continuity of human consciousness

The development of Artificial Consciousness technology has triggered philosophical thinking on the continuity of human consciousness. The continuity of human consciousness involves the relationship between individual consciousness and collective consciousness, as well as the continuation and transfer of individual consciousness. When discussing the impact of Artificial Consciousness technology on future civilization, we need to think deeply about the following philosophical issues:

The relationship between individual consciousness and collective consciousness: individual consciousness refers to everyone's unique thinking and subjective experience, while collective consciousness refers to the common thoughts and values of the whole society or group. The development of Artificial Consciousness technology may change the dynamic relationship between individual consciousness and collective consciousness, and have a far-reaching impact on the recognition and cohesion of human society.

Continuation and transfer of consciousness: Under the background of Artificial Consciousness technology, the continuity and transfer of individual consciousness will become an important issue. For example, if a person's consciousness is transferred to a machine or network, are they still regarded as the same individual? Does the continuation of consciousness depend on the physical carrier or the replication of information mode? These problems involve a profound discussion of individual identity and the essence of consciousness.

The challenge of individual identity and social structure: Artificial Consciousness technology may challenge the traditional individual identity and social structure. For example, if individual consciousness can be transferred between different physical carriers, traditional identity and sense of belonging may be affected. This may lead to the reshaping of social structure and the redefinition of power relations.

Ethical and social issues: When discussing the impact of Artificial Consciousness technology on future civilization, ethical and social issues cannot be ignored. For example, how to protect the independence and dignity of individual consciousness? How to prevent abuse and manipulation of consciousness? How to ensure that the development of Artificial Consciousness technology conforms to public interests and social values?

To sum up, the development of Artificial Consciousness technology has caused a series of profound philosophical problems, involving individual consciousness, collective consciousness, the continuation and transfer of consciousness and so on. When discussing the impact of Artificial Consciousness technology on future civilization, we need to fully consider these philosophical issues and find suitable theoretical framework and solutions.

摘要

本报告探讨了人工意识技术的发展对未来文明的影响，特别关注了个体意识与全球意识的演变，以及脑机接口技术下的科学研究范式变化。首先，我们回顾了脑机接口技术的发展对科学研究和学术交流的颠覆性影响，然后探讨了人类意识连续性的哲学问题。接着，我们从特修斯之船的悖论出发，探讨了人工意识技术对个体认同和社会结构的挑战和可能影响。最后，我们展望了未来人工意识技术可能带来的全球意识网络，以及在此过程中面临的伦理和社会挑战。

1 引言

人工智能技术的迅猛发展已经深刻改变了我们的生活和工作方式。随着人工智能的不断进步，人类对人工意识的探索也日益深入。人工意识被视为人工智能领域的终极目标之一，其实现将标志着人工智能技术的巅峰时刻。然而，人工意识的概念不仅仅涉及到技术上的突破，还涉及到对人类自身认知的深刻思考。本报告将探讨人工意识技术的可能性，以及其对未来文明的影响。

2 脑机接口技术下的科学研究范式变化

脑机接口（BMI）技术的发展为科学研究和学术交流带来了前所未有的新视角和机遇。这项技术使得科学家能够直接通过思维交流研究想法和成果，不再受限于传统的语言或书写形式。以下是脑机接口技术对科学研究范式带来的颠覆性变化：

直接的思维交流： 脑机接口技术使得科学家能够通过思维交流直接研究想法和成果，不再受限于语言或书写形式。这种交流方式提高了学术交流的效率和精确性。

增强的认知能力： 利用脑机接口，研究人员可以扩展自己的认知能力，提高处理信息和解决问题的能力。这有助于加速科学发现的过程，促进跨学科的融合和创新。

虚拟实验室和模拟实验： 结合虚拟现实技术，脑机接口技术可以创建高度逼真的虚拟实验室，使研究人员能够在完全控制的环境中进行实验和探索。同时，模拟实验可以降低研究成本和风险。

数据直觉感知： 脑机接口技术允许研究人员直接感知和解析大量数据，揭示数据之间的联系和模式。

个性化学习和知识传播： 根据个人认知状态和学习习惯，脑机接口技术可以定制化学习和知识传播的内容和方式，提高学习效率。

公众参与的扩展： 脑机接口技术使得非专业研究人员和公众能够更直接地参与科学研究，促进科学知识的普及和共享。

除了上述提到的科学研究范式的变化，脑机接口技术还对科学研究的方法论和伦理框架产生了深远影响。以下是这些影响的几个方面：

数据隐私和安全： 随着脑机接口技术的发展，个人的思维和认知数据可能会变得可获取。这带来了对数据隐私和安全的新挑战，需要建立严格的法律和伦理框架来保护个人数据的安全和隐私。

思维操纵和伦理问题： 脑机接口技术的发展可能会引发思维操纵的伦理问题。例如，如果脑机接口被用于修改或控制个体的思维或行为，将涉及到个体自主权和伦理道德的许多复杂问题。

认知自由和责任： 随着脑机接口技术的发展，个体的认知自由可能会受到挑战。例如，如果脑机接口被用于操纵个体的思维或决策过程，个体的自主性和责任可能会受到影响，从而引发对道德责任和法律责任的新思考。

脑机接口技术的伦理框架： 面对脑机接口技术可能带来的伦理挑战，建立适当的伦理框架至关重要。这个框架需要平衡科技发展的推动力和对个体权利的尊重。以下是建立脑机接口技术伦理框架的一些建议：

透明度和知情同意： 对于使用脑机接口技术的研究和应用，需要确保参与者完全了解可能涉及的风险和潜在影响，并在知情同意的基础上参与。透明度和知情同意是保护个体权利和尊严的基本原则。

数据隐私和安全保护： 建立严格的数据隐私和安全保护措施，确保个人的思维和认知数据不被滥用或泄露。这可能涉及加密技术、数据匿名化和访问控制等措施的应用。

自主权和个体权利： 尊重个体的自主权和权利，不对个体的思维和行为进行未经同意的操纵或控制。个体应有权决定其思维和认知数据的使用方式，并能够随时撤销参与脑机接口技术相关研究或应用。

公平和公正： 确保脑机接口技术的发展和应用不会加剧社会不平等或对某些群体造成不公正的影响。应该采取措施促进技术的普及和公平的获取，避免技术的滥用或歧视性的应用。

国际合作和标准化： 在脑机接口技术的发展和应用过程中，加强国际合作和标准化工作，建立统一的伦理准则和规范。这有助于促进技术的安全性和可持续性，避免不同地区之间的法律和伦理冲突。

长期影响评估和监管： 对脑机接口技术的长期影响进行评估，并建立有效的监管机制。及时发现和解决技术可能带来的负面影响，确保技术的持续发展符合社会的整体利益。

综上所述，建立脑机接口技术的伦理框架是保障个体权利和社会稳定的关键一步。只有在合适的伦理框架下，脑机接口技术才能实现其潜在的价值，并为人类社会的发展做出积极贡献。

3 人类意识连续性的哲学问题

人工意识技术的发展引发了对人类意识连续性的哲学思考。人类意识连续性涉及到个体意识与集体意识之间的关系，以及个体意识的延续和转移问题。在探讨人工意识技术对未来文明的影响时，我们需要深入思考以下哲学问题：

个体意识与集体意识的关系： 个体意识是指每个人独特的思维和主观体验，而集体意识则是指整个社会或群体的共同思想和价值观。人工意识技术的发展可能会改变个体意识与集体意识之间的动态关系，对人类社会的认同和凝聚产生深远影响。

意识的延续与转移： 在人工意识技术的背景下，个体意识的延续和转移将成为重要议题。例如，如果一个人的意识被转移到机器或网络中，他们是否仍然被视为同一个个体？意识的延续是否取决于物理载体还是信息模式的复制？这些问题涉及到对个体身份和意识本质的深刻探讨。

个体认同与社会结构的挑战： 人工意识技术可能会挑战传统的个体认同和社会结构。例如，如果个体意识可以在不同的物理载体之间转移，传统的身份和归属感可能会受到影响。这可能导致社会结构的重新塑造和权力关系的重新定义。

伦理和社会问题： 在探讨人工意识技术对未来文明的影响时，伦理和社会问题不可忽视。例如，如何保护个体意识的独立性和尊严？如何防止意识的滥用和操纵？如何确保人工意识技术的发展符合公共利益和社会价值观？

综上所述，人工意识技术的发展引发了一系列深刻的哲学问题，涉及到个体意识、集体意识、意识延续与转移等方面。在探讨人工意识技术对未来文明的影响时，我们需要充分考虑这些哲学问题，并寻找合适的理论框架和解决方案。

Reference

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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