Ethical issues concern the future technological direction of artificial intelligence, rule-making, acceptance, etc., and are the primary issues that need to be solved in the development of generative artificial intelligence. The generative artificial intelligence represented has strong language understanding and text generation capabilities, but it only absorbs digital code integration in the virtual world, and still has a long distance to interact with the objective world. We should be wary of its ethical dilemma that shakes the status of human subjects, clarify the humanistic stance in generative artificial intelligence applications, construct ethical rules for generative artificial intelligence governance, start from the organizational mechanism of artificial intelligence ethical governance and the ethical normative mechanism of artificial intelligence to be a human being. The society seeks proper ethical solutions.

At present, the international organizational level mainly focuses on ethical advocacy norms, aiming to build consensus on artificial intelligence ethics and have strong declaring significance. With the breakthrough of leading generative artificial intelligence technology, the United States attaches great importance to its ethical issues beyond the past. Several documents propose to ensure the ethicality, trustworthiness of artificial intelligence and the personal information, privacy, fairness and freedom of citizens. and other basic rights protection and expression in the formulation of federal policy and legal frameworks, an ethical governance model that advocates parallel to regulation is being formed. In generative artificial intelligence supervision, the UK focuses on maintaining market order and protecting the legitimate rights and interests of related consumers, and emphasizes the maintenance of basic ethical order and the protection of basic rights. my country is in the early stages of building artificial intelligence ethical norms, and is exploring a balanced solution for safe development and collaborative participation. The Interim Measures for the Management of Generative Artificial Intelligence Services" and the "Regulations on the Promotion of Artificial Intelligence Industry in Shenzhen Special Economic Zone" and other legislation put forward clear requirements for artificial intelligence to respect social morality and ethics, adhere to the core socialist values, prevent discrimination, and respect the legitimate rights and interests of others. , in the future, it will be improved in terms of organizational structure, programming, standard unification and responsibility assumption.

Multiple ethical dilemmas in generative artificial intelligence applications

First, weaken the value of human subjects. Human beings are given some inherent value or value priority, and the ethical order revolves around human beings, and the ethical construction is centered on "humans shape the world". However, in a society where human-computer coexistence is becoming an implementer with a certain ability to act independently, and artificial intelligence is very easy to analyze, identify and shape human concepts and cognitive systems through the output of conclusions, triggering "Artificial intelligence shapes humans" As a result, human subjectivity will suffer setbacks. Furthermore, due to the differences in individual abilities, the emergence of the "artificial intelligence gap" may intensify the internalization of the community, and vulnerable groups will face elimination or become victims of algorithmic bullying, shaking the humanistic stance in the general sense.

Second, aggravate algorithmic bias and discrimination. First, as big data isomorphic to human society, it contains deep-rooted prejudice. Artificial intelligence can learn stereotyped associations from data, and it will also inherit bias from training data sets, causing some people to suffer unfair treatment. Second, generative artificial intelligence can obtain and analyze human responses during human-computer interaction, feedback self-reinforcement learning, and improve accuracy. If the user disseminates false or false data, or the reply itself contains personal value factors such as bias and discrimination, harmful output will be generated.

Third, over-reliance on mimicry environment output results. Generative artificial intelligence makes people accustomed to relying on their output to recognize things around them and to trust their results. At this time, experience is transmitted instead of practical experience, and the mimic environment becomes an intermediary existence between people and the world. Therefore, what the machine ultimately presents to the public is not entirely objective facts in the real world, but it has the possibility of producing a mimetic situation of "symbolic reality". After users receive mimicry facts and output them through mass communication channels, they will become universal social reality, becoming the standard for human actions and the basis for understanding the world.

Fourth, it is difficult to align value. If artificial intelligence cannot understand human intentions, when setting multiple goals for them, machines may make wrong choices and the output may not match human intentions. If the human-machine value cannot be aligned, the machine will choose to perform goals that humans do not need. If we cannot stick to the human value position, we may lose control over it, making machine applications ultimately above humans.

Humanistic ethical position of generative artificial intelligence applications

Focusing on the relationship between human-computer coexistence, we urgently need to uphold a humanistic standpoint to position the relative position of the two in the social genealogy. First, clarify the priority of humans over machines, and also take into account the advantages of human-computer interaction. Second, clarify the subordinate attributes and secondary nature of machines, and always regard artificial intelligence as a tool to achieve human goals. Its task is to assist rather than replace humans, and it cannot manipulate and dominate humans and make humans alienated into tools. Third, whether it is traditional tools or artificial intelligence, they are valuable social practice objects or social practice activities created by humans. They must follow the ethical position of "people are the purpose" and cannot change their "human nature" characteristics.

The author believes that based on the humanistic ethical standpoint, we should adhere to the principles of welfare, dignity and responsibility. The principle of welfare is the fundamental goal of people-oriented, the principle of dignity is the premise and inevitable requirement for realizing people-oriented, and the principle of responsibility is an important guarantee for realizing people-oriented. The above principles aim to ensure that the development and application of generative artificial intelligence have a positive ethical impact on human society.

Humanistic ethical governance mechanism for generative artificial intelligence applications

Laws are lagging, and technological innovation must take ethics first. When the future risks of artificial intelligence are incompletely cognitive, risk assessment and cost-benefit analysis are incompletely effective, my country should uphold a humanistic standpoint and explore the way to be good for science and technology that conforms to China's reality.

First, build a human-oriented artificial intelligence ethical governance organization. my country's artificial intelligence ethical governance organization should be based on a humanistic standpoint, attach importance to the ethical risks and impacts of generative artificial intelligence references in normalized and scenario-based assessment, and formulate ethical security standards, technical specifications, risk prevention and control and response strategies. Ethical institutions should play a coordinated role, coordinate with each other, communicate information with clear division of labor, and build an organizational framework for collaborative governance of ethical supervision. We should adhere to the principle of prevention, intervene in a timely manner on the ethical risks of generative artificial intelligence, plan its development direction and development strategy, formulate safety standards and specifications, and improve our ability to manage risks. Ethical institutions should also pay attention to how citizens’ basic rights are effectively protected in generative artificial intelligence applications.

Second, improve the human-oriented artificial intelligence ethical normative mechanism. First, clarify the fair mechanism for the application of technology. Pay attention to discriminatory prejudice arising from generative artificial intelligence applications, etc., and improve the fair guarantee mechanism. Solve design ethics issues, expand the evaluation standards for technical system quality, and develop algorithms that meet the value tendencies of the application. Form a standardized system for the authenticity of generative artificial intelligence applications, and promote the interpretation of the process of generative artificial intelligence application. The second is to improve the early warning mechanism of ethical risks. Strengthen the security guarantee of artificial intelligence technology, establish intelligent monitoring, early warning and control mechanisms for ethical risks, and improve the security transparency of generative artificial intelligence. The third is to make up for the accountability mechanism for ethical review. The ethical responsibility of the question and answer and information output by generative artificial intelligence should ultimately point to the subjects that assume actual roles in each link. Generative artificial intelligence is still a "dehumanized" fitting tool, based on the analysis of parameters and data. It does not have subjective consciousness and emotions, and strictly speaking, it does not have ethical awareness and responsibility. Therefore, at this stage, we should clarify the ethical responsibilities of all parties such as providers, users, designers, etc. based on a humanistic standpoint, implement the ethical responsibility assumption mechanism, and improve the responsibility system. A mechanism should also be established to monitor the entire life cycle of a generative artificial intelligence system, monitor and audit algorithms, data and system operation processes, and pay attention to the realization of traceability and auditability of generative artificial intelligence applications. (Professor of Feng Zixuan, Southwest University of Political Science and Law)

(The original article was published in Journal of East China University of Political Science and Law, 2024 Issue 1)