The "Dangers" and "Opportunities" of Generative Artificial Intelligence

Recently, generative artificial intelligence has drawn close attention from the academic community. On the basis of existing models, generative artificial intelligence can continuously update its models through data training and guidance, preliminarily exhibiting human-like creativity. This powerful capacity for understanding, analysis, and synthesis not only represents a technological breakthrough but also brings a certain impact on human society. The substitution of generative artificial intelligence for repetitive and simple mental labor prompts individuals to re-examine their own knowledge structures, to find points of connection that maintain openness and flexibility, and to continuously enhance their survival capabilities and work skills, especially those abilities superior to machines. This also triggers reflections on the intrinsic value of human beings and their future direction. A comprehensive exploration and discussion of the developmental potential of generative artificial intelligence, as well as the unique value of humanity, can promote better coordinated development between humans and technology. For humanity, the emergence of generative artificial intelligence is both a "danger" and an "opportunity." It may impact people's current modes of production and life in multiple ways, while also bringing new development opportunities. We need to comprehensively assess the "dangers" and "opportunities" of generative artificial intelligence and actively explore the "best possible approach."

近期，生成式人工智能引发学界密切关注。在既有模型的基础上，生成式人工智能可以根据数据训练和引导不断更新模型，初步展现出类人的创造性。这种强大的理解分析综合能力，不仅代表着技术上的突破，更是给人类社会带来一定冲击。生成式人工智能对重复性和简单脑力劳动的替代，促使个体重新反思自身的知识结构，寻找能够保持开放性和灵活性的接洽点，不断提升自我的生存能力和工作技能，特别是提高那些优于机器的能力。这也引发了对于人的内在价值以及未来走向的思考。全面探索与讨论生成式人工智能所具有的发展潜力，以及人类的独特价值，能够促使人与技术更好地协同发展。对人类而言，生成式人工智能的出现是“危”也是“机”。它可能在多方面冲击人们当下的生产生活方式，同样也会给人们带来新的发展机遇。我们需要综合判断生成式人工智能的“危”与“机”，并积极探索“最好的可能方式”。

Challenges

挑战

The development of generative artificial intelligence, with its technological potential, will increase people's work efficiency, while also potentially causing unemployment. The replacement of human labor by new technologies or modes of production is also known as technological unemployment. With the development and application of generative artificial intelligence, more and more mental labor may be replaced, making technological unemployment unavoidable. This unemployment problem is a microcosm of the changes in modern social development. Since the First Industrial Revolution, people have been experiencing the replacement of human labor by machines, thus causing human unemployment, but through the adjustment of social structures and individual knowledge transformation, many people have been able to achieve re-employment.

生成式人工智能的发展以其技术潜力，将提高人们的工作效率，同时也可能造成失业问题。人类劳动力被新的技术或生产方式取代，亦被称为技术性失业。随着生成式人工智能的发展与应用，可能越来越多的脑力劳动将被替代，技术性失业在所难免。这种失业问题是现代社会发展变化的一个缩影。从第一次工业革命开始，人们就一直在经历着机器取代人的劳动，从而造成人类的失业这种问题，但借助社会结构的调整和个体的知识转型，不少人也能够实现再就业。

Generative artificial intelligence possesses certain learning and generation capabilities and can already replace part of human mental labor. However, as far as current generative artificial intelligence is concerned, it cannot completely replace humans. Although generative artificial intelligence already has strong data analysis capabilities, preliminarily exhibits human-like properties, and can perform certain logical analyses in problem-solving, it is still unable to handle work that requires high creativity and flexibility. Moreover, while technological development leads to the disappearance of some occupations, it often also brings new job positions, and generative artificial intelligence is no exception. Unemployed workers need to update their skills and knowledge structures according to technological development and requirements, thereby adapting to new job demands and achieving re-employment.

生成式人工智能具有一定的学习和生成能力，已能够替代人类的部分脑力劳动。不过，就目前的生成式人工智能而言，其并不能完全取代人。虽然生成式人工智能已具有很强的数据分析能力，初步具有类人的性质，并且能够在问题的解决过程中进行一定的逻辑分析，但对于具有较高创造性、灵活性的工作，生成式人工智能仍然无法胜任。并且，技术发展在导致一部分职业消失的同时，往往也会带来一些新的工作岗位，生成式人工智能也不例外。失业的劳动者需要根据技术的发展和要求，更新自身技能与知识结构，从而适应新的岗位要求，实现再就业。

Regarding the process of technology replacing humans, Bernard Stiegler argues that the process of technology replacing humans can be divided into three stages: the dispossession of human technical knowledge, the dispossession of human knowledge of life, and the dispossession of human rational knowledge. The entire dispossession process is called by Stiegler the "proletarianization" of humans. In Stiegler's view, "proletarianization" does not refer to the poverty of people's economic conditions, but rather to the "stupefaction" or "disablement" of humans caused by the "intellectualization" of technology. That is to say, technological development can not only replace the human body and substitute for human productive labor, but also, to a certain extent, provide humans with life choices—designing options for people to make value choices within them, or even replacing people in choosing how to live. Those who lose the knowledge of "know-how" are regarded as "disabled persons," because they no longer possess knowledge that can sustain themselves, and even lose the "knowledge of living" (savoir vivre). With the development of technology, humans' capacity for rational thought and logical judgment will continuously decline, becoming increasingly mediocre and flattened. The development and application of generative artificial intelligence have gradually approached the second and third stages described by Stiegler—increasingly dispossessing humans of rational knowledge, and even, to a certain extent, depriving them of rational judgment.

关于技术对人类的取代过程，斯蒂格勒（Bernard Stiegler）认为，技术对人的取代过程可以分为三个阶段：对人技艺知识的剥夺，对人生活知识的剥夺，对人理性知识的剥夺。整个剥夺过程被斯蒂格勒称为人的“无产阶级化”（proletarietization）。在斯蒂格勒看来，“无产阶级化”并非指人的经济状况的贫穷，而是指技术的“智能化”导致的人的“愚钝化”，抑或“废人”化。也就是说，技术发展不仅能够取代人类身体，代替人类的生产劳动，还能在一定程度上为人类提供生活选择——设计选项让人们在其中作出价值选择，甚至代替人们选择如何生活。那些失去知道“怎么做”（know-how）的知识的人会被视为“废人”，因为他们不再拥有可以自给自足的知识，甚至也失去了“生活的知识”（savoir vivre）。随着技术的发展，人类的理性思考能力以及逻辑判断能力会不断下降，越来越趋于平庸化、扁平化。生成式人工智能的发展与应用，对人的取代已逐渐接近斯蒂格勒描述的第二、三阶段——越发剥夺人的理性知识，甚至在一定程度上剥夺人的理性判断能力。

Generative artificial intelligence can already replace many repetitive mental tasks and simple analytical summary work, increasingly demonstrating technology's shift from replacing physical labor to deeply replacing mental labor. This poses a certain threat to many knowledge producers or mental workers. In fact, in most cases, the work people engage in is not necessarily creative. According to Thomas Kuhn's paradigm theory, even most of the time in scientific research is in the normal period, which does not require strong creativity (only during paradigm shifts is the period of stronger creativity). If this reasoning is followed, it is possible that the mental labor of most people for most of the time has the potential to be replaced by artificial intelligence. Therefore, the emergence of generative artificial intelligence may pose major challenges to human society.

生成式人工智能已能够取代很多重复性脑力劳动和简单分析综述工作，越发展现出技术由替代体力劳动逐渐深入到对脑力劳动的替代。这对于不少知识生产者或脑力劳动者都带来了一定威胁。实际上，在大多数情况下，人们所从事的并不见得都是具有创造性的工作。根据库恩的范式理论，甚至科学研究的大部分时间段都处于常规时期，这一阶段并不需要很强的创造性（只有在范式转换的时期，才是创造性较强的时期）。如果按此推论，可能多数人的多数时期的脑力劳动都有被人工智能取代的可能。所以，生成式人工智能的出现，可能对人类社会带来重大挑战。

Opportunities

机遇

Generative artificial intelligence has given rise to a sense of crisis in people, making issues such as human autonomy, the relationship between humans and others, and the relationship between humans and the world increasingly important. Generative artificial intelligence can assist humans in knowledge production and even generate new "thoughts." Facing the development of generative artificial intelligence, we need to think about what the irreplaceable value of humans is and how to adjust our own state to welcome the future intelligent era. For individuals, perhaps cultivating their own flexibility, creativity, and understanding ability will become increasingly important. The flexibility and openness that humans possess, the ability to adjust their communication styles and behavioral patterns according to specific situations, can enable us to continuously readjust our knowledge structures and learning methods according to the development of the times and the environment, to seek new opportunities, to actively seize the initiative, and to exert the advantages of subjectivity. Moreover, for work that requires comprehensive judgment and organizational communication, or work that requires displaying "personal charisma," current generative artificial intelligence is still unable to handle it. The unique appeal and affinity of humans make it difficult to replace work that requires human presence to stimulate better results. Therefore, in daily work and life, we can consciously exercise our organizational coordination skills, communication and expression skills, and emotional management abilities.

生成式人工智能催生了人们的危机意识，使人的自主性、人与他者关系、人与世界关系等问题变得越发重要。生成式人工智能可以协助人类进行知识生产，甚至能够生成新的“思想”。面对生成式人工智能的发展，我们需要去思考作为人的不可替代的价值是什么，应如何调整自身状态迎接未来的智能时代。对于个人而言，或许培养自身的灵活性、创造力和理解能力会变得越发重要。人类所具有的灵活性和开放性，能够根据特定情境调整自身的沟通方式和行为方式，可以使我们能够不断根据时代与环境的发展重新调整自身的知识结构和学习方式，探寻新的机遇，积极把握主动权，发挥主体性优势。并且，对于需要综合判断和组织沟通的工作，或者说需要展现“人格魅力”的工作，目前的生成式人工智能尚不能胜任。人所特有的感染力和亲和力，使得需要人在场才能激发出更好效果的工作或许都难以被代替。因此，在平时的工作和生活中，我们可以有意识地锻炼自身的组织协调能力、沟通表达能力以及情绪管理能力等。

Humans possess a cognition of the world and can construct stable models based on their relationship with the world. This cognitive process is a comprehensive cognition that fully mobilizes various senses and is closely related to the current scene and sensory experience. The same individual will have different cognitions in different scenes, and different individuals will have different cognitive methods and experiences in the same scene. The human individual's cognition of the world is not a conditioned reflex type of understanding, but a result based on multiple perspectives and the coordination of multiple senses. Maurice Merleau-Ponty conducted an in-depth discussion of human cognition, arguing that the form of human perception exists according to the current situation, that humans fully mobilize all bodily functions in the situational world in which they are situated, and that these are comprehensively embodied in the body. The body is an important form through which we understand the world; we can mobilize all senses and emotions through the body, forming perceptions in communication with the world. Human cognition shapes human values, which then sediment in the state of human development. This sedimentation belongs to the emotional memory and rational thinking of each individual; the current state of humans is closely related to their past state. This kind of cognition, based on emotions, non-flattened, and carrying the unique memory of the individual, is precisely what current generative artificial intelligence cannot replace. Therefore, we need to change traditional learning methods, not limited to textbook knowledge learning and test-taking ability cultivation, but should pay more attention to personal observation and experience, stimulating subjective initiative and practical rationality in this process, learning in scenes, and actively cultivating multi-perspective understanding ability and rational thinking ability.

人类有着对于世界的认知，能够根据自身与世界的关系构建稳定的模型。这个认知过程是充分调动各种感官的综合认知，与当下所处的场景及感官的体验综合密切相关。同一个体在不同场景下会有不同认知，不同个体在同一场景中的认知方式和体验也是不同的。人类个体对世界的认知不是条件反射式的认识，而是基于多个视角、多种感官协调的结果。梅洛-庞蒂（Maurice Merleau-Ponty）对人的认知进行过深入探讨，认为人的知觉形式是依据当下情境而存在的，人在所处的情境世界中充分调用所有的身体官能，并在身体中得到综合体现。身体是我们认识世界的重要形式，我们能够通过身体而调动所有感官和情绪，在与世界的交流中形成知觉。人的认知会塑造人的价值观，从而沉淀在人的发展状态中。这种沉淀属于每个个体的情感记忆以及理性思维，人的当下状态与过去状态密切相关。这种基于情绪、非扁平化、带有个体独特记忆的认知，恰恰是目前的生成式人工智能所不能替代的。所以，我们要改变传统的学习方式，不能局限于课本知识学习和答题能力培养，而应更加注重亲身观察和体验，在此过程中激发主观能动性与实践理性，在场景中学习，并主动培养多视角理解能力和理性思维能力。

Furthermore, we must maintain a love for knowledge and free exploration. In the future intelligent era, perhaps the knowledge and positions currently regarded as “practical” will be the most easily replaced. To some extent, this can also be described as a return to humanity’s natural state. We should not confine ourselves to a perspective of utility and calculability; rather, in the process of understanding learning, we should think more about the construction of knowledge and those deep-level questions of “why it arises” and “how it arises” in thinking. Free exploration of knowledge can fully mobilize the capacity for deep thinking and critical reasoning, and helps cultivate humanistic spirit and comprehensive quality.

此外，我们要保持对于知识的热爱与自由探索。在未来的智能时代，或许当下越是被视为“实用”的知识和岗位越容易被替代。在某种程度上，这也可以说是一种对人的自然本性的回归。我们不应局限于实用、可计算性的视角，而是要在理解学习的过程中，更多思考知识的建构方式和深层次思维中那些“为何产生”“如何产生”等问题。对于知识的自由探索，能够充分调动深入思考能力和批判推理能力，有助于培养人文精神和综合素质。

In summary, the development and application of generative artificial intelligence not only prompts us to change our own learning state and knowledge structure, returning to the original state of humanity, but also prompts us to change educational models and adjust social structures. Regarding the current situation, Norbert Wiener already predicted in his 1948 book *Cybernetics*: “If the Second Industrial Revolution has been completed, those with average academic ability or worse will have nothing worth selling that others will pay for.” Yuval Noah Harari also foresightedly mentioned in *Homo Deus* that in the future, both our physical labor and the vast majority of our mental labor will be replaced by artificial intelligence. The definition of the value and meaning of work in the future intelligent society will undergo great changes, requiring multidisciplinary research to jointly address. In this process, the profound modes of thinking and questioning in philosophy and ethics can better help us recognize who we truly are and how to respond to change. For philosophy and ethics to better play this role or function, they cannot be limited to thinking about the past and the present; they must face the future and possibilities, becoming a discipline of the future. “Facing the future” is not just a slogan, but an attitude capable of anticipating problems and directly solving them. Only in this way can we think comprehensively and respond quickly in possible technological development and application, fully mobilize humanity’s inherent characteristics, and promote technology to better serve humanity’s good life. This may also be the “best possible way” for the development of generative artificial intelligence for humanity. Reflecting on these issues helps us prepare and better welcome the arrival of the future intelligent era.

总之，生成式人工智能的发展与应用，不仅提示我们要改变自身学习状态和知识结构、回归人类的本然状态，更是提示我们要改变教育模式、调整社会结构。对于目前的情况，维纳（Norbert Wiener）在1948年出版的《控制论》中就有预判：“假如第二次工业革命已经完成，具有中等学术能力水平或更差一些的人将会没有任何值得别人花钱来买的可以出卖的东西了。”赫拉利（Yuval Noah Harari）在《未来简史》中也前瞻性地提到，未来我们的体力劳动以及绝大多数脑力劳动都会被人工智能替代。未来智能社会对于工作价值和意义的定义会发生很大改变，需要多学科共同研究携手应对。在此过程中，哲学和伦理学的深刻思考方式和追问方式，能够更好地让我们认清楚自己究竟是谁、如何应对变化。哲学和伦理学要想更好地发挥这种作用或功效，就不能仅局限于思考过去和当下，而是要面对未来和可能性，做未来之学。“面向未来”不仅是一句口号，更是一种能够预判问题、直面解决问题的态度。唯有如此，才能在可能的技术发展与应用中全面思考、快速反应，充分调动人类的本然特性，促使技术更好地服务于人类的美好生活。这可能也是生成式人工智能发展对于人类而言“最好的可能方式”。对于这些问题的思考，有助于我们做好准备，更好地迎接未来智能时代的到来。

Online editor: Paul

网络编辑：保罗