Discussion about the replacement of intellectual human labour by ``thinking machines'' has been present in the public and expert discourse since the creation of Artificial Intelligence (AI) as an idea and terminology since the middle of the twentieth century. Until recently, it was more of a hypothetical concern. However, in recent years, with the rise of Generative AI, especially Large Language Models (LLM), and particularly with the widespread popularity of the ChatGPT model, that concern became practical. Many domains of human intellectual labour have to adapt to the new AI tools that give humans new functionality and opportunity, but also question the viability and necessity of some human work that used to be considered intellectual yet has now become an easily automatable commodity. Education, unexpectedly, has now become burdened by an especially crucial role of charting long-range strategies for discovering viable human skills that would guarantee their place in the world of the ubiquitous use of AI in the intellectual sphere. We highlight weaknesses of the current AI and, especially, of its LLM-based core, show that root causes of LLMs' weaknesses are unfixable by the current technologies, and propose directions in the constructivist paradigm for the changes in Education that ensure long-term advantages of humans over AI tools.
翻译:自二十世纪中叶人工智能(AI)作为概念和术语诞生以来,关于“思维机器”取代人类智力劳动的讨论一直存在于公众和专家话语中。直到最近,这更多是一种假设性担忧。然而,近年来,随着生成式人工智能的兴起,特别是大型语言模型(LLM)的发展,尤其是ChatGPT模型的广泛普及,这种担忧已变得现实。人类智力劳动的许多领域必须适应新的人工智能工具,这些工具为人类提供了新功能和机遇,但也质疑了某些曾被视作智力性、如今却易自动化的人类工作的可行性和必要性。出乎意料的是,教育现在承担起一项尤为关键的角色:制定长期战略,以发掘能够确保人类在智力领域普遍使用AI的世界中立足的可行技能。我们指出了当前人工智能(尤其是其基于LLM的核心)的弱点,表明LLM弱点的根本原因无法通过现有技术修复,并在建构主义范式下提出了教育变革的方向,以确保人类相对于AI工具的长期优势。