“AI一作”会为我们带来什么?What the ＂AI masterpiece＂ Will Bring Us?

今日主题:“AI一作”会为我们带来什么？

Today’s Topic:what the "AI masterpiece" will bring us?

过去知识生产是靠个人的探索或人类之间的合作进行，而“AI 一作”是人和人工智能合作，甚至人工智能发挥了主要作用，这对知识生产将产生什么影响？

In the past, knowledge production relied on individual exploration or cooperation between humans, while "AI first work" was a collaboration between humans and artificial intelligence, and even artificial intelligence played a major role. What impact will this have on knowledge production?

AI 一作之后，人类与 AI 形成了一种“分治”关系——AI 负责探索可能性如快速生成假设、挖掘关联，人类则负责做出判断如验证真伪、赋予意义、承担认知责任，知识生产的核心瓶颈从“如何生产更多知识”转向了“如何筛选和信任知识”。

After the emergence of AI, a "divide and conquer" relationship has formed between humans and AI - AI is responsible for exploring possibilities such as quickly generating hypotheses and mining correlations, while humans are responsible for making judgments such as verifying authenticity, assigning meaning, and assuming cognitive responsibility. 

The core bottleneck of knowledge production has shifted from "how to produce more knowledge" to "how to screen and trust knowledge".

AI 打破了传统知识精英对知识获取和生产的垄断，普通人可以更快学习、更好地探究问题，这是知识民主化的巨大进步。但“知识的霸权”有可能很快转换成“AI 霸权”。

传统的学术堡垒看似坍塌，但也许只是学术权力的转移。谁控制着最强大的 AI 模型，谁拥有训练数据能力，谁决定 AI 的价值观和知识边界，谁就是“AI 领主”。

这些“AI 领主”将拥有前所未有的、塑造集体认知的权力。他们可以不费吹灰之力地定义“主流知识”、边缘化异见，甚至操纵公众认知。相比过去分散的、可被辩论的学术精英，这种霸权可能更集中、更隐蔽、更难反抗。

The traditional academic fortress may seem to have collapsed, but perhaps it is just a transfer of academic power.

Whoever controls the most powerful AI models, possesses the ability to train data, determines the values and knowledge boundaries of AI, and is the 'AI Lord'.

These 'AI lords' will have unprecedented power to shape collective cognition. They can effortlessly define 'mainstream knowledge', marginalize dissent, and even manipulate public perception. 

Compared to the dispersed and debatable academic elites of the past, this hegemony may be more centralized, covert, and difficult to resist.

未来大学里，教授和学生最应该培养的、AI 最难替代的“核心能力”是什么？ 

What are the most important "core competencies" that professors and students should cultivate in future universities that are most difficult for AI to replace?

人机协同商数（Collaboration with Ai Quotient），简称“C 商（CQ）”，与智商（IQ）和情商（EQ）并列，共同构成人工智能时代一个人的核心素养。过去我们描述一个人“会用 AI”，这太笼统了。

而 C 商将这种模糊能力转换成为可量化、可测量、可培养的核心素养。未来，一个人可能不再因“背不出知识点”而自卑，而会因“能与 AI 高效协作解决复杂问题”而自豪。 

Collaboration with Ai Quotient, also known as C Quotient, is a core competency of an individual in the era of artificial intelligence, alongside IQ and EQ.

In the past, we described a person as' capable of using AI ', which was too general.

And C business transforms this fuzzy ability into quantifiable, measurable, and cultivable core competencies. 

In the future, a person may no longer feel insecure about not being able to memorize knowledge points, but rather proud of being able to efficiently collaborate with AI to solve complex problems.

“高 C 商”将成为未来人最重要的能力要素之一。大学被赋予了新的使命，大学不再垄断知识，而是成为培养“高 C 商”人才的核心场所。 

High C-level business will become one of the most important skill elements for future individuals.

Universities have been given a new mission, no longer monopolizing knowledge, but becoming the core venue for cultivating "high C business" talents.

当知识获取和常规认知任务很多被 AI 替代后，一个人与 AI 协同、互补、共进的能力，将成为衡量其学习、工作能力和生产效能的关键能力。

When knowledge acquisition and conventional cognitive tasks are largely replaced by AI, a person's ability to collaborate, complement, and progress with AI will become a key ability to measure their learning, work, and productivity.

C 商不仅仅是“会用 AI 工具”，人机协同能力是一个综合性的能力组合，至少包含以下几个层面，而这些恰恰可以成为未来大学入学、毕业乃至终身评价的重要维度：

C Business is not just about "knowing how to use AI tools", human-machine collaboration capability is a comprehensive combination of abilities, including at least the following levels, which can become important dimensions for future university admission, graduation, and even lifelong evaluation:

一是提问与任务拆解能力，核心是将模糊的、开放性的现实问题或好奇心，转化为 AI 可以理解、分步处理的具体指令或任务链；

二是信息鉴别与批判性整合能力，核心是对 AI 生成的信息如文本、数据、代码等，进行事实核查、逻辑检验、偏见识别和情境化评估，并能将碎片化的 AI 输出整合成连贯、有洞见的结论；

One is the ability to ask questions and break down tasks, with the core being to transform vague and open-ended real-world problems or curiosity into specific instructions or task chains that AI can understand and process step by step;

The second is the ability to identify and critically integrate information, with the core being the ability to conduct fact checking, logical verification, bias recognition, and situational evaluation of AI generated information such as text, data, code, etc., and to integrate fragmented AI outputs into coherent and insightful conclusions;

三是结果诠释与意义赋予能力，核心是 AI 能输出“是什么”，但难以理解“这意味着什么”，人类需要将冰冷的计算结果， 置于更广阔的社会、伦理、历史或人性语境中加以诠释；

四是认知责任与伦理判断能力，核心是明确知道何时、为何，以及以何种方式对 AI 辅助的产出承担最终责任，并能识别和规避协同中的伦理风险； 

The third is the ability to interpret results and assign meaning. The core is that AI can output "what it is," but it is difficult to understand "what this means."

Humans need to interpret cold computational results in a broader social, ethical, historical, or human context;

The fourth is cognitive responsibility and ethical judgment ability.

The core is to clearly know when, why, and in what way to take ultimate responsibility for AI assisted output, and to be able to identify and avoid ethical risks in collaboration;

五是自我迭代与元认知能力，核心是在与 AI 的协作过程中，能反思自己的认知局限、AI 的优缺点，并主动调整协作策略，实现“人机协同”的整体效能提升、人与机器的共同进化。 

The fifth is self iteration and metacognitive ability. The core is the ability to reflect on one's cognitive limitations, the strengths and weaknesses of AI, and actively adjust collaboration strategies in the process of collaborating with AI, achieving overall efficiency improvement of "human-machine collaboration" and co evolution of humans and machines.

愿我们每一个人都能有高cq高iq，高eq...

May each of us have high CQ, high IQ, high EQ