Tacit Knowledge

The distinction theory between Explicit Knowledge and Tacit Knowledge was proposed by philosopher Michael Polanyi in the 1950s.

The concept of tacit knowledge was first proposed by philosopher Michael Polanyi in 1958

The concept of tacit knowledge was proposed by cognitive scientist Michael Polanyi, whose core insight is 'we can know more than we can tell'.

Tacit Knowledge is a concept proposed by philosopher Michael Polanyi, referring to knowledge that is difficult to express in words and is acquired through accumulated experience.

The concept of tacit knowledge was first proposed by Michael Polanyi in 1958

The concept of "Tacit Knowledge" was systematically elaborated by philosopher Michael Polanyi in 1966, with the core characteristic that "we can know more than we can tell."

AI programming assistants typically lack real-time security verification capabilities when recommending dependencies, which objectively expands the attack surface.

Polanyi's Paradox states that humans know far more than they can express, with explicit knowledge being easily acquired by AI while tacit knowledge remains a uniquely human advantage

硬件工程中的仪器使用（示波器、万用表等）涉及大量隐性知识（Tacit Knowledge），无法通过文字描述传递给AI

The core challenge of organizational knowledge management lies in making tacit knowledge explicit.

The concept of tacit knowledge was proposed by the philosopher Michael Polanyi and refers to knowledge that is difficult to convey fully through language and text and can only be acquired through practice and immersion in context.

In laboratory automation, tacit knowledge constitutes a core obstacle: sensors can record position, force, and images, but struggle to capture the immediate judgments chemists make based on years of experience.

Explicit rules can be reused and audited by the system, while the tacit judgments that remain with people become sharper through repeated use.

Making tacit knowledge explicit means translating intuitions that are hard to put into words into transferable, executable rules; the concept originates from Michael Polanyi's theory of tacit knowledge.

Process-obsessed people enjoy the cycle of breaking down problems, verifying hypotheses, and optimizing details, are willing to invest time that others are unwilling to invest, and accumulate a large amount of tacit knowledge through repeated trial and error.

Tacit knowledge can only be acquired through firsthand practice, repeated trial and error, and prolonged immersion, and cannot be quickly replicated by competitors through reading papers or poaching people.

In large-scale game development, the loss of tacit knowledge caused by staff turnover is often the primary cause of project delays and quality fluctuations.

Human managers accumulate tacit knowledge through long-term observation, informal communication, and empathy, whereas current AI systems can only judge based on explicit data and preset rules, and cannot capture soft information such as office politics, emotional atmosphere, and historical grudges.

"Contextual intuition" is called "tacit knowledge" in cognitive science and organizational management, namely experiential judgment that is difficult to express explicitly through words or rules yet is crucial to decision-making.

A company's tacit knowledge is scattered across emails, meeting minutes, business rule engines, and employees' minds, and is rarely fully written into databases.