The Importance of Tacit Knowledge in AI and Expertise

The Importance of Tacit Knowledge in AI and Expertise

In the ever-evolving field of artificial intelligence (AI), there is a constant need to stay updated and informed about the latest advancements. To become smarter about modern AI, it is crucial to rely on curated resources that have had a significant impact on the field. This curated list of papers, blog posts, courses, and guides, known as the "AI Canon," provides valuable insights and knowledge that can shape our understanding of AI (source: AI Canon | Andreessen Horowitz).

When discussing the acquisition of knowledge, one concept that stands out is tacit knowledge. Tacit knowledge refers to knowledge that cannot be easily captured through words alone. It encompasses the embodied feelings and experiences necessary to successfully perform a task or skill. Instead of relying solely on deliberate practice, which involves following a set of predefined procedures, tacit knowledge emphasizes the importance of emulation, action, and apprenticeship (source: "The Knowledge-Creating Company" by Ikujiro Nonaka).

Learning complicated judgments and making instantaneous decisions that balance multiple considerations requires the acquisition of tacit knowledge. This type of knowledge is challenging to learn through explanation alone. It often involves understanding nuances, exceptions, and context-specific factors that cannot be explicitly taught. Attempting to encode all possible branches and nuances into an expert system has proven to be extremely difficult, limiting the ability to build expertise and hindering creative problem-solving (source: Tacit Knowledge is More Important Than Deliberate Practice).

The belief in the existence of tacit knowledge encourages a shift in perspective. Instead of hoping for a breakthrough that makes tacit knowledge explicit, it is more useful to focus on ways to gain tacit knowledge directly. By immersing oneself in a field and learning from masters through emulation, feedback, and osmosis, individuals can develop tacit knowledge and expertise. This approach is different from deliberate practice, which is more suitable for domains with well-established pedagogy, such as music, math, and chess. Tacit knowledge acquisition involves finding a master, working under their guidance, and internalizing the principles behind their actions (source: Tacit Knowledge is More Important Than Deliberate Practice).

In the realm of expertise, the field of Naturalistic Decision Making (NDM) plays a crucial role. NDM focuses on making the practice of acquiring tacit knowledge more effective. By exploring NDM methods and paying attention to resources that emphasize tacit knowledge, individuals can delve into the most interesting and often overlooked aspects of expertise. These methods provide valuable insights into how experts develop their skills and make informed decisions (source: Tacit Knowledge is More Important Than Deliberate Practice).