INSIGHTS
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Published on 11/15/2022
Last updated on 03/21/2024
The Tacit Knowledge Blog Series 5/6
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From Tacit Knowledge to Explicit Knowledge
Tribal knowledge is an alternative term widely employed in the industry to denote the tacit knowledge of some senior staff subject matter experts (SME) who have gained profound and critical expertise on some equipment or methods. It represents how people act unconsciously and intuitively and is associated with action since it reflects knowing-how more than knowing-that. The Six Sigma Business Dictionary describes tribal knowledge as "any unwritten information not commonly known by others within a company. This term is used most when referencing information that may need to be known by others to produce a quality product or service". Tacit knowledge is a subset of institutional knowledge, which comprises all documented (explicit) knowledge and undocumented (tacit) knowledge in an organization. It brings decades of hands-on experience without direct instruction, self-study, or help from others. In this sense, it belongs to the company. Still, it is subjective and stored within the heads of the experienced workforce, never transformed into the company knowledge base, and quantifiable only indirectly as a significant loss when senior workers leave or retire or are laid-off and cannot get replaced by new hires with comparable skills [2]. Tacit knowledge is a social attribute in the sense that it is not possible to capture the tacit knowledge —from workers' heads to corporate databases— without considering the social, cultural, legal, and sociological contexts of the data collection and representation.How to Capture the Tacit Knowledge of Experts
Traditionally, knowledge elicitation has been considered an extraction process to transfer knowledge from one individual to another one using, for example, internal reports or one-on-one mentoring. This approach works well when the knowledge is documented and made explicit. But when much of the knowledge individuals possess is tacit, these simple approaches do not work as expected. Not to say of the barriers and resistance of workers when asked to transfer their knowledge just before leaving the company. That happens because workers are not motivated enough to share their knowledge extra time. They want to get knowledge but not to share, perceive it as an occupational threat, or do not want to communicate their skills to others. Institutional knowledge is created by the continuous social interaction of tacit and explicit knowledge through dialogue and debate. The tacit knowledge is the industrial culture, the occupational traditions, and the cultural values of the workforce that uses, develops, administers, and operates the technology. It is unique to each organization and represents 80-90% of its knowledge. It is also very reductive to think that institutional knowledge belongs exclusively to one group of experts or to a single individual as competence, skills, expertise, or know-how. It is far better to consider tacit knowledge as the result of social accomplishments of constructing and reconstructing new expertise, promoting collaboration towards innovations, and a more robust company culture. This blog describes the two-stage process described in Tacit knowledge elicitation process for industry 4.0 through socialization and externalization using a cognitive pipeline for capturing explicit knowledge complemented by a cooperative role game to capture tacit knowledge. I will focus on problem-solving knowledge, which is about capturing the domain knowledge of workers in an industrial structure. Still, the approach can be easily extended to other working environments if a rich ontology is available.The Tacit Knowledge Elicitation Process
The knowledge elicitation process [1] consists of a set of methods to elicit the tacit knowledge of a domain expert with a mix of algorithmic techniques and a cooperative game:- A neuro-symbolic cognitive framework to automatically transform heterogeneous textual inputs and domain ontologies into a knowledge graph (KG) for explicit knowledge storage. It is a hybrid neuro-symbolic system where a neural network is focused on sub-symbolic tasks that interact with a symbolic system through a conceptual layer that bridges the gap between symbolic and subsymbolic representation with an intermediate layer for sharing knowledge structures.
- A role game model in which human (H) and virtual (V) participants with different skill levels, from experts (E) to apprentices (A), play together to refine the KG using human cognitive processing for implicit knowledge infusion.
Clearly, the role game is meant to facilitate the translation of workers' tacit knowledge (somatic tacit knowledge, relational tacit knowledge) into explicit knowledge recreating the social working environment in the organization. The human experts are the necessary society-in-the-loop wisdom agency to ensure that the societal contract is respected and allow that tacit knowledge is efficiently translated into relationships in the Operational KG.
Therefore, the knowledge engineers will double-check the practices used by the SMEs and determine which knowledgeable facts can be kept and stored in the KG and which others must be questioned and avoided because they are dangerous, unsafe, or illegal. In this way, human apprentices can eventually interact with the cognitive system without the risk of learning uncontrolled facts that may compromise their learning experience and future productivity in the organization.
The overall process for capturing tacit knowledge can be broken down into four phases: Phases I, II, and III capture tacit knowledge into a KG, while Phase IV is an operational setup-up to let the human apprentice interact with the virtual expert (the cognitive assistant). Detailed information on the approach can be found in this paper.
The Nonaka-Takeuchi Model
- Socialization (from tacit to tacit),
- Externalization (from tacit to explicit),
- Combination (from explicit to explicit),
- Internalization (from explicit to tacit).
What's next?
In the next blog, I will discuss the Ethical and Societal Implications of Tacit Knowledge.References
- Fenoglio, E., Kazim, E., Latapie, H. et al. Tacit knowledge elicitation process for industry 4.0. Discov Artif Intell 2, 6 (2022). https://doi.org/10.1007/s44163-022-00020-w
- Lartey, P. Y. , et al. Importance of Organizational Tacit Knowledge: Barriers to Knowledge Sharing. In M. Mohiuddin, M. A. Moyeen, M. S. A. Azad, & M. S. Ahmed (Eds.), Recent Advances in Knowledge Management https://doi.org/10.5772/intechopen.101997
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