A knowledge retention project aims to prevent undesirable loss of professional knowledge, which is the key to the organization's success.
Generative Artificial Intelligence is a sub-field within the world of Artificial Intelligence, and like knowledge retention, it focuses on processing and creating textual, visual, and symbolic content.
In the video "Leveraging the value creation of Tacit Knowledge using Generative AI", Dr. Moria Levy addresses the question of the connection between knowledge retention and Generative AI, and how the use of AI tools can assist in better and faster preservation and accessibility of the following types of knowledge:
Knowledge that resides above the surface (Explicit Knowledge)
Knowledge that resides below the surface (Shallow Knowledge)
Deep Knowledge
Dr. Levy argues that the use of Generative AI tools allows the discovery and sharing of existing knowledge, both tacit and explicit and that these tools have the potential to widely influence the development of new (artificial) professional knowledge, based on existing knowledge.
A knowledge retention project is carried out according to an orderly and structured methodology, allowing the extraction of knowledge through human means. Today, it is possible and advisable to use Generative AI tools in a knowledge retention project, due to the following prominent advantages:
Resource-saving and process optimization, for example:
Building infrastructure for a knowledge retention project work plan (identifying experts, questionnaires, etc.).
Using tools for transcribing and summarizing meetings.
Generating a list of action items deriving from meetings. .
Coverage of the following topics, for example:
Basic learning of the professional field in which the organization and employees operate.
Preparing an initial topics outline for meeting.
Formulating relevant questions related to the areas of activity, typical challenges of the organization, and an employee in a specific role, ina specific time (corona, war), and circumstances that might have affected work routine.
Creating spectacular products, such as presentations, videos, tables, and information sheets.
Deepening and reaching tacit knowledge - exposing and discovering tacit knowledge, for example:
What are typical exceptional cases in the relevant professional field?
Surfacing the expert’s deeper memory sometimes knowledge that wasn't even known to exist.
Generating insights about the reasons that led to a certain decision.
Assistance in critical thinking and creating new knowledge - for example: Collecting relevant documents written by the expert, using Generative AI tools in creating synthesis and summary, , and for asking some questions, such as:
Are there additional courses of action?
Should we act differently in the future? Under what conditions? How?
It is recommended to get familiarized with and experiment with various artificial intelligence tools that can be helpful in knowledge retention. The Futurepedia website, for example, is a repository of AI tools by categories, daily updated. browsing through it can bring up ideas for additional uses of innovative tools in knowledge retention processes.
It's important to remember that the use of Generative AI tools requires human creative and critical thinking, from the very beginning of the process and writing the first prompt, throughout the whole process, and at the end of the process, for smart utilization of the advantages of both human and machine (Man-Machine Augmentation).
The use of tools entails human responsibility in all matters related to examining the tool's suitability for the needs, examining the relevance and reliability of the information received, and having the final say in all matters related to the use of the products.
The responsibility for a knowledge retention product, including new knowledge that is developed as a result of the involvement of the artificial tool, is (still), fortunately, in human hands.
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