by Rumesh Kumar
We live in an era of the Knowledge Age. An age where organizations and humans are increasingly empowered by knowledge. In this era, knowledge management has the potential to process knowledge and turn it into expertise needed to drive organizational performance.
What is Knowledge Management?
Knowledge Management involves a range of activities such as identifying, creating, representing, distributing and enabling the adoption and reuse of knowledge within an organization. Sensing the need for new expertise to cater for specific market requirements is an example where knowledge management is required. This is being done primarily by knowledge workers.
Who are Knowledge Workers?
Knowledge workers leverage knowledge to generate value. For example, designers, engineers, and software programmers engage in critical thinking and creative thinking to improve performance. Such people are usually associated with the development of new products or services, problem-solving, or creating strategies and actions. Collectively knowledge workers contribute significantly towards knowledge management in organizations.
What is ChatGPT?
Owing to its iterative learning capability, ChatGPT learns from data and responses from a very wide source to refine the information provided over time and hence develop the intelligence to contextualise information. By doing so it gradually evolves into a good knowledge source for people who need to understand issues better.
The big question
The advent of Large Language Models (LLMs) like ChatGPT has sparked debates about their potential to automate knowledge work and render knowledge workers obsolete. Will ChatGPT be better suited to manage knowledge in organizations compared to knowledge workers in the near future? Very unlikely because of limitations inherent within ChatGPT that require the involvement of knowledge workers to address.
Limitations of ChatGPT
ChatGPT is well suited to provide quick and convenient access to knowledge that is gained from its huge database. However, the use of ChatGPT for knowledge management presents challenges. They include issues pertaining to potential biases, reliability concerns, and the lack of transparency in outputs. These challenges impact the applicability and transferability of such knowledge within a specific organizational setting.
For example, ChatGPT may recommend technical work be done autonomously and quickly in an evolving business environment. However this may not be appropriate in a bureaucratic organization. ChatGPT is a machine learning model that is not capable of independently managing or organizing knowledge within a unique organization setting. It can only generate text based on patterns and relationships it has learned from data it has been trained on. It needs data has to be provided by knowledge workers who have a deeper appreciation of the cultural limitations and realities on the ground.
Involvement of knowledge workers in developing ChatGPT
It is unlikely that ChatGPT will be able to manage knowledge in an organization without the involvement of knowledge workers. They will be needed to develop algorithms that will be used by ChatGPT. Relying on ChatGPT on its own to manage knowledge is risky as it is important to have a well-rounded knowledge management strategy that designed and continued reviewed by knowledge workers.
Knowledge workers will need to keep their capabilities constantly updated in the world of KM in order to leverage ChatGPT knowledge in their organizations accurately. This requires a strong KM strategy in place, and qualified KM workers. They are more familiar with unique requirements that evolve both within the organization and in the business environment the organization functions.
Knowledge workers are required to play a critical role in assessing the recommendations made by ChatGPT with regard to applicability and transferability of knowledge. In addition, they are best positioned to provide critical feedback to enhance the learning mechanism within ChatGPT to be better customized for the organization that uses it to enhance organizational performance.
How ChatGPT transforms knowledge work
The extent to which knowledge workers may be displaced will depend on their familiarity with the concept of knowledge management. More specifically how knowledge management contributes to organizational learning. By this realization, they will be able to integrate their expertise to leverage on the benefits derived from the adoption of Artificial Intelligence such as ChatGPT.
ChatGPT may be used as a starting point for organizations to explore the complex terrain of business. However, they will need to engage knowledge workers for their expertise to establish the relevance, suitability and appropriateness of the recommendations offered by ChatGPT. A positive outcome would be the development of a customised development of knowledge base that is iteratively developed and included within the machine learning mechanism to deliver better results.
In summary ChatGPT will not replace knowledge workers provided knowledge workers actively contribute their expertise towards developing knowledge management for enhancing organizational learning. To do so, knowledge workers need to develop the right attitude towards learning, unlearning and relearning and acquire skills that contribute towards effective knowledge management.
Rumesh Kumar is a Certified Professional Trainer; Certified Knowledge Manager; Certified Project Management Professional (PMP); ScrumStudy Certified Trainer; and Certified Tetramap facilitator.
Rumesh specializes in the areas of project management, knowledge management as well as agile leadership development. In addition to being the Managing Director of Sharma Management International, he is the Senior Denison Consulting Partner for Denison Consulting USA and is an Approved Training Provider for the Project Management Institute USA as well as an Approved Training Instructor for the Knowledge Management Institute, USA.
