Society 5.0 is characterised by the merging of cyberspace and the physical space, aiming to balance economic advancement with the resolution of social problems.
The “merging” of cyberspace and the physical space is rooted in the process of applying the cyberspace to assist the linking of real-world phenomena so as to create new value.
This is achieved by gathering and processing large datasets from the physical space in order to derive models in cyberspace, summarising and presenting expert systems and knowledge that informs evidenced-based decision-making and ultimately derive value. In turn, such value may be accumulated and shared again.
In this process, artificial intelligence (AI) enables and ensures a broader array of data is collected, and gathered at a greater volume and a higher frequency than is humanly possible.
We are therefore required to reconsider two kinds of relationships: the relationship between technology and society, and the technology-mediated relationship between individuals and society, and in particular, how it is crafting our knowledge-intensive society.
Some attributes of such a knowledge-intensive society include:
Revised human-computer interactions
Traditionally, human-computer interactions facilitated the conversion of data to information to knowledge. Humans added context to data to create information and then considered patterns to create knowledge and derive insight.
In Society 5.0, this process will have much less human intervention and the final output of this conversion process will be AI-derived knowledge. With this greater opportunity to access insight, humans may now combine AI-derived knowledge with human knowledge to inform evidence-based decisions, strategies and courses of action.
Digital literacy skills
With the revised human-computer interaction and knowledge combination, the expectation is that all humans in Society 5.0 must be information literate. They need to understand the application and implications of society-wide use of data.
By clustering and combining internal knowledge with external collaboration and networking, innovation activities are enhanced.
If the aim of Society 5.0 is that services for society are to be available to all for the benefit of society at large, then we must also consider cultivating digital literacy among information users.
Digital literacy as a knowledge competency is key as we move towards a truly people-centric society, and AI applications and evolution must be accompanied by efforts to raise the information literacy of each and every citizen.
Optimised knowledge creation
Knowledge generation strategies combine organisational activities and management approaches in order to generate new knowledge and increase competitiveness. This requires the creation of an information integration architecture that enables data to be collected, synthesised, and then integrated with heterogeneous information.
Technology will play a vital role in building such an information integration architecture, taking cognisance of new human-computer knowledge exchanges in facilitating knowledge-creation processes.
Apart from presenting insight from structured and unstructured datasets, conversational interfaces such as chatbots may optimise and integrate a myriad of knowledge sources and resources, while creating and storing new knowledge.
Innovation enablement
New knowledge is created when data and information are deployed inter-connectedly, by seeing the data and information in context. In a knowledge-intensive society, such new knowledge may drive new business models, new revenue streams, generate new industries and transform industrial structures.
By clustering and combining internal knowledge with external collaboration and networking, innovation activities are enhanced − for smart cities, for example.
By considering the attributes of such a knowledge-intensive society, it seems useful to consider the roles of knowledge management (KM) and AI through the lens of business capabilities and opportunities, rather than solely from a technology perspective.
Broadly speaking, AI can support three important business requirements: business process automation, engagement with customers and employees, and deriving insight through data analysis.
Typical knowledge management capabilities in an organisation include knowledge creation and acquisition, knowledge sharing, knowledge transfer and knowledge application. The AI4KM grid illustrates the potential of an AI-KM integrated organisational capability.
Through the application of the AI4KM grid, information-intensive domains, such as healthcare, financial services, marketing, professional services, education, etc, in general and organisations specifically, may derive invaluable insights.
The oversight of extracting data from large datasets, repeatedly answering the same questions, and routine transactions, may be facilitated by AI, freeing up employees to be more productive and creative.
Establishing an AI-KM integrated organisational capability augments human activity as it performs tasks (without eclipsing entire vocations) or it contributes to tasks that humans did not deliver in the first place, such as big data analysis.
In Society 5.0, an AI-KM integrated organisational capability may introduce greater productivity, work satisfaction, innovation and growth opportunities – to the benefit of all.
Share