Abstract
The growing numbers of unemployment raises concerns around the world. With the arrival of the Fourth Industrial Revolution (4IR) many believed that 4IR might increase the unemployment rate by replacing the current jobs with automated machines such as robots whereas some argued that 4IR might reduce the unemployment rate by creating millions of new jobs. The paper aims to share the scenario of Industry 4.0 processes that affect future talent management, in determining which jobs will be severely affected, and that will be less affected. The talent mapping is a conceptual framework of job landscapes and the following four clusters examine job characteristics: machine-centric to human-centric, routine to complex, and optimization to identity. A qualitative method was deployed to extracts primary data from educators' perspectives in developing talents required for 4IR through Education 4.0. The adoption of Education 4.0 will be advantageous for developing talent in keeping up with the progressive and demanding talents in 4IR. The proposed model defined that clusters of machine-centric are jobs performed routinely on an application basis and usually structured and do not require any compassion or emotions. While developing talents for clusters in human-centric jobs, it may be difficult to replace humans due to complexities in the decision-making process and required compassion for task completion.
Highlights
Advancement in technology has reshaped the structure of jobs affecting the workforce both positively and negatively
Previous research shows that this growing trend could reduce the unemployment rate by creating thousands or even millions of new jobs or increasing the unemployment rate by displacement of the current jobs by smart machines or robots (Balliester and Elsheikhi, 2018; Ford, 2009; Görmüş, 2019; Kergroach, 2017)
The aim of the paper is to propose a conceptual model of the job matrix of 4IR which has highlighted the nature and characteristics of a job and talent development
Summary
Advancement in technology has reshaped the structure of jobs affecting the workforce both positively and negatively. Previous research shows that this growing trend could reduce the unemployment rate by creating thousands or even millions of new jobs or increasing the unemployment rate by displacement of the current jobs by smart machines or robots (Balliester and Elsheikhi, 2018; Ford, 2009; Görmüş, 2019; Kergroach, 2017). Jobs (Ford, 2009; Görmüş, 2019; Kergroach, 2017) due to new innovation and economic growth that is supported by the advancement of technology (Ford, 2009). The economic and social factors include Telecommuting, technologically-enabled freelance and consulting services, and people becoming used to work that are more flexible leading to interdependency in regards to work relationships
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