Smart technology, artificial intelligence, robotics and algorithms (STARA): Employees' perceptions and wellbeing in future workplaces

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Abstract

Futurists predict that a third of jobs that exist today could be replaced by smart technology, artificial intelligence, robotics and algorithms (STARA). Robots will handle 52% of current work tasks by 2025, almost twice as many as in 2019. Rapid changes in machines and algorithms or computer processes could create 133 million new roles in place of 75 million that will be displaced between 2019 and 2022 (World Economic Forum, The Citizen, 2018). The objective of the chapter was to present a critical review of how employees perceive technological innovations (STARA) with regard to their own jobs and careers, and their wellbeing in future workplaces. STARA awareness is a measure that encapsulates the extent to which employees feel their career could be replaced by these modes of technology. Age as a moderator of STARA also plays a role due to career development and technology expertise associated with age. STARA awareness will not only effect job outcomes, but also wellbeing outcomes. The way employees construct their identity with their career and evaluate their own career achievement can have an impression on their financial and psychological wellbeing (Mirvis & Hall, Journal of Organizational Behavior, 15(4), 237-255, 1996; Wiese, Freund, & Baltes, Journal of Vocational Behavior, 60(3), 321-335, 2002). Brougham and Haar, Journal of Management & Organization, 24(2), 239-257 (2018) state that, in their research, greater STARA awareness was negatively correlated to organisational commitment and career satisfaction, and positively correlated to turnover intentions, cynicism and depression.

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APA

Oosthuizen, R. M. (2019). Smart technology, artificial intelligence, robotics and algorithms (STARA): Employees’ perceptions and wellbeing in future workplaces. In Theory, Research and Dynamics of Career Wellbeing: Becoming Fit for the Future (pp. 17–40). Springer International Publishing. https://doi.org/10.1007/978-3-030-28180-9_2

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