Robot-Proof Work Capabilities

Robot-Proof Work Capabilities

Richard A. George, Marcus Bowles, Nicholas Nouri, Ria Bhargava
DOI: 10.4018/978-1-7998-6537-7.ch010
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Abstract

Jobs are changing fast as many firms automate or augment work-tasks. Constant change is the new normal as technology relentlessly infiltrates all industries and businesses. This puts pressure on employees to upskill and stay relevant. While some jobs are relatively immune from disruption, these are in the minority. Most employees will need to continually build the necessary skills and capabilities that will help them safeguard their current careers or shift to entirely new careers or industries. This chapter describes an approach to answer the following question: What are the core work capabilities that students and employees should be learning now to future-proof their careers? The authors apply a prediction of automation and augmentation to work-tasks to model the change to the future workforce and analyse the remaining work skills and abilities required in the future. These future skills and abilities are further grouped to determine 32 future-work capabilities, including 13 digital and data literacies that can be targeted by employees, firms, and governments in L&D programs.
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Methods

Our approach is split into five main parts:

  • 1)

    Simulate the impact of emerging technology on work-tasks over the next 15-years;

  • 2)

    Identify the skills, knowledge, abilities, activities and personal behaviours (called ‘attributes’ throughout this chapter) that remain important in the future of work;

  • 3)

    Derive future capabilities and literacies by manually grouping the future important work attributes into relevant human and work capabilities drawn from evidence-based research (Bowles, 2020; Bowles, Gosh & Thomas, 2020);

  • 4)

    Determine a standardised levelling of capability for all occupations and extrapolate the future development need for individual occupations;

  • 5)

    Apply the future capability framework to an organisation’s workforce or country’s census data to determine current and future state capability needs (see results section)

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