Difference between revisions of "Automation and the future of work"

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(Created page with "==Description:== Growing automation adoption adds to the challenges that women face in the workplace. MGI research found that the share of women whose jobs are replaced by machines and will likely need to make job transitions due to automation is roughly the same as for men: up to one in four over the next decade may have to shift to a different occupation. Between 40 million and 160 million women globally may need to transition between occupations by 2030, often into hi...")
 
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*https://www.oecd.org/employment/Going-Digital-the-Future-of-Work-for-Women.pdf
*https://www.oecd.org/employment/Going-Digital-the-Future-of-Work-for-Women.pdf
*https://www.mckinsey.com/featured-insights/future-of-work/retraining-and-reskilling-workers-in-the-age-of-automation
*https://www.mckinsey.com/featured-insights/future-of-work/retraining-and-reskilling-workers-in-the-age-of-automation
(Jose Luis)

Revision as of 14:23, 8 December 2021

Description:

Growing automation adoption adds to the challenges that women face in the workplace. MGI research found that the share of women whose jobs are replaced by machines and will likely need to make job transitions due to automation is roughly the same as for men: up to one in four over the next decade may have to shift to a different occupation. Between 40 million and 160 million women globally may need to transition between occupations by 2030, often into higher-skill roles.

The particular challenge for women is that long-standing barriers make it harder for them to adapt to the future of work. Women and men alike need to develop (1) the skills that will be in demand; (2) the flexibility and mobility needed to negotiate labor-market transitions successfully; and (3) the access to and knowledge of technology necessary to work with automated systems, including participating in its creation. Unfortunately, women often face long-established and pervasive structural and societal barriers that could hinder them in all three of these areas.

Enablers:

  • IoT and software/hardware connectedness
  • Democratization of formal and technical education
  • Technological advancement/Moore’s Law
  • Investments in infrastructure and smart buildings
  • Interest in renewable energy/energy efficiency

Inhibitors:

  • Weak academia-industry link
  • Lack of digital savviness
  • Increasing training costs
  • Inflexible/regulated job markets
  • Low transition support policies

Paradigms:

Whatever I studied now or will study in the future will guarantee my entire working life

Experts:

  • Caroline Castrillon, founder of Corporate Escape Artist
  • Monserrat Bustelo, senior specialist in the IDB’s Gender and Diversity Division
  • Aditi Mohapatra, Former Managing Director, BSR
  • Katie Abbott, Former Manager, Inclusive Economy, BSR

Timing:

Web Resources:

(Jose Luis)