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Why We Should Train Workers like We Train Machine Learning Algorithms
Article

Why We Should Train Workers like We Train Machine Learning Algorithms



Editorial Rating

7

Qualities

  • Innovative
  • Applicable

Recommendation

How do you prepare students for jobs that don’t yet exist? According to Brookings Institution scholar Makada Henry-Nickie, educational systems are putting too much emphasis on specific, teachable skills rather than on preparing students to thrive in a rapidly changing work environment. Taking cues from the way computer scientists program algorithms, Henry-Nickie advocates for an experiential, learning-based curriculum that will help equalize the existing skills gap between advantaged and disadvantaged students. getAbstract recommends her analysis to HR professionals and educational policy makers.

Take-Aways

  • Formal education focuses too much on hard skills despite evidence that soft skills – such social and problem-solving competencies – are highly sought-after in the job market.
  • Two recent studies suggest that jobs requiring higher levels of social competencies also pay better salaries.
  • Students develop problem-solving skills and other behavioral competencies from exposure to a diverse set of experiences.

About the Author

Makada Henry-Nickie is a Fellow of the Brookings Institution as part of its governance studies, race, prosperity and inclusion initiative.