McKinsey Global Institute (MGI) recently published a report titled, “Jobs Lost, Jobs Gained: Workforce Transition In A Time of Automation.” It suggests that by 2030, 15% of global labor could be displaced by intelligent automation. Instead of forecasting a dystopian future where human labor becomes increasingly irrelevant, the report finds that the productivity benefits of enhanced labor efficiency could create demand for millions of new jobs. By way of a historical example, “[t]he personal computer enabled the creation of 15.8 million net new jobs since 1980, accounting for 10 percent of employment.”
However, going forward, “…people will need to find their way into these jobs.” In other words, companies and governments will need to take proactive action through investment and skills programs in order to remain competitive. This is a non-trivial challenge, especially in light of the fact that “[e]ducational models have not fundamentally changed in 100 years; we still use systems designed for an industrial society to prepare students for a rapidly-changing knowledge economy.”
It isn’t news that governments are frequently challenged to anticipate the future and achieve the political consensus required to deploy effective strategies to address it. Part of the problem is that human beings are generally bad at predicting outcomes. In their excellent book, “Machine, Platform, Crowd,” authors Andrew McAffee and Erik Brynjolfsson quote study after study establishing that human predictive accuracy is severely watered down by unconscious bias.
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