A new study from MIT CSAIL (in collaboration with MIT Sloan, The Productivity Institute, and IBM’s Institute for Business Value) has concluded that job losses associated with AI-enabled task automation won't be as fast/impactful as previously estimated:
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[The research] findings show that currently, only about 23 percent of wages paid for tasks involving vision are economically viable for AI automation. In other words, it's only economically sensible to replace human labor with AI in about one-fourth of the jobs where vision is a key component of the work.
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The study departs from the conventional broad-brush approach to AI's potential impact. Instead, it offers a meticulous examination of AI's feasibility in automating specific tasks. What sets this research apart is its tripartite analytical model. The framework assesses not just the technical performance requirements for AI systems, but also delves into the characteristics of an AI system capable of that performance, and the economic choice of whether to build and deploy such a system.
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I don't doubt that this is a robust analysis of both current-state AI technologies AND current-state work processes/ways of working.
But history tells us that when new technologies emerge, new management processes follow and, eventually, workplace design and work processes are completely reimagined.
This won't happen immediately.
Electrification enabled factories to arrange each independently powered machine on the shop floor for more efficient production flow. Yet in many cases, this didn't happen for more than a decade. Why? Because factory leaders were entrenched in the current "best practices" of factory floor layouts and work allocation.
However, when the next generation of factory leaders emerged, they were willing to experiment with redesigning factory floor layouts and how and when tools were used, and as a result, enjoyed significant productivity boosts.
Today, most leaders and managers alike cannot imagine how AI technologies might be adopted in ways that change the fundamental nature of current jobs/tasks. But when they can, I don't doubt that the current perceived limits on AI task automation will very quickly disappear.
#ai #aiadoption #automation #impact #waysofworking #economic
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