MIT’s recent research dives into AI’s potential to automate jobs, challenging common predictions. Despite widespread concerns, the economic viability of automation lags, providing time for strategic policy planning.
Goldman Sachs estimates a 25% automation rate in the labor market soon, but MIT’s study suggests a more gradual shift. Contrary to expectations, the majority of jobs deemed at risk aren’t currently “economically beneficial” to automate.
The study, focused on visual analysis jobs, reveals that only 23% of wages for such tasks are economically attractive for AI automation. Even with rapid cost decreases, it could take decades for automation to be efficient for firms.
While the study acknowledges limitations, including the rise of new tasks and jobs, it emphasizes the importance of preparing for AI job automation. Policymakers can use this information to plan initiatives, and for AI developers, reducing deployment costs and expanding scope becomes crucial for widespread adoption.
