This article was originally published on the Brown Center Chalkboard.
Accelerating trends in artificial intelligence (AI) and robotics point to significant economic disruption in the years ahead. Together machine learning, natural language recognition, biometrics, and decision management are converging toward what the World Economic Forum has described as the Fourth Industrial Revolution. While in the past, technology has consistently generated more jobs than it destroys, many now worry that “this time is different.”
According to McKinsey & Company, half of all existing work activities could be automated by currently existing technologies, saving some $16 trillion in wages. Forecasts indicate that revenues from AI will expand from the current $8 billion to more than $47 billion by 2020. Industries attracting the highest investments include automated customer service, quality management and recommendation, medical diagnosis and treatment, and fraud analysis and investigation.
For many policymakers, a natural response to this shift has been to focus on more and improved training in science, technology, engineering, and math (STEM) subjects. What is often less appreciated, however, is the role liberal arts will play in this Fourth Industrial Revolution.
Education policy and automation
As many studies now demonstrate, creative problem solving, people management, and social intelligence remain significant bottlenecks to machine learning. This suggests that these “soft” skills will increase in value as AI matures. Indeed, even as technology eliminates the need for routine labor, it will also open up whole new opportunities in industries that leverage creativity and innovation. Surfing this Fourth Industrial Revolution will mean marrying human intelligence to machine intelligence in new and creative ways.
In order to ensure the future prosperity of advanced economies, students will need skills that match with a wide range of disruptive technologies. In fact, new tools that build on speech recognition, digital assistance, augmented reality, and generative design are already amplifying human capabilities. Growing calls to bridge AI with human ingenuity suggest that our education systems will need to focus on teaching skills that will augment and complement AI to meet the impact of machine automation.
As our social systems adapt to this new wave of technological disruption, the design of education systems will need to meet a new and different standard. Even as education policy in advanced economies has traditionally focused on inculcating basic skills, an AI-driven society will increasingly demand an entrepreneurial workforce, well versed in the application of knowledge.
Indeed, it is becoming obvious that we are entering an era in which many kinds of routine work are simply becoming much less valuable. At the same time, AI has limitations. Machine learning has been particularly effective at making predictions, but it has been much less successful at managing challenges associated with judgment, decision-making, and interpretation. What is striking is that these kinds of skills are not generally the focus of STEM disciplines. In fact, they more closely align with the type of learning that liberal arts degrees are equipped to deliver.