Revisiting the Jobs Artificial Intelligence Will Create
This audio conversation digs into research on the emerging job categories spurred by AI and what leaders should be thinking about next.
Topics
Frontiers
MIT SMR editor in chief Paul Michelman recently spoke with authors Paul Daugherty and H. James Wilson to discuss the research that went into their (and coauthor Nicola Morini Bianzino’s) 2017 article “The Jobs That Artificial Intelligence Will Create” and to find out what new developments in this space have their attention.
Listen to the full conversation here:
Key takeaways from the discussion include:
Soft skills will be crucial for collaborating with smart machines.
A major focus of the Daugherty and Wilson article is what kinds of skills will enable job transformation in the age of AI. Surprisingly, they’ve found that STEM skills, while important, are certainly not a prerequisite for transformation. In fact, their research shows that four soft skills are becoming much more valuable as human-machine collaboration advances. These skills include complex reasoning, creativity, social and emotional intelligence, and sensory perception.
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Training for AI will require shifts in learning.
Humans have never trained for many of the new jobs that AI will create — so the question becomes, how do companies develop their workforce? Daugherty and Wilson cite the importance of experiential learning through hands-on apprenticeships and using technology to advance skills in new categories of jobs. In addition, the burden for skilling and reskilling must shift from the individual employee to the collective institution or organization. If learning is going to become a core competency for global businesses, then organizations will need to step up to help build learning platforms for employees.
Responsible AI marks a new frontier.
Daugherty and Wilson point out that responsible AI, which was hinted at in their original research and spelled out in more detail in their recent article “Using Artificial Intelligence to Promote Diversity,” has become a much more important question. Thinking about bias, transparency, and accountability will be crucial in the future development of AI systems. As the authors describe, “These are going to be really important issues for businesses and organizations to grasp and to make sure that as we have increasing numbers of people working in AI and more powerful solutions delivered with the AI, how do we make sure we deliver the right outcomes in all cases?”
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