What Happens When There May Not Be Enough Jobs To Go Around Due To Automation And AI Advancements?

By C. M. Rubin

Nick Bostrom, Howard Gardner, Charles Fadel, Andrew Hargreaves, and Michael B. Horn Share Perspectives on Reimagining Education and Curriculum Design to Prepare Youth for a Future Where Traditional Employment May Not Be the Norm

What happens when there may not be enough jobs to go around due to automation and AI advancements? This pressing question demands a fundamental reimagining of education and curriculum design to prepare children for a future where traditional employment may not be the norm. Insights from top global thought leaders—Nick Bostrom, Howard Gardner, Andrew Hargreaves, Charles Fadel, and Michael B. Horn—highlight what education systems can do about it.

In my recent interview with Nick Bostrom, renowned philosopher and author of “Deep Utopia: Life and Meaning in a Solved World,” he emphasized the need for a major change in education to equip individuals with the skills and mindset necessary to thrive in an AI-driven world.

Bostrom’s insights underscore the limitations of traditional education models in preparing individuals for the challenges and opportunities presented by AI. He advocates for a more dynamic approach that integrates AI tools into education, fostering adaptability, critical thinking, and digital literacy among students.

Reflecting on historical perspectives, Bostrom highlights the traditional role of education in preparing individuals for the workforce. However, he raises a crucial question: What happens when there may not be enough jobs to go around due to automation and AI advancements? This reality necessitates a fundamental reimagining of education and curriculum design to prepare children for a future where traditional employment may not be the norm.

Personalized Learning and Lifelong Adaptation

Bostrom emphasizes the potential of AI in providing personalized tutorial systems, stating, “There are great opportunities as well for more personalized tutorial systems using these AI technologies.” Instead of “having one teacher maybe telling a class of 30 students how to do some mathematics thing, you could have systems that understand precisely where each student is at, what they are stuck at, what they get wrong, and then create personalized explanations to help them overcome hurdles.” This approach holds promise in addressing individual learning needs and overcoming educational barriers, thereby maximizing learning outcomes for all students.

Furthermore, lifelong learning has always been important, but the rapid pace of technological change today makes it even more critical. The speed and scale of disruption are unprecedented, affecting nearly every industry worldwide. These changes are revolutionizing the entire frameworks of production, management, and governance. Bostrom stresses the importance of cultivating a mindset of continuous learning and adaptation. He suggests, “I think it might be a useful skill to not think of learning as something you do once at the beginning of your life in school, and then you have done your learning and now you’re just kind of coasting on that until you retire. Like I think increasingly we will need to think of our lives as one big ongoing process of learning, a lot of which needs to come not from some external authority telling you ‘you have to do it,’ but cultivates that kind of mindset of growth and curiosity, I think will also put you in a better position.”

Expert Perspectives on AI Integration in Education

Charles Fadel, a global education thought leader and futurist, believes what is most important is “modernized knowledge, how we use our knowledge, how we behave and engage in the world, and how we reflect, adapt, and learn how to learn.” Fadel highlights the challenge of implementing these frameworks effectively, noting that “even the most advanced jurisdictions provide little to no efficacious professional development and no assessment of these competencies.”

Fadel highlights the importance of ethical considerations and warns against over-reliance on AI. The “cognitive miser” effect, where humans prefer easy solutions, can exacerbate dependence on imperfect AI systems. “Simply put, our brains are lazy through good evolutionary design, which means we take the route of least effort every time possible. This leads to over-reliance, which is particularly concerning as these algorithms, like humans, are not perfect, and confabulate with gusto.”

Andy Hargreaves, visiting professor at the University of Ottawa and former president of the International Congress of School Effectiveness, discusses the engagement crisis post-Covid-19 and how AI can help or hinder the drive to re-engage students and teachers. “AI will be a hindrance if it just offers more bad learning in a more efficient, slightly less toxic, and more stylish way. If the driving priority is to make learning more engaging by supporting rather than bypassing the teacher, then there’s a lot to work with.”

Hargreaves also highlights the broader societal implications of AI, emphasizing the need for a fair global tax agreement on wealth generated by AI and robotics. “If there is no agreed global principle of fair distribution, AI will become our next greedy master, not our servant for a better society.”

Howard Gardner, the John H. and Elisabeth A. Hobbs research professor of cognition and education at Harvard Graduate School of Education, stresses the importance of ethical considerations and cultural sensitivity in integrating AI into education. “First, of course, do no harm, and if harm is done, try to understand why and avoid it in the future. Second, understand and be sensitive to various cultural norms and practices, including religious and political systems.”

Gardner advocates for a holistic approach to education, likening it to a model of physical health that spans from pediatrics to gerontology. “Education can and should remain central, but we need to be very open to the form that education will take—from cradle to grave, with new kinds of roles, expertise, and options.”

Michael B. Horn, co-founder of the Clayton Christensen Institute for Disruptive Innovation, offers practical insights on integrating AI tools into the current education system. “The lowest risk and most immediate opportunity for impact is for AI tools to support teachers in everything from helping them lesson plan to creating more personalized learning opportunities for students in different places in their learning to helping them assess student work.” He emphasizes that supporting teachers is crucial because experts can mitigate AI’s occasional hallucinations, reducing the likelihood of misleading students.

Horn also discusses the potential benefits and challenges of implementing personalized tutorial systems using AI in classrooms. “Tutoring is one of the biggest hypes and excitements around AI. AI tutors are great when there’s not another option—more affordable, scalable, and accessible. But not as good as a human tutor, particularly a human tutor with AI at their disposal.” He highlights the benefits of personalization, such as allowing students to work on concepts at their right level and providing a myriad of examples to help them understand concepts. However, he cautions that AI tutors are not perfect and simple mistakes could mislead students, potentially hurting their confidence and self-efficacy.

Conclusion

Bostrom’s insights, along with perspectives from Fadel, Hargreaves, Gardner, and Horn, underscore the need for a fundamental reimagining of education in the AI era. By integrating AI tools into education, fostering adaptability, and addressing ethical considerations, we can better prepare individuals to thrive in an AI-driven future. As we navigate this transformative landscape, policymakers, educators, and stakeholders must collaborate to ensure that education remains a cornerstone of human progress, equipping individuals with the skills and mindset to lead purposeful lives.

Are our current assessment systems, which heavily rely on traditional testing models, adequately evaluating the skills and knowledge needed for success in a rapidly evolving AI-driven world? Is now the time to explore alternative appraisal methods that align with the demands of this new era?