By Guest Author: Katherine Prince
The world of work is changing rapidly. Those changes will have big implications for how we approach learning and what our education system aims to achieve.
We increasingly organize work according to projects. The platform or gig economy means that more people are stitching together mosiac careers instead of working full-time for a single organization. Interest in entrepreneurship is rising, with the U.S. Chamber of Commerce Foundation reporting that one-half to two-thirds of Millennials are interested in entrepreneurship and that 27% are already self-employed. But it's bigger than that.
Artificial intelligence and machine learning are ushering in the rise of smart machines that will be able to carry out many of the complex cognitive tasks that once seemed exclusive to middle class work in the knowledge economy. Already, doctors are using deep learning to help diagnose illnesses, entry-level lawyers are finding themselves out-analyzed by machines that can harvest case history faster than any human, artificial intelligence is writing news stories, and robots are staffing restaurants. This is just beginning: one Oxford University study suggests that as many as 47% of current middle-class American jobs could get displaced or change significantly over the next two decades due to automation.
The rise of smart machines in the workplace will have a huge impact on human work, but the nature and extent of that impact remain uncertain:
- Working alongside smart machines could lead to a clearer focus on what is uniquely human, as people work increasingly in complement to our new machine partners. Those new labor relations could go so far as to lead to more satisfying and creative work for many people.
- On the other end of the spectrum, the proliferation of smart machines could lead to massive technological unemployment, either for a time (think Industrial Revolution) or long-term (think total redefinition of the role that wage labor plays in people's lives).
The uncertainties around the future of work are many and are profound, their implications deep. As the societal debate about the role of people in the workplace intensifies, we are going to need to redefine what it means to be career-ready. Some questions to consider:
- Might readiness come to mean acquiring and updating portfolios of demonstrated skills, with people dipping in and out of educational experiences throughout their lifetimes?
- Will education emphasize career readiness, human development, or some mix of both?
- Could focusing on career readiness set people up to chase rapidly changing and increasingly elusive work, with workforce projections and education systems struggling to keep pace with exponential change?
- Could focusing education on human development undermine our ability to work effectively - or might it be the key to differentiating people's contributions from those of machines?
One thing is certain: current approaches to education are insufficient to address these questions and help learners of all ages prepare for meaningful contributions to work and other facets of life amid rapid change and increasing complexity. We need to create and foster new approaches that align with and support people in thriving in the emerging era.
In exploring what education could and should look like in the decades ahead, we could find that:
- The K-12 sector no longer pushes students toward post-secondary options that might not adequately prepare them for the new world of work
- The higher education sector splinters as diverse definitions of the purpose of education emerge
- Education at all levels comes to focus on skill development
- Learning structures become increasingly fluid, with learning experiences organized around learners' needs and interests rather than traditional boundaries
- Personalized learning comes to focus on dynamic curation of customized learning relationships with an expanding range of educators and other learning partners
- Algorithmic coordination helps match learners with the learning experiences they need to succeed (think Uber School)
- Lifetime personal learning bots help learners navigate experiences and develop machine partnership literacy
- Public funding for education shifts to provide lifetime support for people of all ages to move in and out of learning as their needs dictate
In the context of far-reaching questions about the future of education, I see a shift toward personalized learning as being critical to helping prepare current education systems for a much bigger transition. Under that umbrella, competency based education and project-based learning offer pedagogical strategies that we can use to support learners today. But without broader context, no pedagogical strategy can be the end game. We need to have deep and extensive conversations about readiness, the purpose of education, and the structures that support learning.
In short, we need to redefine readiness for an uncertain future of work in which people's desire for meaningful and authentic contribution will sit alongside and shape new platforms of exchange and value creation and a complex economic landscape. Let's make sure education is ready.
Katherine Prince leads KnowledgeWorks' exploration of the future of learning. Follow them @KnowledgeWorks.