Automation and the gig economy are radically changing how we work.
How we learn must keep pace with these new technologies.
We need learning to be cross-disciplinary, personalised and focused on human skills.
Together, government and the private sector can future-fit education.
We are in the midst of a profound social and economic transformation that has been catalysed by breathtaking advances in automation and artificial intelligence, and unprecedented access to data and computation. The impact of these technologies pervades nearly every sector of our economy, affecting a wide range of occupations across healthcare, finance, transportation, energy, manufacturing and beyond. As with previous industrial revolutions, these advances have the potential to bring extraordinary benefits to society, contributing to tremendous prosperity in the long run. Innovations will also transform the future of work, exacerbate the skill bias of recent decades, and contribute to a growing chasm between the best and least educated in society.
There are a significant number of predictions and analyses about the risks posed by advances in these technologies. One such study, conducted by the Organisation for Economic Co-operation and Development (OECD), estimated that about 14% of jobs across its member countries are highly automatable and another 32% will be radically transformed by technological progress. To add to that, consider how the rise of the gig economy in recent years has challenged traditional work structures. According to the McKinsey Global Institute, 20-30% of the working-age population in the United States and the European Union is engaged in technology-enabled and on-demand, independent work; a number that is expected to grow.
While some jobs will become automated and others will change significantly because of technology, we also recognize that new markets, industries, and jobs will be created – some of which we cannot even imagine today. In this fast-paced economy, learning should be seen as a lifelong endeavor for individuals at every stage of their career. How should higher education and its partners be adapting in order to provide the workforce the foundational competencies and skills they’ll need, both now and into the future? I offer four broad areas where we can find solutions:
Focus on “human” skills, not just digital competencies
As entire new industries are created and traditional ones expand and contract significantly, the skills needed to keep up are evolving at a faster rate than ever before. Educators and higher education leaders must approach skills competency with a flexible growth mindset that will serve students well across the global, knowledge-based economy – and throughout their careers. There is an undeniable need to train the next generation in emerging digital competencies and to be fluent in designing, developing or employing technology responsibly. At the same time, 21st-century students must learn how to approach problems from many perspectives, cultivate and exploit creativity, engage in complex communication, and leverage critical thinking. With a future of work that is constantly evolving, these non-automatable “human” skills are foundational, and will only increase in value as automation becomes more mainstream.
Embrace the T-shaped approach to knowledge
The broad set of skills needed by tomorrow’s workforce also affects our approach to educational structure. At Carnegie Mellon University—like many other institutions—we have been making disciplinary boundaries much more porous and have launched programmes at the edges and intersections of traditional fields, such as behavioral economics, computational biology, and the nexus of design, arts, and technology. We believe this approach prepares our students for a future where thinking and working across boundaries will be vital. The value of combining both breadth and depth in higher education has also led to many universities embracing “T-shaped” teaching and learning philosophies, in which vertical (deep disciplinary) expertise is combined with horizontal (cross-cutting) knowledge.
Invest in personalised, technology-enhanced learning
The demand for more highly skilled workers continues to grow. Recent analysis of U.S. data by The Wall Street Journal found that more than 40% of manufacturing workers now have a college degree. By 2022, manufacturers are projected to employ more college graduates than workers with a high-school education or less. Technology-enhanced learning can help us keep up with demand and offer pathways for the existing workforce to gain new skills. AI-based learning tools developed in the past decade have incredible potential to personalise education, enhance college readiness and access, and improve educational outcomes. And perhaps most importantly, technology-enhanced learning has the compelling potential to narrow socioeconomic and racial achievement gaps among students. The Simon Initiative at Carnegie Mellon aims to accelerate this trend through learning engineering, an approach that combines learning research, data and technology. Last year, CMU released the OpenSimon Toolkit, which makes technology-based learning techniques, software and underlying code freely accessible. We believe these tools can democratise learning science, and create a global, collaborative community of learning engineers within higher education.