Getting into a top-ranked college and crushing a four-year degree course—once-and-done learning—was sufficient for both career and life success in the past. This mindset worked well for decades, but unfortunately, this approach won’t cut it in the future. The rise of automation and AI has flipped the traditional linear model of education-employment-career on its head and has raised questions about our educational institutions’ abilities to train students not only for jobs that exist, but also for jobs that don’t exist yet. Are they teaching them to become a flying car developer or a machine risk officer? How about teaching them to save the world by becoming a cyber calamity forecaster, or helping businesses find the purpose of their existence through the role of chief purpose planner? In case you are wondering which jobs will emerge in the future, check out two of our masterpieces here and here.
Jobs of the future will be defined by the new tools of the trade (AI, AR/VR, big data, IoT), which will have a significant impact on the future of work, yet only 25% of higher education students have the necessary skill base to work and interact with emerging digital technologies. We are still preparing students to work against machines and not alongside them. Making future work preparation an education priority will require transformations that are every bit as dramatic as those that came about in the early part of the 20th century. In particular, higher education institutions must take three immediate steps to ensure they are preparing students for future jobs:
- Adopt a skill-based education. Our education institutions act as a knowledge provider and not a skills provider. Automation and AI will increasingly take over not just routine, repetitive and low-end tasks, but also higher level work, making some people’s capabilities irrelevant, and leaving behind those unable to keep up. Education institutions will need to figure out which skills will be essential for surviving and thriving in a world where machines will do almost everything. Big data and data science jobs are more likely to demand creativity, teamwork, research and writing skills. STEM streams need to be supplemented with design thinking, entrepreneurship, creativity and social science skills. And that’s where the challenge arises: While 80% of businesses believe the importance of human skills will be critical in the future, only 46% of higher education institutions agree, creating a disconnect between ‘talent produced’ and ‘talent needed.’ Education institutions that don’t consider changing-world contexts can’t help students develop the competencies and dispositions they need to be successful.
- Make education resilient with Netflix-style learning. The current global pandemic has resulted in thousands of schools and colleges being shut down and forced millions of students to stay at home. This is making us rethink the fundamentals of our education system and the way we learn. This forced trend presents educational institutions with an opportunity to redefine learning. Netflix knows what you enjoy watching and provides the relevant content to keep you engaged. What if an artificial intelligence-powered education app/portal knew how to keep students engaged with personalized learning, content and teaching – whether they are at home, in college, or anywhere else? Imagine every student having his/her own customized learning assistant. It will completely change the way we learn. Moreover, AI will help teachers break free from the one-size-fits-all approach and focus on learning that matters. AI assistants can also help teachers provide real-time feedback on students’ performance, strengths, and weaknesses so that teachers can determine the exact skills gaps and learning needs of each student and provide supplemental guidance accordingly. It’s time for education institutions to rethink not only what they teach, but also how they teach in these unprecedented times.
- Set the speed context to make education relevant for future jobs. Employable skills will evolve more rapidly in the future than they do now, creating a sense of urgency to learn faster or be left behind. Traditional educational and career pathways aren’t designed to develop skills for a fast-changing market, or to match the speed of changing industry requirements. Longstanding educational models that prioritized standardization and stability have resulted in the slow pace of change for the education industry. Very simply, if higher education institutions wish to keep themselves relevant in the future, they will have to meet the speed of market and technological change. In particular, they will have to accelerate the speed to monetize data. The speed with which they collect skill identification data (labor market data, employee and student data, etc.), analyze and apply it for content creation and curation (based on data intelligence and not gut feeling), and feed it into the AI-driven training/teaching systems to deliver personalized teaching and learning, will determine the speed with which they prepare the future workforce.
Skilling and reskilling the workforce for future jobs is rocking our entire education system and society. To reprise a classic cliché, this truly is a moment of great opportunity and great risk. How we respond to this moment – the choices and decisions educators make in the next few years – will shape the fate of many individuals. Now is the time for educators to rethink their education models and their relationship with future jobs.