THE PROBLEM

With widespread disruption in the job market through factors such as the widespread adoption of generative artificial intelligence and robotics, geo-political upheaval, pandemics and remote work, there is an urgent need for a dynamic workforce that can quickly adapt to the changing landscape through continuous reskilling.

WHY

Traditionally a stable job market allowed for predictable skills needs. In a time of AI automation, job tasks are changing fast and thinking skills are being outsourced. Due to the shifting landscape we don’t know what skills will be required for future jobs at this point in time, so the ability to adapt by learning fast and build skills quickly has become essential.

WHAT

Learning how to learn is about understanding one’s learning processes to improve one’s ability to learn flexibly and independently to ultimately fulfill one’s unique human potential.

HOW

As learning processes are often invisible as we often lack awareness of how we think and learn, so we aim to make the implicit explicit.

Rather than being stuck in the past and the present, in order to prepare for a fast changing environment, generative learners go back to the future to survey the future landscape, examining trends and evidence to reason out future scenarios in their minds. Generative Learners project themselves into the future to imagine their future self in five, ten or twenty years time and the jobs or community work that they will be doing. They use these future images to prepare for future work or lack thereof and develop the future skills they think they will need.

With increased use of AI, rather than claims for augmenting intelligence, there is misuse of the technology resulting in an outsourcing of thinking and reduced critical thinking