But the past few years have only highlighted the limits ofcurrent AI technologies.
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Aouns message: to stay relevant in this new economic reality, higher education needs a dramatic realignment.
What makes artificial intelligence different?
AI is not the first technology to change the way we work.
In every instance, old jobs were destroyed as new ones were created.
In the 1960s, there was little trust for the first ATM machines.
Today, there are millions of ATMs worldwide.
Twenty years ago, there was no sign of Facebook and Twitter.
Today, theyve become fundamental pieces of the socioeconomic puzzle across the world.
But what makes artificial intelligence different is the pace of change it will bring.
Stanford University professor and Coursera Founder Andrew Ng describes AI as the new electricity.
In any predictable task, computers have humans at a cognitive disadvantage.
And because software is cheap to copy, any digital advance can be instantly replicated throughout the world.
Any predictable task is an overstatement.
I would also contest computers having humans at a cognitive disadvantage.
A more accurate term would be that computers have humans at a, well, computational disadvantage.
In many fields, this means well finally be able to meet the growing demand for human expertise.
But in other fields where the supply already meets demand, it might reduce the need for human experts.
Software-only solutions do not rely on expensive production chains.
And with cloud computing and internet connectivity becoming ubiquitous, they will quickly become accessible to everyone.
This is why changes brought by AI will be much faster than previous technological revolutions.
How to stay competent in the age of AI?
For learners, a key goal will be to find ways to distinguish themselves from machines.
The fact remains that machines will keep getting better at performing skilled work.
Many of the jobs todays learners will occupy in the next 20-30 years do not even exist today.
This means universities must repurpose themselves to serve learners throughout their working lives.
Prof. Aoun calls for a new education model that is different in delivery method, content, and context.
AI algorithms are very efficient at retrieving patterns and making predictions based on data.
But when it comes to abstract thinking, common sense and transfer learning, humans still have the edge.
They will continue to be how we distinguish ourselves as individual actors in the economy.
Whatever the field or profession, the most important work that human beings perform will be its creative work.
The robot-proof education model
How does the education system reinvent itself to nurture creativity?
Instead of training laborers, a robot-proof education trains creators.
Experiential learning replaces the passive absorption of information with the integration of knowledge and real-world experience.
Near transfer happens when the contexts are similar, such as poetry and drama.
But when the contexts are largely disparate, such as poetry and public relations, the transfer is far.
Our potential to master far transfer is our competitive advantage over intelligent machines, Aoun writes inRobot-Proof.
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