“ WE NEED TO VALUE THE KIND OF HUMAN WORK THAT IS UNIQUELY HUMAN AND SHIFT OUR ECONOMY TO LOOK FOR HIGHER QUALITY THINKING AND SOLUTIONS THAT ARE NOT COMMON AND CREATE VALUE ADD TO OUR ROLES.”
BEN NELSON, CEO & FOUNDER, MINERVA
One option is to just condition ourselves to do what the machines can do and produce work which is of equivalent or even lesser quality than the machine. The second option, he notes, is for humans to create added value and rise above what is broadly known by the population and become experts with unique insights – “tastemakers in the highest degree.” “AI is based on a large language
model that is based on what is out there. It can extrapolate but it can’t think. The general AI that we see in films and science fiction is not the generative AI we currently have. It might get here at some point but what we’re dealing with now is a machine learning-based large language model.” Humans can spot and analyse
broader forces, complex ideas and understand how those ideas or concepts apply to different and diverse contexts. “That is not something generative AI can do. It can fake it. But it wouldn’t be able to understand it.” “We need to enable our
employees to be generative and original in their understanding of what is it they can produce that is different,” he added. But there are some challenges
ahead. For one, the education system needs to change for this future of work and higher thinking.
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CHALLENGES AHEAD “Our education system in schools and universities is fundamentally not relevant to an AI age where information is not only readily available but useable and where AI will be able to create using that access to an infinite amount of information. We are spending $3 trillion a year globally to equip human beings to be vastly degraded versions of a machine.” So, how do we adapt for the
future of work? “Our unique insight is around taking ideas from one area and being able to originally apply them in another,” he said. We need to get better at knowing
what to do in a context that we’ve never encountered before – focusing on ‘durable cognitive skills’. According to Nelson, an education that is centred around information and how much knowledge we retain only puts us level with machines at best. “We need to value the kind
of human work that is uniquely human and shift our economy to look for higher quality thinking and solutions that are not common and create value add to our roles. Or, we are in danger of degrading the quality of output and accruing value to institutions that will not harness human potential or accelerate what we can do with AI and instead decelerate what it is that’s possible.”
But if the talent pipeline comes
from higher education asked a delegate, how do companies get the people they need while the education system catches up? Some delegates also voiced that education entities may be resistant to change and expressed a lack of leadership to help develop future ready people. Nelson discussed how industry
and education can work together to develop AI ready talent. A particular gap that Minerva has been working on closing through its distinct programmes. While other delegates expressed concern on educating people to this higher level of thinking when there may not be many jobs for it yet. How do you balance educating people for the future and right now?
HALF-LIFE OF SKILLS Change is coming, but for now there are still many unknowns. What is clear is that skills will need to be reviewed, and fast. In a follow-on panel, Kian Katanforoosh, CEO and founder of Workera spoke of the half-life of skills – citing a World Economic Forum metric that claims every five years a skill is half as useful as it was before. “The half-life of skills is probably
the lowest it’s ever been. Even more so in digital areas where are a skill on average is used for about 2-2.5 years. If you look at programming
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