I’ve been playing for a while now with the idea proposed by Donald Clark that our education is mainly text-based. “From 5 to now 25 [years old],” explains Donald, “young people spend almost all of their time reading, writing and critiquing ‘text’ in an educational system”.

If you think this through, it makes sense. Our very definition of intelligence is text-based. Intelligent people are those who know how to read and write very well -or do something that comes with knowing how to read and write very well. Considering that less than 200 years ago almost 90% of the population were illiterate, if not more, knowing how to read and write puts one among the 10% and gives access to information, ideas, opportunities, and long-range communication.

However, even today with most young people having access to education, reading and writing performance continues to drop, but we do not exactly lack brilliant people doing extraordinary things. Why?

In 1921, psychologist Lewis Terman began an audacious experiment that would span decades and shape our understanding of intelligence and success. Armed with IQ tests, stacks of questionnaires, and an unshakable belief in the power of intellect, Terman set out to answer a question that had haunted educators and psychologists alike: What happens to gifted children when they grow up? Terman and his team scoured California schools, identifying 1,528 children with IQs above 135—an extraordinary threshold. These children, whom Terman affectionately referred to as his “Termites,” became the subjects of one of the longest and most ambitious longitudinal studies in history: the Genetic Studies of Genius. The premise was simple but profound: if intelligence was the key to success, these children were destined for greatness.

However, intelligence, Terman would discover, is only one part of a much larger equation. At first, the results seemed promising. Many Termites excelled in school, pursued higher education, and secured stable, respectable careers. Some became professors, scientists, doctors, and lawyers. Yet, beneath the sheen of success lay a messier reality. Some Termites with extraordinarily high IQs failed to meet expectations, while others with merely “above-average” scores achieved remarkable feats.

By the time of Terman’s death in 1956, the data painted a nuanced picture. Intelligence correlated with success, but it was far from a guarantee. Motivation, perseverance, emotional intelligence, and even sheer circumstance mattered just as much, if not more.

Just like Terman concluded, a text-based education is not nearly enough to prepare students for what comes next. However, with the upcoming threat to text-based education, the Large Language Models (LLM) AIs, most traditional education systems are advocating against it like antibodies fighting a disease. I have explored this threat in education before, but the same is happening in the workplace.

Doing meaningful work demands automating as much as we can in the systems, with technology doing better and faster the work we shouldn’t be doing anymore. This principle is not new in civilization; humans always created tools to make life easier, automating parts or all the work.

For those who work depend heavily on text, automation may be seen as a threat, not an opportunity, as we will see these jobs be transformed or even disappear. But as Kenneth Megill explains in his book, Thinking For A Living: The Coming Age Of Knowledge Work:

“An enlightened ‘owner’ of his labor has a very different attitude. Automation is welcomed, for the work becomes easier and if tasks are taken over by machines, this is a liberation, not a threatening force. The work of the enlightened ‘owner’ is the work of someone who is open to, and eager to, innovate and create. These are the primary characteristics of knowledge work.”

Not surprisingly, many of these systems, such as educational and organizational, are perceiving the use of AI as cheating. But if an AI can pass university tests and job interviews, is technology the real problem? Or is it how we insist on doing things?

Just like we changed horses for cars and iron cogs for silicon, my point here is that our systems need to change or adapt to this new technology. In other words, our modus operandi should be revised.

For good or worse, AI is now part of our daily lives, and excluding it from education and the workplace (or at least think that it is possible) is just nonsense. If we are in need of good ideas, AI can be just what we need if we only know how to use it correctly –and for that, we need to learn how to use it.

Anyone is now able to do at least mediocre work using an AI that otherwise would be just bad work. In contrast, this is also an opportunity for incredibly competent professionals. They are free of mediocre work (because the clients can do it themselves now), but having the knowledge of how to do outstanding work or even knowing what outstanding work looks like is still reserved for them.

Also, knowing how to work with an AI will be also a challenge. There is a big difference between going through an iterative process with an AI and just asking it to do it for you. If you need brilliant and effective work, hiring a flesh-and-blood professional still is your only option.

Just as Terman’s study revealed the limits of text-based intelligence in defining life outcomes, AIs are exposing the flaws of relying too heavily on it. The rise of AI challenges not only our traditional systems of education and work but also our deeply ingrained definitions of intelligence.

From the printing press to the internet, technological advancements have consistently forced us to redefine our understanding of the world. Intelligence is no different. The question is not whether AI will make us less intelligent, but whether we are willing to redefine intelligence in a way that embraces these “new ways of doing business”.

Intelligence in the AI era will belong not to those who fear or reject it, but to those who learn to work with it, question it, leverage it, and push it to new creative and intellectual frontiers.

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Felipe Zamana: Professor, Writer, Speaker, and PhD Researcher | Bridging academic knowledge and professional practice through Education | Strategic Creativity Management for Decision-Makers. LinkedIn

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