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The author, being the chief executive of the New America think-tank and an FT contributing editor, shares insights on AI.
In the age of AI, traditional classrooms transform into knowledge hubs. Teachers serve as guides, helping students navigate and effectively utilize the abundance of information right at their fingertips.
ChatGPT, an AI language model, was able to reinvent one of Shakespeare’s famous speeches thanks to the writer’s guidance and critical feedback. This highlights the need for more mentors, tutors, and advisers in a world inundated with AI. These roles emphasize personalized teaching, which aims to unlock and maximize individual and group potential.
In the past, intelligence was a relatively simple concept categorized by an individual’s IQ score. Teachers were responsible for imparting knowledge to students, treating their brains as containers that needed to be filled. Higher IQ usually correlated with faster learning, memory retention, regurgitation, and calculation abilities.
Today, intelligence is multi-faceted. Back in 1983, Harvard psychologist Howard Gardner proposed eight distinct types of intelligence: linguistic, logical-mathematical, musical, spatial, body-kinaesthetic, interpersonal, intrapersonal, and naturalistic. EQ tests, developed in the 1990s by psychologists like Peter Salovey (now president of Yale), measure emotional intelligence – the ability to perceive, use, understand, and regulate emotions.
Generative AI focuses on generating new patterns of symbols (words, numbers, notes, images) by recognizing and distilling existing patterns from the vast expanse of knowledge available. The line between generated ideas and genuine creativity is already being blurred. Additionally, the capacity of AI to process information at an unprecedented speed raises concerns.
Generative AI is not significant because it is artificial, but because it replicates and highlights specific aspects of intelligence. This necessitates integrating these dimensions into our understanding of human abilities, similar to how we have adapted to previous technological advancements. For instance, Google acts as an artificial memory, supplementing our mental recollection when we experience memory lapses.
The advent of instant encyclopedias on our smartphones, much like calculators before them, has minimized the importance of memorization and emphasized the need to learn how to utilize these new tools effectively. Generative AI prompts us to reconsider not just what we teach, but also why, how, and when we teach it.
Critical thinking skills have never been more crucial. Both natural and artificial generative intelligence can organize, synthesize, and distill vast amounts of knowledge, but they are also prone to errors. Nobel laureate Daniel Kahneman’s book Thinking, Fast and Slow offers insights into the mistakes stemming from different cognitive processes. The internet is rife with unintentional (and intentional) errors in books, articles, blog posts, tweets, and videos. Generative AI will inevitably amplify these errors in increasingly authoritative ways.
Teachers of all disciplines must foster an environment where students continuously question their own knowledge and utilize both natural and artificial sources of intelligence. Equipped with curiosity, healthy skepticism, and an ability to navigate nuance, students must learn to ask effective questions. This is exemplified by the emerging profession of “prompt engineers.”
If the purpose of education is to unlock our full potential, we must redefine how we develop all human capabilities by leveraging technological tools that enhance our natural abilities. This approach to education should be lifelong.
In sports, music, and increasingly in business, top performers benefit from various types of coaches. These coaches utilize technology to provide their clients with enhanced feedback, constantly working towards improvement. As technology continues to augment human capabilities, our need for human guides will only grow.
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