George Armitage Miller lived in a world of words. Every object that fell into his vision and every word he heard instantly set off a cascade of associations, synonyms, and antonyms that flashed through his mind. A psychologist with an interest in understanding the cognitive processes behind language and information processing, he founded the Center for Cognitive Studies at Harvard. And, in 1980, long before digital networks were part of everyday life, he was the driving force behind the development of Wordnet, a still functioning online database that details the myriad lexical relationships between most words in the English language.

But for a while in 1983 he was stuck looking for a word to describe the relationship between living organisms and information. A fan of Erwin Schrödinger’s What Is Life, Miller was certain that Schrödinger had left something important out of his definition of life. In order for living organisms to consume free energy per entropy’s demands, Miller insisted, they had to be able to find it, and to find it they had to have the ability to acquire, interpret, and then respond to useful information about the world around them. It meant, in other words, that a significant proportion of the energy they captured was expended seeking out information using their senses and then processing it in order to find and capture more energy.

Some analogies are so useful that they don’t merely shed light on a concept, they actually become platforms for novel thinking. For example, the metaphor of the brain as a computer has been central to the insights generated by cognitive psychologists during the past fifty years. It’s easier to define how a computer works than to define how the brain works. For this reason it can be fruitful for psychologists to use various, well-understood aspects of a computer—such as memory, buffers, or processors —as inspiration to locate similar functions in the brain.

Good metaphors are “generative.” The psychologist Donald Schon introduced this term to describe metaphors that generate “new perceptions, explanations, and inventions.” Many simple sticky ideas are actually generative metaphors in disguise. For example, Disney calls its employees “cast members.” This metaphor of employees as cast members in a theatrical production is communicated consistently throughout the organization:

• Cast members don’t interview for a job, they audition for a role.

• When they are walking around the park, they are onstage.

• People visiting Disney are guests, not customers.

• Jobs are performances; uniforms are costumes.

This very same sentiment could apply just as well to every single person in our study, not because of their “genius,” but because of how they played exquisitely to their unique constellation of encodings.

Each constellation of encodings is its own category-of-one distinctive blend. There was just one Barbara McClintock, one John Glenn, one Alice Paul, one Toni Morrison, one Benjamin Franklin. Just as there is only one of you, and only one of me. The thing that set them apart is their ability to play so consistently to their own individual (and sometimes quite peculiar) package of encodings.

Chapter 11: The Power of the Tongue: Language

“I have learned to sense which me linguistically a situation demands, and with whom it is safe to sound like myself. Today we call this code-switching, but when I was younger there was no name for the delicate dance so many Black people do. The one where we bend and twist our tongues in order for white people at our places of work or education to see us as smart or respectable enough to be there, and then adjust once we’re with friends or family, in order to show we are not lost to that white world. It is a dance that even revolutionaries feel they must partake in.

Finally, to redistribute power along our third axis, influence, we need broad-based education. The antidote to the mysticism and mirage of AI hype is to teach people about how AI works, about its strengths and shortcomings, about the systems that shape its development, about the worldviews and fallibility of the people and companies developing these technologies. As Joseph Weizenbaum, MIT professor and inventor of the ELIZA chatbot, said in the 1960s, “Once a particular program is unmasked, once its inner workings are explained in language sufficiently plain to induce understanding, its magic crumbles away.” I hope this book is just one offering to help induce understanding. It builds on the work of the many scholars, journalists, activists, and educators before me who have dedicated themselves to public education. May it be a new ground upon which many more after will rise up and build.