The Importance of Words: Understanding "Artificial Intelligence"
Today, let’s talk about words — their meanings, the nuances they carry, and how they often juxtapose in unexpected ways. This reflection might seem old-fashioned, but it’s essential, especially when discussing something as modern and transformative as artificial intelligence (AI). Consider the juxtaposition of the words artificial and intelligence.
To unpack this, I turned to an old friend: my trusty Webster’s dictionary. The very one I purchased during my undergraduate days in policy and government, and the same type of resource famously used by the late Supreme Court Justice Antonin Scalia to contextualize words in their true meaning.
Here’s what Webster offers:
- Artificial:
(1) Made or contrived by art; produced or modified by human skill and labor, often as an imitation of something found in nature — opposed to natural.
(2) Feigned, fictitious, assumed, not genuine.
Synonyms include imaginary, unnatural, and counterfeit.
- Intelligence:
(1) Formerly the faculty of understanding, the capacity to know or apprehend, the capacity for knowledge and understanding, especially as applied to the handling of novel situations.
When we pair these definitions, artificial intelligence emerges as an apt descriptor for the generative AI we see today.
Generative AI is indeed “made or contrived by art,” its training data derived from human-created works — literature, blogs, editorials, and countless other sources curated by programmers. It is “produced or modified by human skill and labor” and distinctly “opposed to natural.” In fact, much of its so-called “intelligence” is, by definition, “feigned, fictitious, and counterfeit.”
Generative AI doesn’t truly possess “intelligence.” It lacks the capacity to know or apprehend and cannot achieve true understanding. This is its defining feature — its very artificiality.
Why does this matter? Because the words we use shape our understanding of the technology we adopt. When we label something as “intelligent,” it carries a weight of expectation — a belief in its ability to reason, comprehend, and even empathize. But generative AI, for all its remarkable capabilities, cannot truly do any of these things. It mimics. It imitates. It predicts patterns based on the vast datasets it has been trained on.
As we integrate AI into our work and lives, we must critically understand both the terminology and the technology. Words matter. And in the case of artificial intelligence, they remind us to approach this tool with clarity, respect for its limitations, and an appreciation for its potential.
Let’s use this understanding to engage with AI thoughtfully — not as something more than it is, but as something precisely what it claims to be: artificial.
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