Artificial Intelligence: What it really means and why it’s everywhere
Oct 08, 2024 03:27PM ● By Adam CochranLast year, I wrote about a new technology that was all the rage—artificial intelligence, or AI. I revisited the topic over the next two months because it was too vast to cover in a single column. My goal was to prepare readers for the flood of AI buzz that was coming.
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Based on past market-driving buzzwords such as “HD”, “Next Gen,” “broadband” and “interactive,” I predicted that companies would use AI to market anything. Well, the future is here, and now, they’re not just marketing home appliances, smartphones and computer programs with AI. They’re sticking it on exercise equipment, food packaging and even analog items like reading glasses and camping gear.
Artificial intelligence is a self-defining term—intelligence that is, in fact, synthetic. While I’d love to go down the philosophical and physiological rabbit hole of defining intelligence, almost all definitions apply. Intelligence can involve processing, organizing, remembering, anticipating, recognizing, judging or calculating. But it doesn’t mean “thinking.” Living beings think as part of demonstrating intelligence.
However, what we typically measure as “intelligence” on standardized tests often has more to do with recall or task efficiency. Thinking involves abstract considerations like ethics, imagination, critical thinking or creativity.
In other words, artificial intelligence is programming that uses existing data to produce new data that is derivative, augmented or aggregated based on patterns and past information. AI is not real intelligence, nor is it sentience (feeling emotions and pain) or self-awareness.
Now that AI has become a buzzword in marketing, it’s important to differentiate between its beneficial and irrelevant uses.
- AI can be highly effective for tasks like gathering data, making predictions or generating art and designs based on existing parameters. But AI cannot innovate, empathize or add value beyond the parameters it’s been programmed to consider.
- AI can solve problems, but determining whether those solutions are suitable for the client, market, culture or intended use is a decision only a human can make.
- AI can check for spelling and grammar, organize complex data or generate something as quirky as a tintype photo of Abraham Lincoln holding his therapy octopus on a city bus.
There is no magic or creative intellect behind AI. It analyzes data and produces results based on patterns and user preferences, learning through trial and error. As people use AI, the technology tracks their responses, updating its algorithms based on user feedback.
AI essentially replicates the process humans use to learn a skill or craft: mastering known concepts and adapting them to meet individual needs.
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When I asked ChatGPT to write a poem about French fries from the perspective of a pigeon in Central Park, it gave me a poem that might earn a B- in a 12th-grade poetry class:
In Central Park, where shadows play,
I wander in the light of day,
A humble pigeon, eyes alight,
On golden fries, a pure delight.
They tumble down like crispy rain,
From picnics on the grassy plain,
With every crunch, my heart does soar,
Oh fries, I dream of you once more.
Of course, the computer doesn’t appreciate poetry, but it can create a suitable poem by analyzing and aggregating examples humans have labeled as “good poetry.”
AI can be unsettling for teachers, artists and anyone whose work relies on skill or craft with established rules. But is AI really taking work from humans, or have we built our education and industries around turning humans into machines?
This isn’t new—augmenting human work with machines dates back to the earliest tools.
A positive perspective that isn’t discussed much is that AI forces us to re-evaluate how we value intelligence compared to human traits like creativity, emotion, compassion, ethics and relationships.
The value of humanity isn’t in our intelligence. It’s in our ability to recognize that the best answers are not always the right ones, and the most perfectly calculated solution isn’t necessarily the most appropriate.
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