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Before we can understand what artificial intelligence is doing to the world, we need to understand what it is—and why it marks a fundamental break from the kind of computing that came before.

THE BEFORE ERA: Modern computers have been around for roughly a century. And for most of that time, they’ve done what they were built for: math. Fast, precise, emotionless math.

But they’ve also had major limitations. Traditional computers need precise instructions—clear input, clear output.

For many computer scientists—and more than a few science fiction writers—the dream has always been something more: a machine that doesn’t just follow orders, but “thinks” for itself, asking the questions and finding the answers.

THE CHANGE: That kind of computing requires vast amounts of processing power, data, storage, and energy—four areas where we've seen exponential advances over the past two decades.

At the same time, the amount of data available to computers has exploded—thanks to digitization projects like Google Books, which has scanned over 25 million volumes.

All of this would be meaningless without the energy to power it. Advances in green energy and efficient computing infrastructure have made it possible to keep the AI engine running—without collapsing under the weight of its own electricity demands.

THE RACE: Those new technologies fueled a race to develop this new style of computing. The public got a first glimpse of this with IBM’s Watson supercomputer, which became famous for beating humans on Jeopardy.

THE BREAKTHROUGH: The true breakthrough came more than a decade later with the release of ChatGPT—a chatbot built on OpenAI’s large language model, GPT-3.5.

It wasn't just answering questions—it was creating them.

It marked a turning point: artificial intelligence meant that computers could generate their own code—a major step towards being autonomous and “thinking” for themselves.

To be fair, there are many different types of artificial intelligence—each designed to handle specific tasks like vision, movement, sound, or decision-making.

But in this Deep Dive, we’re focusing on the branch of AI that deals with language.

THE TECH: The AI technology that processes and handles language is called a large language model, or LLM for short.

They can write emails, summarize articles, generate code, answer complex questions, and even mimic your own writing style. But how do they actually work?

HOW IT WORKS: An LLM is “trained” on hundreds of billions of words from the internet—books, Wikipedia, news articles, Reddit threads, blog posts, and other websites.

But “training” doesn’t just mean feeding all that information into a supercomputer. The model doesn’t store facts like a library.

Instead, it analyzes patterns across all that language—how words appear together, how sentences tend to start and end, and what kinds of words are likely to follow others.

IT’S ALL MATH: At the end of the day, a computer is still a computer and works best with math (just like the computers before). In an LLM, language gets boiled down into a massive web of statistical probabilities.

When the AI sees a prompt—say, part of a sentence—it predicts the next word. Then it predicts the next one, and the next, building a full response one word at a time.

All that guessing makes LLMs really great at guessing—so much so that if you give it a question like, “write a poem about the sky,” it will guess a very good answer that looks a lot like poems about the sky that it’s seen elsewhere.

BUT BUT BUT: LLMs don’t know if what they’re saying is true or false. They aren’t thinking or fact-checking—they’re predicting, based on everything they’ve seen before.

It’s not magic. It’s not sentient. But it is very powerful—because it turns raw data into fluent, convincing language in real time.

And it’s only just getting started.

For science fiction writers, the biggest risk of AI is that it will one day become smarter than us—and either accidentally, or by design, try to wipe us out.

QUICK ASIDE: Experts disagree wildly on whether that’s something we should actually worry about.

BACK TO NOW: But whatever the future holds, there are two immediate, real-world risks AI poses today—and they affect everyone:

These aren’t speculative. They’re already happening.

JOB LOSSES: Technology has been replacing workers for centuries. The Industrial Revolution displaced weavers and artisans. The 20th century brought robots to factories and devastated mining communities.

But what makes AI different is who it's coming for.

But large language models like ChatGPT are targeting white-collar jobs once considered "safe" from machines: copywriters, paralegals, accountants, customer service reps, journalists, even software engineers.

THE IMPACT: According to a 2023 report from Goldman Sachs, generative AI could impact up to 300 million full-time jobs worldwide.

The loss of all of those once-safe jobs could continue to drive social unrest both here and abroad. Unless workers fight for protections and their fair share of the profits, the rewards will go almost entirely to the top.

THERE’S MORE: Training and running AI requires staggering amounts of electricity.

And that’s just one model. The day-to-day operation of AI depends on sprawling data centers powered by massive energy loads.

Tech companies love to boast about “green AI,” but many data centers still rely on fossil fuel-heavy grids, especially in the U.S. and Asia. And the race to build even larger models means demand is only accelerating.

Unless we put pressure on the government to ban fossil fuels, our embrace of AI will only accelerate the climate crisis.

OTHER RISKS: Beyond jobs and energy, AI threatens to amplify inequality, entrench corporate power, and become a tool for surveillance and social control—threatening democracies and freedom everywhere.

That being said, AI isn’t going away. The technology is already being built into the tools we use every day—whether we choose it or not.

Because if AI is going to reshape the world, we need to understand how it works—not just to protect ourselves, but to reclaim some power in a system that’s moving fast without our consent.

So here’s a breakdown of AI tools you can start using today—what they do, how to use them, and what they cost.

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