What IT Is

As a writer who has (rarely) been paid for the craft, I find attribution to be not only important, but a moral obligation. Especially when the quote resurfaces in my thinking time and again.

I first read “There are three kinds of lies: lies, damned lies, and statistics” in a Robert Heinlein novel, where he (through his character) attributed it to Mark Twain. Samuel Clemens actually attributed this truism to someone else, though that providence has not been agreed upon by scholars (per Wikipedia), so I will leave this instance of noblesse oblige as having made my best effort. But I digress (a specialty of mine).

Despite my failed attempt at correct attribution, it’s still true. And it is being proven once again, in the various reports and claims around AI. Allow me to categorize them as I see them today:

1. Lies

…are that AI will be able to do X by N. No one really knows how long. Extrapolating future data based on similar but different prior data has an unknown margin of error. This is why every honest company states at the beginning of their demo or presentation or pitch that you should not base purchase decisions on functionality not currently released (and I would add not proven for your specific use case).

2. Damned Lies

…are about what people are accomplishing now. The app vibe coded in a weekend is either going to be feature frozen in the near future, suffer a major failure through bad coding or bad actors, or (most rare) be the result of extensive planning prior to the weekend of wonder.

“The ‘vibe-coded’ apps that fail are not failures of code, but failures of craft.”

3. Statistics

…are the worst of the three, because anyone with half a brain and less scruples can get the same numbers to say entirely different things, like:

• MIT report: 95% of generative AI pilots at companies are failing.

• 56% get nothing from adoption.

• Two-thirds of nonmanagement staffers said they saved less than two hours a week or no time at all with AI, while over 40% of executives reported saving more than eight hours weekly.

• Enterprise AI adoption grew with worker access rising 50% in 2025.

• 60% of executives report AI boosts ROI/efficiency.

• Corporations plan to double AI spending.

Lies Aside

What we call AI (usually) isn’t actually AI. What everyone is calling AI is still the biggest paradigm shift in Information Technology since computers shrunk from needing a room to sitting on a desk (and, not long after, a lap).

Impacts to humanity are a physics phenomenon in that every positive improvement has an equal and opposite potential that will eventually be realized. Whenever the many benefit, a very few benefit a lot more. Some deserve those benefits, and some don’t.

The Mirror and the Machine

We find ourselves at a peculiar crossroads where the technology is accelerating faster than our ability to tell the truth about it. We are told AI is a magic wand, a job-thief, or a savior, but the “Lies, Damned Lies, and Statistics” reveal a simpler reality:

“AI is not a destination; it is a mirror.”

The statistics that show executives “saving eight hours a week” while workers save none aren’t an indictment of the technology—they are an indictment of how we value human time. When we strip away the marketing gloss and the manipulated ROI reports, we are left with the same struggle that has defined every Information Technology shift since the first mainframe: the tension between efficiency and agency.

The Paradox of Progress

If my “physics phenomenon” theory holds true, the equal and opposite reaction to the AI boom will be a renewed, premium demand for the irreplaceably human.

“AI makes it remarkably easy to be mediocre at scale.”

The paradigm shift isn’t just about computers moving from desks to our pockets, or from pockets to our cognitive workflows. It can generate the lies, the damned lies, and the statistics for us in seconds. But it cannot provide the providence of a thought. It cannot feel the moral obligation of attribution. It cannot understand why a quote from a Heinlein novel matters to a writer’s soul.

The New Bottom Line

We should stop asking when AI will “arrive” or if the pilot programs will finally hit their 100% success rate. Instead, we should ask: Who is being served by the current narrative?

If the many are to benefit—and not just the few—we must look past the “weekend of wonder” and the padded ROI spreadsheets. We must demand a version of progress that doesn’t just prioritize the speed of the output, but the integrity of the outcome.

The lies will continue to evolve, and the statistics will continue to shift. But the truth remains:

“A tool is only as profound as the intent of the person wielding it.”

The question isn’t what AI can do for you by 2030; the question is what you are willing to stand for today while everyone else is busy chasing the vibe.

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