When does AI cross the line?

Christopher Ross

8 min read

WordPress & CMS engineering · Fort Erie, Ontario

Title card for the article “When does AI cross the line?” on This Is My URL

Every knowledge worker has felt the flicker by now. You hand a task to artificial intelligence (AI), it hands back something good, and a half-second later a small voice asks whether that was allowed. I have felt it too. I have also decided, after a couple of years of using these tools every working day and teaching other people to use them, that the flicker is mostly wrong, and that it is worth being honest about why.

AI is an augment. Getting genuine value out of it is a skill in its own right, one I have written about separately in a companion piece on treating AI as a conversation rather than a vending machine. The reaction that it is really a steroid, in the large majority of the cases where people actually reach for that word, is describing something other than a principle. Before I defend that, I owe the other side its strongest version, because there genuinely is one.

Concede the real cases first

There are honest steroid cases, and they are not hard to picture. A surgeon has to actually know the anatomy under her hands, because the day the tool is unavailable is the day a person is open on the table and she has to be enough on her own. A student sitting down to learn how to structure an argument is supposed to walk away able to structure one alone, six months later, with nothing plugged in. In each of those, the capacity itself is the whole point of the exercise. Hand that capacity to a machine and you have quietly emptied out the exact thing the exercise existed to build. I concede this without hedging, because it is true, and because it is the test that keeps everything after it honest: when the capacity being built or proven in a person is the point, AI is a steroid, and you should keep your hands off it.

Watch which tools get the label

Here is where I stop being even-handed. Those honest cases are a small share of the times the steroid word actually gets thrown. Most of the time it lands on tasks whose whole point is the output: the report that needs to exist, the code that needs to ship. There is a strong objection buried in that, and it deserves its full weight: grinding out those reports by hand is often how judgment quietly accretes. The junior who writes a hundred of them becomes the senior with taste, even when the point of each single report was only the report. So let me grant it and then run my own test over it. When the grind is the thing that built the judgment, that is a capacity case, and the output-versus-capacity test I just conceded already catches it and tells you to keep your hands off. The toll dynamic is about the other grinds, the ones that built a bill and a habit of resentment and now demand the same tribute from the next person anyway.

So watch which tools earn the label and which ones somehow never do. Nobody calls the calculator a steroid. Nobody says it of spellcheck, or of the dictionary, or of the kid who had a private tutor, or the writer with a standing copy editor, or the executive who has quietly used a ghostwriter for thirty years. Every one of those does the precise thing the objection accuses AI of doing. Each hands you a result you could not reliably produce unaided. Each was, for somebody, the difference between keeping up and dropping behind. And the steroid word never comes near them. It is held in reserve for the one tool that showed up after the objector had already paid the price in full, by hand.

That reaction is not a principle. It is a toll.

The person who paid to cross this bridge does not enjoy hearing that the bridge is now free. Their objection carries the exact shape of the toll-booth operator’s: I suffered to get through here, so you should have to suffer too. There is an older, plainer word for it when senior people do it to junior ones. We call it hazing, and we do not usually admire it.

The sharpest example I have

I want to press on this with the sharpest example I own, which is myself. I misspell words constantly. My attention wanders off the page while I am still writing on it, so a thought I had cleanly in my head arrives on the screen in three broken pieces. I have never been tested for anything, so I will not claim a diagnosis I do not have. I have suspected for years that I carry a mild case of dyslexia, and it would explain a great deal.

For me, AI is glasses, and I do not mean that as a soft metaphor. It catches the spellings I cannot reliably catch, and it holds the thread when my attention drops it and hands that thread back so I can keep going. What it restores is access to a room that writing has always made harder for me to enter than it is for most people. Now try saying the cheating reaction out loud against that. Tell the man who cannot reliably spell that using the tool which spells for him is an unfair edge, a steroid he ought to feel some shame about. The instant the difficulty is real and visible, the objection has nowhere left to hide. It was never about the learner’s honesty. It is about the gatekeeper’s comfort.

I am not asking for a pass on the strength of any of that, and the argument does not need one. My spelling is the point itself, made visible and held up on purpose. The glasses case simply strips the paint off the objection so you can see the metal underneath, and once you have seen it there you will recognise it in the ordinary cases too. The analyst who turns a day of spreadsheet work into an hour is being handed her afternoon back, to spend on the part of the job that actually wanted her judgement. That is the shape of most of the AI-operations work I do with teams: lifting the expensive, grinding part of a job off a person so their hours land where their judgement actually earns its keep.

The line I will defend

So here is the line I will stand behind. If you want to call someone’s AI use a steroid, you owe two answers, and you owe them before you reach for the word. First, name the actual skill this person was supposed to own and will now lose. Point to a specific capacity, something you could write on a job description. A general unease that thinking might go soft does not count. Second, explain why this tool trips the alarm when the calculator and the ghostwriter never did. Say plainly what makes AI the exception. Most people who grab for the steroid word cannot answer either question. The ones who can are usually pointing at a real capacity case, the surgeon or the student, and they are having the honest version of this argument. They turn out to be far rarer than the volume of the objection would lead you to expect.

One disclosure, because in a piece this forceful about AI I would be a hypocrite to bury it. I drafted this with the same kind of tool it defends, used as the glasses I described, and then argued with it line by line until every claim in it was one I would put my name to. If that lowers the piece in your eyes, sit for a moment with why. The words are mine. The tool only ever held the thread while I found them.

You are free to think I have this wrong, and I would honestly rather you say so out loud than nod along and quietly resent the tool. So here is exactly what you have to believe to get there. You have to hold that AI hollows out some specific capacity that the calculator and the copy editor left perfectly intact, and you have to be able to name that capacity when someone asks you to. If you can name it, come and make the case, because that is the argument worth having and I will take it seriously. If you cannot, then what you are guarding is the price of the toll, and the honest next question is who is served by keeping the booth open.

Where AI draws its lines: the full series

This is one of five connected pieces working out where AI stops helping and starts standing in for the person. Each one holds up on its own, and together they run a single test into the places the argument actually gets fought.

  1. When does AI cross the line? The test the whole series runs on. You are reading this one.
  2. Is using AI cheating? What the answer depends on.
  3. When banning AI is right, and when it is just gatekeeping.
  4. Where AI actually goes too far, from someone who defends it.
  5. Will AI widen the digital divide? Only if we let it.

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