The Performance of Human Effort

A friend recently told me about a colleague who submitted a report that was, in their words, obviously written by AI.

What bothered them wasn't necessarily the quality of the report or the accuracy of its contents. It was that the employee hadn't even bothered to make it look like they'd written it themselves.

My immediate reaction was: Why should they?

We've spent years developing tools to make our work easier, and now that we have one capable of producing entire documents, we're apparently expected to spend additional time disguising the fact that we used it.

I don't know much about the report itself. I don't know how it was prepared, whether the employee reviewed it, or even whether it was particularly good. But the reaction interested me because it suggested an emerging expectation around AI in the workplace: using it might be acceptable, but letting other people recognize that you've used it somehow isn't.

What exactly are we accomplishing with that expectation?

An Email That Does Its Job

Consider something as simple as writing an email.

You've been going back and forth with a vendor, trying to get an answer to a straightforward question. Maybe you're frustrated because you've already asked twice. Maybe you're tired, distracted, or simply don't want to spend another ten minutes figuring out how to phrase something that should take two sentences.

So you use AI.

You explain what you need, perhaps vent a little about the situation, and ask it to turn your thoughts into a professional email.

Seconds later, you have a clear, polite message that asks exactly the question you need answered.

You review it and hit send.

The recipient might recognize the familiar phrasing of AI-generated writing. Perhaps it's a little more polished than necessary or includes expressions that have become synonymous with ChatGPT.

But does that matter?

The question still needs answering. The information being requested hasn't changed. And the relationship might actually be better preserved because you didn't send the passive-aggressive message you were tempted to write.

In that situation, AI hasn't necessarily made your communication less authentic. It may have helped you communicate your actual intentions more accurately.

Your goal wasn't to express frustration. It was to get an answer while maintaining a productive relationship.

Would spending another five minutes rewriting the message to sound less like AI have improved anything?

The Performance of Human Effort

We're introducing technology specifically designed to reduce the effort required to accomplish tasks, then creating expectations that require people to perform additional work to disguise the fact that they've used it.

Imagine two employees preparing the same report.

The first uses AI to generate a draft, reviews it carefully, verifies the information, and submits it unchanged.

The second generates a similar draft but spends twenty minutes rearranging paragraphs and removing recognizable AI phrasing.

Assuming both reports are accurate, clear, and appropriate, has the second employee created more value?

Not necessarily.

They've performed more visible labor. But if their edits haven't improved the report, they've simply made it appear more human.

And somehow, that might make their contribution seem more legitimate.

We've spent generations developing tools to eliminate unnecessary work. Calculators reduced the need for manual arithmetic. Spreadsheets transformed financial analysis. Spell-checkers made professional writing more accessible.

We don't expect someone to redo a calculation by hand just to demonstrate they could have performed it without a calculator.

Yet with generative AI, we're sometimes uncomfortable when the technology does exactly what it was designed to do.

Perhaps that's because writing and communication have traditionally been treated as distinctly human contributions.

But just because a tool can perform part of that work doesn't mean the human contribution has disappeared.

Better Tools Don't Make People Less Valuable

Imagine an experienced HVAC technician who's spent twenty years diagnosing and repairing commercial heating and cooling systems.

They can walk into a mechanical room, listen to a compressor, inspect a few components, and identify a problem that might take a less experienced technician hours to diagnose.

They understand the equipment, recognize patterns of failure, and know which repairs will actually solve the problem.

They're exceptionally good at their job.

But at the end of the day, they're expected to produce a detailed service report explaining what they found, what they repaired, and what the customer should do next.

And maybe writing isn't their strength.

Their reports might be technically accurate but difficult to follow. Important details might get buried in shorthand, or their recommendations might not clearly communicate why a particular repair matters.

Now imagine that technician uses AI to turn their field notes into a clear, organized, professional report.

The AI didn't diagnose the equipment. It didn't identify the failing component. It didn't draw on twenty years of experience to recommend the appropriate repair.

The technician did all of that.

AI simply helped turn that expertise into something the customer could understand.

Perhaps the resulting report is substantially better than anything the technician could have written independently.

Does that make the technician less valuable?

Their knowledge, experience, and professional judgment remain essential. The tool has simply made those contributions easier to communicate.

The technician spends less time struggling with documentation, and the customer receives clearer information.

That's not a failure of professional responsibility. That's a successful use of technology.

The value of an employee shouldn't be measured by how much of their work they could have done without the tools we've given them.

We're Still Figuring This Out

Part of what makes this conversation difficult is that we're still figuring out how AI fits into everyday professional life.

The tools are changing constantly, and organizations are still developing policies and expectations around their use.

Yet we're already forming strong social judgments.

Using AI to brainstorm might be considered resourceful. Using it to organize information might be considered efficient. Using it to polish a few sentences might be perfectly acceptable.

But using it to write an entire document?

Suddenly, that might be interpreted as lazy or unprofessional.

Where exactly is the line, and what makes that distinction meaningful?

Different situations demand different standards. An academic dissertation intended to demonstrate original research has different expectations than a routine operational report or an email to a vendor.

And none of this is an argument for blindly accepting whatever AI produces.

These tools can invent information, misunderstand context, and present inaccurate conclusions with remarkable confidence. Employees should understand what they're submitting, verify important details, and follow their organization's policies.

But that's a question of accountability, not simply authorship.

A report rewritten to sound human can still contain serious errors. An AI-generated report submitted without stylistic changes can still be accurate, appropriate, and thoroughly reviewed.

We can't determine how responsibly someone used a tool simply by looking at whether the final product resembles that tool's typical output.

Shouldn't we be evaluating the work itself?

Is it accurate? Is it useful? Does it communicate what it needs to communicate? Has the person responsible exercised appropriate judgment?

Those seem like more meaningful questions than whether someone bothered to remove a few recognizable phrases.

Learning to Recognize Human Value

I keep coming back to that original conversation about the AI-generated report.

Not because I know whether the employee used AI responsibly. I don't.

But because the reaction revealed something about how we're approaching this technology.

We're quick to recognize when AI makes something easier, but we're not always comfortable with what that ease implies.

If a task that once required an hour can now be accomplished in five minutes, we might celebrate the productivity improvement in theory while questioning the employee who actually takes advantage of it.

Perhaps we're still accustomed to treating effort as a proxy for value.

But effort and value have never been the same thing.

Someone can spend hours producing something inaccurate or ineffective. Another person can use the right tools, apply sound judgment, and produce a better result in minutes.

The second person hasn't necessarily contributed less. They've simply worked more efficiently.

And isn't that what we've been trying to accomplish with technology all along?

AI is changing the relationship between effort and output in ways we're only beginning to understand. There will be mistakes, uncomfortable adjustments, and legitimate disagreements about where these tools belong.

But we should be careful not to create expectations that undermine the benefits we're trying to realize.

If someone uses AI to communicate more clearly, produce better work, or accomplish something more efficiently, perhaps our first instinct shouldn't be to question how much of it they personally wrote.

Perhaps we should start by asking whether they did their job well.

The challenge isn't learning how to make AI-generated work look more human.

It's learning how to recognize human value when effort becomes less visible.