Who remembers when: Instagram feeds were full of posts asking, “Hot dogs or legs?”

If you don’t, it was a thing, I promise.

It looked a little something like this:

Why am I bringing up such important social media memes of the mid-2010s? Because, as silly as guessing whether an image represents two hot dogs or a pair of slick, tanned legs, it feels like the “is it AI or is it human” phenomenon we’re all living in is quite similar. However, the stakes for the latter are higher.

While using AI to enhance thinking and increase high-value output should now be table stakes, this shouldn’t come at the cost of humans still presenting themselves as thoughtful, intelligent and discerning.

I use AI all the time.

I’m learning, evolving and getting better daily.

I’m thinking strategically about new ways to use it to my advantage, professionally and personally (an aside, Claude has become an AWESOME weekly meal planner 👩‍🍳).

But what I don’t do is pass off outputs without my own thinking. When faced with rushed scenarios or points that require a quick gut check, I’ll disclaim if I’m sending a response directly from AI and indicate I’ll take a deeper dive when time allows.

The proliferation of AI adoption has given rise to countless examples of taking AI outputs at face value and shipping them as is. We’ve all heard about and experienced the AI slop fest. It’s not a pretty look.

Today, I’m sharing the most obvious tells I’ve observed across scenarios.

Maybe these help you better detect AI-only materials.

Perhaps they encourage you to infuse your humanity.

They say there’s no such thing as bad PR, right? If that’s true, the em dash has had a spotlight moment since ChatGPT came on the scene. There’s no shortage of rage posts, articles or people editing content with the comment: “Everyone’s going to know this is AI because of the number of em dashes you used in one paragraph.” Even still, it shocks me how much I see AI-generated text copied and pasted with excessive use of this choice punctuation.

Make it human: Provide your LLM instructions in personalization settings and include “sparse use of the em dash.” Take the time to proofread and edit AI-generated outputs before sending them to teammates, clients, investors or publishing content more broadly.

Claude builds you an artifact, complete with formatting and tables. Then, it’s time to export and send, right?

The problem I notice?

The receiver views weirdly formatted bulleted lists that don’t match how a normal Word or Google Doc format bullet points. If details need to be added, it’s not a simple “return” and “add bullet point.” The tables are finicky and challenging to reformat if you need to make a change. The colors and fonts don’t match the brand.

It’s not always the substance of what’s sent; it’s the presentation. By not refining the output, the sender may be inadvertently creating more work for the receiver.

Make it human: Anything with your name on it is a reflection of your standards. An AI-produced artifact is a strong starting point, but it’s rarely the finish line. Be a strong editor. Think about the consumer(s) of the work product.

Don’t get me wrong, AI is extremely effective at cutting time to completion, especially for commonly created and similarly structured documentation. But, without the proper foundational knowledge, the AI-generated process document may have no bearing on the business at hand or on how work actually flows in the specific circumstances.

Make it human: AI doesn’t know your business. It knows about business broadly. The difference between generic documentation and something that your team can adopt lies in the context you bring to the prompt, the point of view you infuse and the judgment you apply in refining the output.

Let me start with the disclaimer that I’m not providing legal advice here.

I’ve noticed another tell on this topic, though.

A contract gets sent to someone who isn’t an attorney. The sender is generally familiar with the receiver's speech and tone. When that receiver returns the contract with their questions and comments, there’s a long email cover with the most buttoned-up and precise language. The sender no longer recognizes the “person” behind the words.

Make it human: AI as a gut check is useful. Make sure you actually understand what the output means. If you don’t, dig deeper and/or consult a legal professional. When returning comments, take care to (1) translate back into your voice and (2) make sure you can stand up to each word when questioned.

This one can be harder to spot if you don’t already know the sender’s assumptions or hypotheses.

A user will feed an AI tool information, and then ask for a synthesis of market research on a particular topic. For the sake of this example, let’s say it’s competitor research for a product. The output is a well-constructed artifact, with information about the market landscape, capability comparisons and an assessment of how this product adds value to the ecosystem.

The only problem?

It sounds too much like a parrot.

The same three things the user previously input as hypothesized unique value propositions are exactly what the AI-generated output identifies as the product’s wedge. Or, better yet, sources are cited and linked, but the links lead nowhere or are unverifiable.

Make it human: Don’t take your LLM’s research at face value. Read it through a critical lens, ask it to explain its work and research process. Check the citations. Use AI as one input to the research process, not the only one.

In a range of scenarios, it should probably be both.

Your voice, judgment and experiences aren’t optional nice-to-haves. Whether you incorporate them or not sends a signal every time something goes out with your name or business attached to it. Your ability to harness them well is your edge. Use that to your long-term advantage.

P.S. - All the images displayed above are AI-generated, with a touch of Jessica flair and humor.

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