How do you distinguish AI content from real, human-made content?

The patterns Nika describes show up clearly in financial analysis too. AI-generated financial content tends to be structurally fluent but contextually flat — it can explain what a DSCR is, but it struggles with the judgment call: given this specific lender, this specific project, and this macro environment, what should the DSCR floor be, and why does it differ from the standard covenant? That requires having sat across a credit committee, not just having processed thousands of credit papers.

The tell I notice most: AI financial content defaults to the median. It gives you the textbook answer, not the deal-specific one. A practitioner knows that a 1.20x DSCR floor might be appropriate for a contracted solar project with an investment-grade offtaker, and completely wrong for a merchant wind project in a volatile power market — same metric, fundamentally different answer, and the difference requires experience the model doesn’t have.

For distinguishing it in documents: AI reads as authoritative on concepts but vague on specifics. Real deal analysis tends to be the reverse — telegraphic on the concepts (your reader knows what a DSRA is) but precise on the numbers, the counterparty, the stress case logic, and why those particular assumptions were chosen. That specificity is hard to fake at volume.

Is it important to do so? Or is it enough to apply validation and good judgement to everything you read?

for a small videos like a 30 second or less than 2 minutes. If content is not ridiculous and done it with proper care. It's near to impossible for a layman to identify if it's AI or humanize.

Also now AI is giving humanize context as well. We are move to a towards a reality which was unimagine to a wide part of world just a decade ago.

interesting that this thread is all text / image / video and nobody's touched audio yet, which is the dimension i think about most (we work on AI music).

the music tells are pretty specific once you know what to listen for:

• the mix is surgically clean. real recordings have some room noise, mic bleed, a breath, a fret squeak. AI tracks are silent in between hits in a way no real recording is.

• timing is too perfect. a real drummer pushes or drags by 5–15ms depending on the section. AI is dead on the grid every beat.

• arrangements are weirdly symmetrical. 8 bars verse, 8 bars chorus, 8 bars verse. real songs sit on a bar longer than expected, drop out, breathe.

• and the giveaway nobody mentions: emotional register stays flat across the whole track. real artists shift dynamics hard, soft verse, big chorus, breakdown to almost nothing. AI keeps the energy graph oddly even.

it's the same "too perfect" tell @mikita_aliaksandrovich and @maliikb pointed at, just for ears instead of eyes. on the maker side we spend most of our time trying to inject those imperfections back in on purpose. Funny problem to have.

I think AI-generated content becomes easier to notice when everything starts sounding too polished and emotionally “safe.” Repeated structures, predictable wording, perfect grammar, and overuse of formatting patterns are usually the biggest signals for me.

But at the same time, many human writers are now influenced by AI writing styles too, so the line is getting blurry. The future probably won’t be about detecting AI perfectly — it’ll be about identifying originality, personality, and real experience behind the content.

The same applies to images and videos. Once you notice repeated visual styles, unnatural motion, overly smooth skin, or “too perfect” compositions, AI patterns become more visible.

I’ve been exploring how digital platforms and informational websites are evolving with this shift as well through projects like https://ekipportals.tr/ — especially how users engage with online content and trust signals today.

Glad that someone else feels the same, especially with LinkedIn, every other post I see is basically AI crap. Every other post you see is AI. It is genuinely creepy. You kind of lose interest in reading those posts, because there's no emotion in there, no genuinity. Also, I see more and more people AI-ing their reactions, like something happens, you post your reaction to AI, and then it generates a long paragraph.

Since you asked,

1) When we’re so flooded with AI-generated content, do you have any methods to recognise it?

Yes, you can easily understand it

• Em dashes

• Short sentences (2 or 3 words), half-baked sentences, excessive use of fillers

• Z happens, not because X, but because Y

• And honestly, blah blah blah

• X matters, only if Y is done properly

• No typos, grammatical errors, or idiosyncratic punctuation

• No humor, sarcasm, or genuine personality, you'll also see that AI writing often avoids controversial stances, or anything that could potentially be deemed "problematic"

2) But what about beyond text, like images or video?

• This one's a bit tricky, most of the times you'd be able to flag AI generated images and videos, but it is getting tougher, we have to admit that

• Personally, for videos, I watch the lip movements closely most of the times, it works

• And for images, watch out for the lighting, shadows etc

Some are obvious, you'd be surprised how less of an effort someone makes to fix the content generated by AI

Few are difficult but if you LLMs regularly you'll get a sense

I do believe AI content will get better and more inrecognizable but at the end its less about content and more about the thought behind it, if you are outsourcing thinking to LLM then that will catch up very soon

I think the stronger test is not “can I spot AI?” but “can I spot absence of lived context?”

The tells I notice most are generic confidence, no concrete tradeoffs, no scar tissue, and a rhythm that never changes. Human writing usually has unevenness: a specific example, a sentence that carries a personal bias, or a detail that only appears because the person actually did the thing.

So I’d look less at punctuation and more at whether the piece contains decisions, constraints, and consequences.

I think the bigggest problem with AI is too perfect.English is not my first language,so i rely a lot on AI to express myself.But sometimes it makes me feel like i am speaking like a robot.
For me,whether i can tell if something was generated by AI heavily depends on how familiar i am with the area.If it is a field i know well,i can quickly spot AI-generated content.But if it is something i know nothing about,i am much more likely to trust the information.

It is getting harder every day! I find that perfection is often the biggest giveaway. Human writing usually has more idiosyncrasies and varied sentence lengths that AI tends to smooth out. The uncanny valley of text is definitely real.