^{Designed in Canva}

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Greetings everyone! Hope you're all doing well. I've been bothered by something for a few days and I'm here to talk about it. I know this is going to stir up controversy just like my last post did on the Steem Watcher community about two months ago. Although I really wanted to post this in the Steem Watcher community again, due to some reasons, I'm sharing it in a different community this time. I hope it sparks a healthy discussion, maybe even leading to a solution, or at least raises some awareness among the moderators about this issue.

Ever since the advertising of ChatGPT and other large language models (LLMs) on social media started, I think hardly anyone connected to the writing profession is unaware of them. Ethically used, these LLMs can greatly assist you and help present your work more effectively. However, today, I'm not here to discuss the 'use vs. abuse' of LLMs—that's a topic for another day.

My focus today is on the reliability of the different tools we use to detect AI-generated content. How do we identify false positives? Should moderators rely solely on detector results to make their final judgment, or should posts be manually analyzed as well?

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Reliability of AI-detectors

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As AI tools advance, so do the AI detectors, becoming increasingly strict. Some are now so sensitive that they often yield false positives, and as a community moderator, I've observed these myself—I've even been a recent victim in one community. For those unfamiliar with the term false positive, in the context of AI detectors, a false positive occurs when the AI detector labels your own written content as AI-generated.

About 10 days ago, I wrote an article in the Steem Alliance community, which a moderator flagged as AI-generated and issued me a warning without attaching any screenshots or proof to support their claim. This was frustrating for me as the article was my own work. I then scanned my article with four detectors I use for moderating posts in my community; all of them declared it human-written. I commented asking for justification, but received no response from the moderator.

Later, I sought justification on the Steem Alliance community's Discord server in the appeal section and was told the moderator was unavailable due to his exams. This led to some heated arguments, and eventually, I had to seek help from a reputed friend who spoke to the Steem Alliance admin to help resolve my case.

After about 24 hours, they finally sent me a screenshot as 'AI evidence,' which you can see below.

Unfortunately, they did not share their AI detection method with me. I urged them to manually analyze the post and not to declare content as AI-based solely on one detector's result. They still didn't acknowledge their mod's mistake, and eventually, they told me no more discussion was needed on this topic. This is why I decided to leave it there and resolved not to post in that community for now because I can't explain to everyone that my content is my own.

Another interesting point is that some communities have moderators who aren't very familiar with the English language; they mostly use translators. If these moderators judge your content as AI-generated just by looking at the tool's percentage, how can you convince them it's your own work? It would be like casting pearls before swine.

Now about false positives. I've observed several posts recently where more than 40% of the content was shown as AI-generated in ZeroGPT, but when you read the post or check the author's history, it's clear the content is originally human-written. Moderators who rely solely on tools find it hard to understand this.

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Example of a False Positive

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Let me give you an example of a false positive. Many of you might know @huzaifanaveed1. I enjoy reading his articles and always try to learn something. He's been an inspiration and has been writing since before ChatGPT was even released. He even won the 2021 Steemit best author award. There's no question of his content being AI-generated, but if you ask the detectors, they might declare the following post as AI-generated, which is ridiculous and clear proof that these detectors are not reliable. Therefore, I'm saying this again you must manually analyze a post before making any final judgment.

_{Post link}

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My AI-content Detection Method

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Here's how I handle AI-content detection. First, I scan the post with ZeroGPT; if the AI percentage is over 70%, then I use Copyleaks, GPTZero, and Content at Scale respectively for further scans. If two out of these four detectors declare it human-written, I take no action. But if three declare it AI-generated, then I manually analyze the post myself. If it feels robotic and lacks a human touch, I declare it AI-generated; otherwise, I do not.

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Reasons Behind False Positives

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As per my observation, false positive results often occur when:

• You write perfect English without any grammatical mistakes.
• Your writing style is more academic or essay-like rather than casual or informal.
• You tend to write in a bookish style.
• Your writing accidentally becomes coherent or follows a robotic pattern.
• When you scan less than 300 words.
• Integration of AI into translation and grammar checking tools.

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Final Thoughts

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To sum up, AI-content detection remains a problem. If we follow the guidelines shared by SC01, we can avoid situations where innocent users are wrongly declared as using AI based solely on detector results.

_{Post link}

Some AI detectors now even offer a premium plan that includes a "humanizer" feature that rewords AI content to evade detection.

Ultimately, it seems we'll always need to rely on manual detection, and this is only feasible if the person analyzing the post is an expert in the language, understands it well, and is familiar with concepts like language diction...

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^{I would like to invite @patjewell, @dove11, @irawandedy, @soulfuldreamer, @event-horizon, @alejos7ven, @the-gorilla and @weisser-rabe to share their thoughts on this matter.}

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^{Author: @waqarahmadshah | Date: 21-Jun-2024 | Achievement 1}