AI Detectors Get It Wrong. Writers Are Being Fired Anyway

Based on the article provided, several elements suggest that the narrative could have been written or heavily influenced by an AI. Below are key points from the article that support this suspicion, each backed by direct citations:

1. *Generic Language and Lack of Specific Detail*: The article describes Kimberly Gasuras’s experience with broad, generalized statements that lack specific, nuanced detail that a human writer with deep knowledge might include. For instance, phrases like "I don’t need it," and "How do you think I did all that work?" are rather cliché and could indicate AI usage due to their non-specific nature.

2. *Frequent Mention of AI and Related Technologies*: The story frequently references AI technologies and tools, which might be a characteristic of AI-written content trying to maintain thematic relevance. The tools mentioned, such as "Originality" and others like Copyleaks and GPTZero, align closely with typical AI text outputs that often include relevant keywords to boost perceived relevance and accuracy of the content.

3. *Narrative Coherence and Flow*: The narrative flows in a structured manner typical of AI outputs, where each paragraph introduces new information in a systematic way without the nuanced transitions we might expect from a seasoned journalist. This can be seen in transitions like, "It was already a difficult time. Then the email came." This kind of straightforward sequencing is common in AI writing.

4. *Absence of Emotional Depth or Personal Insight*: Despite discussing a personal and potentially distressing situation for Gasuras, the article does not delve deeply into her emotional response or provide personal insights that a human writer might include. The statement, "I couldn’t believe it," is as deep as it gets, which seems superficial for someone discussing their own career challenges.

5. *Repetitive and Redundant Information*: The article repeats certain themes and statements, such as the reliability issues of AI detectors and the impact on personal livelihoods. For example, the repetition of the impact of AI on writers and the functionality of AI detectors in multiple paragraphs could suggest an AI's attempt to emphasize key points without introducing new or insightful commentary.

6. *Use of Industry Buzzwords and Phrases*: The language includes buzzwords and phrases typical of AI-related discussions, such as "AI boogeymen," "peace of mind," "proof," and "accountability." These terms are often used to artificially enhance the thematic strength of the content, a common technique in AI-generated texts to align closely with expected keyword density and relevance.

These elements collectively suggest the possible use of AI in crafting the article, particularly in terms of the language used, the structure of the narrative, and the absence of deeper, personalized insights one would expect from a human writer discussing their own experiences.

If you're reading nonfiction, it means you're wasting time reading a lot more words when you could have just read the prompt.

Not quite true for an LLM chatbot with RLHF - it aims to provide the most satisfactory response to a prompt. AI detectors are snake oil to begin with, but they're super snake oil if people are smart enough to include something in their prompt like "don't respond in the style of a large language model" or "respond in the style of x".

> Conceptually it seems like the average of all human texts would be distinct from any users because it would blend word choices and idioms across regions

That's only true in the aggregate. Within a single answer, LLMs will try to generate a word choice which is more likely _given the preceding word choices in that answer_, which should reduce the blending of idioms.

> where most of us are trained and reinforced in a particular region.

The life experience of most of us (at least here in HN) is wider than that. Someone who as a child visited every year their grandparents in two different regions of the country could have a blend of three sets of regional idioms, and that's before learning English (which adds another set of idioms from the teachers/textbooks) and getting on the Internet (which can add a lot of new idioms, from each community frequented online). And this is a simple example, many people know more than just two languages (each bringing their own peculiar idioms).

"I'm sorry, but I am unable to comply with that request": https://suno.com/song/50291ff1-f971-4bff-b10e-fd168161cf3c