There are a few general characteristics that may help you spot if a text was written by a machine learning model or by a human:
Fluency: One characteristic that may help you spot if a text was written by a machine learning model is fluency. Machine learning models are often able to generate texts that are fluent and grammatically correct, but they may not always produce texts that sound natural or idiomatically correct to a human reader. For example, a machine learning model might generate a sentence that is grammatically correct, but sounds awkward or stilted when read aloud. This is because machine learning models are not able to fully replicate the nuances of human language and may not always understand how words and phrases are used in different contexts.
Repetition: Another characteristic that may help you spot if a text was written by a machine learning model is repetition. Machine learning models may repeat words or phrases more frequently than a human would, particularly if the model has been trained on a limited dataset. This can lead to a text that is repetitive and lacks variety, which may be noticeable to a human reader.
Lack of variation: A third characteristic that may help you spot if a text was written by a machine learning model is a lack of variation in the words and phrases used. Machine learning models may have a limited vocabulary and may not use a wide range of words and phrases, leading to a lack of variation in the text. This may make the text seem repetitive or monotonous to a human reader.
Lack of context: A fourth characteristic that may help you spot if a text was written by a machine learning model is a lack of context. Machine learning models may not always have a strong understanding of context, and may produce texts that lack coherence or logical progression. This can result in texts that are difficult for a human reader to follow or that seem disjointed.
It is important to note that these characteristics are not definitive and there are many factors that can influence the style and quality of text generated by a machine learning model. In addition, as machine learning models continue to improve, it may become more difficult to distinguish between texts written by machines and those written by humans.
