Editorial Generative artificial intelligence as a plagiarism problem

How to give credit to the nameless authors whose texts were included in the training set.

Below 1%.

The ELIZA program from the 1960s.

Examples in its training set, the wording of the query, and an element of mindless randomness.

Anecdotal accounts suggest a lower accuracy rate.

It can lead to poor scholarship and potential moral breaches.

It can source ideas from unpublished materials without attribution, raising concerns about AI plagiarism.

The software paraphrases it and adds its own text, suitable for a student paper.

A conscious claim of ownership by the author of the idea.

It condenses and summarizes vast quantities of text written by humans.

Citations can be hallucinated or fabricated, leading to inaccuracies.

Authors must declare if an idea is received from ChatGPT output.

It generates new outputs that can differ substantially from previous ones.

It may produce false statements by regurgitating common structures from its training set.

It provides a stepwise solution rather than a typical human response.

Uncontrolled plagiarism.

It highlights the potential for AI to exacerbate issues of academic misconduct, particularly plagiarism.

Hallucinations.

It may summarize content without providing proper citations for the original works.

Because it can generate outputs that may unwittingly plagiarize from online sources.

Generative AI does not involve any kind of reasoning.

Determining intent in cases of plagiarism.

The intent behind appropriating an idea known to belong to another.

It indicates that the program may have specific code to handle queries about copyrighted material.

Authors must remember where they first encountered an idea and maintain confidentiality or declare credit as necessary.

It provides access even when demand is high and includes GPT-4.

It complicates giving due credit, leading to potential plagiarism.

Be transparent about AI usage and declare when AI is the source of an idea.

It represents the fundamental unit of the model, which could be a word or larger units of text.

A free plan and a Plus version for $20/month.

It's difficult to know if the output is derived from a single source or synthesized from many.

The author did not use generative AI technologies for the preparation of this work.

Its implications for facilitating plagiarism.

To seek out and cite prior claims to ideas in the published literature.

Presenting the words, ideas, or images of another as your own, denying creators the credit they deserve.

By predicting the probable next token based on a query and iteratively appending text.

1. A single source, 2) multiple sources, 3) scripted responses, 4) user queries, 5) randomness in algorithms, 6) inchoate patterns across sources.

It is only 26% accurate at detecting AI text and mislabels human text 9% of the time.