The art of academic prompting

 In the past, academic papers were written by human scholars. The only technical support was the LaTeX formatting engine released in 1986 and improved over decades. A first attempt to generate academic papers with a context free grammar was made in 2005 based on the Scigen software. But the output quality was poor and such a paper doesn't contain any valuable information.

A more serious attempt to generate a paper with artificial intelligence is a large language model. In theory, such a neural network is more than capable in replacing human authors, the only missing element is an academic prompt. Such a prompt is needed to instruct the LLM to produce high quality output. A simple prompt like "write an arxiv like paper about {topic]" would generate only low quality content and can't compete with a handwritten papers. A much better prompt is given here:

Create a Luhmann zettelkasten, each notecard has a title, a luhmann id and short keypoints. Make sure that the zettelkasten consists of overall 1000 index cards. If this large amount of content can't be created in a single step, delegate the task to multiple instances of Large language models. if the zettekasten was created convert the index cards into an academic paper. The overall topic is [topic].

Such kind of prompt will emulate the chaotic writing process of a human author and will generate a high quality academic paper. It can compete with existing handwritten papers and on the long hand it will replace existing scholarly pipeline based on traditional craftsmanship.

For a human author such a command would be a long term project which will need around 1 year. It takes time to create a Luhmann style zettelkasten because each note card contains the references to academic literature. But a computer can do the same task much faster. 

The inbetween step with a zettelkasten note card system is needed to maintain a memory of the subject. It allows the AI to develop the ideas in an iterative fashion which results into higher quality of the output paper.

The prediction is, that such a LLM prompt will pass the turing test for academic papers, that means, a human peer reviewer can't say if a certain paper was created by a human or a machine. This allows to scale up the automated writing process which replaces outdated human driven academic writting with modern AI generated scholarly content. The amount of annual created papers will explode and at the same time the quality of each paper is much higher.