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Will AI Be Able to Write Essays for Students in the Future?


Essay writing is something that we all have done as students. And frankly, I did not like drafting new essays on some boring topics every week. I am sure a lot of students feel the same way about essay writing. Unfortunately, students do not have any option besides writing their own essays. However, the future may not be the same for the students.

Artificial intelligence has made a lot of things possible in the past few years. And if you are wondering whether AI can write essays for students in the future, we cannot discard the possibility of such a technology. In fact, there has been a lot of development in the field of content creation lately, which indicates the possibility of having an AI-driven essay typer in the future.

AI and creative writing – the progress so far

Artificial Intelligence has great potential in automating numerous tasks. We have already seen how automated proofreading tools can find errors in the content and improve the quality of writing. Not to forget the auto-filling feature on our phones that accelerates the writing process. And these are just the tip of the iceberg.

Popular media organizations, including Associated Press, The Washington Post, The New York Times, and Yahoo! Sports have already started to use AI technology to create content. According to a current report, the Press Association produces 30,000 local news stories every month, using AI technology.

It is important to note that there are some massive differences between news stories and essays. News stories generally follow the formula of “five Ws and one H”, where essays usually take a creative approach. However, AI is now going beyond the formulaic writing and making its way towards a more creative form of writing with Natural language generation (NLG).

What is natural language generation?

Natural language generation is an AI-powered technology that involves creating a language from non-language inputs. In other words, it is the process of generating meaningful phrases and sentences in the form of natural language.

The technology automatically produces narratives that describe, summarise, or explain structured data in a creative, human-like manner at unparalleled speed. So, if that technology can be personalized, students may be able to use automated essay typer soon.

How does NLG work?

Natural language generation is already being used to create data-driven financial reports, meeting memos, product descriptions, and a lot more. Currently, NLG can summarise data from analysts to automatically write reports that are personalized for the audience.

To understand NLG, you need to understand how it works. To mimic human speech, the NLG system uses different methods and tricks to adapt writing style, tone, and structure used by human writers, as well as the content and purpose of the narrative. Initially, the NLG process had three stages:

  • Stage 1: Document planning:
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This stage involves deciding what needs to be said and generating an abstract document that outlines the structure of the data to be delivered.

  • Stage 2: Micro-planning:

This stage involves the generation of referencing expressions, word choice, and aggregation to give shape to the document specifications.

  • Stage 3: Realisation:

The final stage converts the abstract document specifications to an actual text, using the understanding of syntax, morphology, etc.

With time, technology has evolved. This is why the specific steps and approaches can vary significantly now. All the approaches taken by the NLG system is discussed briefly:

1. Simple gap-filling approach:

This approach is one of the oldest ones on the list. If the texts already have a pre-defined structure and require only a small amount of data to be filled, this simple fill-in-the-gap template system can fill those gaps with the data received from database table entry, spreadsheet row, etc. Unfortunately, this approach has limited use and is not considered to be “real” NLG.

2. Scripts or rules-producing text:

The simple gap-filling systems were improved with common programming constructs via a scripting language or by using business rules. The scripting approach sets in a template inside a general-purpose scripting language. This enables the complex conditionals, access to code libraries, loops, etc.

The business rule approaches, which are used in document composition programs, function similarly as the scripting approach, but focus on writing business rules. Even though they have more powerful gap-filling abilities, they lack linguistic capabilities, and cannot create complex texts.

  • Word-level grammatical functions:

A logical development of the template-based system was due for a long time. And when it came to practice, it was adding word-level grammatical functions to handle morphology, orthography, morphophonology, and most importantly, to handle possible exceptions. Thanks to these functions, it was easier to create grammatically correct texts and develop complete template systems.

3. Dynamic sentence generation:

The next step in NLG development was to move from template-based approaches to dynamic NLG. The dynamic sentence generation approach creates sentences dynamically from representations of the intended meaning of the sentence and/or its preferred linguistic structure. In this approach, the system performs sensibly without the need for explicitly-written codes for every boundary case. It even lets the system optimise sentences more linguistically.

4. Dynamic document creation:

Dynamic sentence generation works at a micro-level. At the macro-level, the system produces a document that is both relevant and useful to the readers while having a well-structured narrative. The procedure depends on the goal set for the text. While persuasive writing is based on the models of argumentation and behaviour change to imitate human rhetoric, a business report may be based on the analysis of key factors that influence the outcome.

As NLG continues to evolve, we will see a more diversified and effective performance from it in creating text in human-like approach. That means the possibility of having an AI-powered essay typer in the near future is very high.

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The limitation of AI-written content

As of now, the AI-generated content is far from perfect. Even though NGL is now able to understand the tone and theme from a couple of sentences from a text and create a few paragraphs of content, the mistakes in it are hard to ignore.

In a recent study conducted by The New Yorker, it was tested whether the AI technology could create an article that would meet its high publishing standards. So, they used GPT-2, an AI tool to feed the necessary data to produce an article.

The test suggested that AI technology could generate grammatically correct sentences. However, it did not have the ability and skill to reason and conceptualise. When it comes to creating articles for The New Yorker, both of those abilities are quintessential.

Coming back to the topic of AI-driven essay typers, it is quite clear that there’s technology to create content. But whether the content will be well-conceptualized or not – that’s the question.

What should students do for now?

Interestingly, there are several websites which are currently offering essay generator as a free tool. However, those tools don’t really create the essays from scratch. Instead, they deliver the closest match of the input data from their repositories.

There are several essay writing services as well, which have human writers to prepare sample solutions for students. Students cannot submit the solution as it is since that would be unethical. However, they can study the sample and draw inspiration to create their own solution.

Moreover, there are several AI-powered tools that can help in essay writing. If you are a student and need some assistance with essay writing, you can try these following tools.

  • Grammarly:

Even though this tool does not write the essay for you, its sophisticated features allow you to improve your content. It detects spelling and grammar mistakes and also offer suggestions for improvements.

  • Ai:

If you need to rework on an essay, you can simply use this tool to generate a fresh and original content out of the existing one. It basically paraphrases your content without changing the essence of the content.

For the time being, this is the best you can get from AI technology.


From the speedy evolution of natural language generation system, it is quite evident that the AI technology will soon be able to create meaningful and structured essays using the basic inputs from the users. The AI-written content is already being used in a number of domains. Needless to say, the development of an intuitive essay typer is just a matter of time

Even if we are able to develop a proper AI-powered essay typer, there are chances that students will not be allowed to use it. After all, the essays are assigned to students to evaluate their knowledge of the subject and skill of writing. If a machine does that on a student’s behalf, what is the credit of the student?

Also Read: Artificial Intelligence has seen quantum advantages

Author bio: Mark Hales is a website developer who is employed at a reputed MNC. He is also associated with MyAssignmenthelp.com as an assignment helper in the UK. As an expert, he provides with programming assignment help to students on request.


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