the ai writing papers

the ai writing papers

The Impact of AI in Writing Papers

1. Introduction

Observing the fast development of AI and the growing requirements of the content providing industry as well as the transformation of the traditional roles of publishers and scientific editors due to technological progress, we also have to consider the future of scientific publishing and scientific knowledge dissemination. The determination of AI’s current application profile is a first step. In a second step we should try to understand important future trends. Such insight would allow the science communication community to develop a vision for the future of scientific publishing and to build new strategies for the creation, dissemination and commercialization of content. Most importantly, the analysis of future trends could guide the development of new tools, new publishing models and the invention of new roles for traditional publishers, scientific editors and content providers. As opposed to the evaluation of transformation driven by current AI application profiles, which is actually experiencing the daily routine of probe-publishing or content access, a discussion of future requirements is quite complex. First, one must assume that the AI community, with its actual financial resources and unprecedented speed, can transform existing tools and instruments in ways that are practically invisible to non-insiders, including scientists and editors. Second, one must assume the technological trends at short and long term that belong, first and foremost, to the private sphere and, secondly, to the research community. Cautious action and strategic decisions would be necessary to determine if future technologies may have an impact upon scientific content aggregation, classification and dissemination.

Both AI and big data are relatively recent technologies that are revolutionizing every field of science because they make patterns visible that can’t be perceived with conventional statistical approaches. AI allows machines to perform human-like reasoning and thinking processes in an artificial way. It enables machines to solve complex problems, to learn from new information and to adapt to new situations. It allows machines to carry out a range of functions that require cognitive abilities and human reasoning such as perception, multilingual communication, robotics and decision making. These capabilities are increasingly relevant in the future transformations of publishing, editing and content aggregation. Content providers like Google, Facebook or IBM use all AI technologies to create data-based products and services. Well-known are the semantic analysis of language, the precise translation of languages, contextual question answering and information aggregation, different reasoning techniques and machine learning.

2. Benefits of AI in Writing Papers

Drafting and revising could be one of the most stressful processes during which writers experience writer’s block. Writers, especially new writers, can benefit from this app that helps with structuring the paper. Throughout the writing process, other tools may be used to help writers automatically summarize elements of their manuscripts. In this report, we present a study of 17 different apps that are designed specifically for the purpose of writing scientific papers. With increasing visibility of the AI impact on various scientific fields, particularly in the preparation of scientific papers for publication, we feel that it is important to look at these AI tools designed specifically for writing scientific papers.

Over the past few years, numerous tools have been developed to help writers in the various steps. Tools such as Google Scholar and PubMed have been helpful in literature searching. Digital libraries including JSTOR are also increasingly offering services such as exporting directly bibliography of selected items as a list. Zotero organizes PDFs in a library and offers mechanisms for note-taking and citation creation. A multitude of apps (e.g. Evernote, Bear, Notion, etc.) offer note-taking and outlining support.

In reality, AI can be used in writing tasks beyond article writing. As of today, there are many different AI tools developed for diverse writing tasks such as writing headlines for news articles, creating captions for images, and suggesting possible conclusions for scientific papers. The task of writing scientific papers is particularly interesting to us due to its multi-faceted nature. Indeed, a writer writing a scientific paper typically goes through a series of steps: literature searching, reading, note-taking, outlining, drafting, revising, analyzing results, defending results, seeking feedback, and submitting.

3. Challenges and Limitations of AI in Writing Papers

Most AI systems focus on a particular task, and generalization is necessary to beat the AI in generating such a system. Since the generation is mainly based on the trained network, only a limited number of topics and references might be given in standalone AI models. To increase the number of topics, generalized AI models have to be used, where the strength of such models is limited. Particularly, the limited support by the developers still affects the completion of tasks by the current AI systems beneficially. In the future, expanded developer support, increased challenge, and usage of generalized models are necessary for better completion of all types of comprehensive, qualified, and standardized writing referred to by different levels and interests, including students, researchers, and publishers.

During the last 5 years, the rate of improvement in the field of AI was unexpected, and the world entered a new era called the AI era, where we are witnessing new products, algorithms, and techniques virtually every day based on AI. Undoubtedly, AI-based solutions are the real solutions for a number of problems in the world. AI is expected to make major impacts in various professions, including accountants, doctors, musicians, etc. Likewise, it is found that AI can also write technical documents such as academic papers and reports. The impact of this AI-based system goes beyond simple assistance to the authors, as it can create hybrid papers, and publishers might also use this system to complete their manuscripts. Although the new AI system has increased the efficiency and effectiveness of papers in many aspects, there are still a number of challenges that need to be handled by the AI community.

4. Ethical Considerations in AI Writing Assistance

According to a recent study, improper or dishonest writing has had a significant impact on academic publication. Ladies and gentlemen are not avoided by the rampant scientific misconduct in academic writing. Dishonest academic writing became chronic such that some began to promote constructive approaches in the use of technology like AI. The honesty of academic writing is based on the integrity of the reporting of both the process and the findings of a research study. Thus, the idea is to enable writers, educators, and researchers to know that they adhere to the standards of scholarship and are able to understand the consequences of their academic writings with AI. For example, research articles packed with AI technology are increasingly accepted and used by researchers, writers, and even educators. The process requires ethical aspects unique to academic publications that are not automatically assimilated into existing AI ethics guidelines. The literature shows that AI ethics guidelines focus on just six top listed ethical aspects.

A writing process requires critical thinking and sound ethical judgment in all phases of planning, writing, and revision as an academic. There are many sets of rules, principles, and values to guide this judgment. Many universities around the world have AI ethics guidelines to define a set of principles that define values and standards to which one commits. However, with more AI writing assistance tools available, the guidelines do not yet mention how this will apply to their academic practices. One wonders about this and would be concerned about AI usage in writing without clear guidelines on what constitutes ethical writing in academic publications with AI assistance.

5. Conclusion

If humans are motivated and willing to learn, we can use AI to write better and write more than AI. When we brainstorm or have a vague concept, we can use AI to turn thoughts into structured pieces and correct the first draft. Existing documents allow review and comments. If we differ, we may want to manually stop the process, since we do not expect 100% matching. Scientific discovery so far has found the disabled as published AI technology, for a number of years after it has been successful, as the continuation of scientific publications, iteratively, mindful, and widely accepted by the research community. Therefore, as researchers, we remain cautiously optimistic when considering using these technologies not for groundbreaking findings, but as a means to expedite our writing process.

The impact of AI in writing papers: excessive reliance on the perceived strengths of AI as a writing aide can lead to problems such as unconscious bias, learned-fact mistakes, ghost writers whose lead authors do not understand the papers they submit, dependency of learning on externally-generated data, inhibiting creativity in research, poor understanding of social issues, terrible scientific papers written by machines, and other problems. We argue that while it is important to carefully and cautiously introduce this new, powerful technology and monitor its development, it is also important to give promise to the potential benefits by well-informed scholars. In our opinion, machine writing is not inferior or superior to human writing; rather, it is just a different way of doing science. Different ways of tackling problems increase creativity and help human researchers pursue tasks that are more challenging to machines than to researchers. In particular, AI can be an excellent source for fair play and for good software engineering practices, such as improving the structure and not offloading the arguments to appendices of conference papers.