Robot or Researcher? How AI is Impacting Scholarly Publishing

Artificial Intelligence (AI) has become one of the fastest growing areas of study. The applications are boundless; from data analysis to speech recognition, society today has completely embraced the Age of AI. However, with great power, comes even greater responsibility, and sadly not everyone is using this technology for the betterment of the world.

Before the public was introduced to the popular Terminator and the Matrix movie franchises, scientists have theorized about the capabilities of computer-generated intelligence, otherwise known as Artificial Intelligence. In the present day and age, society has implemented AI Technologies for countless tasks such as security (facial recognition software), manufacturing (robots in car factories), travel (self-driving cars), and more (Daley, 2019).

While there is no denying these technologies are extremely useful and efficient, there is still so much to be learned about them. This ultimately presents a variety of concerns and challenges. These innovative technologies, some theorize, may be used in unethical ways and the consequences may affect a variety of industries moving forward. Unsurprisingly, the publishing community is one such industry already seeing a trend of such practices.

In 2005, three MIT students decided to develop a computer program (SClegn) that would randomly generate scientific papers with, “realistic-looking graphs, figures, and citations” to be published by predatory research conferences (Connor-Simons, 2015). As it turns out, this computer program had lasting effects. Due to this program being released to the public, in 2013 IEEE and Springer Publishing had to retract more than 120 papers after a French researcher “discovered that the works were computer-generated nonsense” (Noorden, 2014). This impacted the publishers and all the researchers accessing the work.

While malicious use of this technology will undoubtedly persist, AI can also be quite helpful in improving efficiency across the scholarly publishing arena. In fact, in recent years, AI technologies have acted as plagiarism detectors, identifiers of flaws in data sets, and collectors of potential reviewers for journal editors (Enago Academy, 2018). AI has also been integrated into journal recommendation services, pairing key words with an author’s manuscript and crawling the web to find the most suitable fit for the research contribution.

However, many still beg the question whether a machine-generated publication could ever be widely accepted in academia. Springer Nature recently released a book titled: Lithium-Ion Batteries: A Machine-Generated Summary of Current Research, written entirely by, you guessed it, a computer program! This program, named Beta Writer, collected thousands of articles related to ion batteries and produced a book that, “automatically created introductions, table of contents and references,” to successfully, “arrange the source documents into coherent chapters and sections” (Lehnert-Bechle, 2019).

So how was it ultimately received? This machine- generated book, while most certainly a breakthrough, was still only able to summarize the massive number of articles provided and still fell short of, “contend[ing] with the long-term coherence and structure that human writers generate” (Vincent, 2019).

It’s clear that as these technologies become further refined that AI-generated articles most certainly can pose a serious threat to book and journal editors. Now, more than ever, it is imperative that strict peer review processes are maintained for all scholarly publications to ensure that there aren’t any unsubstantiated, machine-generated research findings being distributed falsely as vetted research within the academic community. Publishers must also work diligently to support their editors and authors by securing any online submissions systems against bot submissions, which not only jeopardize the publication, but also waste the time and hard work of reviewers and editors.

One must wonder, in what other ways will AI technologies shape the scholarly publishing industry in the future? In a few years, will it be impossible to discern between writings from a human and a machine? Someday, we may find out, but until then, it seems AI is here to stay.

References:

Connor-Simons, A. (2015). How three MIT students fooled the world of scientific journals. Retrieved from http://news.mit.edu/2015/how-three-mit-students-fooled-scientific-journals-0414

Daley, S. (2019). 19 Examples of artificial intelligence shaking up business as usual. Retrieved from https://builtin.com/artificial-intelligence/examples-ai-in-industry

Enago Academy. (2018). Is artificial intelligence good or bad for academic research? Retrieved from https://www.enago.com/academy/academic-publishing-machine-learning-era/

Lehnert-Bechle, M. (2019). Springer Nature publishes its first machine-generated book. Retrieved from https://group.springernature.com/gp/group/media/press-releases/springer-nature-machine-generated-book/16590134

Noorden, R. V. (2014, February 25). Publishers withdraw more than 120 gibberish papers. Retrieved from https://www.nature.com/news/publishers-withdraw-more-than-120-gibberish-papers 1.14763

Vincent, J. (2019). The first AI-generated textbook shows what robot writers are actually good at. Retrieved from https://www.theverge.com/2019/4/10/18304558/ai-writing-academic-research book-springer-nature-artificial-intelligence