AI TAKING OVER? RISING NUMBER OF SCIENTIFIC PAPERS ALLEGEDLY WRITTEN BY ROBOTS!
The landscape of scientific research, according to recent linguistic and statistical analyses, is changing dramatically. The research process, typically characterized by meticulous data collection, analysis, interpretation, and then drawing thoughtful conclusions, could see a seismic shift in the coming years. The provocateur of this shift? Artificial Intelligence or more specifically, Generative AI.
Generative Artificial Intelligence as some of you would know, leverages complex algorithms to create content, be it literature, media or more recently, scientific research. According to statistics from two recently published academic papers, an appreciable fraction of scientific research papers could soon be written- at least partially- by AI. The forecast suggests that up to 17.5% of all research papers in 2023 could display the fingerprints of artificial intelligence.
Tracking the usage and frequency of specific words over the years, these studies identified an intriguing trend. Large Language Models (LLMs), AI systems specifically designed to recognize, understand and generate human language, have shown an increased fondness for complex language. Words such as "meticulous," "commendable," "intricate," among others have seen a considerable rise between 2019 and 2023.
What's fascinating, however, is not just that AI is supposedly writing scientific papers, but that its influence is more prevalent in certain disciplines. Pointedly, subjects such as computer science and electrical engineering have been better and more frequently targets of AI integration as compared to the fields of physics or mathematics. This disparity may be due to the former subjects' close ties with the tech industry, where AI's potential is already being exhaustively explored.
This widespread use of AI, however, is not without controversy. Critics have voiced concerns over what they call 'scientific misconduct.' The primary apprehensions revolve around high risks associated with AI models producing inaccurate text, fabricating quotations or citations, thus battling the very premise on which scientific research is based – certainty, credibility, and accuracy.
In response to these concerns, a call for stricter guidelines has been made. Researchers and authors who utilize LLM-generated text are being advised to disclose this usage as a matter of fundamental research integrity. This measure aims to foster transparency and facilitate a wider debate over the role and extent to which AI should have a place in scientific research.
Whatever your opinion might be, it is undeniable that the role of AI in scientific research is changing rapidly. Like any new tool, it offers both opportunities and challenges. While there is the potential of using AI to automate and accelerate the research process, thereby enhancing productivity, there remains a need for caution. We cannot discount the risk of misinformation and unethical practices associated with this technology. Future use of such powerful tools ought to rely not only on their technical functionality and prowess but ultimately, on how responsibly we choose to wield them.