The Rise of Generative AI in Scientific Research and the Risks to Institutions
Introduction
The use of large language models (LLMs) in academic work has caused a tension between the desire for faster work and the need to maintain scientific honesty.
Main Body
There is currently a big difference in how researchers use generative AI. For example, an Elsevier survey showed that usage rose from 37% to 58% in one year. However, a Nature survey suggests that most researchers only use AI to improve their language, while very few use it to write the main text. Some scholars avoid these tools entirely because they want to develop their own thinking skills and avoid ethical problems regarding where the data comes from. Institutional stability is also threatened by 'hallucinations,' which are factual errors made by AI. In chemistry and conservation science, AI often creates fake molecular structures and wrong citations. Consequently, humans must spend a lot of time checking the work, which removes the time-saving benefits of the technology. Furthermore, these tools have a high environmental cost; it is estimated that by 2025, they will produce millions of tonnes of CO2 and use vast amounts of water, which contradicts the goals of climate research. Finally, there is a growing conflict over how to detect AI-written content. Submissions to 'Organization Science' increased by 42% after ChatGPT was released, and many of these papers contained over 70% AI-generated text. Similarly, AI-generated reviews in computer science rose from 7% in 2023 to 43% in 2025. Because current detection tools cannot always tell the difference between AI editing and full AI generation, fake data may enter the official scientific record.
Conclusion
The scientific community remains divided as it tries to balance faster research production with the need for high quality and ethical standards.
Learning
The 'Cause and Effect' Upgrade
An A2 student usually says: "AI makes mistakes. So, humans check the work."
A B2 student uses connecting adverbs to show a logical flow. This makes your writing sound academic and professional.
The Power Word: Consequently
In the text, we see: "AI often creates fake molecular structures... Consequently, humans must spend a lot of time checking the work."
Why this is a B2 move:
Instead of using "so" (which is very basic), Consequently signals that the second sentence is a direct, logical result of the first. It transforms a simple observation into a formal argument.
Expanding Your Logical Toolkit
To reach B2, you need to vary how you connect ideas. Look at these shifts based on the article's themes:
| A2 Style (Basic) | B2 Style (Advanced) | Transition Word |
|---|---|---|
| AI is fast, but it is risky. | AI offers speed; however, it introduces significant risks. | However |
| AI uses water. It also produces CO2. | AI uses vast amounts of water; furthermore, it produces millions of tonnes of CO2. | Furthermore |
| AI creates fake data. This is why it's dangerous. | AI creates fake data; therefore, the scientific record is threatened. | Therefore |
Quick Guide to Usage
- However: Use this when you want to pivot to an opposite idea.
- Furthermore: Use this when you are adding a "second layer" of evidence to your point.
- Consequently / Therefore: Use these when the second fact is a result of the first.
Pro Tip: Notice that these words are often followed by a comma (,) when they start a new sentence. This is a key marker of B2-level punctuation.