The role of AI in empowering researchers

Recent advancements in AI, including Large Language Models (LLMs), have opened up new possibilities for researchers across various fields:

Medical technology: AI is playing a pivotal role in healthcare. Open-source computer vision and deep learning models are aiding in drug discovery, enhancing medical imaging, and leading to more accurate diagnoses and treatments.

Social sciences: in psychology and crisis management, AI and ML are facilitating intervention design and public sentiment analysis, providing valuable insights into human behavior.

Engineering: novel methods built upon modular ML workflows, such as digital twins, enable engineers to perform simulations and modeling for entire cities, driving innovation and efficiency.

Okay, let's talk about how AI is shaking things up in the world of research publishing. It's not just a little nudge, either – it's a real game-changer. You hit the nail on the head with the data analysis piece. Think about it: researchers used to spend ages poring over spreadsheets and trying to find connections. Now, AI can crunch those numbers in a flash, revealing patterns we might have missed entirely. It's like having a super-powered research assistant!

But it's not just about speed. AI is also helping to make research better. It can catch errors in data that a human might overlook – we all make mistakes, right? – which leads to more reliable results. Plus, it can help with the writing process itself. Let's be honest, writing research papers can be a real slog. AI tools can help polish the prose and make sure the arguments are clear, which is a win for everyone.

And the coolest part? AI is opening up doors to new kinds of research. It can help researchers from different fields team up and tackle really complex problems. Imagine the possibilities! AI can also create these amazing data visualizations that make it easier to understand complicated findings. It's like turning dry statistics into a compelling story.

Of course, there are some things we need to watch out for. We need to think carefully about the ethics of using AI in research. Things like who gets credit for discoveries and making sure AI isn't biased are really important. And, yeah, some people worry that AI might take over research jobs. I think it's more likely that AI will just make researchers more effective, not replace them entirely. It's like giving them a powerful new set of tools.

The bottom line is, AI is changing research publishing in a big way. It's making things faster, improving the quality of the work, and creating exciting new opportunities. It's not perfect, and we need to address the challenges, but the potential is huge. It's a really exciting time to be in research!

There is positive and negative impact of AI in Research Publication some of main points that I observe are discussed here:

First discussing the positive impact of AI:

And negative impacts in are:

There is a positive and a negative side to it, in my opinion.

On the positive side, AI can be used when you have no ideas on how to paraphrase a sentence while writing your paper. It can also speed up your analysis and code generation (if you work with code, and the majority of us do to some extent), it can sum up other researcher's papers for you and you can save time and not have to read the whole article. The reasoning models, such as DeepSeek, can even answer your questions in a very comprehensive way.

On the negative side, I am seeing some discussions on using AI in review processes and in paper writing, which I think is not a very good idea. Keep in mind AI makes mistakes, and there is the obvious ethical issue as well. One of my colleagues even read somewhere that people even use to to generate fake data (we truly see everything and anything in today's world). Perhaps due to the overwhelming amount of work that is placed onto the shoulders of academic, some try to relieve it by using AI.

ExplanAItions: An AI study by Wiley

"ExplanAItions is a different kind of study—one that goes beyond sentiment around AI to look deeply at how researchers use and apply it. It explores where interest and technological capabilities align and identifies opportunities for further exploration. Based on feedback from almost 5,000 researchers, this comprehensive study provides real data both on current and potential use cases for AI by authors. It quantifies key statistics around each use case, assessing interest and usage and evaluating where AI might outperform humans. And it uncovers what researchers want from publishers in terms of guidelines, training, and policies.

In sharing this study, we want to help you put our insights into action—to explore opportunities and imagine future possibilities together. And while we’ll continue to use AI to better communicate scientific discovery and learning, in keeping with our AI principles, human creativity, critical thinking, and ethics will always remain at the heart of what we do..."

https://www.wiley.com/content/dam/wiley-dotcom/en/b2c/content-fragments/explanaitions-ai-report/pdfs/Wiley_ExplanAItions_AI_Study_February_2025.pdf