Artificial Intelligence (AI) has become an integral part of our lives today and is transforming the way we live and work. Its impact on various fields is undeniable and the field of research and publication is no exception. AI in research is empowering the world’s researchers to explore new avenues, enhance their academic writing, and make groundbreaking discoveries at an unprecedented pace. Over the past few months, it’s been ChatGPT, a generative writing tool, that has garnered significant attention worldwide and focused the spotlight on the transformative potential of AI in research.
ChatGPT is capable of generating human-like responses to various prompts and is increasingly being used by researchers to automate certain tasks such as literature review and data analysis. But as useful as the tool is, there are concerns about the accuracy and reliability of AI-generated content, especially when it comes to sensitive topics such as healthcare and finance. In contrast, assistive writing tools such as Paperpal, an AI writing assistant for students and researchers, are being seen as more viable option for aspiring researchers looking to enhance their academic writing for better, faster publishing success.
In this conversation with Harini Calamur, Head of Global Marcomm, CACTUS, we cover crucial questions surrounding AI in research, discuss different writing tools for academics, and what the future looks like for researchers looking for ways to accelerate and improve the research publishing and other processes.
Harini Calamur – Head of Global Marcomm, CACTUS
Harini Calamur has 25+ years of experience in building and scaling businesses. In her current role, she works with the higher education academic ecosystem globally to unlock the power of academic research from labs and journals to practical applications that will benefit society at large. As a visiting faculty member at Mudra Institution of Communications, Ahmedabad (MICA) and SP Jain, she teaches programs around Digital Trends, and how they impact society, business, and democracy. Harini is also a regular columnist writing on topics related to technology, economics, gender, and rights.
Question: ChatGPT has surprised the world with its content generation abilities and human-like conversations, leading the way for similar innovations from Google, Microsoft, and other big players. What is your take on this rapidly evolving landscape and the use of AI writing tools for researchers?
AI – and I use this term very broadly to include different types including NLP, ML, generative AI, assistive AI, Generative Adversarial Networks (GAN’s) – will definitely change the landscape of work in every area. And research is no different. The very fact that you can have human-like conversations with ChatGPT and refine its responses is phenomenal; we’re already seeing its impact in areas like content generation in a big way. Its applications are manifold with its relevance visible in fields like digital marketing, e-commerce, design, content writing, and many more. It can perform tasks like creating chat-bots, writing code, creating landing pages, and all of this is as yet just the tip of the iceberg.
Governments across the world are looking at generative AI and its capacity for fake news with bated breath. To cite a recent example, Eruopol has cautioned about the use of generative AI in crime and is recommending policy intervention. But in the main, AI is seen as a means for good that will improve our lives. And this is true for the broad area of academia, including research.
Q: ChatGPT has been mentioned as author on some preprints and research papers. On the other hand, some top publishers have mentioned they would not accept any submissions that use such AI writing tools or have them as authors. What is your take on this – Do you think researchers can benefit from generative AI writing tools like ChatGPT, and if yes, how? How comfortable would you be in using generative AI tools like ChatGPT vs assistive writing tools like Paperpal for your own writing?
The first thing anyone using a tool like ChatGPT has to remember is that it is a tool. It is not the Oracle. It is not God. It is not infallible. It is only as good as its inputs.
The second thing to remember is that it is the early days of generative AI, and ChatGPT is still learning (as are other AI tools).
I am far more comfortable with assistive writing tools like Paperpal than generative tools simply because of the tendency of generative tools to make up things. ChatGPT makes up names of research papers and often citations too.
ChatGPT is good for helping you structure your project, but you have to be super careful in using it for other things like writing. That is why I prefer assistive AI when I need accurate results, whereas I go to generative AI to make my research process easy. For instance, I use generative AI tools to summarize the broad theories of media, and its leading exponents but beyond that I go and research things myself, simply because I would need to verify anything that ChatGPT told me. Recently I asked ChatGPT for academic papers around academic support, and it just made up paper names and author names. So as a word of advice, I would recommend you verify the information you get from ChatGPT. Don’t take its word as gospel truth – because you may end up unpleasantly shocked.
Q: What kind of future do you see for AI in research and what role do you think CACTUS can play in this?
If you talk about AI’s usefulness, it is already playing a large role in research fields such as healthcare, finance, and climate science. It is being used for generating summaries of research papers and identifying important insights in large datasets. In the end, this has great potential to make research more efficient and productive, ultimately leading to more ground-breaking discoveries. When it comes to generative AI tools like ChatGPT, unless it fixes its issues with regards to making up research papers and citations, it will be difficult to take the tool seriously. In fact, if you told someone that you, the researcher, used ChatGPT it would be viewed with suspicion. But we hope this will change soon.
Standing here today, CACTUS is in a great space to deliver true value to the space of AI in research. Watch out for Researcher.Life, which brings together a suite of smart researcher-focused tools, including Paperpal. Moreover, our two decades of knowledge of research and experience working with researchers in different parts of the world allows us to train and develop AI that caters to the diverse, multicultural academic world in a way few others can. This is going to be especially interesting and valuable in furthering research now as the balance of research production shifts to non-US/EU nations.
In addition to this, CACTUS can help train AI to be more useful to the researcher, helping him/her in many ways. We have developed AI writing and language tools that are diverse, unbiased, and ethical and can support specific domains or subject areas. We do this by building frameworks for evaluating and mitigating any potential biases in the data or algorithms used to train these tools. We have AI solutions that can help researchers find relevant articles to read, select the right journal, summarize long articles, visualize their science, and make connections between different pieces of research. With its focus on technology and science communication, which places researchers at the heart of all research, I believe that CACTUS will be a key player in shaping the future of AI in research.
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