In an era where artificial intelligence (AI) is transforming industries, many people wonder whether their efforts as students or the expertise of service providers will soon be replaced. This concern is especially prevalent within academia. If AI can generate content, summarise research and proofread papers, does that mean the role of human authors or subject experts is becoming obsolete? While AI, such as the popular ChatGPT, can make certain processes more efficient in research, it currently does not provide a replacement for human-led academic work. Here’s why AI will never fully take over research and why professionals in this field still have a vital role to play.
Using AI as an Assistant, Not a Replacement
AI is making research and academic writing more efficient. It can help:
Automate grammar and spell checks
Assist with literature reviews by summarising vast amounts of information
Suggest improvements in clarity and structure
Offer citation management to avoid formatting errors
However, these capabilities do not replace deep thinking, critical analysis or ethical decision-making, all of which are crucial to academic integrity. A recent study by Morgan (2023) underscores AI’s value as a tool for assisting researchers in engaging with their data. When using ChatGPT to thematically code data, the study found that AI struggled to capture the nuanced understanding that comes from a researcher’s own deep familiarity with their work. The highly subjective process of meaning-making, which relies on human interpretation and contextual awareness, remains beyond AI’s reach (Morgan, 2023). In addition, while AI excels at detecting technical language errors, it is prone to misjudging regional spelling conventions and colloquialisms, which can impact the accuracy and appropriateness of written communication. Another study by Khalifa and Albadawy (2024) highlight that AI can be useful in 1) conceptualisation and research design; 2) language coherency and structuring; 3) summarising literature; 4) enhancing data management and analysis; 5) supporting editing, review and publishing; and 6) assisting in communication, outreach and ethical compliance. However, challenges in balancing human insight and maintaining academic integrity (ethics) when using AI remains a big concern in academia (Khalifa & Albadawy, 2024). Further, the use of AI created content in work submitted for evaluation purposes, without properly acknowledging the source, is considered plagiarism and can lead to severe repercussions for the author.
Limitations of AI in Research and Writing
Although AI can be used ethically to assist in the efficiency of research processes, its inability to critically evaluate and make meaning of subjective contexts leads to a wide range of error.
1. Generating New Ideas & Critical Thinking
AI can process existing data but lacks the ability to think independently or develop original ideas. Research is about posing new questions, analysing findings in unique ways and drawing meaningful conclusions — a process that requires the researcher’s subjective knowledge and skills. In this sense, AI struggles to find nuances within a dataset and responses would still need to be interpreted by the researcher.
2. Ensure Ethical and Methodological Accuracy
Academic work involves understanding research ethics, designing proper methodologies and ensuring compliance with institutional guidelines. AI is unable to navigate the ethical considerations and nuances required to conduct high-quality, unbiased research that is also specific to the researcher’s institution.
3. Provide Personalised Guidance
Every student and researcher face unique challenges, whether it’s structuring a complex argument, refining their voice, addressing supervisory comments or addressing gaps in their analysis. Human mentors and academic consultants provide personalised feedback that AI simply cannot replicate.
What Sets Mindful Connections’ Services Apart?
Our role involves more than just checking technical language usage through editing and proofreading. We provide support and personalised feedback on:
Critical thinking and structuring arguments
Understanding research methodology and ethics
Ensuring academic integrity and proper citation
Coaching students through complex ideas and research processes
In summary, AI can assist with initial conceptualisation and summation of data and literature, but it struggles with nuanced judgment, ethical decision-making and guiding researchers through the subjective meaning-making process that is the cornerstone of human research. It can therefore be considered as a co-pilot that streamlines tedious tasks while allowing the author to focus on what truly matters: deep thinking, their original research/voice and personalised mentorship. AI isn’t an easy, cheap replacement for the human mind and, therefore, the role of human experts remains indispensable.
References
Khalifa, M., & Albadawy, M (2024). Using artificial intelligence in academic writing and research: An essential productivity tool. Computer Methods and Programs in Biomedicine Update, 5, https://doi.org/10.1016/j.cmpbup.2024.100145
Morgan, D. L. (2023). Exploring the use of artificial intelligence for qualitative data analysis: The case of ChatGPT. International Journal of Qualitative Methods, 22. https://doi.org/10.1177/16094069231211248
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