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Artificial intelligence: the good, the bad, and the future

A Scientia News Biology collaboration


Artificial intelligence (AI) shows great promise in education and research, providing flexibility, curriculum improvements, and knowledge gains for students. However, concerns remain about its impact on critical thinking and long-term learning. For researchers, AI accelerates data processing but may reduce originality and replace human roles. This article explores the debates around AI in academia, underscoring the need for guidelines to harness its potential while mitigating risks.

Benefits of AI for students and researchers


Within education, AI has created a buzz for its usefulness in aiding students to complete daily and complex tasks. Specifically, students have utilised this technology to enhance their decision making process, improve workflow and have a more personalised learning experience. A study by Krive et al. (2023) demonstrated this by having medical students take an elective module to learn about using AI to enhance their learning and understand its benefits in healthcare. 

Traditionally, medical studies have been inflexible, with difficulty integrating pre-clinical theory and clinical application. The module created by Krive et al. introduced a curriculum with assignments featuring online clinical simulations to apply preclinical theory to patient safety. Students scored a 97% average on knowledge exams and 89% on practical exams, showing AI's benefits for flexible, efficient learning. Thus, AI is able to assist in enhancing student learning experiences whilst saving time and providing flexibility. 

Additionally, we gathered testimonials from current STEM graduates and students to better understand the implications of AI. In Figure 1, we can see that the students use AI to benefit their exam learning, get to grips with difficult topics, and summarise long texts to save time whilst exercising caution, knowing that AI has limitations. This shows that AI has the potential to become a personalised learning assistant to improve comprehension and retention and organise thoughts, all of which allow students to enhance skills through support as opposed to reliance on the software. Despite the mainstream uptake of AI, one student has chosen not to use AI in the worry of becoming less self-sufficient, and we will explore this dynamic in the next section.


AI can be very useful for academic researchers, such as making the process of writing and editing papers based on new scientific discoveries less slow or even facilitating it altogether. As a result, society may have innovative ways to treat diseases and increase the current knowledge of different academic disciplines. Also, AI can be used for data analysis by interpreting a lot of information, and this not only saves time but a lot of money required to complete this process accurately. The statistics and graphical findings could be used to influence public policy or help different businesses achieve their objectives. Another quality of AI is that it can be tailored towards the researcher's needs in any field, from STEM to subject areas outside of it, indicating that AI’s utilities are endless. 

For academic fields requiring researchers to look at things in greater detail, like molecular biology or immunology, AI can help generate models to understand the molecules and cells involved in such mechanisms sufficiently. This can be through genome analysis and possibly next generation sequencing. Within education, researchers working as lecturers can utilise AI to deliver concepts and ideas to students and even make the marking process more robust. In turn, this can decrease the burnout educators experience in their daily working lives and may possibly help establish a work-life balance, as a way to feel more at ease over the long-term. 

Risks of AI for students and researchers


With great power comes great responsibility, and with the advent of AI in school and learning, there is increasing concern on the quality of learners produced from schools, and if their attitude to learning and critical thinking skills are hindered or lacking. This matter has been echoed in results from a study conducted by Ahmad et al. (2023), which studied how AI affects laziness and distorts decision making in university students. The results showed using AI in education correlated with 68.9% of laziness and a 27.7% loss in decision making abilities in 285 students across Pakistani and Chinese institutes. This confirms some worries that a former testimonial shared with us in figure 1 and suggests that students may become more passive learners rather than develop key life skills. This may even lead to reluctance to learn new things and seeking out ‘the easy way’ rather than enjoy obtaining new facts. 


Although AI can be great for researchers, it carries its own disadvantages. For example, it could lead to reduced originality while writing, and this type of misconduct jeopardises the reputation of the people working in research. Also, the software is only as effective as the type of data they are specialised in, so specific AI could misinterpret the data. This has downstream consequences that can affect how research institutions are run, and beyond that, scientific inquiry is hindered. Therefore, if severely misused, AI can undermine the integrity of academic research, which could hinder the discovery of life-saving therapies.

Furthermore, there is the potential for AI to replace researchers, suggesting that there may be fewer opportunities to employ aspiring scientists. When given insufficient information, AI can be biased, which can be detrimental; an article found that its use in a dermatology clinic can put certain patients at risk of skin cancer and suggested that it receives more diverse demographic data for AI to work effectively. Thus, it needs to be applicable in a strategic way to ensure it works as intended and does not cause harm.


Considering the uses of AI for students and researchers, it is advantageous to them by supporting any knowledge gaps, aiding in data analysis, boosting general productivity and can be used to engage with the public and much more. Its possibilities for enhancing industries such as education and drug development are endless for propagating societal progression. Nevertheless, the drawbacks of AI cannot be ignored, like the chance of it replacing people in jobs or that it is not completely accurate.

Therefore, guidelines must be defined for its use as a tool to ensure a healthy relationship between AI and students and researchers. According to the European Network of Academic Integrity (ENAI), using AI for proofreading, spell checking, and as a thesaurus is admissible. However, it should not be listed as a co-author because, compared to people, it is not liable for any reported findings. As such, depending on how AI is used, it can be a tool to help society or be detrimental, so it is not inherently good or bad for students, researchers and society in general. 

Written by Sam Jarada and Irha Khalid

Introduction, and 'Student' arguments by Irha

Conclusion, and 'Researcher' arguments by Sam

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