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Bragg Prize runner-up: The Science of AI

Congratulations to Daniel Kim for being a runner-up in the 2023 UNSW Bragg Student Prize for Science Writing

In his response to this year’s theme, how we use and benefit from AI (with a particular focus on science), Scots College student Daniel Kim explores the past, present and future potential of AI.

“A well written, engaging, enlightening look at the history and future of AI, with pertinent daily use examples and potential future developments,” said Donna Lu, a science writer at Guardian Australia and Bragg Prize judge.

Read Daniel’s full essay below!

The Science of AI

by Daniel Kim
Year 10, The Scots College, Bellevue Hill, NSW

‘The integration of AI in science promises transformative advancements by accelerating data analysis, enabling pattern recognition, and facilitating the discovery of novel insights across a multitude of disciplines.’ 

Above is a ChatGPT response to, ‘Write a thesis about AI’s involvement in science’, which was generated in just a second. While it could be improved through some editing and fine tuning, it’s pretty good for a second of work. This response shows the rapid advancements of AI and its scientific capabilities, with the ability to produce anything from reports, methodologies and even poems. 

I am also guilty of using ChatGPT to help with various school tasks. My initial thought when I heard of ChatGPT was, ‘So basically, it’s a cheating tool’. Truthfully, it’s an effective tool that offers human-like conversation which is extremely helpful when generating ideas. In science, it can accelerate the findings of revolutionary discoveries, intensive researching, and efficiently organising many forms of data for quick access.

To understand AI, you have to look at its history. Although brief, it has undergone dramatic improvement. In 1958, John McCarthy created the list processing language (LISP), the first in a long line of AI programming languages which set the foundations for AI innovation. This started with very basic and limited functions that primarily involved the organisation of simple data sets and strings. The thought of these programs becoming creative was unfathomable. This kickstarted a surge of AI research, leading to ‘machine learning’ (1959), the first industrial robot (1962), and the first chatbot (1966). With these new developments, AI’s capabilities were stretching to other fields of study, such as science. AI’s scientific power was shown through supernova and galaxy classification from the limited datasets it had processed.

Returning to the present, society is dominated by AI. How many times do you use facial recognition? Or Google Maps? Or gone through your email? All of these are variations of AI, whether it’s recognising faces, navigating roads, or filtering out spam. No one can deny it’s evolved tremendously from the simple computation of datasets, to engaging in fluid conversations with humans. 

We have already seen what AI is capable of in the scientific field countless times, and it happened again in January this year; where an AI program discovered three new nanostructures at the US’ Department of Energy Brookhaven National Laboratory. Simply put, nanostructures are structures at microscopic and molecular levels, and are involved in all biomolecular interaction within organisms. 

One of the discovered nanostructures was a first of its kind nanostructure ‘ladder’. This ‘ladder’ had not even been hypothesised by human scientists, however was fully comprehended and conceptualised by AI. This is just one example of a significant discovery that has been driven by AI to help the science industry. 

If AI can do this at present, where will we see it in 10, 50, or 100 years in the scientific realm? There are many paths open to the future in terms of what AI could do, especially with the concept of radically augmented thinking. Radically augmented thinking refers to the capability of AI to intentionally process information in a way outside human comprehension. Rather than creating something that is a replica of human intelligence, why not embrace the innovation of AI and expand it outside of our limited processes of thinking? 

As a student who is aiming for a career in the medicine field, it is necessary for me to consider the future developments in this industry. An area rife with AI potential is the discovery of new drugs. AI’s capability allows it to be a valuable asset in all aspects of drug discovery, including drug design, polypharmacology, chemical synthesis, and drug screening. Its endless amounts of information and datasets enables it to make quick and accurate predictions that are vital when developing new drugs. When applying radically augmented thinking to its faster processing, its ability to generate ideas beyond human comprehension will be a vital factor for the future. 

While people may disregard certain ideas as impossible, the unlimited breadth of AI’s knowledge can transform these ideas to make a revolutionary discovery that no human mind would be able to do. 

In discussing the relationship between AI, science and creativity, there are hundreds of ways they interlink and affect each other. Especially recently, where AI and human creativity has significantly improved the scientific field. There has been clear progress in artificial intelligence over the last 100 years, and historic breakthroughs have been made, establishing the foundation for which present day AI has been built on, and this evolution will continue. In response to, ‘What will AI do for the creativity of science’, my answer is that development of AI’s creativity will work in its own way to forever change what science is. 

For the 2023 UNSW Bragg Student Prize for Science Writing we asked Australian high school students to enter 800-word essays responding to the theme how we use and benefit from AI, with a particular focus on science.

Read other winning essays:


For updates on the 2024 UNSW Bragg Student Prize for Science Writing, sign up to the Careers with STEM weekly e-newsletter.

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