Monday, 3 July 2023
University of Sydney, Sydney
Her Excellency the Honourable Margaret Beazley AC KC

Bujari gamarruwa

Diyn Babana Gamarada Gadigal Ngura

In greeting you in the language of the Gadigal, Traditional Owners of the land on which we gather, I pay my respects to their Elders past, present, and emerging. I extend that respect to the Elders of all parts of our country.

I also thank Michael for the warm Welcome to Country, in this, Australia’s oldest University and, in doing so, acknowledge and pay tribute not only to First People’s continued custodianship of these lands, but also, in the spirit of this occasion, to the living body of knowledge, science, and inquiry developed here on this continent, and continuing today, for more than 60,000 years.

Minister^[1], Acting Vice Chancellor^[2],

Almost a year ago to the day, I launched the 42^nd International Science School, where all 120 students joined us online. This year, for the first time since COVID, the School is back on campus, and we have the privilege of welcoming you, the 2023 ISS scholars. 

For more than four decades, this School has been bringing together high school students to interact with world-renowned scientists, to experience firsthand the research which is being undertaken in this University’s leading scientific facilities, and to participate and collaborate in hands-on workshops. Collaboration is vital to research – a matter to which I will return.  

You are here because of your love of, and talent for, science and scientific investigation. You are also fortunate to be part of the generation where it has been recognised that STEM is absolutely essential if Australia is to have not only a thriving economy, but also an innovative one. An economy that will secure the future of our nation and its people. 

It is important, however, from the outset, that as you pursue your studies and your careers, that you keep your eye on the bigger picture, of which there are two aspects that I would like to stress this morning. The first is that everything you do will have an impact on someone else. It is important therefore that when making decisions, you always ask: is this the best solution for the problem I am attempting to solve; how it will it affect others?

Let me give you a simple example: I had the privilege of being on an advisory committee for a project being undertaken by the human rights commission on the interaction of human rights and artificial intelligence. There was a brainstorming session with ideas being thrown around as to uses of AI which would enhance the community good. One suggestion, given the shortage of personnel in aged care facilities, was the use of robots to deliver meals.  

Now, I was a mere lawyer sitting at the table in that session and lawyers aren’t always known for their empathy; but, to me, robots weren’t necessarily a good idea at all – mealtimes might be one of the few times in a day when a resident had any human contact. 

Another example takes one in a slightly different direction – importantly to be aware of inbuilt biases.

There was a small town in Sweden which wanted to reduce the number of injuries sustained during the winter months when everything was iced over. The apparently obvious answer was to invest in machinery which would de-ice the roads. However, an investigation of hospital and other medical records demonstrated that the greatest number of injuries were not due to motor vehicle accidents but to pedestrian slip and falls on the pavement, particularly by mothers walking their children to school and women going out to do the shopping.  

The obvious solution therefore was not the best solution to the problem – but to ensure that bias did not produce a result that failed to comprehend who was most affected; it required someone to think outside the box, and, more importantly, to seek out the data that would lead to the best solution. There are many examples out there of such matters, particularly those that rely solely on artificial intelligence.

These examples leads me immediately to this year’s theme, solve for x, a wonderful overarching metaphor for scientific inquiry. It encapsulates the process by which scientific endeavour unfolds, and the transformational opportunities it enables.

In algebraic terms, solve for x is grounded in a simple but profound realisation. That if you have an unknown variable with a known relationship to other known variables, there is usually a process – an algorithm – by which that unknown can be revealed.

In a recent article^[3], mathematician Dr Matthew Holden from the University of Queensland gave an anecdote illustrating the part solve for x played in transforming him from someone who hated maths into someone who loved it and who would dedicate his career to mathematical pursuits which significantly improved agricultural production. 

When he was at school and I quote him here, Dr Holden “managed to pass a full year’s worth of algebra without learning much algebra at all.” Not really knowing how to solve for x problems that came up in the exam but knowing that there had to be a value for x, he went through every possible value until he arrived at a correct result. His teacher wasn’t impressed with his methodology but had to pass him. 

What this made the young Dr Holden realise was that “Maths is not about following a set of preordained rules. It is about solving problems.”   

That, in a nutshell, is the both the mystery and the beauty of science. 

Today, Dr Holden leads research at the University of Queensland into the application of complex mathematical modelling and decision theory in improving conservation planning.  This includes:

• maximising crop yields while simultaneously minimising the application of harmful pesticides;
• selecting the best spatial arrangement of traps to eradicate invasive pests; and
• optimising the spatial allocation of conservation resources to minimise the extinction risk of native species.^[4]

These are contributions to conserving our natural environment and the sustainability of our agriculture that are timely and vital. They are solutions to contemporary and pressing problems.

This is not an invitation to ‘goof off’ in class. But it does illustrate a number of important things. First, there are usually several ways to solve any problem. Secondly, and perhaps most importantly, creativity, ingenuity, and persistence are foundational to finding different ways to solve problems. Thirdly, different skill sets can be put to use in a whole variety of ways. And finally, the curiosity for discovery and the thrill that comes with achieving it are vital components of who we are as humans.

Let me now turn to something else about this metaphor solve for x; the flip side of the equation if you will, or, perhaps more precisely, the inside of the equation.

Often in science the variables are known – but not the relationships between them.

A paper in last October’s edition of the journal Nature Reviews Physics begins with the following statement:

“An oracle that correctly predicts the outcome of every particle physics experiment, the products of every possible chemical reaction or the function of every protein would revolutionize science and technology. However, scientists would not be entirely satisfied because they would want to comprehend how the oracle made these predictions.”^[5] 

The paper quoted from, was titled ‘On scientific understanding with artificial intelligence’ – and the question it raised was whether machine learning can achieve true understanding of problems it is given to solve and what is its creative potential for further scientific research.

It is a fascinating subject and one that is there for you to further investigate: indeed, whatever career you pursue, artificial intelligence will be part of it. I pause, only to note that one of the paper’s conclusions is that the best way to determine whether a human or AI understands something, is to determine whether they can teach it to someone else. To be able to teach something depends on the ability to communicate and communication is a two-way process. A two-way process is the first step in true collaboration. Is collaboration possible between two machines? Between a machine and a human? Or is collaboration a uniquely human activity?

That is part of the discovery that awaits you. However, at the end of the day, a machine can only solve a problem from the data which is inputted into it: it is, therefore, my prediction that it is human curiosity, understanding, and empathy that advance science for the good of humanity – because without humanity, the world as we know it and want it to be, would simply not exist. And with your curiosity, as you traverse the boundaries between the known and the unknown your futures are assured, as you advance human knowledge and the good that it brings.

I thank the Physics Foundation and the University of Sydney for facilitating this program, for bringing you, the sharpest of young minds, not only in Australia, but from around the world, together. To offer you the opportunity to be inspired and to learn, to embrace your curiosity, to question, and to collaborate.

I thank also, the researchers and presenters who will so generously share with you their expertise, knowledge, and passion.

The very best wishes for the exciting two weeks ahead for you, and for your journeys beyond, that your talents, and the experiences and friendships you form here, will empower you, in whatever future fields you choose to explore.

It is with great pleasure, that I now, as Patron of the Physics Foundation, officially launch the 43^rd Professor Harry Messel International Science School 2023.