Jason Tam

As an 11-year-old, Jason Tam moved from Hong Kong to Aotearoa New Zealand.
His passion for astronomy inspired him to pursue a BSc at Waipapa Taumata Rau, majoring in physics and applied maths, followed by a PGDipSci and MSc in Physics.

Jason completed a PhD in Experimental Particle Physics at Julius-Maximilians-
Universität Würzburg in Germany. After gaining valuable industry experience, he earned an MProfStuds in Data Science in 2018.

He now works as a Senior Statistical Data Scientist at Oritain, a company that
verifies the origins of agricultural products with a scientific approach.

When did you start using AI in your work?

I started working with Machine Learning algorithms (a core part of AI) during my doctoral student days at CERN, the European Organization of Nuclear Research. We had a lot of data to process from the Large Hadron Collider, and this new approach that was rising in popularity was worth the investment to see if it could help us achieve our goals more efficiently.

How does your current work relate to or use AI Technology?

Building and maintaining pipelines that process data in automation is part of my job. These pipelines often include components that perform calculations involving Machine Learning algorithms.

What are some of the challenges AI presents in your line of work?

Machine Learning/AI algorithms remain largely a “Blackbox” method, meaning it is often difficult, if not impossible, to determine why it has produced incorrect results.

Particularly in technical/scientific settings, it is therefore important to keep this under control in our projects, often limiting its use only to places where it can remain highly accurate and the imperfections are within manageable levels.

Is there an AI-related project you are particularly proud of?

While working for enviPath, I contributed to developing an application that predicts chemical reactions using Machine Learning algorithms. Pharmaceutical companies consider this to be a great tool in determining successful research directions.

Are there any aspects of AI technology you think are problematic?

Insights from data are traditionally extracted with statistics, reasoning our way from the input to the result. Machine Learning/AI is useful when the complexity of problems becomes too difficult for traditional approaches and where precise predictions have priority over sound reasoning. Therefore, it should be used carefully and only in settings where unexplainable errors are manageable. AI is also developing at a very rapid pace. All sorts of associated tools are popping up to help us in every aspect of our lives. With great power comes great responsibility; therefore, we must remain adequately knowledgeable about how they work while we enjoy their convenience. Aside from remaining within ethical grounds, we must ensure that we do not become overly dependent on them and can spot errors when they appear.

What excites you most about this technology?

The potential. The AI/ML revolution, in my opinion, is comparable to the birth
of computers and the Internet. It is a foundation platform for endless creativity
to be built on. I am confident that, in time, it will be used in ways that are beyond what we can imagine now, much like the evolution of the use of computers and the Internet.

Do you have any career aspirations you would like to share?

I want to stay involved with the forefront of AI-related work, contributing and witnessing firsthand the wonder it brings.

What advice would you give someone considering AI studies?

I believe AI to be one of the best study options a student can make, as the future will only become more and more technology-dependent, and AI will surely be a part of it. I recommend combining this subject with a second specialty studied in parallel, as the area where two disciplines intersect is often where some of the most innovative ideas are materialised.

Is there anything else you want to share?

I feel very fortunate to witness the wonder of this AI revolution that is rapidly
advancing our society. The University of Auckland is a great place that has played a significant part in my career achievements, and I cannot recommend it enough to people looking to start their journey.

Finally, tell us something about yourself that we can't learn by Googling you.

I have a not-so-common interest in visiting places not commonly travelled to.
Famous places like London and Paris give me the feeling that I can learn a lot about them via the Internet and other channels before going there. In contrast, uncommon destinations often contain the most interesting discoveries.