S2C Storytelling with Australian Analytics Leader Dr Alex Antic
He calls himself “an introverted nerd,” and it’s a term of endearment for this math-minded problem-solver who fell in love with the art of data science.
Today, as head of data science at ANU’s Software Innovation Institute, Dr Antic is passionate about promoting and advancing data science and AI broadly, including helping Australia play a bigger role in the adoption of AI ethics principles and practices.
And he’s already been recognised by IAPA (Institute of Analytics Professionals of Australia) as one of the Top 10 Analytics Leaders in Australia. From his vast experience, he’ll tell you the largest barriers regarding successful data science projects are not technological, but rather people – most notably, misunderstanding.
Sadly, he said many data scientists spend most of their time focusing on the technical aspect alone, without paying enough attention to how their models will be used.
But Dr Antic is on a mission to change all of this and never loses sight of what famed Nassim Nicholas Taleb said in conversation: “You can’t ignore the human element of analytics.”
S2C caught up with Dr Antic to discuss the power of data science – how it makes sense of information overload to deliver impact and change – some of his career highlights; and why it’s still so difficult to sell analytics.
S2C: Did you always envision a career in Data Science?
Data science didn’t exist when I was a boy. From a young age, I enjoyed solving problems, and developed an appreciation of mathematics, and how it can be used to help explain the world around us. Coupled with this, I found computers, and the broader IT field, to be fascinating, and so I enrolled in a double-degree in mathematics and computer science. I enjoyed mathematics so much that I ended up pursuing Honours in Pure Mathematics and a PhD in Applied Mathematics.
I view my career in two stages: Stage 1 was Data Science for Personal Growth, while Stage 2 is Data Science for Public Good. The early days saw me working as a Quantitative Analyst in the financial services industry, for the likes of Macquarie Bank, Colonial First State and Allianz Insurance – which really helped hone my technical skills.
I then moved into the public service, just as the field of data science really started to grow, which has seen me spending more time leading and promoting Data Science initiatives to deliver societal value. To me, a career in data science is ultimately about using mathematics, statistics and computer science to help solve operational and strategic decisions.
S2C: What’s the promise of data science and why is it so pivotal to both government and industry?
Fundamentally, data science is about change. It’s a means to an end to enable data-driven decision making. It ultimately helps make better decisions, but doesn’t necessarily make decision making any easier.
Data is our lives. Information about us is constantly being generated, accumulated and shared. Data science is a tool that helps us make sense of this information overload, so we can deliver impact and change.
The many tangible benefits for most organisations include increased efficiency, automation, uplift in capabilities via scale, mitigation of risk and fraud, and personalised experiences – be it customers or health care patients, for instance.
However, data science/AI is not intelligent, as we understand human intelligence to be. AI systems are devoid of abstraction and reasoning, and don’t generalise well. They’re a subset of the broader intelligence paradigm, albeit, an important and practical one, especially in certain domains, such as computer vision, machine translation and natural language processing. The key for most organisations is to see beyond the hype, and set realistic expectations, with c-suite leadership support to help make it a success.
S2C: What challenges/hurdles have you faced in your career?
An important lesson I learned early in my career is that it’s difficult to sell analytics. As a data scientist, you’re effectively a purveyor of analytics. I’ve had this lesson reinforced numerous times since then.
A part of the reason is that people are often resistant to change, and in certain organisations, they can also be very risk-averse. So how do you establish a capability, such as data science, that is apparently black magic, and that heavily depends on exploration and experimentation, where results, outcomes and timelines can’t easily be predicted?
Success hinges on being able to clearly articulate and relate data science capabilities to strategic goals. To do that effectively, in a trusted way, is an exercise in technical credibility and human understanding – to help effect cultural change. Being an introverted nerd, the former was much easier to grasp than the latter.
S2C: What are some of your biggest lessons learned?
During one of my early roles, I was fortunate to meet the famed Nassim Nicholas Taleb. Having both worked in quantitative finance, we discussed various technical and philosophical aspects of our roles. What I took away from that conversation was that you can’t ignore the human element from analytics. These days, I find myself reflecting more on this, especially in the context of effective decision-making, and how to strategically support organisations to establish a data culture to successfully and realistically leverage data science.
Many data scientists spend most of their time focusing on the technical aspect alone, without paying enough attention to how their models will be used. This can be detrimental, especially as AI algorithms increasingly impact our lives. It is even more pertinent as we, as a society, divert more effort to addressing AI ethics/fairness/dias concerns.
I’d say that the largest barriers regarding successful data science projects are not technological, but rather people – most notably, misunderstanding. It’s paramount that data scientists learn to be effective communicators, to better help promote and advocate their trade.
S2C: What are your top priorities over the next 12 months?
My key focus is to continue to help build and promote ANU’s exciting new flagship initiative – the Software Innovation Institute (SII). There are three specific areas I’m helping lead:
- Educating and training the next generation of data scientists and analytics leaders, including helping establish a state-of-the-art teaching program, using world-leading integrated learning, for data scientists and software engineers. This also includes executive training, and helping upskill our workforce, to ensure that Australia doesn’t fall behind global advances in data science and AI,
- Translational research in emerging areas of data science and AI, to drive impact and change, and
- Strategic advisory, and technical support, to assist public and private sector organisations to meet their strategic goals.
I’m passionate about promoting and advancing data science and AI broadly, including helping Australia play a bigger role in the adoption of AI Ethics principles and practices. I plan to continue to help people better understand data science and AI, and how to use it effectively and responsibly, in a successful, sustainable and scalable way.
S2C: You’ve been recognised by IAPA (Institute of Analytics Professionals of Australia) as one of the Top 10 Analytics Leaders in Australia. So, what does it mean to be a successful leader in the data science realm?
As data science is effectively about change, leadership means supporting and guiding that change to enact a data-driven decision making culture.
It’s also about promoting and advancing the field of analytics, including increasing diversity. I enjoy helping support this via such initiatives as mentoring and hosting local Meetups, that help connect all those interested in the exciting field of data science.
I see the role of a data science leader as that of a linchpin – connecting business problems to technical solutions. The main value I add is to stay out of the way of the smart people I manage, and to help inspire, support, encourage and promote them. I’m passionate about sharing my experience, knowledge and insights, which I believe are the responsibilities of a leader.
S2C: What advice would you offer to others looking to travel a similar path?
Don’t! My path has been described as backwards i.e. industry, government, then academia – most people do it the other way around.
Here’s my advice for aspiring data scientists:
- Continually learn and stretch yourself by seeking challenging opportunities to add value;
- Develop a deep understanding of the fundamental technical concepts;
- Identify what inspires/excites you and develop the necessary skills to excel at it;
- Participate in networking opportunities; and
- Find yourself a mentor.
S2C: Has COVID-19 drastically changed the data science industry, and what are the implications for the future?
It’s hastened the need for many organisations to look for ways to increase automation and improve efficiencies, in large part due to the shifting nature of the workforce.
Organisations will emerge from this with potentially leaner and more specialised Data Science teams, and with a greater awareness and respect for the value that Data Science can deliver.
S2C: What do you do outside of work?
I spend as much time outdoors as I can. I’m fortunate to live on a rural property in the mountains surrounding Canberra. With a national park at my doorstep, I do a lot of trail running, mountain biking and hiking.
What living on a rural property quickly teaches you is the art of self-sufficiency. So when I’m not running or cycling, you’ll find me building and fixing things (often fences), woodworking, or welding various metals together, for one reason or another. My aim is to simply never stop exploring and learning.
S2C: What’s your favourite book or author?
Given that I’m an avid reader, I can’t choose only one! As far as fiction is concerned, some of my favourite authors include Fyodor Dostoevsky, Charles Dickens, Jane Austen, Elisabeth Gaskell, Elliot Perlman and Fredrik Backman.
By way of nonfiction, it’s too varied. Here’s a list of some books that I’ve enjoyed most over the past year: Loonshots, Humankind, Sapiens, The Ethical Algorithm, The Man Who Solved the Market and The Book of Why.
S2C: Who would you like to see featured in an upcoming S2C Storytelling?
Dr Maria Milosavljevic
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