Commissioner of the Australian Border Force (ABF) Michael Outram has spelled out a decidedly upbeat, ambitious and in-control vision for his agency’s ability to create and use new technology to execute and enhance its mission, revealing staff are already working on their third iteration of in-house artificial intelligence while their second is still in development.
In a speech that firmly set out how the ABF expects the new AI stacks, tools and modelling to achieve its mission, Outram revealed work on a predictive analytics capability, dubbed ‘Targeting 2.0’. He said it was now “well advanced” and aims to “incorporate all of our assessments of border-related threats, risks and vulnerabilities along with new data from industry and partners, to support our decision making.”
Like Tax, the ABF, née the Australian Customs Service, has been developing its advanced analytics capabilities quietly for more than a decade, focusing on heavy-duty infrastructure that necessarily has to reside on Australian soil but also communicate with other nations.
Aside from the vast amounts of cargo imported into Australia every year, the ABF also needs to be able to keep track of people and predict and detect modalities of illegal threats as they occur, like nabbing people of interest before they leave the country, or knowing which containers to hit and when.
“Targeting 2.0 seeks to apply the extraordinary power of AI to complement and amplify the deep expertise of our people, to identify new patterns at speed and at scale, to detect and disrupt crime as it happens, and, in time, to get ahead of the perpetual evolution of criminal activities,” Outram told the Milipol Asia-Pacific/TechX Summit in Singapore this month.
“So this is a promising start. As AI continues to evolve, we’re going to be able to look at an increasingly bigger picture and start addressing problems at the systems level — whether in terms of threat discovery, modelling or disruption.”
Which is all pretty much in a day’s work for the head of Customs, except that Outram doesn’t necessarily see it as gazumping human intelligence as much as propelling it.
His main bone of contention is that risk scenarios are now so intertwined and unpredictable — think poly-crisis-as-usual — that crisis leadership needs to be as instinctual as it is informed and process based, and always looking for the next scenario or how factors may come together.
The approach is not dissimilar to how military leadership has evolved over the past 30 or 40 years to take account of communications and network effects, indeed network-centric warfare.
“Many models exist, mostly based on the traditional system of command and control, or C2, which has been expanded to C3, C5, C+ISR et cetera. We have a plethora to choose from. In the ABF we use our own C3 model — command, control and coordination,” Outram said outlining the factors of:
- Command being the authority to plan, direct, coordinate and control the deployment of resources;
- Control being the direction and management of activities, agencies and resources; and
- Coordination being the unity of actions in the pursuit of a common purpose.
But that doesn’t mean it’s good for everything, like when stuff hits the fan.
“This model has proven its worth and is fine for managing routine operations and incidents. It helps us maintain operational discipline and predictability the vast majority of the time, but it is inadequate as a model for leaders during a crisis,” Outram said.
“The ++ is about the leader thinking about the adaptation of whatever model they know on the fly. It’s about understanding the entropy (or the levels of uncertainty or randomness) and thus the novelty of the crisis.”
So what does a modern leader do when they need the code for adaptive leadership on the fly? Pump it into a large language model of course, which is actually quite a neat check to see if a given AI ‘gets’ you.
“I wanted to be less vague about the issue of crisis leadership, to try and codify my thoughts somehow,” Outram said. “Whilst I acknowledge that there may be more detailed approaches available, I came up with a formula to explain my thinking.”
According to the Outram algorithm, the “effectiveness of the leader’s response (C3+) is a function of adapting to Novelty (N), which in turn is a function of Entropy (H), the dimensions of which may have high or low predictability levels (X) that can be subjectively weighted according to judgement and experience (α).”
“So here you have it: C3+response = f(N) = f(αH(X)),” Outram declared.
To put that into more vernacular and less mathematical language, Outram cited “Harvard’s Dutch Leonard and Arnold Howitt define crisis leadership as: ‘A good enough decision, soon enough to matter, communicated well enough to be understood, carried out well enough to work’.
“I always say to my people that they should never ignore their instinct — it’s a survival mechanism. You don’t have to follow it, but ignore it at your peril. Human intuition is always going to be a very big part of leading a response to crises,” Outram said.
The ABF commissioner sees digital twins (essentially complex systems or network clones for things like cities or infrastructure) being made off Australia’s border to help manage it better and do more with finite resources.
Imagine an array of sensors and data feeds, technology stacks with learning ability and visualisation tools; now incorporate digital twins, Bayesian belief networks and quantum computing.
“We’ll be able to model crises and our responses, with augmented decision-making and the ability to monitor those decisions’ impact on complex social systems, during a crisis. Perhaps we could even start to understand and map the global and multi-dimensional interconnections of polycrises. Or maybe I’m dreaming,” Outram said.
Perhaps he is, but it’s a more imaginative and cogent dream than flogging-off transaction processing that so spectacularly cratered.
Outram gave a level-headed assessment of what still needs to be done to win people over to trust the government and tech.
“Building trust in government institutions will require a great deal of time and effort. People must trust that our data is secure, have trust in the information we push to them and they pull from us, trust in our people, trust that we won’t misuse personal information, trust that we won’t act unlawfully or unethically,” Outram said. A change of government and leader may help that.
“One of the best ways to build trust is to demonstrate, measurably, the benefits to people of sharing their information and data with us. Take truly seamless and contactless travel through digital borders,” Outram continued.
“To collect the data we need from travellers, we need to emphasise the benefits of people providing their biometrics, for example. Travellers will reap economic and personal benefits like time-saving and convenience.
“I think we have to introduce human-centric measures of success into our success criteria, budgeting and operating models so that our AI systems aren’t just based on being good value for money but also having a positive effect on people.”
Just don’t call it Systems for People.
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