Voices from Accenture Public Service


These days, there’s a lot of talk about “Human + Machine” – the future where people and smart devices collaborate to continuously augment each other’s capabilities. Well, guess what: it isn’t the future. It’s now.

I can see it in my own life. I used to enjoy keeping a journal and handwriting my thoughts on paper; today, I’m typing this blog on my laptop. Even when I’m sleeping, my watch keeps track of how “effective” my sleep is, helping me adjust my sleep pattern to stay energetic and productive for the next day. In fact, it’s hard to think of any everyday task I undertake that doesn’t involve me interacting with a digital device.

Recently, I read a book that really got me thinking about this topic: Human + Machine: Reimagining Work in the Age of AI, co-authored by Accenture’s CTO Paul Daugherty. The authors paint a compelling vision of the future of Artificial Intelligence (AI) in the workplace, as it reinvents processes by blending people and machines in new ways. As a borders-focused professional, it struck me that nowhere are the potential benefits greater than at our borders.

To see why, imagine you’re passing through the airport of the future – and picture the kinds of human/AI collaboration you might see at immigration. Like machines combining instantaneous facial recognition with flight data to validate who you are and where you’ve arrived from. Then drawing on your full travel history and other data to assess risk levels. And, if necessary, prompting their human counterpart with questions to ask you. Put simply, a true partnership – friendship, even – between people and technology, where each does what they’re best at and the human remains in ultimate control.

Science fiction? Not at all. All of this is achievable. What’s needed is the vision and commitment to make it reality, and elevate the benefits from AI to a whole new level – taking us from the smart border to the smarter one.

The journey has already begun. For years, the “smart border” enabled by technology has been talked about. So far, the focus has largely been on pulling together historical data from border and customs systems, and applying analytics to realise process efficiencies.

This approach is valuable, but can only take us so far. Take customs agencies. Where they’re using AI today, they’re usually deploying it in a supporting role, aimed at providing better information for human officers to make their judgements on. This means agencies are stopping short of merging the human and machine elements to get the very best from both.

What do I mean by this? By way of example, consider today’s typical customs process for freight traffic. Data arrives about what’s coming in across the border, and is crunched against historical information to decide which shipments need to be stopped and checked. Suspect consignments are put through an X-ray machine, with a human officer monitoring the screen for anything suspicious. If the officer’s experience suggests something merits further investigation, then the container will be opened up.

So it’s still highly labour-intensive in human terms. But exploit the full capabilities of AI to learn new things, and the process looks very different. By working alongside human officers and tracking their actions and outcomes, an AI-enabled machine equipped with video analytics can learn to recognise the warning-signs of dodgy merchandise far more quickly, accurately and consistently than any human could. Then it can work alongside humans rather than for them, delivering better results – and freeing up people to focus on dealing with the outcomes of its decisions.

Or take another area where humans’ visual perceptions are used as the basis for decisions – the classification of goods for customs declarations. Was the right code applied at the port where the shipment originated? Is adult apparel being misrepresented as children’s clothes to avoid duties? Are these laptops or tablets coded correctly?

Currently these decisions are made by human officers, meaning they differ from port to port and even person to person. When the shift changes, so might the decision. The result is delays and inconsistencies at the border, but AI never goes off shift. Replace subjective human judgement with machines that can crunch vast amounts of data 24×7 and always reach the same decision, and the inconsistencies and delays evaporate – especially when the technology is deployed across agencies that work with the same shippers and traders.

What’s more, collaborating with machines means human officers have more time to focus on things machines can’t do – like thinking creatively and strategically to solve problems, using their intuition and awareness of body language when questioning suspected wrongdoers, and applying their experience and interpersonal skills in sensitive situations.

That’s the future for the smarter border: from smart to smarter. The only question is when it will happen. So far, most border and customs agencies have only scratched the surface of what AI can deliver. It’s time to dig deeper into AI capabilities – and combine humans and machines in ways that don’t just improve efficiency at the border, but actually reinvent processes and people’s roles in them.

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