Artificial Intelligence

AI + Automation

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The following is an extract of a speech given as part of the CEDA 2018 Innovation and Disruption Series by Deborah Walker, Automation Leader, IBM Australia & New Zealand.

The surge in the adoption of artificial intelligence has been met with excitement, amazement and for some, fear.

According to IDC worldwide spending on artificial intelligence systems is expected to grow to around US$60 billion in 2021 – up from $8 billion in 2016 –  as systems that learn and reason are applied in both commercial and consumer settings. The speed of adoption and innovation is staggering.

The rise of AI is directly related to the phenomenon of data – the world’s “new natural resource”. Within this growing body of digital data lies the potential to defeat cancer, reverse climate change, manage the complexities of the global economy, and improve access to critical services for under-served populations.

However, should fears of AI take root – culturally, politically, economically – it could be difficult to realise this enormous promise.

IBM believes that pursuing AI technology is not only the right the thing to do, but quite possibly essential to the future of humankind.

IBM’s Chairman, President and CEO Ginni Rometty, talks to “Achieving Exponential Impact: AI in the Era of Responsible Tech.”

AI technology – the new category of information systems able to understand and reason over this data in all its complexity, and to learn from its successes and failures – holds the promise to address these challenges and unleash a new age of knowing.

Yet, some influential voices have worried about AI’s potential to be misused or abused, to introduce intended or unintended bias into decision making, to violate personal privacy, or to eliminate jobs.

As we contemplate an AI future today what can we learn from our automated past?

Automation of human tasks has a long and storied history dating back more than 5,000 years.

Throughout history, automation has been an opportunity to create new value from the balance of the classic paradigm of people, process and technology.

From the ancient Mayan aqueducts which automated water transport to the Newcomen Engine which ushered in a new world in the 1800s with the creation of the steam engine locomotive – and ultimately a new profession. Engineering.

Today’s advancements in artificial intelligence are spawning the next phase of automation – intelligent automation – and ushering in a new era. At IBM we call it putting smart to work.

Intelligent automation + AI enables processes to perform in such a way as to minimise the amount of human support needed – just as the Newcomen Engine did.

Chatbots, natural language processing and machine learning are quickly becoming common tools to tackle specific needs within business processes.

In fact, recent IBM research shows that “optimising business processes” is one of the top 3 ways business leaders anticipate AI can help them compete within the next 2 to 3 years. The other top 2 AI impact areas are “personalise customer experiences” and “enhance forecasting and decision-making capabilities”.

Even the basic automation of processes can eliminate errors, reduce biases and perform transactional work in a fraction of the time it takes humans.

Now let’s add AI to basic automation processes.

Not only does this change the speed at which work can get done, but changes the scale of work that can be managed. AI-driven systems can automatically scan millions of documents in a fraction of the time a human could – if they had a few hundred lifetimes!

In Australia, companies are using AI systems in applications as diverse as melanoma diagnosis, prediction of epileptic seizures, and online claims processing for vehicle insurance. Consumers experience it through mobile devices, chatbots, and customer service avatars.

Intelligent automation systems can analyse data up to 25 times faster than the human brain, function around the clock every day of the week, and interact with employees and customers in natural language, all with incredible accuracy.

This shift – moving the burden of processes from humans to technology – again has the potential to redesign the way we work in enterprise today. The increasingly more, and now more complicated, tasks being performed by process automation, means humans are free to engage in higher-value tasks.

Just like the assembly line workers and carriage builders displaced by earlier technological advances, so too will some existing jobs be revamped as digital labour assumes tasks previously completed by humans.

So what has history taught us about the evolution of technology and its impact on jobs?

That 100% of jobs won’t disappear – but 100% of jobs will change.

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