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Are you one of the 140 million people who use Spotify each month? Or maybe one of the 109 million subscribers to Netflix? If so, you’re interacting with artificial intelligence.
Spotify’s individualised Discover Weekly selection, which recommends new music based on your tastes, uses three of the most powerful strategies of predictive analytics. This includes collaborative filtering (using data based on what similar users like and don’t like), natural language processing (correlations in language and sentiment on blogs and other written sources about music) and an audio model which analyses raw audio tracks and finds similarities in factors such as time signature, key, mode, tempo, and loudness. Together, these algorithms decide what your Spotify thinks you should listen to.
AI is not part of a distant future, separate to our current lives and our day-to-day issues. What many people don’t realise is that our lives are being changed and improved by AI every day. Dr Tim Wilkin, Senior Lecturer in the School of Information Technology at Deakin University says we rely on AI to help us in our lives in more ways than we imagine. ‘In the past we used to throw lots of labour or money at problems, these days we view it as throwing lots of data to try and find solutions,’ he says.
From the automotive industry to aged care, AI is one of the biggest areas for future job creation and economic growth. Now Deakin has invested $20 million into a world-leading Applied Artificial Intelligence Institute dedicated to AI’s growth and its practical application in our lives.
Whether it’s analysing our behaviour patterns to solve problems or protecting people on the roads, here are the ways in which AI is shaping our lives every day.
Beyond Spotify and Netflix – which recommends films to you based on what you’ve already watched – advertisers are using predictive analytics every day in order to track your behaviour and serve you ads in anticipation of your needs. That’s why, for example, you see a travel insurance ad on a web page after you’ve looked up holiday plans and destinations.
Predictive analytics tries to map people’s behaviour and how that relates to other cohorts. While such analytics are already a huge part of our day to day lives Dr Wilkin says the area has huge capacity for growth and value creation. Brands like Amazon are spending billions of dollars in AI capabilities like predicting what consumers will need.
There’s a lot of power in that type of analytics, he says, so as we get better there will be more capacity to deliver value, such as supermarket chains delivering products to you before you need to order them.
‘They’ll deliver things to you based on when you need them, not when you tell them you need them. That becomes very powerful, particularly when you link them with notification and delivery systems,’ Dr Wilkins says.
Many people don’t trust robots to drive us. What they may not realise is that autonomous mobility is already a huge part of our daily transport mix.
As Dr Wilkin points out, from the moment you step on a plane to when it lands on the runway, your plane is predominantly running on autopilot. Most people don’t question it because they trust the people handling the planes and their approval of the technology. Singapore airport, for example, has driverless trains.
But when it comes to our cars, many people – especially older generations – are a little less accepting. Dr Wilkin says people have already started giving up cars.
‘Uber is an autonomous vehicle, it’s just a human brain driving the vehicle,’ he says. ‘But in Australia cars represent personal freedom and there’s a belief that driverless cars will take away that sense.’
Dr Wilkins says over the past 10 years, we’ve made great leaps in driverless technology such as autonomous vehicles being allowed to operate in natural environments.
'They’ll deliver things to you based on when you need them, not when you tell them you need them. That becomes very powerful, particularly when you link them with notification and delivery systems.'Dr Tim Wilkin,
Deakin University
Whether you have Siri, Cortana or Alexa, your personal assistant is a further example of AI already at work. From connecting your home, to finding answers to your questions – personal assistants are constantly working their way into our everyday lives.
The next evolution in personal assistants, Dr Wilkin says, will be the ability to use their own knowledge to come up with solutions to your problems and give you information that you didn’t explicitly ask for but might need – cognitive solutions.
The developing generation of personal assistants and technology will understand the context of what you are asking for. The example Dr Wilkins gives is saying: ‘Tell me what the weather is today.’ But maybe you’re really asking: ‘Is it going to rain because I’m having a picnic?’
‘Combine that with predictive analytics and behaviour modelling, it starts to answer questions for you. It can recommend.’
With raw machine learning, AI is also being used by individuals and businesses every day to optimise their products and business processes. Working in this way, machine learning can change the parameters of products and see the impact on production and costs, for example on chemical settings in drugs or paint products. ‘In the past humans would have done that and this can be costly and time consuming,’ Dr Wilkin says.
In this scenario, machine learning uses data collected to inform the system of the next thing to change and how to get to the end result faster and with less experiments. And people are starting to use machine learning on problems we never thought about, such as collecting mass data – such as identifying people with weapons.
Beyond advancements in AI technology like fully-autonomous vehicles, predictive and intuitive personal assistants – a big question posed for AI is the one of ethics. The amount of devices produced each second is more than the babies born in a particular country, Dr Wilkin says.
And part of the debate is around potential situations in which robots have governance over our lives. The best example of this is an autonomous car that is about to crash. Should the car sacrifice the life of its passenger or the lives of the people in the other car? And what if that other car is less likely to avoid an accident because it is not autonomous?
At the end of the day, Dr Wilkin says, it’s not so much that we’re unable to trust a machine to act upon algorithms that poses the biggest ethical dilemma.
‘We don’t know what information and priorities to give it to, because we are still lacking consistent ethical frameworks in our own life,’ he says.
Discover how Deakin is continuing to drive the digital frontier to support future jobs, with the establishment of its new Applied Artificial Intelligence Institute.
Senior Lecturer in the School of Information Technology, Deakin University
