Credit Union Australia (CUA) has turned to Sydney-based artificial intelligence (AI) firm Flamingo AI to pilot its chatbot Rosie in its CUA health insurance business. Under the agreement, Flamingo's cognitive virtual sales assistant, Rosie, will be piloted by CUA Health to provide a service for potential new members visiting its website, assisting the user from the quote stage, through to the point of sale. CUA Health CEO Philip Fraser says: "Consumers are becoming more financially and technologically savvy and there is an ever increasing number that prefer the convenience and accessibility of a digital sales channel." To placate any human anxiety, he adds: "This channel is certainly not a replacement for our human service team – rather it provides us with a huge opportunity to grow our health member base by lifting the number of quote requests that are followed all the way through to taking out a policy." After a period of "learning" the commonly asked questions and answers, Rosie will be deployed on the CUA Health web channel for a three-month pilot, expected to kick off in the next few months.

The idea that machines can make intelligent decisions has been around since the 1950s when the first learning programme was built. At the time, the machine itself was groundbreaking, improving at the game of checkers the more it played. Since then, the idea of such machines has become more and more prevalent, particularly in pop culture. But over the last few years, the concept has moved from the realm of fiction, such as Iron Man's JARVIS (Just A Rather Very Intelligent System), the highly advanced computer system supporting Tony Stark, to our phones and even our living rooms. We're growing more and more comfortable with AI services, such as Apple's Siri and Amazon's Alexa, the latter of which Amazon recently announced would make its way to Australia and New Zealand in 2018.

Businesses will take the leap and embed augmented reality (AR) and machine learning into their business practices in 2018 according to Deloitte's 2018 Technology, Media and Telecommunications (TMT) predictions. With invisible smartphone innovations opening up application opportunities, consumers will be more connected and more distracted by smartphones than ever before. Deloitte Australia TMT leader Kimberly Chang says, "We're at the tipping point of widespread adoption of a number of technologies. "In 2018 we will finally see business challenges being addressed by what has to date been consumer-driven technology." "But it will be a year of trial and error." Deloitte predicts that over a billion smartphone users will create AR content at least once in 2018 and by 2020 AR will generate direct revenues of US$1 billion. Currently around half of AR uses are non-enterprise focused but Australia is on the precipice of mass adoption, with particular potential in industries such as mining, retail, training and marketing. AR also has a role to play in the future of work and job creation in Australia. With the smartphone predicted to be the primary device for AR content creation, Deloitte is predicting smartphone penetration will continue to increase, surpassing 90% by the end of 2023. Machine learning is also set to hit its stride in 2018 with Deloitte predicting the number of implementations and pilot projects using the technology to double from 2017, with two-thirds of large companies having 10 or more implementations and a similar number of pilots. To date, the uptake of machine learning in Australia has been slow, but Deloitte expects to see leaps in experimentation around machine learning applications in 2018, in particular in relation to consumer electronics, autonomous vehicles, finance, insurance, human resources and clinical operational diagnosis in healthcare. Chang continues, "Machine learning is not a new concept, but it is about to revolutionise our daily lives.

Augmented reality and machine learning will be embedded into business practices in 2018, according to Deloitte's 2018 Technology, Media and Telecommunications Predictions. And the annual predictions show that smartphones will be more distracting than ever before as they become more a part of the business day. "We're at the tipping point of widespread adoption of a number of technologies," says Kimberly Chang, Deloitte Australia's Technology, Media and Telecommunications leader. "In 2018 we will finally see business challenges being addressed by what has to date been consumer driven technology. But it will be a year of trial and error," Augmented reality, a special effect that enables digital images to be superimposed on real ones, has become an increasingly popular smartphone application, often for entertainment applications such as face swapping or live face filters.

The actual impact of artificial intelligence (AI) on the world's economy and jobs will likely be somewhere between the utopian and dystopian futures that it is often discussed in terms of, according to a new report from the Economist Intelligence Unit. The report, commissioned by Google, examined how AI will impact certain industries in the US, the UK, Australia, Japan, and Asia as a whole. The findings are based on econometric modelling, desk research, and interviews with academic and industry experts. Firms developing and using machine learning need to better communicate among themselves as well as with the public and policymakers, the report stated. This means doing more to manage expectations around the impact of machine learning, acknowledging the potential risks and rewards, improving trust and transparency, and educating the public.

In media stories last week, for example this one in The West Australian, former airline Captain Kevin Sullivan broke his long silence on what happened on Qantas Airways flight QF72 in October 2008. Traveling from Singapore to Perth, the Airbus A330-300 aircraft suddenly lost altitude over the north-west of Western Australia, causing unrestrained passengers and crew to be flung around the cabin. The injuries were serious, and included fractures, lacerations and spinal injuries. Captain Sullivan called a mayday and made an emergency landing at the remote Learmonth Royal Australian Air Force (RAAF) base. At least 110 of the 303 passengers and nine of the 12 crew members had been injured.

Health insurer Nib is running a proof-of-concept to improve its ability to extract claim information from photos of medical receipts submitted by customers through an app. The PoC is one of a number either underway or completed by Nib as it explores how artificial intelligence might improve both its backend and customer-facing activities. The insurance industry in general has been quick to find AI use cases, as evidenced by recent deployments by the likes of Suncorp, as well as iTnews' recent study of the AI space. Nib has publicly discussed its entry into the chatbot space, with its IBM Watson-based'Frankie' bot and AWS Lex-based'Nibby' bot launched in New Zealand and Australia respectively late last year. But behind the scenes it is already pursuing a wide range of different use cases for AI, as long as there is demonstrable value to be had.

Artificial intelligence is proving to be a revolutionary tool across many industries, but the technology is having a particularly big impact when it comes to healthcare. Researchers are using AI to combat the flu, by building improved seasonal forecasts that inform the development of influenza vaccines, and the technology is already helping to diagnose rare diseases so that patients can get the treatments they need. Now, scientists have found a new medical application for AI: predicting when a seriously ill patient admitted to the hospital will likely die. In hospitals, palliative care teams are charged with improving the quality of life of gravely ill patients and making sure their final wishes are carried out. But clinicians sometimes don't refer their patients to these specialists because they believe their patients are better off than they really are.

Cross-industry collaboration Announced in a blog post today, Microsoft said the institute will look for ways to directly integrate AI research into Cortana. The organisation is being co-funded by Microsoft Research, Cortana Research and the RMIT University in Melbourne, Australia. The Institute is unique in its intention to directly combine research with real-world implementation. Currently, AI researchers tend to operate independently of the engineers building applications such as Cortana. The Cortana Intelligence Institute will bridge the gap, providing researchers and engineers with a two-way link to each other.

In its latest bid to become the go-to flight management mobile tool, Google has added a new feature to Google Flights which can predict flight delays. "One of the most stressful parts of traveling happens between heading to the airport and waiting to board your flight, as you start checking to see if your flight is on time. Flights already shows delays, and now we're sharing reasons for those delays and delay predictions too. Using historic flight status data, our machine learning algorithms can predict some delays even when this information isn't available from airlines yet--and delays are only flagged when we're at least 80% confident in the prediction. "We still recommend getting to the airport with enough time to spare, but hope this information can manage expectations and prevent surprises.