Artificial Intelligence, or AI, is here to stay. As the volume of data we are inundated with continues to increase, our ability to manage, interpret and act on it becomes increasingly difficult. AI offers a path forward but how we work with AI is changing on the back of greater accessibility to tools such as IBM’s Watson.
Andrew Tucker, the CEO of service provider ITonCloud, says “Some companies need to make better decisions. Some companies want to make more money. There are ways of doing that with AI, as it lets you make better decisions in order to make more money”.
Tucker says companies are still looking for the first mover advantage, where they get the jump on competitors. But there’s also a challenge in getting the technology right. Watson, he says, does particularly well with unstructured data where people can ask plain language questions and receive structured answers in response. For example, data from IoT devices is particularly well suited to Watson.
One of the fields he’s seeing benefit is in the health sector, particularly in aged care.
“Aged care is unique. You can have a lot of sensors. For example, there can be sensors in a bed to track when someone doesn’t get out of bed at the expected time. There are also applications when making prognoses based on demographic and health information. It’s much more accurate than ever before,” says Tucker.
Another application, he says, was with accounting company H and R Block. Watson has been used to deliver better information about tax returns. With the volume of data in tax rules and the number of past returns, there is capacity to give clients better information about how their tax returns will be resolved.
However, Tucker says that Watson is really a specific type of AI - what he calls QA, or Question/Answer. Watson works when it is fed a lot of data and people ask it questions using natural language.
When you start to learn to get the benefit from this, you’re a long way to getting the ahead of competitors and reaping a first mover advantage.
The challenge of AI or QA is knowing what questions to ask. Tucker says this will breed a new type of expertise in knowing what questions to ask of the data and AI systems. This is the next stage as he says the AI technology is now moving into a reasonable level of maturity.
At the moment, a lot of the focus of AI is about detecting anomalies in data. Over time, this will evolve into not just detecting the anomalies but also dispensing advice about what to do next. For example, in health care this can be used to analyse health information and offer recommendations on prescriptions.
"It’s more than trends - you can get those from spreadsheets. It’s about getting a better, more precise answer,” he says. For example, in health this would take into account patient history and family history, existing medical conditions such as heart disease, and current factors such as temperature.
Tucker says we can expect to see AI infiltrate all sorts of places. For example, he is seeing businesses embrace AI in the HR function to measure the health, well-being and efficiency of staff taking into account factors such as weather, desk locations, work hours and other measures that have, until now, too difficult to bring together meaningfully.
As for there future, Tucker says the big shift int he coming year will come from the accessibility of platforms such as Watson. For relatively low cost, businesses of all sizes will be able to access AI.
But the question then becomes, are they asking the right question?