Oracle: Expect neuroanalytic, AI-powered diaries to give your work life peak efficiency

'I'm sorry Dave, you have to be in a meeting now'

We should soon come to expect neuroanalytic, thought-reading AI-powered calendars to help us organise every second of our work life, according to a top Oracle executive.

Appearing on Computing's web seminar entitled So you want to be an AI billionare? Correct use of cloud for cutting edge innovation, Oracle head of technology and cloud for UK, Ireland and Israel John Abel talked about his research into neuroanalytics to "capture how the mind works, and ask how it's relevant to our business day".

Abel envisions a future where - beyond the likes of Cortana and Siri - our AI calendars will actually be able to understand human notions such as prioritisation, and help us structure our working day to be more efficient.

"These days you'll find a [time] slot and perform an action, but it's not always the best way to do it," said Abel.

But with machine learning, we could find out when the most suitable time is. We could train AI to ask, ‘When is the best time for me to something?' and set our diaries accordingly.

The benefits of neuroanalytics would help a machine to know "if you were nervous or stressed," by your brain signals, and could reorganise your schedule on the fly to reflect it, Abel continued.

"You could take a Myers-Briggs [test result], and overlay those data sets - you could get a perfect point to take the action point in hand," he said.

Abel opined that these sorts of interactions "can show the positive side of AI," clearly conscious of an increasing view of AI and "robots" as potential troublemakers who may gain a dangerous level of control, or even external exploitability once they're embedded in our lives.

"Of course, we also have to make sure it doesn't manage us!" Abel quipped.
He also championed the notion of machine learning assisting human intellect in innovation, as "if you have the mass of data that allows you to learn, it could take you years to learn it," whereas a machine learning intelligence could crunch those numbers faster.

"There aren't going to be 7,000 more Larry Ellisons," Abel qualified.