Backed up with software that learns from its mistakes, artificial intelligence is already augmenting human performance and intelligence in ways that would have been impossible only a few years ago.

Efforts to develop a human-like synthetic intelligence have advanced the growing supply of the feedstock needed to make it work, vast amounts of data that can be mined for hidden patterns. The computer programme ploughs through the mass of data but it is still up to the human operator to pluck out what is important.

UCD Professor Barry Smyth lives in this science fiction-like world, developing systems that support human-centred services that can really change lives and the way we currently do things. Artificial intelligence will change lives, he says, with better medical diagnostics, cars that drive themselves and a new kind of “personal assistant” that can do anything from keeping you connected to the office to helping you run a faster marathon.

“Artificial intelligence is not so much a replacement as an augmentation,” he says. It is not about replacing humans with robots. “It will be more interesting in that we will work together with machines and then real power emerges.”

Professor Smyth holds the Digital Chair of computer science in University College Dublin’s College of Science. He is also a founding director of the Insight Centre for Data Analytics, a multi disciplinary, multi institutional research centre that supports 450 researchers working in big data, artificial intelligence and machine learning. It collaborates with 80 partner companies and has a budget of about €100m supported by Science Foundation Ireland.

Smyth is working on recommender systems but is also involved in a project linked to marathon running and exercise more generally. We already have smart phones and smart watches that measure things such as heart rate, blood oxygenation and running pace, but the research would deliver a much higher level of sophistication.

Smyth is a marathon runner and wanted to know whether endurance running performance could be improved if a smart system was there to help. For example all runners are warned not to rush off at the start but there was no data to prove this made any real difference.

In fact it turned out to be very important, particularly for recreational runners, he said. “What you do at the start of a race has a great impact on how you finish.”

The use of artificial intelligence and machine learning was brought to bear on the problem and then became part of a new kind of “digital personal assistant” for personal fitness and training that could help the marathon runner deliver a peak performance. It is able to provide kilometre by kilometre advice on pace achieved and target pace. It takes account of the actual topography of the running route and even factors in the weather forecast if it is likely to have an impact. “It’s not difficult to imagine how, in the near future, similar ideas could be extended by taking advantage of our eating habits and sleep patterns to provide a more complete training picture,” he suggests.

He notes however that a large component of the big data mountain is actually personal information and in many cases actual medical data captured by fitness devices. Controls are needed to limit who can see or access this information. In the coming years it is likely that individuals will have much more control over their personal data, he says.

“It will change the way the internet works in the future. In the past there was open data but in the future (third parties) might have to pay for services if we don’t want to surrender personal data. People will come to realise how valuable their personal information is.”

Where will this technology take us in the coming years? “These technologies come into their own when we learn to work with them rather than as (human) replacements,” says Smyth who admits to being a technological “optimist”. If we use them in a responsible way the changes they can bring are to the good of everyone.”