The hysteria surrounding both machine learning and artificial intelligence is substantiating mathematician Alan Turing’s assertion that eventually “no one will be able to speak of machines thinking without expecting to be contradicted”.
Indeed now, the concept of the ‘rise of robots’ is no longer merely a plot in a Hollywood sci-fi blockbuster, but an area being explored by academics, researchers and technologists across the world.
Silicon Valley start-up Lumiata, for example, uses AI to map out current and future health trajectories of individuals and provide detailed reasons behind every prediction.
Ash Damle, founder and CEO of the company, told BusinessCloud that AI solves an issue of scale.
“If we gave physicians enough time to go through all of the data and look for patterns and individuals, they could get some wonderful insight, but the reality is that people are constrained,” he said.
Add to that the complex nature of healthcare data – by far more complicated than other industries including the financial and automotive sectors, and there is a need to help clinicians to do their jobs – with the added caveat of potentially improving the lives of patients.
A lot of the supposed benefits from AI are very similar to those that have been talked about for years with big data analytics – huge swathes of data being crunched and new insights being unveiled. But AI goes a step further than big data.
“It’s about being able to predict the trajectory of someone, but more importantly how to make a prediction to affect or bend that trajectory into the right direction,” added Damle.
AI is about acting on insight, rather than the insight itself.
Jeff Spight, president of collaborative health systems at healthcare organisation Universal American explained: “Big data is giving you insights and priorities but it is not able to translate that into a clinical action or intervention which AI can – big data is the necessary background to get there, but it can’t do the steps in terms of making it actionable.”
Universal American is a customer of Lumiata’s and Spight said the way the machine communicates with clinicians was a big reason that Lumiata had the edge over other vendors.
“It’s not just an AI tool – we spent a lot of time looking at IBM Watson and although it will eventually be a very powerful tool, Lumiata’s clinician screen over the information which enables it to interpret the data in a semantic way and put it into clinical speak, made the difference,” he said.