Cognitive computing and business
An example of extracting insight from data to help make better decisions could be as simple as using a fitness tracker to help motivate someone to take the stairs instead of the lift. At a more sophisticated level, doctors could use cognitive computing to triage X-rays, recognising those which are simple to read and those that require a human eye to interpret.
“We are going to see more and more tasks that can be automated in interesting ways and there is good and bad in that. People wearing more sensors like fitness trackers and heart monitors will almost certainly lead to better healthcare,” McNamee said. “There will be constant data streams coming out of those devices that can be monitored for interesting patterns, something that just isn’t possible without that technology.”
According to Dadong Wan of Accenture, artificial intelligence and cognitive computing have the distinction of being futuristic technologies that happen to be well established.
“On the one hand, we’re still in the early stage of AI as a big technology development, but at the same time, in some ways it’s already well established. Every time we use our smart phones or buy things from the larger online retailers we are using AI, so it’s definitely here,” he said.
Wan is a senior research and innovation executive at Accenture’s Technology Labs, with cognitive computing being one of his specialist areas. He runs a research and development lab in Dublin focusing on artificial intelligence, the term he prefers to cognitive computing.
The question is for large enterprises in particular, Wan said, is what are some of the key applications. In the case of Amazon, he suggests that the way it is using AI capabilities to drive its core business really exemplifies the art of the possible.
“Large companies like Amazon can really use AI to achieve competitive advantage. Look at the different facets of their business influenced by it. Take product recommendations—over a third of the products bought from Amazon are recommended through their most advanced recommendation engines,” he said.
“Secondly, the majority of the products bought on Amazon are priced in real time based on the availability of the product, taking into account the supply chain and also maybe particular promotions they’re running.”
Amazon takes all this data into account and is able to learn over time what promotions work. As a result of this, its sales models change and are refined to reflect that new information over time.
“Thirdly and perhaps the most brilliant piece of work they’re putting out there is the Alexa AI and the echo appliance. Again, it’s relatively early days but they’re really working to remove as much friction from dealing with them as possible. Of course, the goal is to lock people into their ecosystem,” Wan said.
In the US, many people purchase all their weekly domestic shopping items on Amazon and have them delivered. Through using Alexa, they can just say ‘Alexa, order the same groceries as last week.’
“Doing an online shop is pretty painless but it’s still a chore to select 30 or so items to put in a virtual shopping basket. Using Alexa is extremely simple and it’s the ultimate friction remover—it makes life so much easier.”
According to Wan, there are potentially many other uses for this kind of technology, but they’re not being utilised because of a lack of understanding of the potential the tech holds.
“I firmly believe that the underlying IT systems are technically capable, but they’re not being fully leveraged. At the moment, there is friction between people and computer systems because we don’t speak the same language, and people are forced to speak in a machine language,” he said.
“This conversational commerce that’s developing will serve to reduce the friction between humans and the system.”