In the marketing and technology sector, this territory is currentlydominated by the data scientists. The challenge of extracting value fromhuge data sets is in some ways fuelling the interest in AI. The goal here is tomake even better use of data to support strategic planning and drive real-time decision making, reducing our dependency on expensive, fallible datascientists and customer support staff, and increasingly automating the nextsteps without human intervention.
There is already a wide range of examples in this space, from automatedpricing to predictive customer care, personalisation of ad targeting, andmore. This list from econsultancy of 15 examples is worth a scan. And as time goes on, we can expect these services to become moreaccessible to less technically minded people. There has also been plenty oftalk about bots, especially after Facebook introduced a way of embeddingbots in its Messenger app. Facebook refers to it as a hybrid betweenlanguage recognition, decision tree mapping and customer care – in otherwords, it’s essentially a form of Interactive Voice Response for text.
For the best examples, check out Poncho and either CNN or the Wall StreetJournal on Messenger. The demos look good, but early results are poor.And even when it improves, this only barely qualifies as AI. Until it reachesa greater level of sophistication, it’s mostly creating the illusion ofintelligence because of its dependence on pre-determined decision trees.
That isn’t to say the bot approach isn’t worth exploring; far from it. Justdon’t get lulled into thinking you’re in the vanguard of artificial intelligencewhile you’re at it, and get ready for a frustrating time in the short term.
While general artificial intelligence might be many years away, it’s worthkeeping an eye on emerging developments in that space as well. They’llprobably be useful well before they hit their stated goals.
One of the more interesting developments is viv.ai, a service beingdeveloped by one of the ambitious Siri co-creators, Dag Kittlaus. Not onlydoes he want to create a cloud-based platform for finding connectionsbetween disparate data sets, he wants to put a universally recognised voiceinterface on it. He’d like his ‘V’ logo to be as ubiquitous as the bluetoothlogo, so we know how to engage with the system. Apparently we speak 3-4times faster than we write, so this makes sense so long as the system isn’t plagued by the same challenges as Siri or Google Now.
When it comes to voice interaction in general, the early signs fromAlexa (from Amazon) are very promising, so maybe we’re on the cusp of abreakthrough here.