|Gartner Hype Cycle|
Who wants a chatbot experience like navigating a call centre voice response tree?
"Creating interfaces for people to interact with machine learning will be a challenge. At the moment, since the technology is so new, one of the only patterns we know is what Siri showed us on the iPhone.Alex Moore's company, Boomerang, designed their system to streamline the interaction model.
"Most of the conversations with Siri tend to become an elaborate back and forth. Talk to the device, and it will ask whatever questions it needs to ask to get you what you want. But what that interface turns into is a slightly more usable command-line interface. And while Bash has its adherents even today, Windows won. Conversational interfaces will not be able to replace the rich visual interactions that we’ve become used to over the past decades."
"Our best predictions came from throwing pure neural networks at the problem. The difficulty with that is that the output of those neural networks is complete gibberish to humans. The neural networks provide a matrix of weights that are applied to different parameters that the algorithms determine on their own. If you look at that matrix of weights, there is no way to make sense out of it. You just feed new data into it, let the machine make its calculations, and report a result.We're in the hype phase. Soon we'll get the backlash and maybe a few years out, something which actually works.
"By contrast, when we used classifiers from the decision tree family of algorithms, we were able to have a data scientist manually review the outputs of the machine learning algorithms for common combinations. We were able to manually translate the machine learning output in those frequent cases into something understandable to people. Rather than put a conversational agent between the analysis and the user, we traded off a slight bit of accuracy for a dramatic decrease in the amount of time users have to spend interacting with the product to receive the value."