Are Chatbots and Voice
Assistants Superfluous?
David Linthicum & Chett Rubenstein
While it may be convenient to talk to
your computer, today chatbots pro-
vide little value to many processes,
yet they get an inordinate amount of
attention from providers.
There’s yet another cloud service from AWS: Amazon
Lex, which lets developers build conversational inter-
faces into applications for voice and text. It uses the
same deep learning technologies that power Ama-
zon's Alexa voice assistant.
Lex lets you quickly build natural language conversa-
tional bots, aka chatbots. Microsoft has a similar
technology, called the Microsoft Bot Framework.
This seems to be a common service that most public
cloud providers are looking to offer. Many third par-
ties offer chatbot technology as well.
But the question is not if we can have a voice conver-
sation with our applications—we clearly can—but if we
should have a conversation with our applications?
30 | THE DOPPLER | FALL 2017
Natural language processing has been around for
some time. But only recently has it gotten practical.
Still, it’s not perfect.
Most of us have been frustrated with misunderstand-
ings as the computer tries to take something as
imprecise as your voice and make sense of what you
actually mean. Even with the best speech processing,
no chatbots are at 100-percent recognition, much
less 100-percent comprehension.
It seems very inefficient to resort to imprecise sys-
tems when we have more precise ones available. Even
if they were 100-percent accurate in their recogni-
tion and comprehension, why use voice? If things
need to talk to each other, let’s use direct digital
mechanisms, which are way more accurate than me
talking to a machine.
One distinct advantage of cloud computing is to auto-
mate things that have yet to be automated, in many
cases removing people from the system. In other
words, let the machines chat at 100-percent accuracy
rather than have me talk to a chatbot. The ultimate