How hot is work chat in the enterprise? So trendy that it’s now being used to improve the very thing it’s supposedly killing off email.
Cognition Meets Communication
The user taps on the most appropriate one to embed it in her response and has the option to manually type or verbally dictate additional text.
Google announced yesterday a new feature for its Inbox application, which is an alternate Gmail interface designed for use on mobile devices. That feature, called Smart Reply, lets Inbox users reply to an incoming email with a short message (one phrase or sentence) that has been suggested by the application.
Google’s blog post announcing the new feature highlights the natural language processing, artificial intelligence, and machine learning technologies that work behind the scenes. Inbox uses these technologies to formulate three possible short responses for each incoming message. The user taps on the most appropriate one to embed it in her response and has the option to manually type or verbally dictate additional text.
How Smart Reply Works
The three auto-generated, suggested responses are based on the content of the incoming email message and the responses that were generated and selected for previous, similar messages. Smart Reply uses separate neural networks that work in tandem; one network reads and makes sense of every word in the incoming text and the second network predicts best-fit responses and synthesizes them into grammatically correct replies.
The principles and even some of the technologies behind Smart Reply are not new. The Autonomy IDOL technology that Hewlett-Packard infamously acquired four years ago is used to auto-classify digital documents based on their content. Once classified, the documents can more easily be searched for, used in workflows, and archived.
Just last week IBM announced its new intelligent data capture solution, IBM Datacap Insight Edition, which uses cognitive computing capabilities to read document-based content and auto-classify it. Like Google’s and H-P’s technologies, IBM’s software must initially be trained with a set of control documents and then continues to learn as it reviews documents in a production environment.
Smart Reply and Chatbots
Inbox’s new ability to read text and formulate multiple, viable short responses doesn’t quite turn email into real-time messaging, but it does help individuals respond more quickly to the incoming messages in their email queue. Pair that with instant notifications of new incoming email messages on a mobile device and email becomes much more like instant messaging and other forms of work chat.
Google has taken a significant first step toward creating an intelligent bot that replies to email messages for you based on their content. Contrast this with the current practice of employing prebuilt, user-defined rules to reply with a canned response depending on who sent the incoming email or based on the recipients schedule (think vacation autoreplies).
If Google were to apply its deep neural network technology in Hangouts, it would move closer to Slack, HipChat, Telegram and other work chat tools that use bots to reply to user generated queries and as intermediaries between users and integrated third-party applications. In fact, Hangouts would have a differentiated advantage – the ability to parse not only incoming messages and suggest appropriate responses, but to do the same with text-based documents that are attached to chat messages.
It is likely that Google will go beyond applying this new technology in apps like Inbox and Hangouts. Imagine the power of having Smart Reply baked into Android, so it could be deployed on watches, in cars and as part of other emerging hardware-based platforms that run on that operating system. Tap on the watch’s or car’s display and quickly choose and send a response to an incoming message.
Some more advanced variant of Smart Reply might be used to semi-automate communication between nodes in mixed networks of machines and humans – Networks of Everything. Take as an example the current generation of software (the machine) that listens to social media and discerns trending topics related to a company’s customer-facing operations. This type of software could be enhanced with cognitive capabilities so that it would be able to suggest appropriate Twitter-length responses to an individual tasked with responding to relevant incoming social content. Eventually, the software might be able to respond, without human intervention, directly to someone expressing their opinion on social media.
The possibilities are numerous and mind-boggling. For now, Google has taken an important step toward a computing future in which real-time communication at work is increasingly semi- or fully-automated.
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