Google Patents Robot help for Social Media Burnout
If maintaining your presence on social media is becoming a burden, Google may be able to help. The search giant has patented plans for software which slowly learns how you react on social networks. The software can mimic your usual responses to updates and messages from friends and relations to help cope with the daily data deluge. The software also analyses continuing interaction and flags messages that demand a more personal response.
“The popularity and use of social networks and other types of electronic communication has grown dramatically in recent years,” wrote Google software engineer Ashish Bhatia in the patent. “It is often difficult for users to keep up with and reply to all the messages they are receiving.”
In a bid to help people cope Mr Bhatia envisions a sophisticated system that collects information about all the different social networks someone has joined. This logs what they do and notes how they respond to the different types of messages, notifications, status changes, videos, images and links sent to them.
The system analyses these responses so it can eventually start making suggestions of its own that, ideally, should be indistinguishable from those of an actual person.
The suggested system should also be flexible enough to cope with many different types of event, use data culled from other interactions with a person and shape the responses to match the style demanded by different social networks. For instance, suggested responses to events on professional social networks should be more formal than those on services where someone interacts with friends and family.
Instead of writing every response individually or clicking buttons to “like” or forward messages, the software would generate suggested responses which a person could simply agree to be posted on their behalf.
Despite its potential sophistication, examples provided in the patent suggest it still needs refinement. In response to learning that an acquaintance called David has changed jobs, the system might suggest: “Hey David, I am fine, You were in ABC corp for 3 years and you recently moved to XYZ corp, how do you feel about the difference, enjoying your new workplace?”
Social media technologist Hadley Beeman said the subtleties of human interaction might undermine the ability of Google’s suggested system to pick out what matters most and flag it appropriately. A calendar appointment for lunch might look unimportant but loom large in someone’s life for reasons the software cannot spot.
“The problem is that the ‘important stuff’ (or the trivial) depends on what our relationship is,” said Ms Beeman. “If I had lunch with you, for example, then your message about hating that terrible sandwich is actually relevant to me.”
Prof Shaun Lawson from the University of Lincoln who studies social computing wondered who would be compelled to use such a service. “Are we really so concerned with posting messages to every friend or follower that we feel compelled to have to automate that process?” he said.
Google’s system seemed to underline the common misconception that social media was reducing contact between people, he said. “The fabulous thing about social media is the reverse,” said Prof Lawson. “It facilitates human-to-human interaction in ways that were impossible even a few years ago.”