Can NLP Save the World?

I was reading over Maureen Dowd's article this morning about Twitter civility, when my eye stopped at this statement by Farhad Manjoo, that Twitter had “tweaked its central feed to highlight virality, turning Twitter into a bruising barroom brawl featuring the most contentious political and cultural fights of the day.” Really? I've had a Twitter account for a few years and I never get any politically virulent tweets in my personal feed, but then I only follow NLP and ML researchers, people I have worked with, a couple of literary sites, etc., pretty nerdy stuff. I vote,  I keep up with issues by reading national news, I occasionally write my Senator and await his patronizing reply. I would call myself mildly politically active but I have always thought that posting something political on the Internet was pointless. It seems that a lot of people feel otherwise. I've been missing out on the bruising barroom brawl. Thankfully.

The article went on to mention that Twitter was proposing using dialog health metrics to monitor the tone of the Twitter discourse in terms of four characteristics of healthy dialog identified by the non-profit Cortico research organization:  (1) shared attention, (2) shared reality, (3) variety of opinion, and (4) receptivity. Twitter is calling out for expert help (see link) to implement tools for monitoring the discourse. This will be a very interesting NLP task to watch in coming years. We know that NLP and ML have been used to try to influence both the Brexit vote and the 2016 US election. Now it will be interesting to watch if NLP and ML can save us from lies, manipulation, and trolling. What if a truthfulness (or lack thereof) icon were to appear next to tweets containing nonsense that has already been debunked by sites like Snopes? That seems like a relatively easy first step for  an NLP/ML application. But how will people feel when an algorithm calls them a liar? This is going to get interesting.


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