Can machines help us digest the flood of information regularly face? Some thoughts about using technology to help us...

Can machines help us digest the flood of information regularly face? Some thoughts about using technology to help us…

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Can machines help us digest the flood of information regularly face? Some thoughts about using technology to help us process and understand the countless terms of services notices we regularly sign without reading.

Originally shared by Wasim Muklashy

Teaching Machines to Understand, and Summarize, Text

*We humans are swamped with text. It’s not just news and other timely information: Regular people are drowning in legal documents. The problem is so bad we mostly ignore it. Every time a person uses a store’s loyalty rewards card or connects to an online service, his or her activities are governed by the equivalent of hundreds of pages of legalese. Most people pay no attention to these massive documents, often labeled “terms of service,” “user agreement,” or “privacy policy.”

These are just part of a much wider societal problem of information overload. There is so much data stored—exabytes of it, as much stored as has ever been spoken by people in all of human history—that it’s humanly impossible to read and interpreteverything. Often, we narrow down our pool of information by choosing particular topics or issues to pay attention to. But it’s important to actually know the meaning and contents of the legal documents that govern how our data is stored and who can see it.

As computer science researchers, we are working on ways artificial intelligence algorithms could digest these massive texts and extract their meaning, presenting it in terms regular people can understand…”

#Future = #REALnews #robots #tech #innovation #science #design #singularity #engineering #automation #AI #artificialintelligence #economy #finance #universalbasicincome #basicincome #money #UBI 

https://singularityhub.com/2017/07/21/teaching-machines-to-understand-and-summarize-text/

https://singularityhub.com/2017/07/21/teaching-machines-to-understand-and-summarize-text/

7 comments

  1. The first mistake both authors make is to label this flood of material as information. Any material whether it is in printed or online must contain facts that are useful to be considered information. Much of the flood of material we are exposed to does not meet this definition. It is spam, pure and simple and has no value. Email accounts already have spam filters. Humans need to develop their own internal spam filters so they can sort the wheat from the chaff. Expecting a machine to do this for us is problematic since one person’s spam may be seen as useful information by another. I do not give a hoot about the joys of gardening, yet my wife does. We are both right.

  2. I was just complaining about this sort of thing the other day, and wishing I had a VPA to deal with it.

    In particular sorting and storing login/profile info on the many online accounts I am forced to make, which sometimes forces me to abandon and restart an account, as I recently had to do with my G+ account, after my old phone was stolen, and Google wouldn’t accept just my password to log in.

    I’m also having a difficult time setting up Samsung Pay for similar reasons.

    I can’t wait for the day I interact through a single interface that knows everything about me, and also the web. To be able to just tell the VPA what I want to do and wait for it.

  3. I’m using Google+ but I have a few doubts:

    https://plus.google.com/photos/

  4. I have used the auto summarize feature of MS Word to see if I want to read a long document.

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