Fake news: a problem that neither humans nor Facebook can solve?

Written by on November 8, 2017 in Guest Blog with 0 Comments

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A problem that humans can’t solve. There is a silver bullet to deal with the fake news issue, but the problem is that Facebook is not even close to being able to produce one and is having to rely on old, ineffective bullets instead.

This problem has been around for a while but really came to light in the summer of 2016, following a move to automate the selection of trending stories on Facebook.

Simply put, Facebook’s AI is incapable of working out which stories are fake and which are true which led to false stories being highlighted by Facebook as treading.

  • Facebook’s reaction to this problem has been to throw humans at the problem and a Bloomberg investigation has indicated that this is not working well at all.
  • Facebook has outsourced fact checking to PolitiFact, Snopes, ABC News, factcheck.org and the Associated Press for the period of 12 months but this has been problematic.
  • In order to be flagged as disputed on Facebook, two of the contracted organisations have to mark the story as false at which point the number of users seeing the story is cut by around 80%.
  • This manual process takes about three days to complete in many cases, it takes much longer.
  • On Facebook this is effectively useless as many stories will have trended, been seen by millions of users and disappeared again long before the humans can mark the story as false.
  • Consequently, the only way to solve this problem is to have AI that scans stories as they begin trending and can accurately weed out the fake ones.
  • This is where Facebook comes unstuck as RFM research has found that when it comes to AI, Facebook’s position is very weak (see here).
  • This is not because Facebook does not have good employees in this area but merely because it has not been working on it for long enough.
  • I believe that currently, excellence in AI has very little to do with how many big brains one has on the bench but how long one has been crunching the data.
  • This is where Facebook really suffers as it has only been working on AI for a couple of years whereas Google, Baidu and Yandex have all been crunching data for over 20 years.
  • To be fair, Facebook has shown some progress on image and video recognition (see here) but on the recognition and elimination of fake news, I have seen none whatsoever.
  • As a result, I think that Facebook’s contention that there is no silver bullet to deal with the fake news problem is incorrect.
  • There is a silver bullet but the real problem that Facebook has is that it has no idea how to make it.
  • Until it figures this out, it looks to me like the fake news problem is here to stay.
  • This weakness in AI is not limited to fake news but shows up everywhere across Facebook’s services making it the biggest challenge that Facebook is facing.
  • This problem has to be solved properly for Facebook to achieve its long-term potential as a fully-fledged ecosystem offering deep and intuitive services to 2bn+ users.
  • It is based on this that I can make a case for liking Facebook long-term meaning that this has to be fixed at all costs.

This article was first published on Radio Free Mobile.

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Richard Windsor

About the Author

About the Author: Dr Richard Windsor is the founder of Radio Free Mobile which is an independent research provider. The research helps clients to understand and evaluate the players in the digital ecosystem and presents a unique perspective on how all the pieces fit together in an easy to read and digest way. The product is available on a subscription basis and counts members of the handset, telecom carrier, Internet, semiconductor and financial industries as its subscribers. RFM is the land of the one man band meaning that Dr. W. also makes the tea. .

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