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Please permit me to play the pessimistic man on the street: If Facebook can deploy AI to detect the early signs of suicide, why can't they deploy AI to detect "

Please permit me to play the pessimistic man on the street: If Facebook can deploy AI to detect the early signs of suicide, why can't they deploy AI to detect "fake news" or those susceptible to "fake news"? Furthermore, "cui bono" (for whose benefit [0])? What does Facebook gain from being able perform this sort of detection given it is a for-profit corporation and not a non-profit philanthropic organization? An aside: I wonder if there will be accounts of similar to Dante's Inferno [1], or Joseph Conrad's Heart of Darkness [2] about today's corporations in the future some day. [0] https://en.wikipedia.org/wiki/Cui_bono https://en.wikipedia.org/wiki/Cui_bono [1] https://en.wikipedia.org/wiki/Inferno_(Dante) https://en.wikipedia.org/wiki/Inferno_(Dante) [2] https://en.wikipedia.org/wiki/Heart_of_Darkness https://en.wikipedia.org/wiki/Heart_of_Darkness

balls187 9y ago
Al Franken asked that question (at least a version of it). https://www.youtube.com/watch?v=SlPRP-XrRBc https://www.youtube.com/watch?v=SlPRP-XrRBc
danso 9y ago
I'm not a psychiatrist nor have any expertise or insight into suicidal behavior, but I feel very confident in saying that the detection of a potential suicide is a much easier problem than the detection of fake news. There's a few reasons for why suicide seems easier to detect, but I'll just give one: it is feasible to conceive of a reliable and reasonably efficient threshold for detecting some suicides. And I can say this even though off-hand, I can't think of anyone close to me that has killed themselves...the closest example might be Aaron Swartz, who I did not know off of the Internet, and whose suicide even to this day stuns me. And yet I can come up with a few real-life scenarios in which I would feel comfortable in calling 911 about: - I see someone (a total stranger) standing on the railing of the Golden Gate bridge, facing in the direction they need to face to jump out into the water. - I see someone, again, doesn't matter if a total stranger or someone I know, holding a gun to their head with their finger to the trigger. - A friend I haven't heard from for sometime, and am not expecting to hear from in the near future, suddenly calls me to tell me they've swallowed an entire bottle of Tylenol and they wanted to at least talk to me one more time before death. All these situations, I have no problem calling 911 and screaming at the operator to get help quick. The first 2 situations aren't easily detectable in the framework of Facebook communication. But the third one, I'm pretty sure have actually happened on Facebook and other social media networks, and people, with and without the help of the social media service, attempted to save the person's life: - http://www.cnn.com/2009/SHOWBIZ/Movies/04/03/moore.twitter.threat/index.html http://www.cnn.com/2009/SHOWBIZ/Movies/04/03/moore.twitter.t... - https://www.reddit.com/r/AskReddit/comments/3ham0a/serious_those_who_have_been_talked_down_from/cu68fmx/ https://www.reddit.com/r/AskReddit/comments/3ham0a/serious_t... - https://www.theguardian.com/technology/2011/jan/05/facebook-suicide-simone-back https://www.theguardian.com/technology/2011/jan/05/facebook-... - https://www.buzzfeed.com/drumoorhouse/my-best-friend-saved-me-when-i-attempted-suicide-but-i-didnt https://www.buzzfeed.com/drumoorhouse/my-best-friend-saved-m... The content of these messeages, and other meta-factors, such as time of day and relationship and frequency of contact between receiver/sender, are signals. The threshold can be set to a level high enough that false positives are relatively rare -- as rare as someone who looks like they're about to jump off the Golden Gate Bridge but turns out to be posing for a photoshoot, or is just being an extreme troll. The downside is that there may be a lot of false negatives. But as tragic as that is -- some lives saved through automation is better than nothing. And this heuristic could be implemented in an efficient way. So what's the difference between suicides and fake news? For fake news, it seems impossible to conceive of any kind of threshold that would catch items that are indisputably fake news while having a very low rate of false positives. The main reason? There is no objective definition of either "fake" or "news", nevermind "fake news", when it comes to items that are purported to be news stories. Let's ignore the concept of news. Let's consider assertions. How easy would be for Facebook to come up with an algorithm to flag true and false for these examples: - The earth is flat - Barack Obama is a Muslim - The Holocaust is a fabricated historical event. For the sake of argument, I'll agree that FB's NLP and Knowledgebase-type tech can accurately flag the above assertions -- in fact, Alexa did a pretty good job of answering "Yes" and "No" when I rephrased them as questions. How about when these assertions are reworded to be a little bit different: - There are researchers today who believe the Earth is flat and say they have evidence to prove it - Barack Obama may secretly be a Muslim, according to some pastors - Did the Holocaust happen? Assume the above examples are titles to news articles. And if you don't think such phrasing would be used in a mainstream news source, I invite you to visit washingtonpost.com or huffingtonpost.com on any given day. If you've paid attention to recent controversies about Google SERP, you'll recognize that the third example -- "Did the Holocaust happen?" -- was recently a major problem for Google. And that was for something much simpler -- what sites are most relevant for that query -- than what Facebook has to figure out: "Is this fake news" Maybe you want to argue that in this situation, Facebook should definitely filter it out as "fake news" because not only does the article contain a lot of implied bullshit, it is simply not a news article. But then you've introduced a whole other problem: how does Facebook determine the difference between a purported news story and an op-ed? Human beings have problems with this when it comes to newspapers and their editorial sections: https://www.nytimes.com/2015/01/11/public-editor/an-uneasy-mix-of-news-and-opinion.html https://www.nytimes.com/2015/01/11/public-editor/an-uneasy-m... https://www.americanpressinstitute.org/publications/good-questions/news-opinion-rebecca-iannucci/ https://www.americanpressinstitute.org/publications/good-que... The ability for Facebook's fake news regulator to tell the difference between opinion and news is critical. Because while we may agree that a news story titled "The Holocaust is a Jewish Conspiracy" should not be treated as truth nor news, it's a whole other can of worms to argue that Facebook should surpress someone wanting to go on a angry opinionated rant, no matter how distasteful their opinion. I'm not a NLP expert, but this seems to me like a pretty hard NLP problem to do with reasonable accuracy and efficiency. OK, let's make things simple and assume a universe in which the only article wall-post type that Facebook has to deal with are news stories, i.e. no one ever posts opinion pieces/blog rants -- or hell, satire, something that Google News has had trouble with even though Google News uses a whitelist... One of the other fundamental challenges is that the definition of what is "news" is very hard for humans to objectively quantify. Look at the popularity of Reddit's r/todayilearned, one of Reddit's most popular subreddits even though it consists of posting facts that are years/decades old. And yet, for the vast majority of users, those facts are most definitely news, and news that is enlightening and interesting. ----- Let's consider some real-life example headlines of purported news stories: "SHOCKING: How Barack Obama lived with an single white teenage mother without Michelle knowing" Is this fake news? It is most definitely not fake: Barack Obama was born to an unmarried white 19-year old. And I bet there are plenty of people who might not realize that his mom was so young and was a single mother. Some people might not even realize Barack is half white! So this headline not only contains no falsehoods, but assertions that are news to many readers. And you you could make a strong argument that it should be penalized as "fake news" because the wording of the headline is trying its best to imply a sexual and illicit multiracial affair. I can't even imagine how difficult it would be to have an algorithm that works with this example, nevermind detects "bad intentions". How about this one: - Bill Cosby said to be a serial rapist Does this seem like an obvious real news story? Tell that to all the journalists -- including the CNN executive who was writing Cosby's biography -- before a shaky YouTube clip of Hannibal Buress calling Cosby a rapist went viral: http://www.latimes.com/entertainment/tv/showtracker/la-et-st-hannibal-buress-cosby-joke-20151231-story.html http://www.latimes.com/entertainment/tv/showtracker/la-et-st... Buress's routine was based off of a long-ago news story that never got major play. You can go to the TMZ archives for the Bill Cosby tag and see for yourself that even TMZ had nothing about Cosby's allegations until Buress went viral. And Buress's routine was not even new -- he said he'd been using it for about 6 months before the random YouTube clip got noticed. Pretend Buress never went viral. In this alternate universe of 2015, the Cosby biography has been published, Cosby is still respected, and yet every once in awhile, your Facebook feed has screaming headlines like "HOW THE MEDIA IGNORES BILL COSBY'S HISTORY OF RAPE". Would you be wrong in wondering why the fuck Facebook hasn't suppressed such outlandish posts? Or pretend you were one of the few people to have read the original expose on Cosby's accusers. You know it's a fact that he has a "history", but it is now nearly 10 years later -- if those accusations had any merit, the media, especially TMV, would be all over Cosby. But that's not the case so you flag the post as "fake news". What is Facebook's algorithm supposed to do here? Final example of a news story headline: SHOCK CLAIM: KEVIN SPACEY SEXUALLY ASSAULTED ME WHEN I WAS A BOY This claim is definitely news and of course, we know now that it is unlikely to be fake. But this example illustrates one more core difficulty in telling what is "fake", what is "news" and what is "fake news". BuzzFeed was the first to report the claim by Anthony Rapp, and it was an exclusive -- meaning no other major news outlet had anything that could confirm it: https://www.buzzfeed.com/adambvary/anthony-rapp-kevin-spacey-made-sexual-advance-when-i-was-14 https://www.buzzfeed.com/adambvary/anthony-rapp-kevin-spacey... It's easy for Facebook to tell that this is "news". But what signals does it have that it isn't fake, when no other major outlets is reporting it? BuzzFeed's entire story is based off of one person's recollection of a decades-ago incident. In the hours between Buzzfeed's shocking scoop and reports of other allegations that eventually doomed Spacey and House of Cards -- a strong case could be made that FB should be penalizing the Buzzfeed article as "fake" or at least "maybe fake". And a lot of this would hinge on how much you think buzzfeed.com should be treated as reliable.
- tareqak 9y ago
  Thank you for that detailed reply! I really appreciate it, and I read through all of it. One thing that I forgot to mention were that the some of the ads, if not all, run by the IRA (Internet Research Agency [0]) were veritably false. If Facebook kept score of ads that were known to be false run by an ad buyer couldn't they present that information beside the ad e.g. a sort of running "boy crys wolf" heuristic? Thanks again for your well-researched and extensive reply. [0] https://en.wikipedia.org/wiki/Internet_Research_Agency https://en.wikipedia.org/wiki/Internet_Research_Agency
  - danso 9y ago
    Yes, I can definitely agree that there is far more that Facebook can do in investing enough manual effort into shutting down outliers in egregious abuse.
AlexandrB 9y ago
> Please permit me to play the pessimistic man on the street: If Facebook can deploy AI to detect the early signs of suicide, why can't they deploy AI to detect "fake news" or those susceptible to "fake news"? It's not about detection success rates, but economic outcomes if they screw up. If Facebook claims to detect fake news, but does it incorrectly they will be pilloried in the press (again). If they detect suicidal behaviour wrong the victim of said detection has little recourse. In short, it's far safer to use vulnerable individuals as guinea pigs for AI than organizations that buy (digital) ink by the barrel.

balls187 9y ago

Al Franken asked that question (at least a version of it). https://www.youtube.com/watch?v=SlPRP-XrRBc https://www.youtube.com/watch?v=SlPRP-XrRBc

danso 9y ago

I'm not a psychiatrist nor have any expertise or insight into suicidal behavior, but I feel very confident in saying that the detection of a potential suicide is a much easier problem than the detection of fake news. There's a few reasons for why suicide seems easier to detect, but I'll just give one: it is feasible to conceive of a reliable and reasonably efficient threshold for detecting some suicides. And I can say this even though off-hand, I can't think of anyone close to me that has killed themselves...the closest example might be Aaron Swartz, who I did not know off of the Internet, and whose suicide even to this day stuns me. And yet I can come up with a few real-life scenarios in which I would feel comfortable in calling 911 about: - I see someone (a total stranger) standing on the railing of the Golden Gate bridge, facing in the direction they need to face to jump out into the water. - I see someone, again, doesn't matter if a total stranger or someone I know, holding a gun to their head with their finger to the trigger. - A friend I haven't heard from for sometime, and am not expecting to hear from in the near future, suddenly calls me to tell me they've swallowed an entire bottle of Tylenol and they wanted to at least talk to me one more time before death. All these situations, I have no problem calling 911 and screaming at the operator to get help quick. The first 2 situations aren't easily detectable in the framework of Facebook communication. But the third one, I'm pretty sure have actually happened on Facebook and other social media networks, and people, with and without the help of the social media service, attempted to save the person's life: - http://www.cnn.com/2009/SHOWBIZ/Movies/04/03/moore.twitter.threat/index.html http://www.cnn.com/2009/SHOWBIZ/Movies/04/03/moore.twitter.t... - https://www.reddit.com/r/AskReddit/comments/3ham0a/serious_those_who_have_been_talked_down_from/cu68fmx/ https://www.reddit.com/r/AskReddit/comments/3ham0a/serious_t... - https://www.theguardian.com/technology/2011/jan/05/facebook-suicide-simone-back https://www.theguardian.com/technology/2011/jan/05/facebook-... - https://www.buzzfeed.com/drumoorhouse/my-best-friend-saved-me-when-i-attempted-suicide-but-i-didnt https://www.buzzfeed.com/drumoorhouse/my-best-friend-saved-m... The content of these messeages, and other meta-factors, such as time of day and relationship and frequency of contact between receiver/sender, are signals. The threshold can be set to a level high enough that false positives are relatively rare -- as rare as someone who looks like they're about to jump off the Golden Gate Bridge but turns out to be posing for a photoshoot, or is just being an extreme troll. The downside is that there may be a lot of false negatives. But as tragic as that is -- some lives saved through automation is better than nothing. And this heuristic could be implemented in an efficient way. So what's the difference between suicides and fake news? For fake news, it seems impossible to conceive of any kind of threshold that would catch items that are indisputably fake news while having a very low rate of false positives. The main reason? There is no objective definition of either "fake" or "news", nevermind "fake news", when it comes to items that are purported to be news stories. Let's ignore the concept of news. Let's consider assertions. How easy would be for Facebook to come up with an algorithm to flag true and false for these examples: - The earth is flat - Barack Obama is a Muslim - The Holocaust is a fabricated historical event. For the sake of argument, I'll agree that FB's NLP and Knowledgebase-type tech can accurately flag the above assertions -- in fact, Alexa did a pretty good job of answering "Yes" and "No" when I rephrased them as questions. How about when these assertions are reworded to be a little bit different: - There are researchers today who believe the Earth is flat and say they have evidence to prove it - Barack Obama may secretly be a Muslim, according to some pastors - Did the Holocaust happen? Assume the above examples are titles to news articles. And if you don't think such phrasing would be used in a mainstream news source, I invite you to visit washingtonpost.com or huffingtonpost.com on any given day. If you've paid attention to recent controversies about Google SERP, you'll recognize that the third example -- "Did the Holocaust happen?" -- was recently a major problem for Google. And that was for something much simpler -- what sites are most relevant for that query -- than what Facebook has to figure out: "Is this fake news" Maybe you want to argue that in this situation, Facebook should definitely filter it out as "fake news" because not only does the article contain a lot of implied bullshit, it is simply not a news article. But then you've introduced a whole other problem: how does Facebook determine the difference between a purported news story and an op-ed? Human beings have problems with this when it comes to newspapers and their editorial sections: https://www.nytimes.com/2015/01/11/public-editor/an-uneasy-mix-of-news-and-opinion.html https://www.nytimes.com/2015/01/11/public-editor/an-uneasy-m... https://www.americanpressinstitute.org/publications/good-questions/news-opinion-rebecca-iannucci/ https://www.americanpressinstitute.org/publications/good-que... The ability for Facebook's fake news regulator to tell the difference between opinion and news is critical. Because while we may agree that a news story titled "The Holocaust is a Jewish Conspiracy" should not be treated as truth nor news, it's a whole other can of worms to argue that Facebook should surpress someone wanting to go on a angry opinionated rant, no matter how distasteful their opinion. I'm not a NLP expert, but this seems to me like a pretty hard NLP problem to do with reasonable accuracy and efficiency. OK, let's make things simple and assume a universe in which the only article wall-post type that Facebook has to deal with are news stories, i.e. no one ever posts opinion pieces/blog rants -- or hell, satire, something that Google News has had trouble with even though Google News uses a whitelist... One of the other fundamental challenges is that the definition of what is "news" is very hard for humans to objectively quantify. Look at the popularity of Reddit's r/todayilearned, one of Reddit's most popular subreddits even though it consists of posting facts that are years/decades old. And yet, for the vast majority of users, those facts are most definitely news, and news that is enlightening and interesting. ----- Let's consider some real-life example headlines of purported news stories: "SHOCKING: How Barack Obama lived with an single white teenage mother without Michelle knowing" Is this fake news? It is most definitely not fake: Barack Obama was born to an unmarried white 19-year old. And I bet there are plenty of people who might not realize that his mom was so young and was a single mother. Some people might not even realize Barack is half white! So this headline not only contains no falsehoods, but assertions that are news to many readers. And you you could make a strong argument that it should be penalized as "fake news" because the wording of the headline is trying its best to imply a sexual and illicit multiracial affair. I can't even imagine how difficult it would be to have an algorithm that works with this example, nevermind detects "bad intentions". How about this one: - Bill Cosby said to be a serial rapist Does this seem like an obvious real news story? Tell that to all the journalists -- including the CNN executive who was writing Cosby's biography -- before a shaky YouTube clip of Hannibal Buress calling Cosby a rapist went viral: http://www.latimes.com/entertainment/tv/showtracker/la-et-st-hannibal-buress-cosby-joke-20151231-story.html http://www.latimes.com/entertainment/tv/showtracker/la-et-st... Buress's routine was based off of a long-ago news story that never got major play. You can go to the TMZ archives for the Bill Cosby tag and see for yourself that even TMZ had nothing about Cosby's allegations until Buress went viral. And Buress's routine was not even new -- he said he'd been using it for about 6 months before the random YouTube clip got noticed. Pretend Buress never went viral. In this alternate universe of 2015, the Cosby biography has been published, Cosby is still respected, and yet every once in awhile, your Facebook feed has screaming headlines like "HOW THE MEDIA IGNORES BILL COSBY'S HISTORY OF RAPE". Would you be wrong in wondering why the fuck Facebook hasn't suppressed such outlandish posts? Or pretend you were one of the few people to have read the original expose on Cosby's accusers. You know it's a fact that he has a "history", but it is now nearly 10 years later -- if those accusations had any merit, the media, especially TMV, would be all over Cosby. But that's not the case so you flag the post as "fake news". What is Facebook's algorithm supposed to do here? Final example of a news story headline: SHOCK CLAIM: KEVIN SPACEY SEXUALLY ASSAULTED ME WHEN I WAS A BOY This claim is definitely news and of course, we know now that it is unlikely to be fake. But this example illustrates one more core difficulty in telling what is "fake", what is "news" and what is "fake news". BuzzFeed was the first to report the claim by Anthony Rapp, and it was an exclusive -- meaning no other major news outlet had anything that could confirm it: https://www.buzzfeed.com/adambvary/anthony-rapp-kevin-spacey-made-sexual-advance-when-i-was-14 https://www.buzzfeed.com/adambvary/anthony-rapp-kevin-spacey... It's easy for Facebook to tell that this is "news". But what signals does it have that it isn't fake, when no other major outlets is reporting it? BuzzFeed's entire story is based off of one person's recollection of a decades-ago incident. In the hours between Buzzfeed's shocking scoop and reports of other allegations that eventually doomed Spacey and House of Cards -- a strong case could be made that FB should be penalizing the Buzzfeed article as "fake" or at least "maybe fake". And a lot of this would hinge on how much you think buzzfeed.com should be treated as reliable.

tareqak 9y ago
Thank you for that detailed reply! I really appreciate it, and I read through all of it. One thing that I forgot to mention were that the some of the ads, if not all, run by the IRA (Internet Research Agency [0]) were veritably false. If Facebook kept score of ads that were known to be false run by an ad buyer couldn't they present that information beside the ad e.g. a sort of running "boy crys wolf" heuristic? Thanks again for your well-researched and extensive reply. [0] https://en.wikipedia.org/wiki/Internet_Research_Agency https://en.wikipedia.org/wiki/Internet_Research_Agency
- danso 9y ago
  Yes, I can definitely agree that there is far more that Facebook can do in investing enough manual effort into shutting down outliers in egregious abuse.

AlexandrB 9y ago

> Please permit me to play the pessimistic man on the street: If Facebook can deploy AI to detect the early signs of suicide, why can't they deploy AI to detect "fake news" or those susceptible to "fake news"? It's not about detection success rates, but economic outcomes if they screw up. If Facebook claims to detect fake news, but does it incorrectly they will be pilloried in the press (again). If they detect suicidal behaviour wrong the victim of said detection has little recourse. In short, it's far safer to use vulnerable individuals as guinea pigs for AI than organizations that buy (digital) ink by the barrel.