<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>dcolkitt</author><text>On the surface it sounds pretty outrageous. My question would be though, what &lt;i&gt;should&lt;/i&gt; Facebook do instead?&lt;p&gt;A recommendation engine is just an algorithm to maximize an objective function. That objective function being matching users with content that they enjoy and engage with. The algorithm has no in-built notion of political extremism. It almost assuredly seems to be the case that people with radical opinions prefer to consume media that matches their views. If Bob is a three-percenters, it&amp;#x27;s highly unlikely he&amp;#x27;d prefer to read the latest center-left think piece from The Atlantic.&lt;p&gt;Unless you&amp;#x27;re willing to ban recommend engines entirely, the only possible alternative I can see is for Facebook to intentionally tip the scales. Extremist political opinions would have to be explicitly penalized in the objective function.&lt;p&gt;But now you&amp;#x27;ve turned Facebook from a neutral platform into an explicit arbiter of political opinion. It means some humans at Facebook are intentionally deciding what people should and should not read, watch and listen to. Remember Facebook as an organization is not terribly representative of the country as a whole. Fewer than 5% of Facebook employees vote Republican, compared to 50% of the country. Virtually no one is over 50. Males are over-represented relative to females. Blacks and hispanics are heavily under-represented. And that doesn&amp;#x27;t even get into international markets, where the Facebook org is even less representative.&lt;p&gt;The cure sounds worse than the disease. I really think it&amp;#x27;s a bad idea to pressure Facebook into the game of explicitly picking political winners and losers. A social media platform powerful enough to give you everything you want is strong enough to destroy everything you value.</text><parent_chain><item><author>save_ferris</author><text>&amp;gt; In 2016, internal analysis at Facebook found 64% of all extremist group joins were due to their own recommendation tools. Yet repeated attempts to counteract this problem were ignored or shut down.&lt;p&gt;That&amp;#x27;s pretty damning. Facebook execs knew that extremist groups were using their platform and Facebook&amp;#x27;s own tooling catalyzed their growth, and yet they did nothing about it.</text></item></parent_chain></comment><story><title>Testimony to House committee by former Facebook executive Tim Kendall</title><url>https://energycommerce.house.gov/sites/democrats.energycommerce.house.gov/files/documents/09.24.20%20CPC%20Witness%20Testimony_Kendall.pdf</url></story>
<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>rsynnott</author><text>But doing so would hurt engagement, and hence the bottom line!&lt;p&gt;Facebook have, perhaps accidentally, created a monster of perverse incentives. Not sure what the solution is, besides regulation (which would be extremely difficult).</text><parent_chain><item><author>save_ferris</author><text>&amp;gt; In 2016, internal analysis at Facebook found 64% of all extremist group joins were due to their own recommendation tools. Yet repeated attempts to counteract this problem were ignored or shut down.&lt;p&gt;That&amp;#x27;s pretty damning. Facebook execs knew that extremist groups were using their platform and Facebook&amp;#x27;s own tooling catalyzed their growth, and yet they did nothing about it.</text></item></parent_chain></comment><story><title>Testimony to House committee by former Facebook executive Tim Kendall</title><url>https://energycommerce.house.gov/sites/democrats.energycommerce.house.gov/files/documents/09.24.20%20CPC%20Witness%20Testimony_Kendall.pdf</url></story>