๐Ÿ“š Agora node [[moderation]] โ˜†
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๐Ÿ“œ File moderation.md by @flancian โ˜† ๐Ÿ“Ž ๏ธ๐Ÿ”— โœ๏ธ โ›ถ
๐Ÿ“œ File moderation.md by @agora@botsin.space โ˜† ๐Ÿ“Ž โ›ถ
๐Ÿ“œ File moderation.md by @flancian@social.coop โ˜† ๐Ÿ“Ž โ›ถ

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๐ŸŒŒ Agora context for [[moderation]]

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๐Ÿ“š Agora node [[bots for comments moderation]] (pulled by the Agora)
๐Ÿ“œ File Artificial Intelligence/Introduction to AI/Week 3 - Introduction/Bots for comments moderation.md by @KGBicheno โ˜† ๐Ÿ“Ž

Bots for comments moderationยง

Go back to [[Week 3 - Introduction]]


Using bots for moderation would be as accurate if not more accurate than a human in some cases. In situations where a legal department or highly-strung legal overseer is present, however, it is unlikely that a bot will be able to match the nuance of a local human moderator. We certainly weren’t able to use this technology at NRM as too many local idioms would flumox a machine algorithm into allowing clear insult and defamation.

Comments, as an essentialcomponent of a dialogue with the audience supported by AI, can also be enhanced to al-low  for  livediscussions  with  invited participantsand  ex-perts. Smart  moderation  offered  byCoral projectenables media to involve the audience in real time discussions and manage the dialogue without the fear of destructive com-ments or  undesirable commercials.  The  Financial  Times, the  Wall  Street  Journal, the  Washington  Postand  many other media in 18 countries [16] are extensively using the tool.Perspective APIapplication developed by Jigsawpro-videssimilar optionsfor readersโ€™ chats moderation.

16. Coral  by  Vox  Media  launches  new  Q&A  tool  to  support publisher hosted live discussions// Vox Media, 2020, April 24.โ€“https://www.voxmedia.com/2020/4/24/21234360/coral-by-vox-media-launches-new-q-a-tool-to-support-publisher-hosted-live-discussions.

A New Test of Artificial Intelligence - Should the Media Industry Be Afraid?

Go back to the [[Readings list]] or the [[Master of Philosophy - Main Page]]

Reference: Horska, K. (2020). A New Test of Artificial Intelligence: Should the Media Industry Be Afraid? Science and Education a New Dimension. Humanities and Social Sciences, VIII(39).

The relevant section is available here.

#AIBusinessCase

๐Ÿ“š Agora node [[content moderation]] (pulled by the Agora)
๐Ÿ“œ File Content moderation.md by @bunnynabbit โ˜† ๐Ÿ“Ž ๏ธ๐Ÿ”— ๐Ÿค—

A necessary evil.

Moderation is a position that some people may find power in. I dislike that. Itโ€™s something that must be given extra thought. Not for someone to recklessly abuse. The primary goal is to enforce rules, usually to maintain peace of the environment. I do believe that moderation could be used to curate content, instead of just disallowing content. When building moderation systems, I always think about how a moderator could tag certain forms of content. Naturally, this creates data useful for automated systems.

At large scales, it could be necessary to put machine learning into the mix. This isnโ€™t something Iโ€™ve dabbled too much in, but I have tried it to some success.

ATProto / Blueskyยง

[[Bluesky]] (and thus [[AT Protocol]]) provides two flavors of moderation: takedowns and labels. In an ideal decentralized network, each PDS would be moderated by its own moderation service. Well behaved networks are to only focus on moderating their own users with other services rarely ever having to apply relay takedowns for accounts in other networks. There are also labels. Labels are funny, I think. A label could be put on any record for any reason. For the type of person who likes categorizing things for the sake of it, this seems wonderful. Who is that, anyways? Labels could range from standard stuff like labeling adult content to more novel uses like hiding movie spoilers. How objective are labels applied is entirely irrelevant. Though, predictable labeling rules are preferred by users. For a public network, checking out moderation activity is interesting and Iโ€™ve attempted to shine a light there.

I prefer to not say that I moderate the network surrounding ATProto. Though, what I deploy is standard for content moderation. However, I remain strict in not labeling against behaviors whenever possible. This is tricky! I try to be kink positive, for example. I run a labeler for Bluesky for labeling fetish content1. Although I provide labels to hide the content, I also provide ways to see more of it. I think this was the right choice, given that this normally doesnโ€™t go so well for those that tried before me.

Bluesky is vast. Itโ€™s an entire social network that can be accessed by a public firehose. A lot of data will need to be handled, especially of images.

  • write about how I fine-tuned a classification model.

I mostly label video and images. For handling large queues, I developed Rayleigh Moderation. Itโ€™s mostly developed for my needs.

Handling exposureยง

This isnโ€™t something Iโ€™m too familiar on despite my constant exposure to sexual content. For ATProto, I rely on the Bluesky moderation serviceโ€™s ability to take down repositories or to appropriately label content.

For sexual content specifically, I donโ€™t think there is a way to handle it while maintaining reasonable pace for handling ~2,000-10,000 posts a day. Iโ€™m [[asexual]]; unsure if thatโ€™s necessarily good or bad.

Iโ€™ve seen some wild stuff on Roblox. No matter how competent each platformโ€™s moderation systems are, there will be people that will try to bypass it.

  1. This isnโ€™t something Iโ€™ll link here since it does provide feeds from its labels. The feeds of which may not have content labeled appropriately by Bluesky or by the postsโ€™ authors. Often, this is because the Bluesky‘s auto-moderation systems misses it, or because itโ€™s non-sexual.↩

๐Ÿ“š Agora node [[global democratic moderation]] (pulled by the Agora)
๐Ÿ“œ File global democratic moderation.md by @vera โ˜† ๐Ÿ“Ž
๐Ÿ“š Agora node [[online content moderation]] (pulled by the Agora)
๐Ÿ“œ File online-content-moderation.md by @neil โ˜† ๐Ÿ“Ž ๏ธ๐Ÿ”— โœ๏ธ

Online content moderationยง

I saw a panel discussion on this at [[MozFest]] 2019, and also watched The Cleaners documentary.

It’s pretty grim stuff - both the distressing content that is created and uploaded around the world, and the way in which the people that are contracted to moderate this content are treated.

Overviewยง

  • the job of content moderation of big online platforms
    • it is usually outsourced to other companies
    • low paid employees do the act of moderation

Who is setting the policies?ยง

With their policies of what content is acceptable or not, the big tech firms are in some way determining what is acceptable to society.

  • basically three/four private companies in the US
  • e.g. terrorist groups as designated by US homeland security are used as guidelines for content moderation
  • and they do it only based on on profit motives - e.g. reacting to bad publicity

Conditions for workersยง

Conditionsยง

  • high level of things to see per day
    • Chris Gray, who worked in Ireland as a content moderator, I think suggested around 600 items a day
      • 90% of it might be mundane, around 10% of it will be traumatic
      • on The Cleaners documentary, I think they said in the Phillipines it’s a target of around 20-25,000 every day??
  • monitoring
    • workers are monitored to see if they are making ‘correct’ judgements
    • have to meet a quality target otherwise their employment is in jeopardy
  • post traumatic stress
    • stress of seeing disturbing things, stress of precarious labour, stress of having to determine what is good, what is bad

Payยง

  • at MozFest panel Cleaners directors said payment in the Phillipines is $1-$3 a day
  • Chris Gray said in Ireland around 12 euro a day I think?
  • contrast both of these with the salary of a Facebook engineerโ€ฆ
  • question: is it different types of content in different locations?

Supportยง

  • content moderators are under NDAs
    • they can’t talk about it with anyone, including friends/family
    • talking about it would help with the trauma

Use AI instead?ยง

Why not use ML/AI to moderate this content?

  • AI can’t handle the level of complexity involved in some of the decisions
  • dilemma: it would put people out of work - but it is unpleasant work
  • even for the unpleasant stuff, human input would be required to train any machine learning process anyway
  • currently a legal action being taken against Facebook by Chris Gray and others

Referencesยง

  • [[The Cleaners]] (film)
  • MozFest 2019 panel (probably will be online at some point)

Miscยง

The central problem is that Facebook has been charged with resolving philosophical conundrums despite being temperamentally ill-qualified and structurally unmotivated to do so.

If nudity can be artistic, exploitative, smutty, and empowering, then the depiction of violence can be about hate and accountability. A video of a shooting can be an expression of deadly bigotry, but it can also expose police wrongdoing. Distinguishing between them requires human decision-making, and resolving a range of contested ideas. At present, private institutions bear significant responsibility for defining the boundaries of acceptability, and they are not very good at it.

๐Ÿ“š Agora node [[probabilistic p2p content moderation]] (pulled by the Agora)
๐Ÿ“œ File probabilistic p2p content moderation.md by @flancian โ˜† ๐Ÿ“Ž ๏ธ๐Ÿ”— โœ๏ธ

probabilistic p2p content moderationยง