02/19/2020 – Human-Machine Collaboration for Content Regulation – Myles Frantz

Since the dawn of the internet, it has surpassed many expectations and is prolific throughout everyday life. Though initially there was a lack of standards in website design and forum moderation, it has relatively stabilized with various and scientific approaches. A popular forum side, Reddit, use a human lead human-ai collaboration to help automatically and manually moderate the ever-growing comments and thread. Searching through the top 100 subreddits (at the time of writing), the team followed surveyed moderators from 5 varied and highly active subreddits. These moderators are majority Due to the easy to use API provided by Reddit, one of the most used moderation tools was a third party later incorporated into Reddit Automod. This is one of the more popular and common tools used by moderators in Reddit. Since it is very extensible, there is no common standard between all the subreddits. Moderators within the 5 subreddits use this bot in relatively similar but different ways. Not only the sole bot used by moderations, other bots can be used to further interact and streamline other bots in a similar fashion. However due to the complication of bots (technologically or lack of interest in learning the tool), some subreddits let a few people manage the bots, sometimes to damning results. When issues happen, instead of being reactive to various users’ reactions, the paper argues for more transparency of the bot.

I agree with the author of the original of automod, when he started off making the bot purely to automate several steps. Continuing this forward with the scaling of Reddit, I do believe it would be impossible for only human moderators to keep up with the “trolls”.

Though I do disagree with how the rules of the automod are spread out. I would believe the decentralization of knowledge would make the system more robust, especially since the moderators are voluntary. It is natural for people to avoid what they don’t understand, for fear of it in general or fear for what repercussions may happen. Though I don’t think putting all of the work on one moderator is necessarily the right answer.

  • One of my questions is regarding one of the outcomes for Reddit; granting more visibility of the automods actions. Notably due to the scale of Reddit, extending this kind of functionality automatically could incur much more of a memory and storage overhead. Already Reddit stores vast amount of data however potentially doubling the memory capacity (if every comment was reviewed by automod) may be a downfall to this approach.
  • Instead of surveying the top 60%, I wonder if surveying the lower ranked (via RedditMetrics) subreddit with a lower number of moderators would fit the same pattern of the automod use. I would imagine they would be forced to use the automod tool more in depth and in breadth due to the lack of available resources however this is pure speculation.
  • A final question would be, to what percentage is there an over duplication of bots across the subreddits? If there is a big percentage it may lead to a vastly different experience across subreddits, as it seemingly is now potentially causing confusion amongst new or recurring users.

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02/19/2020 – Vikram Mohanty – Human-Machine Collaboration for Content Regulation: The Case of Reddit Automoderator

Summary

This paper thoroughly summarizes existing work on content regulation in online platforms, but focuses on human-machine collaboration aspect in this domain which hasn’t been widely studied. While most of the work in automated content regulation has been about introducing/improving algorithms, this work adopts a socio-technical lens of trying to understand how human moderators collaborate with automated moderator scripts. As most online platforms like Facebook and Google are pretty closeted about their moderation activities, the authors focus on Reddit, which allows moderators to use the Reddit API and develop their own scripts for each sub-reddit. The paper paints a comprehensive picture of how human moderators collaborate around the automoderator script, the different roles they assume, the other tools they use, and the challenges they face. Finally, the paper proposes design suggestions which can facilitate a better collaborative experience.

Reflection

Even though the Reddit Automoderator cannot be classified as an AI/ML tool, this paper sets a great example for how researchers can better assess the impact of intelligent agents on users, their practices and their behavior. In most instances, it is difficult for AI/ML model developers to foresee exactly how the algorithms/models they build are going to be used in the real world. This paper does a great job at highlighting how the moderators collaborate amongst themselves, how different levels of expertise, tech-savviness play a role in the collaboration process, how things like community guidelines are affected and how the roles for humans changed due to the bots amidst them. Situating the evaluation of intelligent/automated agents in a real-world usage scenario can give us a lot of insights where to direct our efforts for improvement or how to redesign the overall system/platform where the intelligent agent is being served.

It’s particularly interesting to see how users (or moderators) with different experience assume different roles with regards to how or who gets to modify the automoderator scripts. It may be an empirical question, but is a quick transition from newcomers/novices to an expert useful for the the community’s health, or the roles reserved for these newcomers/novices extremely essential? If it’s the former, then ensuring a quick learning curve with the usage of these bots/intelligent agents should be a priority for developers. Simulating what content will be affected with a particular change in the algorithm/script, as suggested in the discussion, can foster a quick learning curve for users (in addition to achieving the goal of minimizing false positives).

While the paper comments on how these automated scripts are supporting the moderator, it would have been interesting to see a comparative study of no automoderator vs automoderator. Of course, that was not the goal of this paper, but it could have helped paint the picture that automoderator adds to user satisfaction. Also, as the paper mentions, the moderators value their current level of control in the whole moderation process, and therefore, would be uncomfortable in a fully automated setting or one where they would not be able to explain their decisions. This has major design implications not just for content regulation, but pretty much in for complex, collaborative task. The fact that end-users developed and used their own scripts, accustomed to the community’s needs, is promising and opens up possibilities for coming up with tools which users with no or little technical knowledge can use to easily build and test their own scripts/bots/ML models.

With the introduction of automoderator, the role of the human moderators changed from their tradition job of just moderating the content to now ensuring that the rules of automoderator are updated, preventing users to game the system and minimizing false positives. Automation creating new roles for humans, instead of replacing them, is pretty evident here. As the role of AI increases in AI-infused systems, it is also important to assess the user satisfaction with the new roles.

Questions

  1. Do you see yourself conducting AI model evaluation with a wider socio-technical lens of how they can affect the target users, their practices and behaviors? Or do you think, evaluating in isolation is sufficient?
  2. Would you advocate for AI-infused systems where the roles of human users, in the process of being transformed, get reduced to tedious, monotonous, repetitive tasks? Do you think the moderators in this paper enjoyed their new roles?
  3. Would you push for fully automated systems or ones where the user enjoys some degree of control over the process?

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02/19/2020 – Sukrit Venkatagiri – The Case of Reddit Automoderator

Paper: Shagun Jhaver, Iris Birman, Eric Gilbert, and Amy Bruckman. 2019. Human-Machine Collaboration for Content Regulation: The Case of Reddit Automoderator. ACM Transactions on Computer-Human Interaction (TOCHI) 26, 5: 31:1–31:35. https://doi.org/10.1145/3338243

Summary: This paper studies Reddit’s Automod, a rule-based moderator for Reddit that automatically filters content on subreddits, and can be customized by the moderators to suit each subreddit. The paper sought to understand how moderators use Automod, and what advantages and challenges it presented. The paper discusses these findings in detail and the authors found that: there was a need for audit tools to tune the performance of Automod, a repository for sharing these tools, and for improving the division of labor between human and machine decision making. They concluded with a discussion of the sociotechnical practices that shape the use of the tools, how they help workers maintain their communities, and the challenges and limitations, as well as solutions that may help address them.

Reflection:

I appreciate that the authors were embedded within the Reddit community for over one year and provides concrete recommendations for creators of new and existing platforms, for designers and researchers interested in automated content moderation, for scholars of platform governance, and for content moderators themselves.

I also appreciate the deep and thorough qualitative nature of the study, along with the screenshots, however the paper may be too long and too detailed in some aspects. I wish there was a “mini” version of this paper. The quotes themselves were exciting and exemplary of problems the users faced.

The finding that different subreddits configured and used subreddits was interesting and I wonder how much a moderators’ skills and background affects whether and in what ways they configure and use Automod. Lastly, the conclusion is very valuable and especially as it is targeted towards different groups within and outside of academia.

Two themes that emerged, “Becoming/continuing to be a moderator” and “recruiting new moderators” sound interesting, but I wonder why it was left out of the results. The paper does not provide any explanation in regards to this.

Questions:

  1. How do you subreddits might differ in their use of Automod based on their technical abilities?
  2. How can we teach people to use Automod better?
  3. What are the limitations of Automod? How can they be overcome through ML methods?

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02/18/20 – Akshita Jha – Human-Machine Collaboration for Content Regulation: The Case of Reddit Automoderator

Summary:
“Human-Machine Collaboration for Content Regulation: The Case of Reddit Automoderator” by Jhaver et al. talks about the popular social media website Reddit and the unusual unpaid human moderators and automated moderator collaboration. Reddit moderators make use of the heavily configurable automated program called, ‘Automoderator’ to help make decisions about the content that should be removed from the website. The authors interview 16 Reddit moderators to understand how they benefit from the moderating tool, ‘Automod’ and how they adapt and configure it to reflect the subreddit’s policies to help them moderate the subreddit effectively. The authors also offer valuable insights that may benefit the creators of the platforms, designers of automated regulation systems, scholars of platform governance, and content moderators. The authors conclude by pointing out that the moderation system in reddit is a collaborative effort between humans as well as the automated systems. This hybrid system works but there is definitely a scope for improvement in the development and deployment of these tools.

Reflections:
Online platforms can be a boon or a bane depending on how people choose to engage with it. Regulation might seem necessary to ensure that low quality posts (these posts can be treated as noise) do not drown out informative and worthy posts on the site. However, this is a challenging task. Deciding whether a post is appropriate for the subreddit puts a lot of responsibility on the moderator. In some cases the moderator might be a bot, ‘Automod’ and in other cases the platform relies on paid or unpaid volunteers. Reddit moderators are unpaid. The authors in this work analysed 5 different subreddits: ‘r/photoshopbattles’, ‘r/space’, ‘r/oddlysatisfying’, ‘r/explainlikeiamfive’ and ‘r/politics’. It’s interesting that some reddit moderators prefer to implement moderation bots from scratch while others make use of tools made by others. It’s intriguing how making use of tools made by others forms a sense of community of moderators within the bigger community of reddit. Most redditors use ‘Automod’ which was initially created by ‘Chad Birch’ using the Reddit API in January 2012. However, a major drawback of this study is that all the moderators that the authors interviewed were males. It would be helpful to get the perspective of female moderators, if there are any, since the user base for Reddit is disproportionately male. I feel the authors should have selected ‘r/AskHistorians’ as one of the subreddits for analysis since it’s widely known to be highly moderated and content driven. It would have also been interesting to deep dive into the comments that ‘Automod’ marked as offensive but were not. This would help improve the performance of the moderator while informing us of its limitations. One might also need to wonder about the consequences if the subreddit community grows larger. There might be a need to reflect on the existing tools and their scale.

Questions:
1. Do you agree that social media content should be moderated?
2. What about the mental health of the moderators?
3. What kind of resources should be make available to the moderators since they are dealing with sensitive content all the time?

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