Benjamin Mako Hill: Sad Story

Not a screenshot of despair. But only because it s not a screenshot.

Bits from Debian: New Debian Developers and Maintainers (May and June 2026)

The following contributors got their Debian Developer accounts in the last two months:

Vivek K J (vivek)
Benjamin Somers (bensmrs)
Colin King (colinianking)
Nadzeya Hutsko (nadzeya)

The following contributors were added as Debian Maintainers in the last two months:

Pieter Lenaerts
Syed Shahrukh Hussain
Ural Tunaboyu

Congratulations!

Benjamin Mako Hill: Quote #75514

Although I never submitted to it, I made several appearances in the now-defunct quote database on bash.org (QDB). I m dealing with a broken keyboard now, and went to dig hard to find this classic in the Wayback machine. I thought I would put it back on the web:

<mako> my letter "eye" stopped worng
<luca> k, too?
<mako> yeah
<luca> sounds like a mountain dew spill
<mako> and comma
<mako> those three
<mako> ths s horrble
<luca> tme for a new eyboard
<luca> 've successfully taen my eyboard apart and fxed t by cleanng t wth alcohol
<mako> stop mang fun of me
<mako> ths s a laptop!

It was, in fact, horrble.

Russell Coker: Communication and Hostile AIs

We seem to be entering an AI apocalypse of sorts, they aren t going to kill us or even take our jobs. What they are doing is destroying the Internet commons by filling it with rubbish. This isn t even real AI, just pattern matching and prediction systems, mostly LLMs. The Problem Scott Shambaugh s saga of being attacked and defamed by an OpenClaw AI bot is interesting and raises some disturbing possibilities for future online discussion [1]. Imagine what it would be like if everyone who was in any way notable for free software work had 100 such bots going after them. Dania Dumas wrote an insightful blog post about why OpenClaw is impossible to secure and why it won t go away [2]. Bruce Schneier and Nathan E. Sanders wrote an insightful article about the AI generated text arms race [3] primarily concentrating on situations in which text that was assumed to be written by humans but was actually written in bulk by bots was performing a DOS attack on people who were reviewing it. There are many situations such as book publishing and publishing letters to the editor of newspapers where getting new material from unknown people is an important part of the job but where there are also people making low quality submissions that are almost a DOS attack at the best of times. Currently the email spam problem continues to get worse and when LLM use increases it will get significantly worse. Email encryption isn t viable [4]. The PGP web of trust never really worked well as it s too difficult for most users. The amount of AI generated content that s being recommended to users on platforms like YouTube and Facebook is steadily increasing and the amount of LLM generated commentary that purports to be from real people on Twitter and Facebook is also increasing. Here s an informative blog post by Erich Schubert about this [5]. Potential Solutions Surrender? One option and possibly the default option is to surrender to this and just let everything we built on the Internet over decades get destroyed. Whether to surrender is a decision that can be made on a per-service basis. Twitter is pretty much useless anyway, I quit Twitter because Elon deliberately made it suck [6]. In my opinion this is not surrendering to what s being done there, I m just stopping wasting time on it and using better options. I used to have about 300 followers on Twitter and I don t think that many of them would ever choose to stop following me, so I presume that about 1/3 of the people following me have decided to totally quit Twitter and delete their accounts. I also presume that some of the remainder have done the same as me and just kept a mostly inactive account. If Elon suddenly stopped being a stupid asshole it probably wouldn t change anything as the value of the system was connections to others. Some people will consider my abandonment of Twitter as surrender and I accept that it s not an unreasonable opinion. I think that the possibly 100 Twitter followers of mine who deleted their accounts surrendered. Facebook has been becoming a worse service, it s business model is becoming increasingly exploitative and it s interface is designed to be addictive. It s probably best avoided unless you really need it. The only good thing about Facebook at the moment is that Facebook Marketplace doesn t take a cut on sales and there are some really good deals on computers if you know what to look for. Unfortunately Facebook has a large number of users who are from marginalised communities and have no other alternatives for communication. It would be good to get them migrated to other platforms. We could just give up on a lot of general communications services and have everyone accept that good content is drowned out by rubbish and have the Internet become divided between people who accept the rubbish and those who cease using large portions of the Internet environment to avoid it. Using Non Commercial Services Lemmy is a good FOSS federated alternative to Reddit which also covers some of the uses of Facebook. It needs more users to get critical mass but is still quite usable. A post that might get a dozen comments on Reddit may get 1 comment on Lemmy but that one comment will be a good one. Reddit doesn t appear to be attacked much by LLM generated content at least not yet. Even if the Reddit model proves to be resilient to LLM attack the Lemmy software can be used to replace some things that are done on Facebook, Mastodon is a good FOSS federated replacement for Twitter, it has a decent user-base including some VIPs. While it is aimed at the Twitter use case it can also cover a significant part of the Facebook use case. There are some other FOSS social media programs which could take over other parts of the commercial social media environment. Generally commercially run Internet services will have a financial incentive to allow the problems to get worse so we need to rely on FOSS software, non-commercial implementations, and government services. Web Search For a long time Google has had a monopoly on web search, but now they default to including an AI Overview at the start of the results which is sometimes useful but also sometimes very wrong. You can use the search URL https://www.google.com/search?q=%s&udm=web to get google results without rubbish. But I presume that they will break that if it gets too popular. Searxng is a AGPL licensed metasearch engine that aggregates results from other engines, here s the Searxng source [7] and here s a list of Searxng instances if you want to try one [8]. Even using meta search engines like Searxng won t help if the original data is overloaded with spam, but alleviating the problem is a good temporary measure. Web of Trust for the Web? I ve idly considered the possibility of having some sort of rating system for web pages that uses a web of trust so that you can securely use trust ratings of friends of friends etc. But given all the difficulties in using a web of trust for signing GPG key for software developers (the demographic that is most skilled at doing such things) it doesn t seem viable. Should we surrender the idea of having a usable public web? In the early days of the web (before Google) it was standard practice to rely on recommendations from other people or from trusted sites to find other sites, that could be considered to be an informal web of trust. We could go back to that sort of usage pattern if Google and many of the big sites get overwhelmed by LLM generated spam. Wikipedia I believe that Wikipedia will be at the front lines of this battle. It s model has always included anonymous contributions. Benjamin Mako Hill wrote an interesting blog post about research he did with Kaylea Champion into Wikipedia pages on taboo topics which have a larger portion of contributors choosing to be anonymous than non-taboo pages [9]. Wikipedia also has a long history of being abused for various reasons, one that I witnessed was someone putting false content into Wikipedia pages to immediately cite them in support of their facebook arguments. That sort of thing can be dealt with at human scale but a large scale attack by bots is a different problem to solve. Also with the recent developments in AI developing multiple web sites entirely populated for the purpose of supporting one fake entry in Wikipedia is plausible. The upside of these attacks that I predict is that they will attract the attention of all the people who have skills related to developing counter-measures. While LLM bots are filling the inboxes of publishers with rubbish and messing up the stackoverflow comments section not a lot of people are bothered, but once the attacks on Wikipedia get serious everyone will take notice. National AI Bruce Schneier and Nathan E. Sanders wrote an interesting blog post about nationalised public AI [10]. While that won t directly address this issue it will get the right technology in the hands of people who can use it in the right way. Conclusion This is going to be a difficult problem to solve, more difficult than the email spam problem we have been unable to solve after 30 years of working on it. This is also a very important problem, we are currently in an age where we have access to information that most people couldn t even dream of 30 years ago. We also have disinformation that combines some of the worst aspects of authoritarian regimes throughout history combined with the worst aspects of cult brainwashing. If we lose access to the information but the disinformation remains (or get worse) then the result will be terrible. I don t have great ideas for solving this. I have outlined some small ideas to mitigate things and I hope that others can expand on them. Please write comments with any good ideas you have, or even ideas that don t totally suck. A problem this difficult is not going to be solved in a blog comment, but a blog comment might point in the right direction.

Benjamin Mako Hill: How taboo shapes knowledge production on Wikipedia

Note: I have not published blog posts about my academic papers over the past few years. To ensure that my blog contains a more comprehensive record of my published papers and to surface them for folks who missed them, I will periodically (re) publish blog posts about some older published projects. This post draws material from a previously published post by Kaylea Champion on the Community Data Science Blog.

Taboo subjects such as sexuality and mental health are as important to discuss as they are difficult to raise in conversation. Although many people turn to online resources for information on taboo subjects, censorship and low-quality information are common in search results. In two papers I recently published at CSCW both led by Kaylea Champion we presented a series of analyses showing how taboo shapes the process of collaborative knowledge building on English Wikipedia.

The first study is a quantitative analysis showing that articles on taboo subjects are much more popular and are the subject of more vandalism than articles on non-taboo topics. In surprising news, we also found that they were edited more often and were of higher quality!

Short video of Kaylea s presentation of the work given at Wikimania in August 2023.

The first challenge we faced in conducting this work was identifying taboo articles. Kaylea had a brilliant idea for a new computational approach to doing so without relying on our individual intuitions about what qualifies as taboo (something we understood would be highly specific to our own culture, class, etc). Her approach was to make use of an insight from linguistics: people develop euphemisms as ways to talk about taboos (i.e., think about all the euphemisms we ve devised for death, or sex, or menstruation, or mental health).

We used this insight to build a new machine-learning classifier based on English Wiktionary definitions. If a sense of a word was tagged as euphemistic, we treated the words in the definition as indicators of taboo. The end result was a series of words and phrases that most powerfully differentiate taboo from non-taboo. We then did a simple match between those words and phrases and the titles of Wikipedia articles. The topics were taboo enough that we were a little uncomfortable discussing them in our meetings! We built a comparison sample of articles whose titles are words that, like our taboo articles, appear in Wiktionary definitions. In the first paper, we used this new dataset to test a series of hypotheses about how taboo shapes collaborative production in Wikipedia. Our initial hypotheses were based on the idea that taboo information is often in high demand but that Wikipedians might be reluctant to associate their names (or usernames) with taboo topics. The result, we argued, would be articles that were in high demand but of low quality. We found that taboo articles are thriving on Wikipedia! In summary, we found that in comparison to non-taboo articles:

Taboo articles are more popular (as expected).
Taboo articles receive more contributions (contrary to expectations).
Taboo articles receive more low-quality contributions (as expected).
Taboo articles are higher quality (contrary to expectations).
Taboo article contributors are more likely to contribute without an account (as expected), and have less experience (as expected), but that accountholders are more likely to make themselves more identifiable by having a user page, disclosing their gender, and making themselves emailable (all three of these are contrary to expectation!).

Kaylea attempted to understand these somewhat confusing results by designing a fantastic mixed-methods analysis that sought to unpack some of the nuance missing in the quantitative analysis by delving deep into the life histories of four articles on English Wikipedia: two on taboo topics related to women s anatomy (Clitoris and Menstration) and two nontaboo articles chosen for comparison (Cell membrance and Philip Pullman). Although the findings from the analysis can be difficult to summarize succinctly (as with many qualitative studies), we showed how the taboo example articles success was hard-won amid real challenges and attacks. The paper describes how challenges were overcome through resilient leadership, often provided by a single dedicated individual. The paper provides a template for how taboo can be and frequently is overcome by dedicated Wikipedians in ways that provide useful knowledge resources in real demand. For more details, visualizations, statistics, and more, we hope you ll take a look at our papers, both linked below.

The full citation for the papers are: (1) Champion, Kaylea, and Benjamin Mako Hill. 2023. Taboo and Collaborative Knowledge Production: Evidence from Wikipedia. Proceedings of the ACM on Human-Computer Interaction 7 (CSCW2): 299:1-299:25. https://doi.org/10.1145/3610090. (2) Champion, Kaylea, and Benjamin Mako Hill. 2024. Life Histories of Taboo Knowledge Artifacts. Proceedings of the ACM: Human-Computer Interaction 8 (CSCW2): 505:1-505:32. https://doi.org/10.1145/3687044.

We have also released replication materials for the paper, including all the data and code used to conduct the analyses.

This blog post and the paper it describes are collaborative work by Kaylea Champion and Benjamin Mako Hill.

Benjamin Mako Hill: Pronunciation

Had a discussion about how to pronounce the name of Google s chatbot. Turns out, we were all wrong.

Benjamin Mako Hill: What makes online groups vulnerable to governance capture?

Note: I have not published blog posts about my academic papers over the past few years. To ensure that my blog contains a more comprehensive record of my published papers and to surface these for folks who missed them, I will be periodically (re)publishing blog posts about some older published projects. This post is closely based on a previously published post by Zarine Kharazian on the Community Data Science Blog. For nearly a decade, the Croatian language version of Wikipedia was run by a cabal of far-right nationalists who edited articles in ways that promoted fringe political ideas and involved cases of historical revisionism related to the Usta e regime, a fascist movement that ruled the Nazi puppet state called the Independent State of Croatia during World War II. This cabal seized complete control of the encyclopedia s governance, banned and blocked those who disagreed with them, and operated a network of fake accounts to create the appearance of grassroots support for their policies. Thankfully, Croatian Wikipedia appears to be an outlier. Though both the Croatian and Serbian language editions have been documented to contain nationalist bias and historical revisionism, Croatian Wikipedia seems unique among Wikipedia editions in the extent to which its governance institutions were captured by a small group of users.

The situation in Croatian Wikipedia was well documented and is now largely fixed, but we still know very little about why it was taken over, while other language editions seem to have rebuffed similar capture attempts. In a paper published in the Proceedings of the ACM: Human-Computer Interaction (CSCW), Zarine Kharazian, Kate Starbird, and I present an interview-based study that provides an explanation for why Croatian was captured while several other editions facing similar contexts and threats fared better.

Short video presentation of the work given at Wikimania in August 2023. Based on insights from interviews with 15 participants from both the Croatian and Serbian Wikipedia projects and from the broader Wikimedia movement, we arrived at three propositions that, together, help explain why Croatian Wikipedia succumbed to capture while Serbian Wikipedia did not:

Perceived Value as a Target. Is the project worth expending the effort to capture?
Bureaucratic Openness. How easy is it for contributors outside the core founding team to ascend to local governance positions?
Institutional Formalization. To what degree does the project prefer personalistic, informal forms of organization over formal ones?

We found that both Croatian and Serbian Wikipedias were attractive targets for far-right nationalist capture due to their sizable readership and resonance with national identity. However, we also found that the two projects diverged early in their trajectories in how open they remained to new contributors ascending to local governance positions and in the degree to which they privileged informal relationships over formal rules and processes as the project s organizing principles. Ultimately, Croatian s relative lack of bureaucratic openness and rules constraining administrator behavior created a window of opportunity for a motivated contingent of editors to seize control of the governance mechanisms of the project. Though our empirical setting was Wikipedia, our theoretical model may offer insight into the challenges faced by self-governed online communities more broadly. As interest in decentralized alternatives to Facebook and X (formerly Twitter) grows, communities on these sites will likely face similar threats from motivated actors. Understanding the vulnerabilities inherent in these self-governing systems is crucial to building resilient defenses against threats like disinformation. For more details on our findings, take a look at the published version of our paper.

Citation for the full paper: Kharazian, Zarine, Kate Starbird, and Benjamin Mako Hill. 2024. Governance Capture in a Self-Governing Community: A Qualitative Comparison of the Croatian, Serbian, Bosnian, and Serbo-Croatian Wikipedias. Proceedings of the ACM on Human-Computer Interaction 8 (CSCW1): 61:1-61:26. https://doi.org/10.1145/3637338.

This blog post and the paper it describes are collaborative work by Zarine Kharazian, Benjamin Mako Hill, and Kate Starbird.

Benjamin Mako Hill: Why do people participate in similar online communities?

Note: I have not published blog posts about my academic papers over the past few years. To ensure that my blog contains a more comprehensive record of my published papers and to surface these for folks who missed them, I will be periodically (re)publishing blog posts about some older published projects. It seems natural to think of online communities competing for the time and attention of their participants. Over the last few years, I ve worked with a team of collaborators led by Nathan TeBlunthuis to use mathematical and statistical techniques from ecology to understand these dynamics. What we ve found surprised us: competition between online communities is rare and typically short-lived. When we started this research, we figured competition would be most likely among communities discussing similar topics. As a first step, we identified clusters of such communities on Reddit. One surprising thing we noticed in our Reddit data was that many of these communities that used similar language also had very high levels of overlap among their users. This was puzzling: why were the same groups of people talking to each other about the same things in different places? And why don t they appear to be in competition with each other for their users time and activity? We didn t know how to answer this question using quantitative methods. As a result, we recruited and interviewed 20 active participants in clusters of highly related subreddits with overlapping user bases (for example, one cluster was focused on vintage audio). We found that the answer to the puzzle lay in the fact that the people we talked to were looking for three distinct things from the communities they worked in:

The ability to connect to specific information and narrowly scoped discussions.
The ability to socialize with people who are similar to themselves.
Attention from the largest possible audience.

Critically, we also found that these three things represented a trilemma, and that no single community can meet all three needs. You might find two of the three in a single community, but you could never have all three.

The end result is something I recognize in how I engage with online communities on platforms like Reddit. People tend to engage with a portfolio of communities that vary in size, specialization, topical focus, and rules. Compared with any single community, such overlapping systems can provide a wider range of benefits. No community can do everything.

This work was published as a paper at CSCW: TeBlunthuis, Nathan, Charles Kiene, Isabella Brown, Laura (Alia) Levi, Nicole McGinnis, and Benjamin Mako Hill. 2022. No Community Can Do Everything: Why People Participate in Similar Online Communities. Proceedings of the ACM on Human-Computer Interaction 6 (CSCW1): 61:1-61:25. https://doi.org/10.1145/3512908.

This work was supported by the National Science Foundation (awards IIS-1908850, IIS-1910202, and GRFP-2016220885). A full list of acknowledgements is in the paper.

Benjamin Mako Hill: What do people do when they edit Wikipedia through Tor?

Note: I have not published blog posts about my academic papers over the past few years. To ensure that my blog contains a more comprehensive record of my published papers and to surface these for folks who missed them, I will be periodically (re)publishing blog posts about some older published projects. This post is closely based on a previously published post by Kaylea Champion on the Community Data Science Blog.

One popular approach to protecting our privacy online is to use the Tor network. Tor protects users from being identified by their IP address, which can be tied to a physical location. However, if you d like to contribute to Wikipedia using Tor, you ll run into a problem. Although most IP addresses can edit without an account, Tor users are blocked from editing.

Other research by my team has shown that Wikipedia s attempt to block Tor is imperfect and that some people have been able to edit despite the ban. As part of this work, we built a dataset of more than 11,000 contributions to Wikipedia via Tor and used quantitative analysis to show that contributions from Tor were of about the same quality as contributions from other new editors and other contributors without accounts. Of course, given the unusual circumstances Tor-based contributors face, we wondered whether a deeper look at the content of their edits might reveal more about their motives and the kinds of contributions they seek to make. Kaylea Champion (then a student, now faculty at UW Bothell) led a qualitative investigation to explore these questions. Given the challenges of studying anonymity seekers, we designed a novel forensic qualitative approach inspired by techniques common in computer security and criminal investigation. We applied this new technique to a sample of 500 editing sessions and categorized each session based on what the editor seemed to be intending to do. Most of the contributions we found fell into one of the two following categories:

Many contributions were quotidian attempts to add to the encyclopedia. Tor-based editors added facts, fixed typos, and updated train schedules. There s no way to know whether these individuals knew they were just getting lucky in their ability to edit or were patiently reloading to evade the ban.
Second, we found harassing comments and vandalism. Unwelcome conduct is common in online environments, and it is sometimes more common when the likelihood of being identified decreases. Some of the harassing comments we observed were direct responses to being banned as a Tor user.

Although these were most of what we observed, we also found evidence of several types of contributor intent:

We observed activism: when a contributor tried to draw attention to journalistic accounts of environmental and human rights abuses committed by a mining company, only to have editors linked to the mining company repeatedly remove their edits. Another example involved an editor trying to diminish the influence of proponents of alternative medicine.
We also observed quality maintenance activities when editors used Wikipedia s rules on appropriate sourcing to remove personal websites being cited in conspiracy theories.
We saw edit wars with Tor editors participating in a back-and-forth removal and replacement of content as part of a dispute, in some cases countering the work of an experienced Wikipedia editor whom even other experienced editors had gauged to be biased.
Finally, we saw Tor-based editors participating in non-article discussions, such as investigations into administrator misconduct and protests against the Wikipedia platform s mistrust of Tor editors.

In all, these themes led us to reflect on how the risks individuals face when contributing to online communities sometimes diverge from the risks the communities face in accepting their work. Expressing minoritized perspectives, maintaining community standards even when you may be targeted by the rulebreaker, highlighting injustice, or acting as a whistleblower can be very risky for an individual, and may not be possible without privacy protections. Of course, in platforms seeking to support the public good, such knowledge and accountability may be crucial.

This work was published as a paper at CSCW: Kaylea Champion, Nora McDonald, Stephanie Bankes, Joseph Zhang, Rachel Greenstadt, Andrea Forte, and Benjamin Mako Hill. 2019. A Forensic Qualitative Analysis of Contributions to Wikipedia from Anonymity Seeking Users. Proceedings of the ACM on Human-Computer Interaction. 3, CSCW, Article 53 (November 2019), 26 pages. https://doi.org/10.1145/3359155

This project was conducted by Kaylea Champion, Nora McDonald, Stephanie Bankes, Joseph Zhang, Rachel Greenstadt, Andrea Forte, and Benjamin Mako Hill. This work was supported by the National Science Foundation (awards CNS-1703736 and CNS-1703049) and included the work of two undergraduates supported through an NSF REU supplement.

Benjamin Mako Hill: Dialogue

Me: Do you want your coffee in a Japanese or Western style tea cup? M: Yunomi. Me: Apparently not as well as you think I do!

Dirk Eddelbuettel: RcppAnnoy 0.0.23 on CRAN: Several Updates

A new release, now at version 0.0.22, of RcppAnnoy has arrived on CRAN, just a little short of two years since the previous release. RcppAnnoy is the Rcpp-based R integration of the nifty Annoy library by Erik Bernhardsson. Annoy is a small and lightweight C++ template header library for very fast approximate nearest neighbours originally developed to drive the Spotify music discovery algorithm. It had all the buzzwords already a decade ago: it is one of the algorithms behind (drum roll ) vector search as it finds approximate matches very quickly and also allows to persist the data. This release contains three contributed pull requests covering a new metric, a new demo and quieter compilation, some changes to documentation and last but not least general polish including letting the vignette now use the Rcpp::asis builder. Details of the release follow based on the NEWS file.

Changes in version 0.0.23 (2026-01-12)

Add dot product distance metrics (Benjamin James in #78)

Apply small polish to the documentation (Dirk closing #79)

A new demo() has been added (Samuel Granjeaud in #79)

Switch to Authors@R in DESCRIPTION

Several updates to continuous integration and README.md

Small enhancements to package help files

Updates to vignettes and references

Vignette now uses Rcpp::asis builder (Dirk in #80)

Switch one macro to a function to avoid a compiler nag (Amos Elberg in #81)

Courtesy of my CRANberries, there is also a diffstat report for this release.

This post by Dirk Eddelbuettel originated on his Thinking inside the box blog. If you like this or other open-source work I do, you can sponsor me at GitHub.

Benjamin Mako Hill: Effects of Algorithmic Flagging on Fairness: Quasi-experimental Evidence from Wikipedia

Note: I have not published blog posts about my academic papers over the past few years. To ensure that my blog contains a more comprehensive record of my published papers and to surface these for folks who missed them, I will be periodically (re)publishing blog posts about some older published projects. This particular post is closely based on a previously published post by Nate TeBlunthuis from the Community Data Science Blog. Many online platforms are adopting AI and machine learning as a tool to maintain order and high-quality information in the face of massive influxes of user-generated content. Of course, AI algorithms can be inaccurate, biased, or unfair. How do signals from AI predictions shape the fairness of online content moderation? How can we measure an algorithmic flagging system s effects? In our paper published at CSCW, Nate TeBlunthuis, together with myself and Aaron Halfaker, analyzed the RCFilters system: an add-on to Wikipedia that highlights and filters edits that a machine learning algorithm called ORES identifies as likely to be damaging to Wikipedia. This system has been deployed on large Wikipedia language editions and is similar to other algorithmic flagging systems that are becoming increasingly widespread. Our work measures the causal effect of being flagged in the RCFilters user interface.

Our work takes advantage of the fact that RCFilters, like many algorithmic flagging systems, create discontinuities in the relationship between the probability that a moderator should take action and whether a moderator actually does. This happens because the output of machine learning systems like ORES is typically a continuous score (in RCFilters, an estimated probability that a Wikipedia edit is damaging), while the flags (in RCFilters, the yellow, orange, or red highlights) are either on or off and are triggered when the score crosses some arbitrary threshold. As a result, edits slightly above the threshold are both more visible to moderators and appear more likely to be damaging than edits slightly below. Even though edits on either side of the threshold have virtually the same likelihood of truly being damaging, the flagged edits are substantially more likely to be reverted. This fact lets us use a method called regression discontinuity to make causal estimates of the effect of being flagged in RCFilters.

To understand how this system may affect the fairness of Wikipedia moderation, we estimate the effects of flagging on edits on different groups of editors. Comparing the magnitude of these estimates lets us measure how flagging is associated with several different definitions of fairness. Surprisingly, we found evidence that these flags improved fairness for categories of editors that have been widely perceived as troublesome particularly unregistered (anonymous) editors. This occurred because flagging has a much stronger effect on edits by the registered than on edits by the unregistered. We believe that our results are driven by the fact that algorithmic flags are especially helpful for finding damage that can t be easily detected otherwise. Wikipedia moderators can see the editor s registration status in the recent changes, watchlists, and edit history. Because unregistered editors are often troublesome, Wikipedia moderators attention is often focused on their contributions, with or without algorithmic flags. Algorithmic flags make damage by registered editors (in addition to unregistered editors) much more detectable to moderators and so help moderators focus on damage overall, not just damage by suspicious editors. As a result, the algorithmic flagging system decreases the bias that moderators have against unregistered editors. This finding is particularly surprising because the ORES algorithm we analyzed was itself demonstrably biased against unregistered editors (i.e., the algorithm tended to greatly overestimate the probability that edits by these editors were damaging). Despite the fact that the algorithms were biased, their introduction could still lead to less biased outcomes overall. Our work shows that although it is important to design predictive algorithms to avoid such biases, it is equally important to study fairness at the level of the broader sociotechnical system. Since we first published a preprint of our paper, a follow-up piece by Leijie Wang and Haiyi Zhu replicated much of our work and showed that differences between different Wikipedia communities may be another important factor driving the effect of the system. Overall, this work suggests that social signals and social context can interact with algorithmic signals, and together these can influence behavior in important and unexpected ways.

The full citation for the paper is: TeBlunthuis, Nathan, Benjamin Mako Hill, and Aaron Halfaker. 2021. Effects of Algorithmic Flagging on Fairness: Quasi-Experimental Evidence from Wikipedia. Proceedings of the ACM on Human-Computer Interaction 5 (CSCW): 56:1-56:27. https://doi.org/10.1145/3449130.

We have also released replication materials for the paper, including all the data and code used to conduct the analysis and compile the paper itself.

Gunnar Wolf: The comedy of computation, or, how I learned to stop worrying and love obsolescence

This post is a review for Computing Reviews for The comedy of computation, or, how I learned to stop worrying and love obsolescence , a book published in Stanford University Press

The Comedy of Computation is not an easy book to review. It is a much enjoyable book that analyzes several examples of how being computational has been approached across literary genres in the last century how authors of stories, novels, theatrical plays and movies, focusing on comedic genres, have understood the role of the computer in defining human relations, reactions and even self-image. Mangrum structures his work in six thematic chapters, where he presents different angles on human society: How have racial stereotypes advanced in human imagination and perception about a future where we interact with mechanical or computational partners (from mechanical tools performing jobs that were identified with racial profiles to intelligent robots that threaten to control society); the genericity of computers and people can be seen as generic, interchangeable characters, often fueled by the tendency people exhibit to confer anthropomorphic qualities to inanimate objects; people s desire to be seen as truly authentic , regardless of what it ultimately means; romantic involvement and romance-led stories (with the computer seen as a facilitator for human-to-human romances, distractor away from them, or being itself a part of the couple); and the absurdity in antropomorphization, in comparing fundamentally different aspects such as intelligence and speed at solving mathematical operations, as well as the absurdity presented blatantly as such by several techno-utopian visions. But presenting this as a linear set of concepts that are presented does not do justice to the book. Throughout the sections of each chapter, a different work serves as the axis Novels and stories, Hollywood movies, Broadway plays, some covers for the Time magazine, a couple of presenting the would-be future, even a romantic comedy entirely written by bots . And for each of them, Benjamin Mangrum presents a very thorough analysis, drawing relations and comparing with contemporary works, but also with Shakespeare, classical Greek myths, and a very long etc tera. This book is hard to review because of the depth of work the author did: Reading it repeatedly made me look for other works, or at least longer references for them. Still, despite being a work with such erudition, Mangrum s text is easy and pleasant to read, without feeling heavy or written in an overly academic style. I very much enjoyed reading this book. It is certainly not a technical book about computers and society in any way; it is an exploration of human creativity and our understanding of the aspects the author has found as central to understanding the impact of computing on humankind. However, there is one point I must mention before closing: I believe the editorial decision to present the work as a running text, with all the material conceptualized as footnotes presented as a separate, over 50 page long final chapter, detracts from the final result. Personally, I enjoy reading the footnotes because they reveal the author s thought processes, even if they stray from the central line of thought. Even more, given my review copy was a PDF, I could not even keep said chapter open with one finger, bouncing back and forth. For all purposes, I missed out on the notes; now that I finished reading and stumbled upon that chapter, I know I missed an important part of the enjoyment.

Russell Coker: Digital Sovereignty and Email

Running Your Own Email Srever I run my own mail server. I have run it since about 1995, initially on a 28k8 modem connection but the connection improved as technology became cheaper and now I m running it on a VM on a Hetzner server which is also running domains for some small businesses. I make a small amount of money running mail services for those companies but generally not enough to make it profitable. From a strictly financial basis I might be better off just using a big service, but I like having control over my own email. If email doesn t arrive I can read the logs to find out why. I repeatedly have issues of big services not accepting mail. The most recent is the MS services claiming that my IP has a bad ratio of good mail to spam and blocked me so I had to tunnel that through a different IP address. It seems that the way things are going is that if you run a small server companies like MS can block you even though your amount of spam is low but if you run a large scale service that is horrible for sending spam then you don t get blocked. For most users they just use one of the major email services (Gmail or Microsoft) and find that no-one blocks them because those providers are too big to block and things mostly work. Until of course the company decides to cancel their account. The Latest News The latest news is that MS is shutting down services for the International Court of Justice after a panel of ICC judges issued arrest warrants against Israeli Prime Minister Benjamin Netanyahu [1] . This is now making politicians realise the issues of email accounts hosted outside their jurisdiction. What we need is for each independent jurisdiction to have it s own email infrastructure, that means controlling DNS servers for their domains, commercial and government mail services on those domains, running the servers for those services on hardware located in the jurisdiction and run by people based in that jurisdiction and citizens of it. I say independent jurisdiction because there are groups like the EU which have sufficient harmony of laws to not require different services. With the current EU arrangements I don t think it s possible for the German government to block French people from accessing email or vice versa. While Australia and New Zealand have a long history of cooperation there s still the possibility of a lying asshole like Scott Morrison trying something on so New Zealanders shouldn t feel safe using services run in Australia. Note that Scott Morrison misled his own parliamentary colleagues about what he was doing and got himself assigned as a secret minister [2] demonstrating that even conservatives can t trust someone like him. With the ongoing human rights abuses by the Morrison government it s easy to imagine New Zealand based organisations that protect human rights being treated by the Australian government in the way that the ICC was treated by the US government. The Problem with Partial Solutions Now it would be very easy for the ICC to host their own mail servers and they probably will do just that in the near future. I m sure that there are many companies offering to set them up accounts in a hurry to deal with this (probably including some of the Dutch companies I ve worked for). Let s imagine for the sake of discussion that the ICC has their own private server, the US government could compel Google and MS to block the IP addresses of that server and then at least 1/3 of the EU population won t get mail from them. If the ICC used email addresses hosted on someone else s server then Google and MS could be compelled to block the addresses in question for the same result. The ICC could have changing email addresses to get around block lists and there could be a game of cat and mouse between the ICC and the US government but that would just be annoying for everyone. The EU needs to have services hosted and run in their jurisdiction that are used by the vast majority of the people in the country. The more people who are using services outside the control of hostile governments the lesser the impact of bad IT policies by those hostile governments. One possible model to consider is the Postbank model. Postbank is a bank run in the Netherlands from post offices which provides services to people deemed unprofitable for the big banks. If the post offices were associated with a mail service you could have it government subsidised providing free service for citizens and using government ID if the user forgets their password. You could also have it provide a cheap service for non-citizen residents. Other Problems What will the US government do next? Will they demand that Apple and Google do a remote-wipe on all phones run by ICC employees? Are they currently tracking all ICC employees by Android and iPhone services? Huawei s decision to develop their own phone OS was a reasonable one but there s no need to go that far. Other governments could setup their own equivalent to Google Play services for Android and have their own localised Android build. Even a small country like Australia could get this going for the services of calendaring etc. But the app store needs a bigger market. There s no reason why Android has to tie the app store to the services for calendaring etc. So you could have a per country system for calendaring and a per region system for selling apps. The invasion of Amazon services such as Alexa is also a major problem for digital sovereignty. We need government controls about this sort of thing, maybe have high tariffs on the import of all hardware that can only work with a single cloud service. Have 100+% tariffs on every phone, home automation system, or networked device that is either tied to a single cloud service or which can t work in a usable manner on other cloud services.

Colin Watson: Free software activity in December 2024

Most of my Debian contributions this month were sponsored by Freexian, as well as one direct donation via Liberapay (thanks!). OpenSSH I issued a bookworm update with a number of fixes that had accumulated over the last year, especially fixing GSS-API key exchange which was quite broken in bookworm. base-passwd A few months ago, the adduser maintainer started a discussion with me (as the base-passwd maintainer) and the shadow maintainer about bringing all three source packages under one team, since they often need to cooperate on things like user and group names. I agreed, but hadn t got round to doing anything about it until recently. I ve now officially moved it under team maintenance. debconf Gioele Barabucci has been working on eliminating duplicated code between debconf and cdebconf, ultimately with the goal of migrating to cdebconf (which I m not sure I m convinced of as a goal, but if we can make improvements to both packages as part of working towards it then there s no harm in that). I finally got round to reviewing and merging confmodule changes in each of debconf and cdebconf. This caused an installer regression due to a weirdness in cdebconf-udeb s packaging, which I fixed - sorry about that! I ve also been dealing with a few patch submissions that had been in my queue for a long time, but more on that next month if all goes well. CI issues I noticed and fixed a problem with

Restrictions:
needs-sudo

in autopkgtest. I fixed broken aptly images in the Salsa CI pipeline. Python team Last month, I mentioned some progress on sorting out the multipart vs. python-multipart name conflict in Debian (#1085728), and said that I thought we d be able to finish it soon. I was right! We got it all done this month:

The Python 3.13 transition continues, and last month we were able to add it to the supported Python versions in testing. (The next step will be to make it the default.) I fixed lots of problems in aid of this, including:

audioread
celery
cloud-sptheme
djangorestframework
dominate
fenics-basix (investigated and suggested a fix, although it hasn t yet been uploaded)
ipykernel
ipython
jupyter-server (contributed upstream)
mdp (contributed upstream)
pastescript (contributed upstream)
pypandoc (contributed upstream)
python-aiosmtpd
python-cheroot
python-hjson
python-miio
python-pyramid
python-trustme (uploaded by Robie Basak)
rich (investigated and tested; uploaded by Sandro Tosi)
supervisor
tomopy

Sphinx 8.0 removed some old intersphinx_mapping syntax which turned out to still be in use by many packages in Debian. The fixes for this were individually trivial, but there were a lot of them:

I found that twisted 24.11.0 broke tests in buildbot and wokkel, and fixed those. I packaged python-flatdict, needed for a new upstream version of python-semantic-release. I tracked down a test failure in vdirsyncer (which I ve been using for some years, but had never previously needed to modify) and contributed a fix upstream. I fixed some packages to tolerate future versions of dh-python that will drop their dependency on python3-setuptools:

I fixed django-cte to remove a build-dependency on the obsolete python3-nose package. I added Django 5.1 support to django-polymorphic. (There are a number of other packages that still need work here.) I fixed various other build/test failures:

black
datalad-next: #1080969 and #1088038 (contributed upstream)
dipy (uploaded by Andreas Tille)
pyfribidi
pylibmc, fixing a build failure in cachelib
pympress
pytest-forked (contributed upstream)
python-mongomock: c03f91b51048 and c485fb8fef23
python-nox

I upgraded these packages to new upstream versions:

aioftp
alot
astroid
buildbot
cloudpickle (fixing a Python 3.13 failure)
django-countries
django-sass-processor
djoser (fixing CVE-2024-21543)
ipython
jsonpickle
lazr.delegates
loguru (fixing a Python 3.13 failure)
netmiko
pydantic
pydantic-core
pydantic-settings
pydoctor
pygresql
pylint (fixing Python 3.13 failures #1089758 and #1091029)
pypandoc (fixing a Python 3.12 warning)
python-aiohttp (fixing CVE-2024-52303 and CVE-2024-52304
python-aiohttp-security
python-argcomplete
python-asyncssh
python-click
python-cytoolz
python-jira (fixing a Python 3.13 failure)
python-limits
python-line-profiler
python-mkdocs
python-model-bakery
python-pgspecial
python-pyramid (fixing CVE-2023-40587)
python-pythonjsonlogger
python-semantic-release
python-utils
python-venusian
pyupgrade
pyzmq
quart
six
sqlparse
twisted
vcr.py
vulture
yoyo
zope.configuration
zope.testrunner

I updated the team s library style guide to remove material related to Python 2 and early versions of Python 3, which is no longer relevant to any current Python packaging work. Other Python upstream work I happened to notice a Twisted upstream issue requesting the removal of the deprecated twisted.internet.defer.returnValue, realized it was still used in many places in Debian, and went on a PR-filing spree informed by codesearch to try to reduce the future impact of such a change on Debian:

Other small fixes Santiago Vila has been building the archive with

make
--shuffle

(also see its author s explanation). I fixed associated bugs in cccc (contributed upstream), groff, and spectemu. I backported an upstream patch to putty to fix undefined behaviour that affected use of the small keypad . I removed groff s Recommends: libpaper1 (#1091375, #1091376), since it isn t currently all that useful and was getting in the way of a transition to libpaper2. I filed an upstream bug suggesting better integration in this area.

Chris Lamb: Favourites of 2024

Here are my favourite books and movies that I read and watched throughout 2024. It wasn't quite the stellar year for books as previous years: few of those books that make you want to recommend and/or buy them for all your friends. In subconscious compensation, perhaps, I reread a few classics (e.g. True Grit, Solaris), and I'm almost finished my second read of War and Peace.

Books

Films Recent releases

20 Days in Mariupol (Mstyslav Chernovm, 2023)
All the Beauty and the Bloodshed (Laura Poitras, 2022)
Anora (Sean Baker, 2024)
La Chimera (Alice Rohrwacher, 2023)
Do Not Expect Too Much from the End of the World (Radu Jude, 2023)
Evil Does Not Exist (Ryusuke Hamaguchi, 2023)
Godland (Hlynur P lmason, 2022)
The Remarkable Life of Ibelin (Benjamin Ree, 2024)
R.M.N. (Cristian Mungiu, 2022)
Robot Dreams (Pablo Berger, 2023)
The Zone of Interest (Jonathan Glazer, 2023)
Good One (India Donaldson, 2024)

Seen at a 2023 festival. Disappointments this year included Blitz (Steve McQueen), Love Lies Bleeding (Rose Glass), The Room Next Door (Pedro Almod var) and Emilia P rez (Jacques Audiard), whilst the worst new film this year was likely The Substance (Coralie Fargeat), followed by Megalopolis (Francis Ford Coppola), Unfrosted (Jerry Seinfeld) and Joker: Folie Deux (Todd Phillips).
Older releases ie. Films released before 2023, and not including rewatches from previous years.

Angel (Ernst Lubitsch, 1937)
Come and See (Elem Klimov, 1985)
The Fly (David Cronenberg, 1986)
Gaslight (Thorold Dickinson, 1940)
Harakiri (Masaki Kobayashi, 1962)
Make Way for Tomorrow (Leo McCarey, 1937)
Man with a Movie Camera (Dziga Vertov, 1929)
Manhunter (Michael Mann, 1986)
Purple Noon (Ren Cl ment, 1960)
Shoah (Claude Lanzmann, 1985)
Squid and the Whale (Noah Baumbach, 2005)
Xala (Ousmane Semb ne, 1975)

Distinctly unenjoyable watches included The Island of Dr. Moreau (John Frankenheimer, 1996), Southland Tales (Richard Kelly, 2006), Any Given Sunday (Oliver Stone, 1999) & The Hairdresser s Husband (Patrice Leconte, 19990). On the other hand, unforgettable cinema experiences this year included big-screen rewatches of Solaris (Andrei Tarkovsky, 1972), Blade Runner (Ridley Scott, 1982), Apocalypse Now (Francis Ford Coppola, 1979) and Die Hard (John McTiernan, 1988).

Benjamin Mako Hill: Thug Life

My current playlist is this diorama of Lulu the Piggy channeling Tupac Shakur in a toy vending machine in the basement of New World Mall in Flushing Chinatown.

Gregory Colpart: MiniDebConf Toulouse 2024

After the MiniDebConf Marseille 2019, COVID-19 made it impossible or difficult to organize new MiniDebConfs for a few years. With the gradual resumption of in-person events (like FOSDEM, DebConf, etc.), the idea emerged to host another MiniDebConf in France, but with a lighter organizational load. In 2023, we decided to reach out to the organizers of Capitole du Libre to repeat the experience of 2017: hosting a MiniDebConf alongside their annual event in Toulouse in November. However, our request came too late for 2023. After discussions with Capitole du Libre in November 2023 in Toulouse and again in February 2024 in Brussels, we confirmed that a MiniDebConf Toulouse would take place in November 2024! We then assembled a small organizing team and got to work: a Call for Papers in May 2024, adding a two-day MiniDebCamp, coordinating with the DebConf video team, securing sponsors, creating a logo, ordering T-shirts and stickers, planning the schedule, and managing registrations. Even with lighter logistics (conference rooms, badges, and catering during the weekend were handled by Capitole du Libre), there was still quite a bit of preparation to do. On Thursday, November 14, and Friday, November 15, 2024, about forty developers arrived from around the world (France, Spain, Italy, Switzerland, Germany, England, Brazil, Uruguay, India, Brest, Marseille ) to spend two days at the MiniDebCamp in the beautiful collaborative spaces of Artilect in Toulouse city center.