Followups: Mastodon and the pursuit of a utopian online community
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The content police: Cyberabuse, cyberbullying, fake news, and reductive solutions
by Annotote TLDR 2017.12.07
The future of free speech and social media regulation: The panic button, the special internet standard, and its independent arbitration system
by Adventures in Consumer Technology 2019.04.15
See also: Free Speech Followups
Federation is the Worst of all Worlds
by Sarah Jamie Lewis (Field Notes) 2018.07.10
The threat model and economics of federated systems devolve to concentrating trust in the hands of a few, while missing out on the scale advantages of purely centralized solutions.
Federation results in the data of users being subject to the whims of the owner of the federated instance. Administrators can see correspondence and derive social graphs trivially. They are also in a position to selectively censor inter-instance communication. All of this while gaining none of the benefits of scale and discovery that centralized systems provide.
All the privacy issues, none of the scale advantages… In short, federation is the wrong model because it concentrates trusts, and we must look to building privacy-preserving peer-to-peer infrastructure if we have any hope of building a decentralized future.
Markets are eating the world
by Ribbon Farm 2019.02.29
Bueno de Mesquita calls this Selectorate Theory. The selectorate represents the number of people who have influence in a government, and thus the degree to which power is distributed. The selectorate of a dictatorship will tend to be very small: the dictator and a few cronies. The selectorate in democracy tends to be much larger, typically encompassing the Executive, Legislative, and Judicial branches and the voters which elect them.
Historically, the size of the selectorate involves a tradeoff between the efficiency and the robustness of the governmental system. Let’s call this the “Selectorate Spectrum.”
Dictatorships can be more efficient than democracies because they don’t have to get many people on board to make a decision. Democracies, by contrast, are more robust, but at the cost of efficiency.
The Mastodon community is dealing with an influx of hateful content into its decentralized open source protocol
by The Verge 2019.07.13
[L]ast week, the social network Gab migrated to Mastodon — and Mastodon’s admins have been forced to deal with the internet’s Nazi problem head-on…
Many prominent Mastodon servers already moderate against racism, so Gab has faced a wave of individual blocks from individual servers. But going further has proven controversial, exposing profound questions within the community…
Mastodon founder Eugen “Gargron” Rochko, meanwhile, believes a scorched-Earth campaign against Gab’s fork of Mastodon isn’t practical. “You have to understand it’s not actually possible to do anything platform-wide because it’s decentralized… I don’t have the control.” […]
Gab calls itself the largest Mastodon instance, boasting over a million accounts before migration. That number is almost double the user base of the previous largest listed instance, Japanese-language forum Pawoo.net, and triple the base of Mastodon.Social, the next-largest instance.
Senate testimony: The internet; artificial intelligence; and Congress’ options for algorithmic transparency and algorithmic explanation
by Stephen Wolfram 2019.06.25
Wolfram Alpha’s founder on “Optimizing for Engagement: Understanding the Use of Persuasive Technology on Internet Platforms”
So why not just “open up the AI” and see what it’s doing inside? Well, that’s what the algorithmic transparency idea… no, that can’t work. If we want to seriously use the power of computation — and AI — then inevitably there won’t be a “human-explainable” story about what’s happening inside.
So… what about putting constraints on what the AI does? Well, to do that, you have to say what you want. What rule for balance between opposing kinds of views do you want? How much do you allow people to be unsettled by what they see? And so on.
And there are two problems here: first, what to want, and, second, how to describe it. In the past, the only way we could imagine describing things like this was with traditional legal rules, written in legalese. But if we want AIs to automatically follow these rules, perhaps billions of times a second, that’s not good enough: instead, we need something that AIs can intrinsically understand [like computational contracts in a computer language. [Today, that’s starting to be] fueled by blockchain — I expect that this will accelerate in the years to come. But it’s going to be a while before the US Senate is routinely debating lines of code in computational laws…
[But] there’s still the huge question of what the “computational laws” for automatic content selection AIs will be… one day things like Section 230 [CDA] will, of necessity, not be legalese laws, but computational laws. There’ll be some piece of computational language that specifies for example that this-or-that machine learning classifier trained on this-or-that sample of the internet will be used to define this or that…
Why does every aspect of automated content selection have to be done by a single business? Why not open up the pipeline, and create a market in which users can make choices for themselves? […] I came up with at least two potential ways to open things up [without ruining preexisting platforms or monetization].
One of my ideas involved introducing what I call “final ranking providers”: third parties who take pre-digested feature vectors from the underlying content platform, then use these to do the final ranking of items in whatever way they want. My other ideas involved introducing “constraint providers”: third parties who provide constraints in the form of computational contracts that are inserted into the machine learning loop of the automated content selection system.
The important feature of both these solutions is that users don’t have to trust the single AI of the automated content selection business. They can in effect pick their own brand of AI — provided by a third party they trust — to determine what content they’ll actually be given…
Social networks get their usefulness by being monolithic: by having “everyone” connected into them. But the point is that the network can prosper as a monolithic thing, but there doesn’t need to be just one monolithic AI that selects content for all the users on the network. Instead, there can be a whole market of AIs, that users can freely pick between.
Twitter announces BlueSky: A new initiative to create an open, decentralized social media and networking protocol
by Jack Dorsey (Twitter CEO via Tweetstorm) 2019.12.11
Twitter is funding a small independent team of up to five open source architects, engineers, and designers to develop an open and decentralized standard for social media. The goal is for Twitter to ultimately be a client of this standard.
twitter was so open early on that many saw its potential to be a decentralized internet standard, like SMTP (email protocol). For a variety of reasons, all reasonable at the time, we took a different path and increasingly centralized Twitter. But a lot’s changed over the years…
First, we’re facing entirely new challenges centralized solutions are struggling to meet. For instance, centralized enforcement of global policy to address abuse and misleading information is unlikely to scale over the long-term without placing far too much burden on people.
Second, the value of social media is shifting away from content hosting and removal, and towards recommendation algorithms directing one’s attention. Unfortunately, these algorithms are typically proprietary, and one can’t choose or build alternatives. Yet.
Third, existing social media incentives frequently lead to attention being focused on content and conversation that sparks controversy and outrage, rather than conversation which informs and promotes health.
Finally, new technologies have emerged to make a decentralized approach more viable. Blockchain points to a series of decentralized solutions for open and durable hosting, governance, and even monetization. Much work to be done, but the fundamentals are there[…]
For social media, we’d like this team to either find an existing decentralized standard they can help move forward, or failing that, create one from scratch. That’s the only direction we at Twitter, Inc. will provide.
Why is this good for Twitter? It will allow us to access and contribute to a much larger corpus of public conversation, focus our efforts on building open recommendation algorithms which promote healthy conversation, and will force us to be far more innovative than in the past[…] the work must be done transparently in the open, not owned by any single private corporation, furthering the open & decentralized principles of the internet.
We’d expect this team not only to develop a decentralized standard for social media, but to also build open community around it, inclusive of companies & organizations, researchers, civil society leaders, all who are thinking deeply about the consequences, positive and negative.
Mastodon founder says Donald Trump’s TRUTH Social seems to be using a Mastodon fork, based on a screenshot of an error message featuring Mastodon’s elephant mascot
by Vice 2021.10.22
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