Finished reading The Fediverse is Already Dead by noracodes j and still trying to work out what I think — which I love. Some initial thoughts:

  • ActivityPub is where it’s at. I keep wondering if there’s a way ActivityPub can help make social graphs so those are the networks we talk about rather than the tool, such as Mastodon
  • I like the distinction of talking about communities and prioritizing the values of the particular server or instance
  • I would also separate the idea of a network which can cross communities
  • Tools like are using ActivityPub to help people publish and share across tools — even different form factors
  • Others like let you publish to Mastodon. I worry about the value of that republishing when it doesn't come with engagement
  • PolicyKit is a decentralized tool that replaces permissions/roles with rules/policies. I wonder if it could be integrated with, say, a mastodon server so that the community itself could determine the rules
  • I just read about Spring '83 last night so this might really be recency bias but ... I wonder how the concept of a “board” articulated in that protocol could be used to help follow across a wide variety of published content and how it could play with/use ActivityPub

#Areas #Fediverse #ActivityPub


After defending false data, Comcast admits another FCC broadband map mistake | Ars Technica.

Last week, I spent two days with food bankers. Digital equity was a big part of what they talked about. The stories they told give more color and detail to the findings in the recent digital equity survey published by Connect Humanity. TechSoup partnered in the survey.

We do not have good maps of access (see the link above). We have worse data on all the various elements that makes up real genuine access – space, time, devices, skills.

We’ve got to change this.

#Areas #DigitalEquity


I keep thinking about The ‘Enshittification’ of TikTok by Cory Doctorow.

He describes the process:

This is enshittification: Surpluses are first directed to users; then, once they're locked in, surpluses go to suppliers; then once they're locked in, the surplus is handed to shareholders and the platform becomes a useless pile of shit. From mobile app stores to Steam, from Facebook to Twitter, this is the enshittification lifecycle.

This process begins with finding the hard side of the market, described by Andrew Chen. This is the group — the Uber drivers, the Amazon shoppers, the Google searchers — that you need to bring in first.

The vicious cycle that Doctrow describes is one built on capitalism. The question that sticks in my mind: what other systems can we build that distribute the value in different ways?

I work in civil society. In other words, for and with nonprofit organizations. This whole sector exists to support people who have not been able to access the systems and resources made available by the model of capitalism that is practiced in much of the world. We can build shelter, transport food, provide education, collect memorabilia in museums. We can do so many things. However, so much of that is completely inaccessible to ever larger groups of people.

We are still — still — extracting value for the benefit of a minuscule part of our communities. And then many of us — I include myself — are just comfortable enough that our urgency for change does not lead to system change. We spend too much time doing system adjustment.

So, what does system change look like? Does it look like the fediverse?

People stand on what appears to be a train platform iso_pace on; Pixelfed is an ActivityPub-powered photo sharing network

ActivityPub-powered tools depend on protocols, not platforms. This promise is called out in an essay by Mike Masnick published by the Filecoin Foundation for the Decentralized Web. Masonic writes:

So much of our thinking about today’s world is based on a mental model that effectively craves centralization. We’re working off of a model that focuses on efficiency and profit maximization that automatically pushes towards centralization and what is, in effect, a dictatorial (benevolent or not) view of how society should be structured.

What if, he asks, we can maximize for the benefits of a decentralized value:

Smaller, more decentralized projects can be more nimble, quicker to adapt and change. The fact that lots of smaller groups are trying out ideas allows for rapid experimentation with different approaches, often leading to faster iteration and innovation, driven by competition rather than sheer power and dominance. It also distributes power to the ends, decreasing the risk of abuse of power.

Decentralization is also more resilient. One part of the network can fall, without bringing down everything.

Protocols and decentralization bring benefits: – they make the rules explicit – this makes it possible for people to use the system – and to build at the edges – it provides a way for people to interrogate and improve those rules – this exposes this system and provides an opportunity for change

I muddled around recently in a thought experiment about using Mastodon (another ActivityPub-powered piece of the fediverse) to illuminate the network relationships of civil society organizations.

What if we develop the protocols and language that let us make our relationships explicit and make equally explicit the way resources are shared along the network? What if we support the policies that enable that? We can find chokepoints. We can find places where there are too many resources, places where there are not enough.

The call to action in Blueprint 2023 by Lucy Bernholz is also very relevant here. She argues:

… all civil society needs to engage deeply with the public policies that shape digital systems. It is the only sector that has the incentives and aspirations to do so on behalf of individuals and communities. Civil society organizations and advocates need to discard the sense that they are passively subject to the outcome of digital public policy negotiations or technology innovation. Civil society must recognize that it is, and must be, a leader in how digital systems are designed, regulated, deployed, and prohibited.

We can turn the energy of small civil society organizations into a benefit — they can illuminate a problem that would be otherwise invisible to the network. To do that, we need a decentralized network, multiple protocols for valorizing those organizations, and a way to visual the resources that travel over them.

We need more tools for this than tax records — which is by and large what we have today.

This thinking is still so messy — pulling together a variety of ideas and trying to hack them into working order. Since ideas come from the accretion of knowledge, I’m going to keep plugging away and trying to put these thoughts together.

#Areas #Decentralized #CivilSociety #Networks


I'm Going To Scale My Foot Up Your Ass via Hacker News

You don't need to worry about scalability on your Rails-over-Mysql application because nobody is going to use it. Really. Believe me. You're going to get, at most, 1,000 people on your app, and maybe 1% of them will be 7-day active. Scalability is not your problem, getting people to give a shit is.

GitHub – mattnigh/ChatGPT3-Free-Prompt-List: A free guide for learning to create ChatGPT3 Prompts

Prompt engineering is the process of designing and refining the initial text or input (the prompt) that is given to a language model like ChatGPT to generate a response. It involves designing prompts that guide the model to generate a specific tone, style, or type of content.

Daring Fireball: Joanna Stern on Microsoft’s New AI-Powered Bing’d be a fool to count Google out in this race. But shipping talks and bullshit walks. Microsoft is opening up the new Bing to real people now.

Yes, Republicans are discussing genocide against LGBTQ+ people

Things appear dire for LGBTQ+ rights in the United States, especially when it comes to transgender and non-binary folks— who have found themselves a current primary target of a well-oiled right-wing hate machine fueled by Republican politics. After recently meeting with anti-LGBTQ+ ideologue Chaya Raichik (AKA Libs of TikTok, a major proponent of the “grooming” anti-trans narrative), Donald Trump, the de-facto leader of the MAGA far-right movement and the Republican Party— has followed the trend of genocidal rhetoric against LGBTQ+ people, laying out an apocalyptic vision if he wins in 2024.

#Links #Areas #Scale #AI #LGBTQ #HumanRights


A certain percentage of the Twitter exodus were always bound to return. This is perfectly normal: new services always experience “scalloped” growth. That’s where an outside event — a positive narrative about the new service, or a catastrophe affecting the old one — drives a surge of new users.

Some of those users try the new service, decide it’s not worth it, and leave — but not all of them. Each event triggers a high tide of new signups, but the low tide that follows is still higher than the old level. Surge after surge, the number of users steadily builds, despite the normal ebb and flow.

From Of Course Mastodon Lost Users | by Cory Doctorow

#areas #fediverse #mastadon


  1. It isn't search. Search should give you sources. The excellent is a great application of AI to search.

  2. That we are using it as search shows us how broken search is. At least the model that is monetized by ads. I use DEVONagent as an antidote to search in the way that presents on the world's most popular search engine.

  3. It has limitations. “ChatGPT sometimes writes plausible-sounding but incorrect or nonsensical answers. Fixing this issue is challenging, as: (1) during RL training, there’s currently no source of truth; (2) training the model to be more cautious causes it to decline questions that it can answer correctly; and (3) supervised training misleads the model because the ideal answer depends on what the model knows, rather than what the human demonstrator knows.” (source)

  4. It can be an equalizer. We can use ChatGPT and similar applications built on helping us write to get unstuck. I use tools like these to break away from a blank page.

  5. English teachers (my wife is one!) need to start teaching people a different kind of writing literacy based on prompts, editing, and bringing voice into our writing.

  6. There is a quote I remember being from the Eames documentary: You can't outsource curiosity. What is it we can't outsource to ChatGPT? Curiosity and its close cousin engagement. We have to interact in a way that demonstrates we, as humans, are delivering those two things.

#Areas #AI


A DALL-E 2 generated image of a person standing in a field, painted in an abstract style

Image Credit: A DALL-E 2 generated image of a person standing in a field, painted in an abstract style

In ChatGPT and the Imagenet Moment Benedict Evans writes:

… a generative ML system could make lots more ‘disco’ music, and it could make punk if you described it specifically enough (again, prompt engineering), but it wouldn’t know it was time for a change and it wouldn’t know that punk would express that need. When can you ask for ‘something raw, fresh and angry that’s a radical change from prog rock?’ And when can a system know people might want that? There is some originality in creating new stuff that looks like the patterns we already have, but the originality that matters is in breaking the pattern. Can you score that?

As AI gets better and better at repeating patterns that exist. As we get better at producing prompts – what Evans calls ‘prompt engineering’. As AI starts getting integrated in tools in ways we don’t even notice. As all that happens, we and how do we identify the places we need human intervention? And not just to retain unique value or to increase the amount of interesting hard work we do, but so that we are not building a future based on our past. Because, you know what? That past is full of exploitation, extraction, and oppression. Many would argue the very AI works is an example. It’s intelligence is built off the work of others in a mass consumption way.

So, what does this mean for civil society? How do we take advantage of the technology, influence the system, and judge the output?

  1. Algorithm detectives. We need an independent body who reviews the tools – algorithms, the training of AI – so that we can be clear about the patterns we are learning from and the ways we promote the responses.
  2. Use AI to identify patterns of injustice. This will require excellent prompt engineers who are asking and asking and asking and then sharing the results.
  3. Illuminate what is missing. If AI is trained on available massive data, we need to show what and who is missing from that data. And we have to find ways to include it. Sometimes that will come from technical means – refining, adding, training – and sometimes it will come from advocacy. It must be intentional.
  4. Use the tools. We can’t just opt out. Usage shapes the tools. We have to use them and aggregate our learnings with the goal of improving our own efficiency and shaping the tools themselves. And let’s normalize it. Don’t hide that the you turned the grant question into an AI prompt.
  5. Build context. That’s what struck me about the quote above: context is something’s humans have in a hyper local way. We can adjust, disregard, slow down or speed up what AI generates for us based on the context. We can identify places where the pattern is wrong for reasons of justice and equity. We have the context and the experience.

#areas #AI