Bookmarked Disinformation and its effects on social capital networks (Google Doc) by Dave Troy

This document by US journalist Dave Troy positions resistance against disinformation not as a matter of factchecking and technology but as one of reshaping social capital and cultural network topologies. I plan to read this, especially the premises part looks interesting. Some upfront associations are with Valdis Krebs’ work on the US democratic / conservative party divide where he visualised it based on cultural artefacts, i.e. books people bought (2003-2008), to show spheres and overlaps, and with the Finnish work on increasing civic skills which to me seems a mix of critical crap detection skills woven into a social/societal framework. Networks around a belief or a piece of disinformation for me also point back to what I mentioned earlier about generated (and thus fake) texts, how attempts to detect such fakes usually center on the artefact not on the richer tapestry of information connections (last 2 bullet points and final paragraph) around it (I called it provenance and entanglement as indicators of authenticity recently, entanglement being the multiple ways it is part of a wider network fabric). And there’s the more general notion of Connectivism where learning and knowledge are situated in networks too.

The related problems of disinformation, misinformation, and radicalization have been popularly misunderstood as technology or fact-checking problems, but this ignores the mechanism of action, which is the reconfiguration of social capital. By recasting these problems as one problem rooted in the reconfiguration of social capital and network topology, we can consider solutions that might maximize public health and favor democracy over fascism …

Dave Troy

Bookmarked WordPress AI: Generative Content & Blocks (by Joe Hoyle, found via Chuck Grimmett)

As many others I am fascinated by what generative algorithms like ChatGPT for texts and Stable Diffusion for images can do. Particularly I find it fascinating to explore what it might do if embedded in my own workflows, or how it might change my workflows. So the link above showing an integration of ChatGPT in WordPress’ Gutenberg block editor drew my attention.

The accompanying video shows a mix of two features. First having ChatGPT generate some text, or actually a table with specific data, and having ChatGPT in ‘co-pilot’ style generate code for Gutenberg blocks. I think the latter might be actually useful, as I’ve seen generative AI put to good use in that area. The former, having ChatGPT write part of your posting is clearly not advisable. And the video shows it too, although the authors don’t point it out or haven’t reflected on the fact that ChatGPT is not a search engine but geared to coming up with plausible stuff without being aware of its actual information (the contrast with generating code is that code is much more highly structured in itself so probabilities collapse easier to the same outcome).

The blogpost in the video is made by generating a list of lunar missions, and then turning them into a table, adding their budgets and sorting them chronologically. This looks very cool in the vid, but some things jump out as not ok. Results jump around the table for instance: Apollo 13 moves from 1970 to 2013 and changes budget. See image below. None of the listed budgets for Apollo missions, nor their total, match up with the detailed costs overview of Apollo missions (GoogleDocs spreadsheet). The budget column being imaginary and the table rows jumping around makes the result entirely unfit for usage of course. It also isn’t a useful prompt: needing to fact check every table field is likely more effort and less motivating than researching the table yourself from actual online resources directly.

It looks incredibly cool ‘see me writing a blogpost by merely typing in my wishes, and the work being done instantly’, and there are definitely times I’d wish that to be possible. To translate a mere idea or thought into some output directly however means I’d skip confronting such an idea with reality, with counter arguments etc. Most of my ideas only look cool inside my head, and need serious change to be sensibly made manifest in the world outside my head. This video is a bit like that, an idea that looks cool in one’s head but is great rubbish in practice. ChatGPT is hallucinating factoids and can’t be trusted to create your output. Using it in the context of discovery (as opposed to the justification context of your output such as in this video) is possible and potentially useful. However this integration within the Gutenberg writing back-end of WordPress puts you in the output context directly so it leads you to believe the generated plausible rubbish is output and not just prompting fodder for your writing. ‘Human made’ is misleading you with this video, and I wouldn’t be surprised if they’re misleading themselves as well. A bit like staging the ‘saw someone in half and put them together again’ magician’s trick in an operating room and inviting surgeons to re-imagine their work.

Taking a native-first approach to integrating generative AI into WordPress, we’ve been experimenting with approaches to a “WordPress Copilot” that can “speak” Gutenberg / block-editor.

Copy-pasting paragraphs between ChatGPT and WordPress only goes so far, while having the tools directly embedded in the editor … open up a world of possibilities and productivity wins…

Joe Hoyle


An android robot is filling out a table listing Apollo missions on a whiteboard, generated image using Midjourney

I have a little over 25 years worth of various notes and writings, and a little over 20 years of blogposts. A corpus that reflects my life, interests, attitude, thoughts, interactions and work over most of my adult life. Wouldn’t it be interesting to run that personal archive as my own chatbot, to specialise a LLM for my own use?

Generally I’ve been interested in using algorithms as personal or group tools for a number of years.

For algorithms to help, like any tool, they need to be ‘smaller’ than us, as I wrote in my networked agency manifesto. We need to be able to control its settings, tinker with it, deploy it and stop it as we see fit.
Me, April 2018, in Algorithms That Work For Me, Not Commoditise Me

Most if not all of our exposure to algorithms online however treats us as a means to manipulate our engagement. I see them as potentially very valuable tools in working with lots of information. But not in their current common incarnations.

Going back to a less algorithmic way of dealing with information isn’t an option, nor something to desire I think. But we do need algorithms that really serve us, perform to our information needs. We need less algorithms that purport to aid us in dealing with the daily river of newsy stuff, but really commodotise us at the back-end.
Me, April 2018, in Algorithms That Work For Me, Not Commoditise Me

Some of the things I’d like my ideal RSS reader to be able to do are along such lines, e.g. to signal new patterns among the people I interact with, or outliers in their writings. Basically to signal social eddies and shifts among my network’s online sharing.

LLMs are highly interesting in that regard too, as in contrast to the engagement optimising social media algorithms, they are focused on large corpora of text and generation thereof, and not on emergent social behaviour around texts. Once trained on a large enough generic corpus, one could potentially tune it with a specific corpus. Specific to a certain niche topic, or to the interests of a single person, small group of people or community of practice. Such as all of my own material. Decades worth of writings, presentations, notes, e-mails etc. The mirror image of me as expressed in all my archived files.

Doing so with a personal corpus, for me has a few prerequisites:

  • It would need to be a separate instance of whatever tech it uses. If possible self-hosted.
  • There should be no feedback to the underlying generic and publicly available model, there should be no bleed-over into other people’s interactions with that model.
  • The separate instance needs an off-switch under my control, where off means none of my inputs are available for use someplace else.

Running your own Stable Diffusion image generator set-up as E currently does complies with this for instance.

Doing so with a LLM text generator would create a way of chatting with my own PKM material, ChatPKM, a way to interact (differently than through search and links, as I do now) with my Avatar (not just my blog though, all my notes). It might adopt my personal style and phrasing in its outputs. When (not if) it hallucinates it would be my own trip so to speak. It would be clear what inputs are in play, w.r.t. the specialisation, so verification and references should be easier to follow up on. It would be a personal prompting tool, to communicate with your own pet stochastic parrot.

Current attempts at chatbots in this style seem to focus on things like customer interaction. Feed it your product manual, have it chat to customers with questions about the product. A fancy version of ‘have you tried switching it off and back on?‘ These services allow you to input one or a handful of docs or sources, and then chat about its contents.
One of those is Chatbase, another is ChatThing by Pixelhop. The last one has the option of continuously adding source material to presumably the same chatbot(s), but more or less on a per file and per URL basis and limited in number of words per month. That’s not like starting out with half a GB in markdown text of notes and writings covering several decades, let alone tens of GBs of e-mail interactions for instance.

Pixelhop is currently working with Dave Winer however to do some of what I mention above: use Dave’s entire blog archives as input. Dave has been blogging since the mid 1990s, so there’s quite a lot of material there.
Checking out ChatThing suggests that they built on OpenAI’s ChatGPT 3.5 through its API. So it wouldn’t qualify per the prerequisites I mentioned. Yet, purposely feeding it a specific online blog archive is less problematic than including my own notes as all the source material involved is public anyway.
The resulting Scripting News bot is a fascinating experiment, the work around which you can follow on GitHub. (As part of that Dave also shared a markdown version of his complete blog archives (33MB), which for fun I loaded into Obsidian to search through. Also for comparison with the generated outputs from the chatbot, such as the question Dave asked the bot when he first wrote about the iPhone on his blog.)

Looking forward to more experiments by Dave and Pixelhop. Meanwhile I’ve joined Pixelhop’s Discord to follow their developments.

Bookmarked The push to AI is meant to devalue the open web so we will move to web3 for compensation (by Mita Williams)

Adding this interesting perspective from Mita Williams to my notes on the effects of generative AI. She positions generative AI as bypassing the open web entirely (abstracted away into the models the AIs run on). Thus sharing is disincentivised as sharing no longer brings traffic or conversation, if it is only used as model-fodder. I’m not at all sure if that is indeed the case, but from as early as YouTube’s 2016 Flickr images database being used for AI model training, such as IBM’s 2019 facial recognition efforts, it’s been a concern. Leading to questions about whether existing (Creative Commons) licenses are fit for purpose anymore. Specifically Williams pointing to not only the impact on an individual creator but also on the level of communities they form, are part of and interact in, strikes me as worth thinking more about. The erosion of (open source, maker, collaborative etc) community structures is a whole other level of potential societal damage.

Mita Williams suggests the described erosion is not an effect but an actual aim by tech companies, part of a bait and switch. A re-siloing, an enclosing of commons, where being able to see something in return for online sharing again is the lure. Where the open web may fall by the wayside and become even more niche than it already is.

…these new systems (Google’s Bard, the new Bing, ChatGPT) are designed to bypass creators work on the web entirely as users are presented extracted text with no source. As such, these systems disincentivize creators from sharing works on the internet as they will no longer receive traffic…

Those who are currently wrecking everything that we collectively built on the internet already have the answer waiting for us: web3.

…the decimation of the existing incentive models for internet creators and communities (as flawed as they are) is not a bug: it’s a feature.

Mita Williams

Peter has experimented for a while with Mastodon (and the ActivityPub protocol behind it) and decided that it’s not for him.

Well, this has been fun, but it turns out that the effort-vs-reward for the fediverse doesn’t balance for me; I need fewer reasons to be tethered, not more. @mastohost, recommended by @ton, was an excellent playground. In 24 hours this account will self-destruct. But, now and forever, https://ruk.ca is where you’ll find me.

I very much recognise his point. The disbalance he mentions I felt strongly in the past month, where it was absent in the five and a half years before it. The enormous influx of people, positive in itself, and the resulting growth in the number of people I followed made my timeline too busy. In response I started following topics more and am evaluating rss feeds from ActivityPub servers. The disbalance expresses itself in spending too much time in the home timeline, without that resulting in notable things. (I mean literally notable, as in taking notes) Unlike my feedreader. It does result in some interesting conversations. However such interactions usually start from a blogpost that I share. Because of the newness of AP and Mastodon to the large wave of people joining, many posts including mine are of the ‘Using Mastodon to talk about Mastodon’ type. This is of course common for newly adopted tools, and I still have a category on this blog for metablogging, as blogging about blogging has been a 20 year long pattern here. Yet it is also tiring because it is mostly noise, including the whole kindergarten level discussions between petty admins defederating each other. There’s a very serious discussion to be had about moderation, blocks and defederation, to turn it into a tool that provides agency to individual users and the groups they are part of. These tools are important, and I’m glad I have them at my disposal. Ironically such serious discussion about Mastodon isn’t easy to conduct in a Tweetdeck and Twitter style interface, such as Mastodon provides. I moved the home timeline over to the right in my Mastodon web interface, so I don’t see it as the first thing when I open it up. I’ve concluded I need to step away from timeline overwhelm. Much as I did on Twitter years ago.


A tired purple mastodont lies on the ground sleeping while groups of people are talking in the background, sketchbook style. Dall-E generated image.

There are however two distinct aspects about AP and the recent incoming wave of people that I am more interested to be engaged with than I was before this started.

First, to experiment personally with AP itself, and if possible with the less known Activities that AP could support, e.g. travel and check-ins. This as an extension of my personal site in areas that WordPress, OPML and RSS currently can’t provide to me. This increases my own agency, by adding affordances to my site. This in time may mean I won’t be hosting or self-hosting my personal Mastodon instance. (See my current fediverse activities)

Second, to volunteer for governance related topics in the wider Dutch user group of Mastodon. Regardless of my own use of Mastodon, it is an environment in which many more people than before have new choices to make w.r.t. taking their online presence and tools in their own hands. A step from a global silo such as Twitter to e.g. a larger Dutch instance, while not the same as running one’s own, can be a significant step to more personal agency and networked agency. I’m involved in a group discussing how to establish governance structures that can provide continuity to the Dutch instance Mastodon.nl, lets people on the instance have an active voice and role in its internal governance, and raises awareness of the variety of tools and possibilites out there while purposefully avoiding becoming a new silo (through e.g. providing pathways away from the instance). Such governance is not part of the Mastodon instance, but structured around it. Such involvement is an expression of my experience and role in using tech for the past 33 years online as being inherently political.


A purple mastodont is conversing with a crowd of people, sketchbook style. Dall-E generated image.

In the noisy chaotic phase that Twitter Inc. is going through, I downloaded my data from them 2 weeks ago. Meanwhile in the Fediverse newcomers mention they appreciate how nice, pleasant and conversational things are.

It’s good to note that that is how Twitter started out too. In my network I felt I was late joining Twitter, this because I was using Jaiku (a similar, better I might add, service based in Europe). Sixteen years on that can be seen as early user. My user ID is number 59923, registered on Tuesday December 12th, 2006. Judging by the time, 10:36am, I registered during my regular 10:30 coffee break.

One minute later I posted my first message. It had ID 994313, so my Tweet was just within the first million messages on Twitter (the current rate seems to be over 800 million Tweets per day!). That first message mentioned the tool I was going to benchmark Twitter against: Jaiku.

What followed that first message was like how it was the past 4 years using Mastodon. A bunch of gentle conversations.

Back then everyone was nice, as you tend to be in public e.g. walking through a small village. Over time Twitter conversations tended towards “I need to win this exchange, even if I agree with my counterpart”. Argumentative. Performance above conversation. Performing in front of your own followers by enacting a conversation with someone else. The general tone of voice on Twitter (apart from the actual toxicity) is somewhat like the difference of posture you take in a metropolis versus a village. In a village you greet passersby, project an aura of approachability etc. In an urban environment you tend to pretend to not see others, are pro-active in claiming your physical space, alert that others don’t push you aside or further down the queue etc. Urban behaviour easily looks aggressive, and at the very least unnecessarily rude, in a village.

The past few weeks saw a massive influx of people from Twitter. Which is good. I also noticed that it felt a bit like city folk descending on some backwater. The general tone of voice, directness or terseness in phrasing, reflecting the character limit on Twitter, in contrast with the wider limits in Mastodon-village which allows both for more nuance and for, yes, politeness.
The contrast was felt both ways, as newcomers commented on how nice the conversations were, a breath of fresh air etc.

Quantitative changes, like a rising number of people using a specific communication channel, leads to qualitative changes. It did on Twitter. It will on Mastodon, despite the differences. In the fediverse some of that effect will be buffered by the tools individual users have on hand (blocking, blocking instances, moving instance or run your own, participate from your own website, e.g.). Meaning one can choose to ‘live’ in the middle of the metropolis, or on its outskirts where not many much frequent. But the effect will be there, also because there will be more tools built from other starting principles than the current tree of fediverse applications on top of the underlying ActivityPub protocol. Some will be counter those that underpin e.g. Mastodon, others will be aligned. But change it will.

It’s nice out here, but do regularly check the back of the package for the best-by date.