+ I’ve not had so much time for the stream of late. Most stuff is going in the garden. Of course, changes to the garden are a stream of themselves. I just mean I haven’t been posting much to the social media streams, where others can more easily discover and interact with it.
> If a factory is torn down but the rationality which produced it is left standing, then that rationality will simply produce another factory. If a revolution destroys a government, but the systematic patterns of thought that produced that government are left intact, then those patterns will repeat themselves. . . . There’s so much talk about the system. And so little understanding.
Just a summary. Click the links to find out more on each one.
tl;dr: more eco-socialism. Watching things and trying to get more out of them by thinking about them critically. Some emacs faffing. Much more happened of course, but I don’t tend to write much about work or my private life here in my digital garden.
+ We’ve watched [[The Good Place]], WandaVision, [[Loki]], [[The Falcon and the Winter Soldier]], and [[Hawkeye]] over the last few months. Also watching [[Ms. Marvel]] as the episodes come out. All Marvel ones, apart from The Good Place. All pretty decent and worth a watch. Some of the Marvel ones even have a bit of social commentary in them.
+ So cool that [[KeePassXC]] comes with a CLI! Makes sense but I hadn’t realised. That is very handy for me.
+ Listened: [[The Uber files: the unicorn]]
+ Generally been avoiding a lot of the [[Uber Files]] stuff so far. Not quite sure why… it’s just kind of depressing I guess. And kind of confirming what was already known or suspected – that a firm built on aggression, growth and toxic masculinity is corrupt and rotten on the inside as well as the outside.
> What the system has done, as a mechanism to continue with growth at all costs, is actually to burn the future. And the future is the least renewable resource. There is no way that we can reuse the time we had when we started this conversation. And by building up a system which is more debt-driven—where we keep consumption going, but by creating more and more debt—what we’re actually doing is burning or stealing the time of people in the future. Because their time will be devoted to repaying the debt
+ I need to find a way to share my spacemacs config in both my personal and my work logins, but have some customisations in both spaces.
+ [[spacemacs profile-specific configuration]]
+ I need to renew my passport. This is massively over subscribed and delayed in the UK right now. So I’m following a Twitter bot some guy made that tweets whenever new appointments are available. World beating service from the UK gov once again!
+ Started skim reading (ironically?) [[How To Take Smart Notes]].
+ I’ve encountered most of the ideas before via the numerous articles and posts written about it.
+ I need to spend more time turning literature notes / quotes from books in to my own understanding.
+ Joined the [[Bonfire]] playground but haven’t got time to do much on there at the mo. But I really love the mission they have around social media so following with great interest.
+ I feel happy discovering more and more as I get older that sci-fi books I took off my Mum’s bookshelf as a kid are in fact often allegorical for some kind of radical politics that I had no idea of at the time.
+ I have oscillatory waves of activity on my garden.
+ Sometimes I have blocks of focus on the mechanics of how the garden works.
+ All the PKM, zettelkasten, smart notes, kind of stuff.
+ Then periods of time spent on the actual content.
– Reading, taking notes, writing about politics, technology, the environment, etc.
+ Occasionally there is a moment of harmony between the waves where the two almost intersect.
+ e.g. critical theory of social media, how digital gardens, the Agora, fit in to that, etc.
I think I first heard of the IndieWeb movement in 2016 sometime. It’s a bit hazy now, but I’ve a memory that I stumbled on it through a trail of links starting on Wikity.
I’ve tinkered with web sites in some form or another for a long time, and I have happy memories of various weird Geocities experiments, sadly lost to the sands of time it seems.
I’ve had a self-hosted blog up at doubleloop.net since around 2013 (thanks again Internet Archive). I went through a through static site generators. I actually really like how my old Hexo-based site looked. Better than my current site…
My first documented attendance of HWC London looks to be December 2016, hosted by Calum and Barry who were really welcoming. Around then, I fiddled about with various platforms before switching over to WordPress.
I’ve really enjoyed being part of the IndieWeb community. My active involvement (at events, on IRC, etc) has peaked and waned over the years, but I’ve still always felt part of the bigger whole. That’s another post, though.
How did you find out about the IndieWeb community?
I spent a bit of time switching my spacemacs config in to a Literate configuration style.
Why?
I use spacemacsa lot. For coding, for writing, for work, for organisation, for my personal knowledge management. It’s central to to most of my day-to-day activities on my computer. I’ve been using for maybe 4 years now, and have built up quite a mess of a configuration file with various tweaks over the years.
Given how much I use it, it seems sensible to give a bit of TLC to this configuration. I’ve tried to comment it as I’ve tweaked it, but it still has gotten messy. I’ve learned and copied a lot from other people’s configs, so endeavouring to make my own readable to others seems like a good thing to do.
I’m also just keen to try out org-babel for some literate coding, and this is an easy way in to doing that.
What I did
Here’s what I’ve done to get started on this.
File reorganisation
First off, I put my existing .spacemacs file into a folder structure where you can split it up into multiple files.
Again, check that everything still works fine afterwards.
Move config into an org file and set up tangling on it
The section on Converting your existing config files in Literature Configuration was really helpful for this. It recommends a great path for moving things incrementally to the literate configuration. Essentially you start off with one huge source block, and gradually split that up in to smaller blocks with org-babel-demarcate-block.
I did that, putting each new source block in to a logical org heading, and adding a bit of description and narrative around them. Each time I split out a new bit, I ran org-babel-tangle to check things were still working.
I have the following config properties at the top of the file:
which says for all the elisp source blocks in this file, combine them together in to user-config.el when I tangle the file. And also include my narrative as comments.
So my user-config is now literally all in My Spacemacs User Config here in my wiki. As in, that is the file that I use to generate my .spacemacs/user-config.el that spacemacs runs. (The source is here.)
I like it, and think it works pretty well for config files. I’m going to try it on my org-roam config next.
Since starting my wiki, in addition to a note-taking tool and a writing aid, I’ve wanted it to be a kind of personal textbook – something that helps me memorise the knowledge that I’ve captured and the ideas that I’m working on.
One seemingly good way of doing that is by turning relevant parts of it into flashcards, and revising them with spaced repetition. Andy Matuschak has a lot of notes on the benefits of spaced repetition, and one in particular on using it for application, synthesis, and creation.
If notes are the seeds in your garden, then they need a bit of TLC to grow into fully-fledged, fruit-bearing ideas. I’m hoping flashcards will be a reminder to me to water them regularly.
But I’m most likely to do the flashcards on my phone, not at my desktop, and none of them will work with orgzly.
So, Anki is a piece of software that will be good for this. I’ve used Anki on and off in the past – it’s a libre software tool for flashcards that uses spaced repetition. There’s a cross-platform desktop version, a web version, and mobile apps, so you can do it in a bunch of places.
So I set that up – notes on how below. It’s worth noting that anki-editor is an org-mode thing, not org-roam specific, but as I’m trying to mix my flashcards and my org-roam zettelkasten-ish personal wiki, I’ll probably have more of an org-roam slant here.
Install Anki
First you’ll need Anki. You can get it from the site, but as I’m on Ubuntu I just went for it straight from the repos.
sudo apt install anki
Install AnkiConnect
AnkiConnect is an Anki extension that lets external apps interact with Anki – for example, creating cards in your decks.
anki-editor is the Emacs extension that let’s you push your cards from your org files into your Anki decks. It’s on Melpa, so you can just install it however you would usually do so in your flavour of Emacs. I’m using spacemacs, so I added anki-editor in to dotspacemacs-additional-packages in my .spacemacs and gave everything a refresh with SPC f e R.
Creating flashcards
Now you can create flashcards in your org files, and push them to Anki via AnkiConnect.
anki-editor-insert-note will create a new flashcard. Here’s an example.
Then anki-editor-push-notes will push it to Anki.
Syncing Anki
From desktop
The easiest way to sync your Anki decks is via ankiweb. (I don’t think ankiweb is libre software, but you can set up your own self-hosted equivalent with anki-sync-server if you want).
To use ankiweb, just click Sync from your desktop Anki, create an account on ankiweb, and then log in.
I feel like I’m maintaining the flashcards separately from the body of my notes – it’s a bit of a duplication of effort. It’d be good to get a flow where the flashcard is just part of the note as is, and I can pull it out without duplicating it.
I’ve only been pushing one flashcard at a time at the moment, when the buffer is open. I’ll probably add a Make step that iterates all my notes and publishes flashcards if found.
My flashcards are (probably?) noise that I don’t want added to my published digital garden – perhaps they should be filtered out of the publish site.
Summary
I’ve now got a fairly simple flow for making flashcards from my wiki notes. I’m hoping this will have a dual purpose of helping me to memorise the things that I’m learning and thinking about, and will also prompt me to regularly tend to my wiki.
I’m sure I’ll follow up with notes soon on how this is all working out.
I read Hello World – How to Be Human in the Age of the Machine by Hannah Fry. It’s about the increasing pervasiveness of algorithmic decision-making in everyday life, and how much we should rely on them.
It’s a really good book – very engagingly written and easy to read, on what could potentially be a pretty dense topic. It’s full of real-world stories to ground the more abstract questions, and it also weaves into that a nice basic overview of what algorithms are, and how the latest crop of machine-learning algorithms work.
So briefly – very broadly an algorithm is just a set of step-by-step logical instructions that show, from start to finish, how to do something. However generally the world algorithm is used a bit more specifically, still in some sense a set of step-by-step instructions, but a more mathetmatical and defined series of steps, and usually run by a computer.
And when people talk about whether algorithms are good or bad, they pretty much always mean decision-making algorithms – something that makes a decision that affects a human in some way. So for example long division is an algorithm, but it’s not really having any decision making effect on society. We’re talking more about things like putting things in a category, making an ordered list, finding links between things, and filtering stuff out. And they might be ‘rule-based’ expert systems, in that the creator programs in a set of rules that the system then executes, or more recently machine learning algorithms, where you train an algorithm on a dataset by reinforcing ‘good’ or ‘bad’ behaviour. Often with these we can’t always be sure how the algorithms has come to a conclusion.
So what the book is really focused on is the effect our increased use of decision-making algorithms like these is having on things like power, advertising, medicine, crime, justice, cars and transport, basically stuff that makes up the fabric of society, and where we’re starting to outsource these decisions to algorithms.
The book does a really good job of explaining some of the problems in outsourcing those decisions.
One big problem being that we have a tendency to trust the decision made by a computer. But we have to really aware of the biases in these systems. Part of this bias is part of the bigger problem endemic in the tech industry – that’s it’s overrepresented by white men who have a very limited world view and a particular set of biases. The system is often going to be made in the image of its creator, right.
But aside from that ML can also biased in that if the data that goes in to them is biased, so will the outcomes be. Garbage in, garbage out. And there’s a lot of biases and garbage statistics in the world. So say if policing disproportiately targets a particular group in arrests and justice treats them differently in sentencing, then they’re more likely to be targeted by an algorithm based on existing policing and crime stats. You have to really challenge existing biases, not build them in to the system.
The book is very even-handed, and isn’t a polemic against machine learning by any regards. There are plenty positives, like image classification of tumours where ML at great speed cases that a pathologist should look at in more detail.
I really liked the conclusion that we should not see machine learning decision making as an either or. Like either we hand it over to machine learning, or we keep everything. It gives the great example of ‘centaur chess‘, where a human plays with an artificial intelligence against another human with an artificial intelligence. Interesting this is something being championed by Gary Kasparov, who was famously beaten by IBM’s Deep Blue AI at chess a few decades back. It opens up new possibilities where AI is complementary and not a replacement.
I think my criticism with the book would be that it doesn’t really challenge the framing of the debate around ML. So its lettting the current arbiters of ML set the agenda to some degree, and then the critcism is in the details and not the higher level. So I mean there’s a whole chapter on whether we have driverless cars or not? But no mention of whether we should rather be endeavouring to take cars off the road completely. And with regards to things like predictive policing there is no questioning of the idea of policing as an institution in the first place, just a question of how we should use algorithms within it. And there isn’t a single mention of climate change which I found pretty amazing.
But still it does a great job of outlining the positives and pitfalls of decision-making algorithms. I’d recommend it, I’d just like the follow up book to be how we can use them for more liberatory purposes!
