Box114: I suppose it’s a gift. But not a good one.

30.10.2430.10.24

DS101: One slight benefit of hubristically deciding to produce 20 minutes of oroginal animations for a talk was that I was forced to run a bunch of Blender updates to add-ons and get my syncing sorted out so now actually doing renders is a lot easier so maybe I’ll go back to them.

At least three people said ‘I love your blog’ in the last week and each time I felt crestfallen that I’ve been so lax with this this obligation. I really do try and do everything. I think I’ve seen films where in sound recording studios some of the sliders on the big desk of sliders move on their own; I’m not sure why this is, I assume it’s something programmed in, certainly I’ve never been around audio equipment that sophisticated. My own musical recordings were all done with a combination of Garage Band and crates of Kronenburg. Anyway, that’s how life works sometimes: You turn something up at one end and all the way down the other end of the desk a slider is automatically tweaked down.

Making Five Stores From The Distant Future

For the last two weeks I’ve been spending evenings and early morning working on a series of renders for the opening keynote I gave at Orgatec in Cologne last week. The whole thing was a massive faff but quite fun and diverting at a time where I really needed something creative to call my own. Sure, I could have thrown some slides together for a 25 minute-long witter with some data and ‘trends,’ but having spoken with Robert who was organising the whole shindig I felt quite inspired to go the extra mile and turned the research I did into a series of short stories from the future. At some point I’ll figure out how to share these but I wanted (realising that people who read this website are actually interested in this stuff) to talk about how I went about doing it.

Map of the world-building exercise showing the main ideas with interconnected artefacts. — The first sketch map of the world–building. I just threw down ideas then started connecting them and thinking about what artefacts and visuals might materialise those ideas.

To start with I had three constraints: I knew I wanted to write and tell short stories (just because), I knew I had about 20 minutes in a 35 minute talk to do this so I worked out I wanted roughly 5 short stories of about 4 minutes each. I also knew I wanted them all to be connected somehow. The next thing I knew was the big picture of the world. I’d already sent off a blurb and pinned down a couple of things that would shape the world with ideas like degrowth, the end of high finance and speculation, the end or weakening of global norms and institutions and the stuff we know about like climate and demographic change. The final thing was knowing the audience might be futures-curious but like-as-not unfamiliar with most of these concepts.

I started by throwing those big ideas down on a piece of A3 paper and imagining what connected them. For instance, in a world of managed degrowth, people might want to kick against it and you could get a subculture of people looking to engage in high finance and speculation in the same way that living a fully sustainable lifestyle today could be seen as a subculture. You might also start to see a slowdown in global logistics as a result of climate, degrowth and ending global norms, so rather than a world of next-day delivery, everything takes a long time for things to move. Between those two there’s an obvious conflict; the drive for speed, power and control, the reality of sluggish, uncoordinated and messy physical reality. This was the first one I thought about and came to sailing ships but the rest also flowed quite quickly once I started imagining what occurrred at the intersections of different drivers and ideas.

I spent an hour or so doodling away and thinking about the little visuals that emerged and that actually became the backbone of the whole thing. I started by modelling the scenes I was reasonably confident about (like the sailing ships). For each scene it was about making the familiar unfamiliar; the uncanny. For the ships for instance, I used a boxy, cargo ship that might be easily recognised but then put Chinese junker-style sails on copied from a modern sailing vessel. Each scene I wanted to be recognisable but have something different; diesel ships with sails, an office with a playground, a kitchen with 18 seats etc. etc. This is the starting point for most speculative design; finding something materially familiar and normalised and twisting it so that the audience is forced to reconcile their expectation (diesel ships have engines) with what they’re seeing (these ones have sails). So it’s also important that both those things are recognisable. Where I was introducing a brand new element – like the ‘d-rhizome’ in the home office scene; an AI-augmented alternative to the Internet that is fully node-based and inspired by slime moulds or mycelium – these would have to be explained in the story.

From here the stories and scenes sort of developed in tandem along with prompting ideas for the next scenes. Some stories were easy to flesh out to bullet points and pull together like the Bangladeshi immigrants running a semi-autonomous Norwegian vineyard as part of an international soil restoration programme for migrant workers. The pieces just sort of fall into place. Others took more forcing.

The rooftop scene, for example, is about a building caretaker where the building has so much biomaterial and biotech fitted it’s almost a living thing, so I wanted it to be less of a service and more like a doctor; someone who is widely respected and admired for their expertise and time. This is an idea we explored a little of in the Future of Making work that went to Singapore the other week. I knew I wanted the top-down view of the roof in a sort of satire of green roofs. So I put cows on it. If you’re going to cover a roof in grass you might as well have cows and you might as well use their waste to fuel a bioreactor. And the association of the machines with the animals opened up the story beyond the technological to one more similar to a farmer who cares for their animals but it’s a building.

I worked these out by sketching over and over again the scenes in my notebook, adding elements and writing notes on how they might work and how the character relates to them. I didn’t get to writing the prose of the stories until literally on the train over to Cologne. Luckily, my head was so in the world that this all came quite quickly. I settled on a model in which for each scene a character reflects on how they got there, some exposition, some weirdness. I actually ended up using Copilot quite a lot to figure out details like names, locations, species and so on which probably saved a bunch of time hunting for an endangered species of bird that eats berries and migrates from through Germany to the arctic.

On anti-AI aesthetics

A quick note on the style. You might note at the top of that paper it says ‘like Frostpunk.’ I knew I had a lot of work to do so I wanted to reduce the workload as much as possible. So inspired by the game I adopted three tricks. First of all, I tried to stick to fixed view so that I could keep the lighting simple. Apart from the dinner scene, no camera moves through the scene so I didn’t need to worry about what was ‘behind’ the camera and could build the scene like a set. Second of all was using simple flat images as background parallaxes. The rooftop is a great example. The background here is just a flat image of a street. Finally was keeping the style loose and low poly where possible. I didn’t hit this rule all the time. Ironically, the more time-pressured I got, the easier it became to just pull out pre-made assets from Blender Kit. So while the ships is all DIY, with some cardboard cutout UV mapping, by the time I was doing the office scene I was basically just modelling core bits like the room, the weird screen and table, the vertical farm. The rest is all found assets.

One of the first renders I did for the project. The ships are super low-poly and hand modelled. I got a photograph of a cargo ship as a UV map. I wanted to make it look like it had been made out of cardboard intentionally. The wake is just an image I found, edited to isolate the white and then projected on the ocean surface. I wanted it to look like it was all theatrical, papery and representative.

Nearer crunch time I was using lots of pre-made assets like all the vents, tanks and equipment in the roof scene. The image of the street below though it just a still image. I wanted it to still have that element of feeling like a stage set.

I realised quite late that as well as a time-saving effort, these aesthetics decisions were about intentionally distancing the images from the new generative AI aesthetic. I didn’t want to do over-stylised photo-real images with lots of soft blur because I wanted the audience to know that I had made these images by hand, that it took effort and labour to do and that maybe in that effort and labour I had got the opportunity to think about these future scenarios in more depth. That by moving things around, working out how space might function, designing the workarounds people might have to make for their work to fit their lives, that I would learn a lot more about the subject and that this informs the stories.

I know that generative AI image-making has become a popular speculative design tool but I’m pretty sure it’s not actual design. When you put in a prompt to for ‘a future retrofit commercial office where people are living in apartments and spending their days trading in high finance derivatives around a massive table’ you’re not actually designing anything. I suppose you’re actually asking the machine to elicit your own head-cannon from a cultural median for you. Sure that thing has probably never existed before but you’re not really making anything, just skewing a graph.

Design that is also research is what we learn in the actual designing of things; of keyboards and desks and tables and chairs and lamps and switches. In making those things and thinking about the people who will touch and use them you generate knowledge, understanding and insight about the future. If you’re just taking your preconceptions and getting a machine to make them ‘real’ then have you really learned anything? A reason these renders take so long is that even adding a chair to a desk scene forces me to ask questions like; how long does this person sit? What kind of things do they like? Are the proud of their work? What else might they need to do? How might their personality be reflected in the chair? And in exploring and answering those questions I feed the knowledge back into the stories and the world-building.

Points of failure

Of course, none of these projects ever go right. Even after so many years of honing my Blender-craft and convincing myself I had plenty of time there were problems. With about a week to go I lost my notebook and with it, all the sketches, notes and annotations I had been pulling together for each scene. Pretty sure I dropped it somewhere around Central Saint Martins at an event but despite a couple of visits it never showed up so I had to remember a lot of the ideas I had for the last three or four scenes. Second thing was that the PC I was remoting into to do the rendering went offline and took about a week to get back. So I had all the renders backed up and modelled out but time ticking on the actual render time. I ended up sinking about $300 into cloud rendering to meet the deadline. (I missed the deadline, but got it in before the talk which is what counts.)

And of course, nothing ever looks like you want it to. Each of the renders except the vineyard, rooftop and the forest have multiple versions. And even those were re-rendered a bunch to fix bugs or style problems. The original kitchen was just some tables arranged end-to-end with a cooker at the head. It just felt like a big party not like a kitchen purposefully setup for a large group to eat together regularly. The first office was just basically a bullpen with holographic screens which I threw together at 2am one morning and in the cold light of day, rejected as unimaginative and cliched. The idea of having it as a literal live/work retrofit with apartments in a commercial building came later. So really I ended up producing about 16 rendered animations of about two minutes each to get to the final seven.

Finally, and a critical failure for someone who claims to be a designer; I didn’t get to do any testing. There simply wasn’t time to get someone else to have an eye-over of the stories. I was writing and editing them right up to the morning of the keynote itself You should always give time to have someone else edit your work because, though I may know this world inside and out, no one else does and afterwards several audience members commented that it was ‘very dense’ meaning, I imagine, a lot went over people’s heads when spoken and not read on the page. It also probably meant that I wasn’t as confident in them in presentation as I might have been with more dry-runs, even if I did rehearse the whole thing four or five times.

For example, introducing the d-rhizome, this new type of Internet which prioritises real connection rather than command-and-control was tough. Think about a classic science fiction book; usually it only introduces one new idea (e.g. there’s time travel, plants are an alien species, spiders are the apex species) but everything else is broadly the same (e.g. people want to preserve their life, get wealthier (in some way) saved their loved ones, whatever). But science fiction authors get a whole book and your total attention to introduce and explore that idea. I had 5 minutes and a trade conference keynote so I’m not surprised some of it was lost.

Other than that, it’s just all the stuff that goes with anything you’ve worked super hard on; you notice all the things that could be better but I’m long enough in the tooth to know that that’s life and you just have to move on. Anyway, yes, I will find a way to tell you the stories and show you the full renders. It’s on my to-do with everyhting else.

Recent and Upcoming

Couple of recent and upcoming things.

I’ve taken up a teaching role at the London Interdisciplinary School teaching design. I’ve been following the LIS since it launched and been really interested in what a genuinely interdisciplinary education looks like so this is an interesting little peek inside.
I took on a role as an industry champion at the Creative Industries Policy and Evidence Center to advise and consult on the future of the creative industries.
22nd November: I’m going to be at the next Design Declares! event with a host of amazing and luminary folks. Really quite worried about what I’m able to bring to that party.

As I said, I’ll find a way to document the Orgatec stories. The other big one was the opening keynote at the Design and AI symposium hosted by TU Delft. I’m not sure if they were recorded, if not I will also seek to document that but it’s basically a PhD walkthrough with a dance in the middle. I also have thoughts about some of the other stuff that was there.

Reading

I’m significantly behind on keeping up with newsletters because of all the above work. I’ve managed to crawl and skim through about 40 or so in the last few days. There’s an overarching and exasperated message that the amount of money and resource being thrown at AI ($100s billions) versus the actual tangible provable outcomes (5% is of positive impact at various things) are wildly out of proportion which does give the impression that we’re heading for a very real bubble.

The Ethico-Politics of design toolkits by Tomasz Hollanek explores dozens of ethical AI toolkits with some choice words on ethics- and participation-washing as part of a process that is often depoliticised and fails to match the actual needs of AI development processes. These toolkits often call for alternatives, which he points out there are loads of, which are ignored or maligned by mainstream AI practice.
Microsoft’s Hypocrisy on AI. This is depressingly unsurprising but it’s useful to have a bunch of evidence. In the PhD I’m circling a bit around how claims about AI’s ‘potential’ (to do things like cure cancer or mitigate climate change) gain credibility despite these being completely fabricated assertions. It’s a tricky thing to pin down, the PhD is all about how idea A (it can play games really well or chat with your kid) become claim B (it will cure cancer, mitigate climate change) but this article basically shows how big tech is “talking out both sides of its mouth” about these speculative claims by also making a bunch of money selling prospecting tools to fossil fuel companies. I was at an event where I tried to make this self-fulfilling prophecy point to some city leaders:

Microsoft is reportedly planning a $100 billion supercomputer to support the next generations of OpenAI’s technologies; it could require as much energy annually as 4 million American homes. Abandoning all of this would be like the U.S. outlawing cars after designing its entire highway system around them. Therein lies the crux of the problem: In this new generative-AI paradigm, uncertainty reigns over certainty, speculation dominates reality, science defers to faith.

Brian Merchant has also written up a bit on it here.
Ed Zitron on the Subprime AI Crisis. Zitron (who I like reading but can’t listen to) has been tracking the wobbly finances of big tech in AI for a while and frustratedly pointing out all the inherent contradictions and problems. Zitron extends the usual argument with the specific mechanisms by which AI is sold. One; it’s on you to figure out how to make it useful/valuable (more on this next week) and two: through software as a service that binds you to it. This one gave me real dot-com-bubble vibes. Consume with reporting on underwhelming productivity impacts.
Wes has finally released his Stories from AI-Free Futures. He’s been working really hard on getting this album together as a continuation of Newly Forgotten Technologies which I would broadly describe as ‘specualtion on what comes after AI.’ Please do check them out.
Paul Graham Raven interviewing George Voss here. Part 2 is now out as well.
Apple did another launch which is a great excuse to remember how underwhelming things are. (I would 100% get a Mac Mini though, I really always liked them)
Meta/Facebook is returning to its roots of assessing strangers through computers.

Listening

Still on my K-Pop bingeing at the moment. My Spotify wrapped is going to be lopsided.

WordPress seems to have got super slow? I have refreshed my browser a bunch but it’s just got really clunky and delayed since I was last here. Perhaps something to do with all the lawsuits? Anyway I love you and assure you that following a very unpleasant summer I am back to regular programming.

BOX113: There’s No App for Everything

12.09.24

I took 10 days off a computer which was genuinely wild and came back to hundreds of emails, most of which were newsletters and marketing so I’ve been on one of my periodic unsubscribe binges and being pretty brutal about whether I’ve actually ever read a newsletter and if not, delete. I mostly read aggregating things because I just want the bottom like quick, not thousands of words of hot reckons – I save my PhD time for that kind of reading. Nonetheless here I am scribing out a few hundred words of hot reckons.

I am sort of constantly side-eyeing the app that I want to help me organise my brain but I’m not sure it exists. I never look at the Twitter or Threads feed (just post there) so most things come through the 50 or so newsletters I’m subscribed to. Between other things I scroll through these and, similar to books, have a pretty hard ‘I’m not obligated to read this’ rule e.g. if it’s not grabbing me; skip it.

If it does grab me, then the filing begins. For anything PhD-relevant, e.g. papers and journal articles, it gets downloaded and added to Zotero where it can be read, tagged and annotated properly. I try and read 1-3 things in Zotero a day to keep on top of it. Any pertinent quotes or ideas are dragged out and dumped in Scrivener for later sorting as part of the PhD process as described previously.

Then there might be stuff that’s more transportable or mutable or work-relevant; resources, signals or reckons which all get put into Raindrop via the bookmark bar applet. Resources are lists, maps, toolsets, kits of.. whatever that might be useful one day. Reckons I’ve been less good at looking after because there’s so many of them and they don’t tend to have much staying power but any long-form essays or articles. Finally, signals should be broadly familiar to people; little snippets of change or interesting things that are worth keeping hold of. These actually get used a lot for work.

Regardless, I have another applet that I wrote myself that will quote whatever I’ve selected to post to a tweet which I then copy to the Meta one which is about my only interaction with them and I do more as a sort of ‘I’m still alive’ to the Internet. The thing is, this is such a perfectly honed workflow for my reading and research that I’m not sure what I’m looking for or even if there’s a problem – how would I know if I’m missing or forgetting things? People recommend things and new ways of working and things pop up all the time that I scroll through. Like the ‘obsidian method‘ looks great but then does it just take up more time to learn a new way of doing things any maybe my way of doing things is fine? My issue isn’t organising methods its the time to do everything. And maybe friction is good?

Upcoming

A lot of things. I saw a thing about how taking on lots of bits and bobs is a sign of low stimulation which is something I probably need to do some more should searching with. But, presented for your consideration:

HCID conference 2024 – 18th September, London. With absolute heroes and legends Laura Forlano, Sara Heitlinger and Paulina Yurman amongst others. There should be a word for when you suddenly find yourself platformed with people you’ve looked up to your whole career but feel massive inferiority next to. I’ll be wittering on about design and futures and all you ahve to do is sit through that to get to the good stuff. 18th September
Wherever, Whenever Festival – 22 October, Cologne. This looks huuuuuuge. I love chatting with Rob who is the organiser of this shindig and a super lovely guy. I’m going to be looking at five speculative future of work scenarios. Then getting a train up to Eindhoven for:
Design and AI Symposium at Dutch Design Week – 22/23 October, Eindhoven. I think I’m doing something both days. Both a keynote thing and a panel chat on a different day. More folks I’m a big fan of at the event but I don’t think the full programme is released yet. I’m really looking forward to this one. Should be similar to the amazing panel we did in 2022.

Reading

How to Raise your Artificial Intelligence. I’m a huge fan of Melanie Mitchell and Alison Gopnik’s work and this light-tough chat seems to brush over most of their theories. It may have even been Mitchell’s ‘Why AI is Harder Than We Think‘ that firmed up my PhD thinking a few years ago with a sort of ‘ok, then why do people keep going on about it?’ This interview with them both seeks to redirect attention away form hysterical men talking about the end of the world or enormous profit and towards the still worrying but likely outcomes. Bonus points as well for pointing out that we already have a technology that kills millions of people each year; the car.
Poking Holes in Reality with Prototypes from Libby Miller references some amazing practices, including Strange Telemetry work but is essentially about how shonky, half-finished, sketchy prototypes challenge the inevitbailism of Silicon Valley technological visions.
The Politics of Scaling from Sebastian Pfotenhauer, Brice Laurent, Kyriaki Papageorgiou, and Jack Stilgoe. Yes this is once again going to start being more of a PhD blog and on my reading list was this paper on why and how scaling has become the normative political and economic imperative of social and political change, driven by technology.
The Simple Macroeconomics of AI by Daron Acemoglu landed a few months ago but I only just got to reading through it. Well, reading through the bits that aren’t dense economic calculations. It basically says productivity gains aren’t that great because it’s either automating things that were already automated to some degree, that the ease of integration for contextually complex tasks is overstated and AI can’t theoretically exceed human productivity on ‘hard tasks’ (like diagnosis) because it can only be trained on human historic performance and finally that the costs of fighting ‘bad AI’ (like crime and social media manipulation) dig deep into productivity gains. Finally he basically says ‘if you really want AI to have an (arguably) positive impact on society and economy then focus on making it good and reliable rather than messing around with sci-fi fantasies of human-like intelligence:’

To put it simply, it remains an open question whether we need foundation models (or the current kind of LLMs) that can engage in human-like conversations and write Shakespearean sonnets if what we want is reliable information useful for educators, healthcare professionals, electricians, plumbers and other craft workers.
AI Scaling Myths from the AI Snake Oil substack has some useful data to point to in the ongoing debate about pumping more data at LLMs to make them ‘better.’ What’s interesting about it is they quite succinctly identify two collective myths that AI people hold to be true. One is that ’emergence’ (surprising new behaviour, novelty, gestalt; e.g. do things not in the training data or infer) is a product of more and more data. I’m not sure on this one because I don’t understand the science but there’s essentially two sides as to whether you believe an LLM can surpass its training data or not. Logically I’d say not but AI people are banking on it. The second one is this idea that that benchmark capability is equal to social usefulness. This one is a pretty obvious no from me and a lot of my PhD is about trying to pull this one apart. There’s a sort of baked in assumption that with enough power and novelty, mass AI adoption and social change is inevitable which is just a fundamental misunderstanding of how the world works. This is why AI people spend so much time talking about power and only vaguely hand wave at what their AI is actually for.
Contraption Theory, Venkatash Rao’s love letter to helicopters explores the typology of ‘contraptions’ – objects of enormous complexity and highly limited design variability that defy the tendency to simplify or variegate through design because of their ‘One Weird Trick.’ Arguably, my first ever talk that I did at an event while an undergrad was about a similar thing but I think I called it ‘Designs that Don’t Make Sense’ and talked about tourbillons (we have digital watches now), the SR71 (a plane that barely flies made out of Russian titanium) and the Concorde (a giant stonking battleship at the end of battleships). I guess the point of all of those is that they’re more political or social objects than practical ones.

Listening

I listen to a lot of K and J-pop because it’s beaty, catchy, vibey and I can’t understand the lyrics so I’m not distracted. It’s that or techno or metal but at the moment I’m enjoying the good vibes.

Jeon Somi, Ice Cream (I have a real thing for like rising bridge-chorus things I think)

Alright that’s about it. Another brief one with no big hot reckons but I’m sluggish. Love you, speak later.

BOX112: WHERE WE’VE BEEN WE DIDN’T NEED ROADS

21.08.24

I suppose there’s no excuse for the delay in missives. Things got busy and intense and I had to stop for a bit. Back in March I was getting back to PhD work, a few weeks later I had to put that aside as work got too intense and I had to focus up. Then on Friday I was at an event and, following a nip out for a call, caught the end of Alex’s bit where she said something like ‘blog, just blog’ and I sort of internally sighed and said ‘ok’ to no one in particular.

I am constantly trying to find ways to squeeze the most out of the time in the day but tend to shirk ‘productivity hacks.’ I enjoy doing the work and spending time with things there’s just never enough time so I’ve found rhythm really important – regular beats of physical and mental exercise that refresh the flesh machine. I suppose everyone is different: A post from Jay was about the pressure to produce weekly and he talked about some interesting folks that publish when they feel like it without regard for the algorithm and then there of course is Matt’s advice is to publish when it feels right (which for him is multiple times a week, usually at night).

But I like and rely on rhythms, beats, deadliness and regulation to know what I’m doing moment-to-moment and I think I’d felt ‘I’ll get back to the blog when I have something to say.’ But instead, I just went around saying those things because sitting down to write is a more strenuous process. But that’s sort of the point; putting effort into forming up thoughts and properly reflecting has always been really important and has benefits over time so here we are again. All that said, don’t expect big hot reckons today. I’m just reactivating all these muscles and stretching and yawning. And absolutely do not expect renders right away. Instead, this post contains bits and pieces from the last few months.

LinkedIn is for Boats

A few years ago, amidst the furore over Cambridge Analytica, PRISM and the creeping idea that maybe this whole social media thing was really potentially not very good over all, a new outfit called Ello briefly popped up which the design/futures/art/tech community gleefully hopped on for a few weeks. The premise was simple – no ads, no tracking – but this was before that sort of thing raised suspicions that one day they would start to figure out a way to extract money from you through subscriptions or similar.

Anyway, Ello had a bunch of curious features in its beautiful simplicity such as only being able to integrate the bread and whale emojis instead of like thumbs and hearts which thus became stand-ins (🍞🍞🍞 = very good, for instance) but the whole thing was like busting down the door to a massive empty warehouse with your friends, looking around and wondering ‘…what is this for? What are we supposed to do with it?‘ A sager group of people might have considered that this heralded the end of social media, that without the cajoling and prodding to force interaction, we were kind of fine just hanging out and talking and maybe should have disbanded. But Ello had a very particular design feature; a full-width feed. Yes, instead of a narrow vertical scroll, it had a full-width scroll like an old forum and so… Ello was for boats. Or more accurately, pictures of boats because the aspect ratio of the scroll suited boats.

I was talking with friends the other night (mostly from academia) about how increasingly resigned they are to accepting that LinkedIn is now all that’s left and that’s sort of sad but I think the reason it remains is because LinkedIn is actually for something. Sure, that thing is humiliating self-promotion but at least it has a purpose while the rest of them are sort of just ‘places’ or ‘communities’ in a busy, noisy world.

The fediverse is too complex and fractured to really resuscitate the feeling of early Twitter and the Meta stable are all horrifically over-engineered advertising psyops so really all that’s left is the blue jobs website. When I left academia, well I don’t mind telling you, I was shook by the seriousness with which LinkedIn is taken having spent years understanding it as this strange little interactive CV that you might update once a year while getting in rolling arguments over on Twitter. But while all these others are scrabbling around trying to figure out what they’re for (Instagram is for ~~photos~~, ~~videos~~, ~~reels~~, ~~storie~~s, ~~rooms~~, ~~voice notes~~, ~~calls~~, spaces) LinkedIn is just for hustle. LinkedIn isn’t a network, it’s a service; sometimes literally serving you jobs, sometimes serving your ego. The vast majority of people aren’t going to LinkedIn for lifelong, deep, intellectually and spiritually enriching community engagement: You just take something you did, dress it up as some massive revelatory experience, tag a bunch of folks, lob it over the wall and move on with your life. Everyone’s doing the same so no one finds it particularly obnoxious anyway.

In the post-Muskian Twitter period, there was this frenetic squabbling over where this massive community would relocate, to various decentralised platforms that require a lot of active engagement and push to make work. Maybe that brief period of parasocial relationships with strangers on the Internet is over and that’s just fine. Maybe a super transactional, collective fiction where we treat the platform as a service rather than a community is healthier anyway.

Recents

Malina and I ran a second session on Speculative Design for Milan Politech’s service design executive masterclass. This time we took them through a whole futures and speculative design process from beginning to end, starting with working with trends, to scenarios, to worldbuilding to designing things from that world that they then performed back to the group in diegetic livestreams, court cases and adverts. It’ revealing how tight 7 or 8 hours is to get that stuff across to folks but they really gave it their all to get into it.
I did an interview for Design Decode over the last few weeks. A couple of friends have also been featured recently, Michela who puts it all together is an incredible and diligent researcher and a thoughtful interviewer. Having the questions weeks in advance and such well-crafted ones meant I probably massively over thought it but anyway, you can go there for similar thoughts to what you might get here but perhaps more concise.
A piece I wrote for Towards the Realm of Materiality on the interface from Minority Report has been published. The book invited various authors to explore the ficitonal technologies of Philip K. Dick. I wrote about how it serves as a sort of incarnation of computational imaginaries up to that point (2001) and has perversely incentivised the development of computational technology since. Twenty-three years later, we are still trying to build things from Minority Report. Julian also invited me back on the Near Future Laboratory podcast to talk about it briefly.

Reading

Our friend Paul Graham Raven has been turning his hand to content. Here’s the first bit of content on living with the mess of contradictory but equally true theories and resist the urge to eliminate one or the other. In the case of the titular theory; is doomscrolling causing a decline in mental health or is a decline in mental health causing more doomscrolling. Why not both?
I read this article on AI becoming a technology of faith. There’s nothing surprising in there but it articulates how grandiose promises are used to obfuscate current failures, in this case a promise of a smart health assistant based on technology that makes stuff up. The telling part though, which is not unusual is when the writer brings up Sam Altman on the risks posed by such intimate health data being potentially accessible to employers:

Huffington suggested that Thrive’s AI platform would be “available through every possible mode,” that “it could be through your workplace, like Microsoft Teams or Slack.” This led me to propose a hypothetical scenario in which a company collects this information and stores it inappropriately or uses it against employees. What safeguards might the company apply then? Altman’s rebuttal was philosophical. “Maybe society will decide there’s some version of AI privilege,” he said.

Which sort of summarises another aspect of this hubris; ‘It’s not my fault if my ideas cause harm, that’s society’s problem.’
Ok I didn’t capture any other reading. For your info I tend to ‘tweet’ things I read as I read them here (ew) and here (sigh) but also bookmark things here.

Listening

Aespa – Armageddon, The 1st Album

Ok, sorry it’s been so long. Sometimes feels like that’s all life is – stumbling along, tripping and apologising profusely even as no one actually cares that much. Sonder. Love you.