Potential

The other day I was driving my daughter to swimming. She was playing Pokemon Go on my phone and duly informed me that she had ‘swiped away’ a message from her mum. I tapped on the messages icon on my car’s display and tapped on my wife’s name. Siri told me I had two messages from my wife and asked if I wanted to hear them. I said yes. It read them out and asked if I wanted to reply. Again I said yes, then when prompted I dictated a message. It read the message back to me and asked if I wanted to send it. Once I agreed, the message was sent. This entire interaction was conducted by my phone whilst my daughter continued to play Pokemon Go on it. Granted my interactions were via CarPlay, but that is simply a secondary portal to my phone, all actions and interactions were managed by my phone whilst my daughter continued to use it for an entirely different purpose.

I relate this fairly mundane tale because in many ways it is awesome. Smartphones are incredibly powerful computers that sit in our pockets or our hands and let us have freedom and control of our lives in ways that were barely imaginable when I was my daughter’s age. For me this is exactly the kind of thing technology should be doing: allowing me to drive, stay in touch with my wife and entertain my kid all at the same time. The other reason I relate this is because I’m not sure what difference adding generative AI into the process would make. I guess it could offer suggested content for my message to my wife, but how much time is that likely to save me? I’d still have to select one of the options from the prompts it gave me, saving no time at all vs dictating my message. It certainly couldn’t drive the car for me whilst I text my wife back. Maybe I’m being unfair, or maybe I’m just unimaginative, but this is exactly the sort of area I would think that people who say generative AI is the future would suggest it will make a difference. The problem is it feels to me like in so many areas that difference has already been made.

Take ordering dinner. We’re constantly told that generative AI will make this easier. It will look in our fridge and tell us what we can make for dinner. Or ask us what we want, order the ingredients for us and give us a recipe when the ingredients show up. Or even somehow know what we usually like on a day like this and order it for us. Personally only the first two of those sound vaguely desirable to me and actually some combination of both would be preferable. Although I like going to buy my own ingredients and I’m not sure how much I’d be willing to pay for the recipe service when I can just plonk the contents of my fridge into Google and get recipes for free.

I recently bought a new phone for the first time in five years. The difference between this phone and my last one is notable, but not radical, probably mainly because they both ran the same operating system. Over the five years that I owned my last phone there were probably significant, if incremental improvements in the capabilities of that operating system every year. Elements of what used to be called AI will have been introduced and enhanced in things like the phone’s text prediction, voice recognition and image synthesiser (or camera as it’s more commonly known). Adding generative AI to these things can only make a further incremental improvement to them, equivalent at best to a full version upgrade of iOS*. I’d be interested to understand how much Apple spend on IOS development a year and ditto Google, Samsung, et al on Android. I suspect it is significantly less than is currently being poured into generative AI. To be clear that investment is estimated to be around $400 billion this year. This is justified by saying that generative AI specifically will revolutionise every aspect of our lives, yet we are presented with very few concrete examples of how. If there was an iPhone-like platform on which people could build apps, I could see how an ecosystem could form, but the financial models don’t work because that ‘platform’ (such as it is) doesn’t make any profit. In fact it makes billions of dollars of losses. People will point to Amazon or Uber and say that they lost money for years before they made a profit and that is true, but those companies’ costs decreased with scale, which is not the case with generative AI. OpenAI’s latest model was their most expensive to ‘train’ and costs the company more money per query than the previous model. The infrastructure costs that are being ploughed into AI data centres are not even one off, building the buildings is a fixed cost, but AI data centres run ‘hot’ pretty much all the time, almost literally burning through server hardware constantly. If an AI server lasts three years, it has done really well. All of this capital and infrastructure is being poured into something that is a marginal improvement in UX at best. It’s equivalent to all the biggest companies in America investing all their spare cash into Clippy or Clippy clones. If someone can tell me a functional, chargeable use for generative AI that isn’t either a marginal improvement of UX or an artificially cheap enshittification of a previously human delivered service they’re taking an awfully long time to do so. There was an article in the paper the other day where one of the UN climate directors said that AI was a potential problem, but also that it helped with climate modelling and solutions. The problem is he’s not talking about the same AI. There are specialised machine learning systems trained to model the climate or develop new kinds of medicines or myriad other useful applications, but none of these are the LLMs such as ChatGPT, that are designed as general purpose AI applications and are where the vast majority of the investment is going. In effect generative AI is living off other AI’s glory, almost like it’s some massive con or something. Nothing about generative AI justifies the obscene amounts of money that are currently being poured into it. It is not going to have an iPhone moment because the iPhone already had that. No amount of (extremely vague) input from Jonny Ive is going to change that.

In five years time I’ll probably buy another phone because the technology will have moved on sufficiently by then to warrant an upgrade. Some of those advances will be in what is broadly defined under the umbrella of AI and machine learning, but they will almost certainly have nothing to do with the LLM based generative AI that is where all the money is currently being poured. Honestly if the new features on my phone rely on some vast datacentre somewhere ‘thinking’ about an answer it would probably make me think twice about buying a new phone. I’m still close enough to the EU that I was able to turn off the ‘dumb rainbow’ (Apple Intelligence) in my current phone and I will fight long and hard to keep things that way. This isn’t an anti technology or anti progress stance, it is very much the opposite, I want technological progress that actually improves my life. Enshitification is everywhere in the technology that we are presented wiith, gradually making it harder for us to make technology work for us and easier for technology companies to make us work for them. Generative AI is merely the latest incarnation of this, where there are very few consumer value use cases, but the product has the potential to privatise even more aspects of our lives and then sell them back to us in a shitty format, at a premium. The only problem I foresee for generative AI is that in order to properly enshittify, a technology needs to be appealing and useful in the first place. If it starts off shit there really isn’t anywhere to go. Yet the tech giants continue to pour billions of dollars into building out the infrastructure that only really works for this specific technology (AI data centres are not fit for general purpose computing applications). How does this end well? It doesn’t, but even before the catastrophe unfolds we can start to think about what the alternatives could and should be.

I propose a new approach to technology. No more ‘democratising’, no more ‘disrupting’ and no more ‘paradigm shifts’. Technology should be a thing that improves gradually with the needs of its users. If necessity is going to continue to be the mother of invention, it should be the user’s necessity to do something useful, not the necessity of a massive corporation to make ever more profit (or in the case of the AI companies, attract ever greater investment). We need to find a way to identify technology that is genuinely useful and genuinely consumer focussed. Not as easy as it sounds. Earlier today I was reading a thread about how Corey Doctorow posts long threads on Mastodon. When someone pointed out that if you want to read Doctorow’s long threads as a single ‘article’ you can just add a filter, I thought “that’s a bit of a faff, not sure I can be bothered.” If I can’t be bothered to take steps to make technology work for me, what is the likelihood that someone less engaged is likely to? Maybe we get the technology we deserve and if we can’t be bothered to make a little effort in configuring our technology, then we get configured by it. It’s not like AI actually understands us or does what we want without us learning how to do the prompts ‘right’. The grief of setup and learning a new interface is not removed, it is just presented as an opportunity, rather than a burden. If we understand this, then maybe we can think a bit more about what that setup and interaction results in, what we expect from a technology and if we need it at all. You would think that after crypto, the metaverse and AI, we’d all be wary of technology companies telling us they’ve seen the future and we just don’t get it yet. Let’s hope next time we learn, let’s hope that people start to judge for themselves whether they need a technology or not. Some hope when there’s every chance they’ll have given away their last scrap of agency to generative AI.

*however, given the nature of generative AI, that it is impossible to predict an absolute outcome from it, the chances are that adding it will in some cases make the outcome worse or less reliable.

Polish

“Have you ever heard the sound of disappointment?”

I’m fully aware of how utterly cool this isn’t, but the other day I wanted to listen to a song from my childhood that felt apposite for the moment. What I didn’t realise was how self-referentially appropriate it would be. The song was “Here Comes That Sinking Feeling” from the 1985 album “Be Yourself Tonight” by Eurythmics. I hadn’t heard it for a long time and in my memory it was a snarling growling piece of music, like something hocked up from the back of the throat and spat out in one go. So imagine my surprise when the guitar kicked in and I was greeted by a slightly limp, quite gentle pop album track. Annie Lennox started singing “Have you ever heard the sound of disappointment?” I knew exactly what she meant, I was listening to it right there and then. I understand that our memories can distort or enhance things, music production has moved on a lot in the last 40 years and my expectations of the sound of a track have probably changed accordingly. But it still felt off to me, until I checked the album details: “Be Yourself Tonight (2018 Remaster)”. That last little addition to the title said it all: this wasn’t the track I wanted to hear, but a simulacrum of it reproduced (presumably) from the original masters, probably in order to make the album more ‘suitable’ to digital media, streaming and downloads.

When I first encountered this kind of digital disappointment, I assumed it was a teething issue. As a pretentious teenage boy in the 90s, Martin Scoursese’s Taxi Driver was obviously one of my touchstone movies. Id watched it many times on tired VHS tapes that I was pretty sure were not giving me the full glory of the original 1976 cinematic release. Consequently I was excited to see that they were going to release a digital remaster of the film and duly bought a copy on release (I’m not sure it had been able to buy on VHS for a while). I think I watched it once only and I may not have watched the film at all since, so instant and complete was my disappointment. Gone was the glamorously grimy 70s New York and instead something that looked like a tidy film set (which is weird because I’m pretty sure it was actually filmed in New York). Everything was clean and clear (even the grime) and it felt like all the mystery and reality had been airbrushed out along with the glare of the streetlights. Like I say I thought that was just a mistake, teething issue, digital technology was still new and it was understandable if people went a bit too far with it, accidentally smoothing out the rough edges that made a world unique. Even as more disappointing examples presented themselves, I would excuse it. It’s early days for digitisation I would keep telling myself.

The passage of time proved me wrong. Time and again a digital rendering or remaster of a previously analogue film or piece of music was flatter, duller and in some cases just plain bad. I tried to listen to the 21st anniversary edition of “HUP” by The Wonder Stuff once and couldn’t get past the first track (“30 Years in the Bathroom”) the intro had been redone, presumably because they couldn’t get clearance for the samples that probably no one even thought to clear the first time round, because hey, it was the 90s and who cared if you used 2 seconds of audio from some film. I could excuse that, no one wants to get sued, but then the music started and there was a whole guitar line seemingly missing from the mix. It might still be there, buried, but in the original it was front and centre, a staccato attack driving the song, making it slightly confrontational in a jaunty way. Without it the whole thing is a kind of limpid apologetic indie jangle that lollops along with no real purpose. I didn’t get much further before turning it off and going in search of a copy of the original recording on YouTube.

I realise all of this can very easily be dismissed as the purist rantings of a grumpy (nearly) old man, who thinks everything was better in the 90s when no one had mobile phones and we all had to talk to each other, blah blah, but it’s not just that. Firstly, I love technology and I hate talking to people, the internet and modern communications technology in general have made life easier for people like me. Whilst I’ve previously written on the need for personal communications to assist in empathy and understanding, I am not saying you should never send a text or a WhatsApp message. That stuff is super useful. But also this is actually important, and it isn’t just about being a geek or a purist. The main driver for all of those remasters or special editions is to make them fit a new reality, a digital one. It might be presented as a special anniversary edition, but the main driver for that edition is that the original doesn’t translate well to a digital format and so a new version needs to be created if the owner of the work (the record label or film studio, not the musician, writer or director) is to realise a return from that product on digital (streaming) platforms. This is presented to us as a win win, because we can get all of the things we love in one place at any time of the day or night. Except of course we can’t. I can’t get the original master of “Loveless” by My Bloody Valentine, the one that nearly bankrupted Creation Records, on Apple Music. I can get a digital remaster that took even longer to complete. It is not the same thing, it is good, but it is not the same thing. And I don’t have a choice in that. If I want the convenience, I have to listen to the remaster, I can’t choose to find out how the original sounds pushed straight to 32bit digital compression. I suspect it sounds dreadful but I’m not allowed to find out. Obviously this gives the lie to the idea that modern digital audio is ‘lossless’, because if it was there’d be no need to remaster original recordings, you could just push them directly to ‘lossless’ digital audio formats. Maybe this is now possible and you just don’t see it because all of the most valuable films and albums have already been converted to a digital friendly version at the time of earlier lossy digital formats. The damage has already been done, why waste money undoing it?

So some old music doesn’t sound as good to old people, so what? The problem is that this is a model that is universalised as we push everything into the digital realm. A digital representation of any thing is just that, a representation, it is not the thing itself. It is like taking a colour photocopy of the Mona Lisa and hanging that in the Louvre. It’s the same picture right? What’s the problem? Maybe nothing. But what if we’re photocopying emotions? I was in a meeting the other day when a potential vendor told me they could offer enhanced sentiment analysis of their AI chatbot’s interactions. I didn’t laugh out loud because that would be unfair. I’m sure in the majority of cases their sentiment analysis would be in the right ballpark, but if you’re outside that majority, the chances are the AI isn’t going to get you. If you’re neurodivergent for example, the sentiment analysis is almost certainly going to miss categorise your mood, as, by definition, you’re outside the mean.

As a person of a certain age, the YouTube algorithm has decided to endlessly serve me irritating adverts that tell me I’m using ChatGPT all wrong. These are of course incorrect, I’m using ChatGPT the right way: not at all. Nevertheless I’m told that I just use it for search (I don’t because I’m only interested in finding websites that actually exist) and that young people are using it to build businesses and make millions by using it the ‘right’ way (there is no evidence to support this). The problem with these adverts* is that they somewhat undermine the claims about generative AI, namely that it understands what you want. The USP of generative AI is supposed to be that you just tell it what you need in your own words and it will be able to produce exactly what you want. Yet when anyone complains about the fact that this rarely happens first time, regular users of these tools will scoff at them and tell them that they’re not doing it right. They will then launch into an explanation about some convoluted process that gets them great results from ChatGPT. This will always involve doing effectively the same thing multiple times and will usually include suggestions for optimising your prompts. In other words it doesn’t understand you, or do what you want, it has an arcane system of trial, error and manipulation that may eventually get you what you want**. This doesn’t sound like the computer doing my bidding, it sounds almost completely the opposite to me. Once again we are expected to gloss over the changes to our lives in order to receive the ‘benefit’ of the digitisation and commercial exploitation of aspects of our culture. With generative AI the idea is that this is as much all consuming as possible - all culture, all art, all writing, - but it isn’t actually and that’s the problem. It’s a lot of all those things, but not everything, and by not being everything, it can only ever be the digital remaster. The most palatable, most average version with all the rough edges, all real life interest, all character smoothed out.

People are rediscovering vinyl and with good reason in my opinion. It isn’t perfect, but nothing is and nor should it be. A lack of perfection is what makes vinyl records interesting, and it isn’t just music, but all sorts of media are being rediscovered in their non-digital form. As people like Brian Merchant have pointed out, the tech elite think that removing all friction from life should be the goal of technology, when in reality it is the friction that is what makes life interesting. Friction is not the same as conflict. Friction is what happens when you have a conversation with someone that you disagree with, conflict is what happens when all friction has been smoothed out by technology and you are presented with a simplified version of their opinions that you can easily dismiss as wrong. The ultimate end of all this is a life where you are free from challenges and everything is ‘easy’ as long as you are happy to be given what is available from the machine rather than what you actually want. The goal of all advertising, marketing and now the ‘training’ of AI (ir the AI training you, not the other way round) is to convince you that everything you want can be defined by the machine, that to want anything outside the bounds of the digitised, simplified list of limited options available from the machine is abnormal. The worrying trends towards labelling and othering people outside of a very clearly defined norm that is evident in the tech aligned rightwing governments is another aspect of this. Difference, whether cultural, political, racial or neurological is inconvenient to the technology and abhorrent to the ideology. Fortunately for the ideologues, the technology precludes the diversity they abhor, and it continually trains its users to only think about the options available from the machine and consider all other options as weird, uncool or subversive. Generative AI goes one step further in that it decides what you want for you, because actually you tell it what you need and it decides what you want or like. For example if you are a student and you tell ChatGPT that you need an essay on the Third Reich, ultimately if you don’t check what it writes for you, it decides whether you think nazis are great or not. Outsourcing our lives to computers means they decide what we get, based on the limited options defined by their owners, and this is the problem with AI, it’s not thinking or giving you its own opinion, it is giving you one of a vast set of answers its owners allowed it to give. There is no scenario where you outsource any part of your life to big tech and you get exactly what you want in return, unless you want exactly the same thing as Big Brother.

My wife noted the other day that wherever you are in the world Gen Z look the same. I mean I suspect there are exceptions to this, and I imagine there have been international homogeneities for many years but I’m pretty sure that they were smaller and less all encompassing when I was in my twenties. To an old [argue whether I’m Gen X or Millennial here] like me, this is a strong indicator that the digital remaster of culture that I saw as a rather disappointing anomaly is actually just culture now. That’s all they’re got. Even if someone thinks up something cool and new and different, it’s a meme before lunchtime. It has been normalised and digitally remastered before it can have an identity that might run counter to prevailing cultural or political norms. But none of this would necessarily concern young people today, as there is a space for them to air their grievances, to be ‘heard’, then tagged as a demographic variant for the sales algorithm and a possible subversive element for the surveillance state, noting the the former might do the early stage analysis for the latter. It will be progressively harder to resist the homogeneity of the digital simulacrum of culture as more and more people grow up with its assumption of all culture or all of society, as an absolute with no alternative. It is important for all of us who know an other reality to speak it, to let people know that there was, is and will be another way of being human and being with other humans. There will be no singularity, not in the sci-fi way of intelligent machines taking over consciousness from humans, but there may be a shitty digital remaster version, where the owners of the machines use them to degrade our intelligence to a point where we think the way they want, look the way they want, experience desire the way they want. The singularity happens in reverse, the machines don’t get more clever than us they make us as dumb as them, happy to hoover up any old slop they sling our way. This is the real future AI promises and it shows how little the titans of technology value human art, human culture, human creativity, humanity itself. They think we should accept the lowest common denominator digital remaster of our lives. How does that sound to you?

“Have you ever heard the sound of disappointment?“

*apart from the fact that they are obviously a scam
**much like any other computer programme