Personas are often toothless, but these accessibility personas from gov.uk are more practical and useful than most:
Each profile has a different simulation of their persona’s condition and runs the assistive technology they use to help them.
You can use these profiles to experience the web from the perspective of the personas and gain more understanding of accessibility issues.
I wish more publishers and services took this approach to evaluating technology:
We scrutinize third-party services before including them in our articles or elsewhere on our site. Many include trackers or analytics that would collect data on our readers. These may be standard across much of the web, but we don’t use them.
This short story feels like a prequel to Maneki Neko.
- Start with mostly static HTML.
- Progressively enhance the dynamic parts.
- Pick small, focused tools.
LLMs have never experienced anything. They are just programs that have ingested unimaginable amounts of text. LLMs might do a great job at describing the sensation of being drunk, but this is only because they have read a lot of descriptions of being drunk. They have not, and cannot, experience it themselves. They have no purpose other than to produce the best response to the prompt you give them.
This doesn’t mean they aren’t impressive (they are) or that they can’t be useful (they are). And I truly believe we are at a watershed moment in technology. But let’s not confuse these genuine achievements with “true AI.”
Coincidentally, I was just talking about hammers and nails in another context.
Progressive enhancement used to be a standard approach. Then React came along and didn’t support that approach. So, folks stopped talking about that and focused entirely on JS-centric client solutions. A few years later and now folks are talking about progressive enhancement again, under the new name of “islands”.
What is going on here?
It turns out, it’s the same old thing. Vendors peddling their wares. When Facebook introduced React, that act transformed the font-end space into a hype-driven, cult-of-personality disaster zone where folks could profit from creating the right image and narrative. I observed that it particularly preyed on the massive influx of young web developers. Facebook had finally found the silver bullet of Web Development, or so they claimed! Just adopt our tech, no questions asked, and you too can be a rock star making six figures! We’ve been living through this mess for ten years now.
The cosmic ballet goes on.
I’m sure you’ve heard the law of the instrument: when all you have is a hammer, everything looks like a nail.
There’s another side to it. If you’re selling hammers, you’ll depict a world full of nails.
Recent hammers include cryptobollocks and virtual reality. It wasn’t enough for blockchains and the metaverse to be potentially useful for some situations; they staked their reputations on being utterly transformative, disrupting absolutely every facet of life.
This kind of hype is a terrible strategy in the long-term. But if you can convince enough people in the short term, you can make a killing on the stock market. In truth, the technology itself is superfluous. It’s the hype that matters. And if the hype is over-inflated enough, you can even get your critics to do your work for you, broadcasting their fears about these supposedly world-changing technologies.
You’d think we’d learn. If an industry cries wolf enough times, surely we’d become less trusting of extraordinary claims. But the tech industry continues to cry wolf—or rather, “hammer!”—at regular intervals.
The latest hammer is machine learning, usually—incorrectly—referred to as Artificial Intelligence. What makes this hype cycle particularly infuriating is that there are genuine use cases. There are some nails for this hammer. They’re just not as plentiful as the breathless hype—both positive and negative—would have you believe.
When I was hosting the DiBi conference last week, there was a little section on generative “AI” tools. Matt Garbutt covered the visual side, demoing tools like Midjourney. Scott Salisbury covered the text side, showing how you can generate code. Afterwards we had a panel discussion.
During the panel I asked some fairly straightforward questions that nobody could answer. Who owns the input (the data used by these generative tools)? Who owns the output?
On the whole, it stayed quite grounded and mercifully free of hyperbole. Both speakers were treating the current crop of technologies as tools. Everyone agreed we were on the hype cycle, probably the peak of inflated expectations, looking forward to reaching the plateau of productivity.
Scott explicitly warned people off using generative tools for production code. His advice was to stick to side projects for now.
Matt took a closer look at where these tools could fit into your day-to-day design work. Mostly it was pretty sensible, except when he suggested that there could be any merit to using these tools as a replacement for user testing. That’s a terrible idea. A classic hammer/nail mismatch.
I think I moderated the panel reasonably well, but I have one regret. I wish I had first read Baldur Bjarnason’s new book, The Intelligence Illusion. I started reading it on the train journey back from Edinburgh but it would have been perfect for the panel.
The Intelligence Illusion is very level-headed. It is neither pro- nor anti-AI. Instead it takes a pragmatic look at both the benefits and the risks of using these tools in your business.
It has excellent advice for spotting genuine nails. For example:
Generative AI has impressive capabilities for converting and modifying seemingly unstructured data, such as prose, images, and audio. Using these tools for this purpose has less copyright risk, fewer legal risks, and is less error prone than using it to generate original output.
Think about transcripts of videos or podcasts—an excellent use of this technology. As Baldur puts it:
The safest and, probably, the most productive way to use generative AI is to not use it as generative AI. Instead, use it to explain, convert, or modify.
He also says:
Prefer internal tools over externally-facing chatbots.
That chimes with what I’ve been seeing. The most interesting uses of this technology that I’ve seen involve a constrained dataset. Like the way Luke trained a language model on his own content to create a useful chat interface.
Anyway, The Intelligence Illusion is full of practical down-to-earth advice based on plenty of research backed up with copious citations. I’m only halfway through it and it’s already helped me separate the hype from the reality.
Google has a serious AI problem. That problem isn’t “how to integrate AI into Google products?” That problem is “how to exclude AI-generated nonsense from Google products?”
Bosses have certain goals, but don’t want to be blamed for doing what’s necessary to achieve those goals; by hiring consultants, management can say that they were just following independent, expert advice. Even in its current rudimentary form, A.I. has become a way for a company to evade responsibility by saying that it’s just doing what “the algorithm” says, even though it was the company that commissioned the algorithm in the first place.
Once again, absolutely spot-on analysis from Ted Chiang.
I’m not very convinced by claims that A.I. poses a danger to humanity because it might develop goals of its own and prevent us from turning it off. However, I do think that A.I. is dangerous inasmuch as it increases the power of capitalism. The doomsday scenario is not a manufacturing A.I. transforming the entire planet into paper clips, as one famous thought experiment has imagined. It’s A.I.-supercharged corporations destroying the environment and the working class in their pursuit of shareholder value. Capitalism is the machine that will do whatever it takes to prevent us from turning it off, and the most successful weapon in its arsenal has been its campaign to prevent us from considering any alternatives.
Whether consciously or not, AI manufacturers have decided to prioritise plausibility over accuracy. It means AI systems are impressive, but in a world plagued by conspiracy and disinformation this decision only deepens the problem.
Maggie Appleton:
An exploration of the problems and possible futures of flooding the web with generative AI content.
Google is a portal to the web. Google is an amazing tool for finding relevant websites to go to. That was useful when it was made, and it’s nothing but grown in usefulness. Google should be encouraging and fighting for the open web. But now they’re like, actually we’re just going to suck up your website, put it in a blender with all other websites, and spit out word smoothies for people instead of sending them to your website. Instead.
I concur with Chris’s assessment:
I just think it’s fuckin’ rude.
This anthology of Steve Jobs interviews, announcements and emails is available to read for free as a nicely typeset web book.
Writing, both code and prose, for me, is both an end product and an end in itself. I don’t want to automate away the things that give me joy.
And that is something that I’m more and more aware of as I get older – sources of joy. It’s good to diversify them, to keep track of them, because it’s way too easy to run out. Or to end up with just one, and then lose it.
The thing about luddites is that they make good punchlines, but they were all people.
I feel like there’s a connection here between what Kevin Kelly is describing and what I wrote about guessing (though I think he might be conflating consciousness with intelligence).
This, by the way, is also true of immersive “virtual reality” environments. Instead of trying to accurately recreate real-world places like meeting rooms, we should be leaning into the hallucinatory power of a technology that can generate dream-like situations where the pleasure comes from relinquishing control.
The story that “artificial intelligence” tells is a smoke screen. But smoke offers only temporary cover. It fades if it isn’t replenished.
You know how when you’re on hold to any customer service line you hear a message that thanks you for calling and claims your call is important to them. The message always includes a disclaimer about calls possibly being recorded “for training purposes.”
Nobody expects that any training is ever actually going to happen—surely we would see some improvement if that kind of iterative feedback loop were actually in place. But we most certainly want to know that a call might be recorded. Recording a call without disclosure would be unethical and illegal.
Consider chatbots.
If you’re having a text-based (or maybe even voice-based) interaction with a customer service representative that doesn’t disclose its output is the result of large language models, that too would be unethical. But, at the present moment in time, it would be perfectly legal.
That needs to change.
I suspect the necessary legislation will pass in Europe first. We’ll see if the USA follows.
In a way, this goes back to my obsession with seamful design. With something as inherently varied as the output of large language models, it’s vital that people have some way of evaluating what they’re told. I believe we should be able to see as much of the plumbing as possible.
The bare minimum amount of transparency is revealing that a machine is in the loop.
This shouldn’t be a controversial take. But I guarantee we’ll see resistance from tech companies trying to sell their “AI” tools as seamless, indistinguishable drop-in replacements for human workers.
A profile of the Xerox Alto and the people behind it.
A great piece by James, adapted from the new edition of his book New Dark Age.
The lesson of the current wave of “artificial” “intelligence”, I feel, is that intelligence is a poor thing when it is imagined by corporations. If your view of the world is one in which profit maximisation is the king of virtues, and all things shall be held to the standard of shareholder value, then of course your artistic, imaginative, aesthetic and emotional expressions will be woefully impoverished. We deserve better from the tools we use, the media we consume and the communities we live within, and we will only get what we deserve when we are capable of participating in them fully. And don’t be intimidated by them either – they’re really not that complicated. As the science-fiction legend Ursula K Le Guin wrote: “Technology is what we can learn to do.”