Generative AI: What You Need To Know
Generative AI: What You Need To Know is a free resource that will help you develop an AI-bullshit detector.
You can read all the cards on one page, print them out, or print to PDF.
Generative AI: What You Need To Know is a free resource that will help you develop an AI-bullshit detector.
You can read all the cards on one page, print them out, or print to PDF.
Seven principles for journalism in the age of AI
- Be rigorous with your definitions.
- Predict less, explain more.
- Don’t hype things up.
- Focus on the people building AI systems — and the people affected by its release.
- Offer strategic takes on products.
- Emphasize the tradeoffs involved.
- Remember that nothing is inevitable.
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?”
I woke up today to a very annoying new bug in Firefox. The browser shits the bed in an unpredictable fashion when rounding up single pixel line widths in SVG. That’s quite a problem on The Session where all the sheet music is rendered in SVG. Those thin lines in sheet music are kind of important.
Browser bugs like these are very frustrating. There’s nothing you can do from your side other than filing a bug. The locus of control is very much with the developers of the browser.
Still, the occasional regression in a browser is a price I’m willing to pay for a plurality of rendering engines. Call me old-fashioned but I still value the ecological impact of browser diversity.
That said, I understand the argument for converging on a single rendering engine. I don’t agree with it but I understand it. It’s like this…
Back in the bad old days of the original browser wars, the browser companies just made shit up. That made life a misery for web developers. The Web Standards Project knocked some heads together. Netscape and Microsoft would agree to support standards.
So that’s where the bar was set: browsers agreed to work to the same standards, but competed by having different rendering engines.
There’s an argument to be made for raising that bar: browsers agree to work to the same standards, and have the same shared rendering engine, but compete by innovating in all other areas—the browser chrome, personalisation, privacy, and so on.
Like I said, I understand the argument. I just don’t agree with it.
One reason for zeroing in a single rendering engine is that it’s just too damned hard to create or maintain an entirely different rendering engine now that web standards are incredibly powerful and complex. Only a very large company with very deep pockets can hope to be a rendering engine player. Google. Apple. Heck, even Microsoft threw in the towel and abandoned their rendering engine in favour of Blink and V8.
And yet. Andreas Kling recently wrote about the Ladybird browser. How we’re building a browser when it’s supposed to be impossible:
The ECMAScript, HTML, and CSS specifications today are (for the most part) stellar technical documents whose algorithms can be implemented with considerably less effort and guesswork than in the past.
I’ll be watching that project with interest. Not because I plan to use the brower. I’d just like to see some evidence against the complexity argument.
Meanwhile most other browser projects are building on the raised bar of a shared browser engine. Blisk, Brave, and Arc all use Chromium under the hood.
Arc is the most interesting one. Built by the wonderfully named Browser Company of New York, it’s attempting to inject some fresh thinking into everything outside of the rendering engine.
Experiments like Arc feel like they could have more in common with tools-for-thought software like Obsidian and Roam Research. Those tools build knowledge graphs of connected nodes. A kind of hypertext of ideas. But we’ve already got hypertext tools we use every day: web browsers. It’s just that they don’t do much with the accumulated knowledge of our web browsing. Our browsing history is a boring reverse chronological list instead of a cool-looking knowledge graph or timeline.
For inspiration we can go all the way back to Vannevar Bush’s genuinely seminal 1945 article, As We May Think. Bush imagined device, the Memex, was a direct inspiration on Douglas Engelbart, Ted Nelson, and Tim Berners-Lee.
The article describes a kind of hypertext machine that worked with microfilm. Thanks to Tim Berners-Lee’s World Wide Web, we now have a global digital hypertext system that we access every day through our browsers.
But the article also described the idea of “associative trails”:
Wholly new forms of encyclopedias will appear, ready made with a mesh of associative trails running through them, ready to be dropped into the memex and there amplified.
Our browsing histories are a kind of associative trail. They’re as unique as fingerprints. Even if everyone in the world started on the same URL, our browsing histories would quickly diverge.
Bush imagined that these associative trails could be shared:
The lawyer has at his touch the associated opinions and decisions of his whole experience, and of the experience of friends and authorities.
Heck, making a useful browsing history could be a real skill:
There is a new profession of trail blazers, those who find delight in the task of establishing useful trails through the enormous mass of the common record.
Taking something personal and making it public isn’t a new idea. It was what drove the wave of web 2.0 startups. Before Flickr, your photos were private. Before Delicous, your bookmarks were private. Before Last.fm, what music you were listening to was private.
I’m not saying that we should all make our browsing histories public. That would be a security nightmare. But I am saying there’s a lot of untapped potential in our browsing histories.
Let’s say we keep our browsing histories private, but make better use of them.
From what I’ve seen of large language model tools, the people getting most use of out of them are training them on a specific corpus. Like, “take this book and then answer my questions about the characters and plot” or “take this codebase and then answer my questions about the code.” If you treat these chatbots as calculators for words they can be useful for some tasks.
Large language model tools are getting smaller and more portable. It’s not hard to imagine one getting bundled into a web browser. It feeds on your browsing history. The bigger your browsing history, the more useful it can be.
Except, y’know, for the times when it just make shit up.
Vannevar Bush didn’t predict a Memex that would hallucinate bits of microfilm that didn’t exist.
Every day, a new marketing email, Medium post, or VC who will leave Twitter when they’re cold in a body bag tells us that machine learning (ML, which they call AI because it sounds more expensive) is going to change the way we work. Doesn’t really matter what your job is. ML is going to read, write, code, and paint for us.
Naturally, the excitement around ML has found its way into the design systems community. There’s an apparent natural synergy between ML and design systems. Design systems practitioners are tantalized by the promise of even greater efficiency and scale. We wish a machine would write our docs for us.
We are all, every single one of us, huge fucking nerds.
How do we write, design, and code a link that works for everyone on every device? Let’s dive into the world of creating the perfect link, without making a pig’s breakfast of it.
A handy round-up of recent wrtings on artificial insemination.
This is the flyer that Tim Berners-Lee and Robert Cailliau distributed at the Hypertext 91 Conference—the one where their submission was infamously rejected.
The WWW project merges the techniques of information rerieval and hypertext to make an easy but powerful global information system.
The project is based on the philosophy that much academic information should be freely available to anyone. lt aims to allow information sharing within internationally dispersed teams, and the dissemination of information by support groups.
I’ve spent a lot of time thinking, talking and writing about evaluating technology and what Robin describes here is definitely a bad “code smell” that should ring alarm bells:
What’s really concerning is when everyone is consumed with the technology-first and the problem-last.
Unless you’re working in an R’n’D lab, start with user needs.
I’m certain now that if you want to build something great you have to see through the tech. And that’s really hard to do when this cool new thing is all that anyone is talking about. But that’s why this one specific thing is the hallmark of a great organization; they aren’t distracted by short-lived trends and instead focus on the problem-first. Relentlessly, through the noise.
Manufactured inevitability a.k.a bullshit:
There’s a standard trope that tech evangelists deploy when they talk about the latest fad. It goes something like this:
- Technology XYZ is arriving. It will be incredible for everyone. It is basically inevitable.
- The only thing that can stop it is regulators and/or incumbent industries. If they are so foolish as to stand in its way, then we won’t be rewarded with the glorious future that I am promising.
We can think of this rhetorical move as a Reverse Scooby-Doo. It’s as though Silicon Valley has assumed the role of a Scooby-Doo villain — but decided in this case that he’s actually the hero. (“We would’ve gotten away with it, too, if it wasn’t for those meddling regulators!”)
The critical point is that their faith in the promise of the technology is balanced against a revulsion towards existing institutions. (The future is bright! Unless they make it dim.) If the future doesn’t turn out as predicted, those meddlers are to blame. It builds a safety valve into their model of the future, rendering all predictions unfalsifiable.
I’ve already written about how much I enjoyed hosting Leading Design San Francisco last week.
All the speakers were terrific. Lola’s talk was particularly …um, interesting:
In this talk, Lola will share her adventures in the world of blockchain, the hostility she experienced in her first go-round in 2018, and why she’s chosen to head back to a technology that is going through its largest reputational and social crisis to date.
Wait …I was supposed to stand on stage and introduce a talk that was (at least partly) about blockchain? I have opinions.
As it turned out, Lola warned me that I’d be making an appearance in her talk. She was going to quote that blog post. Before the talk, I asked her how obnoxious I could be about blockchain in her intro. She told me to bring it.
So in the introduction, I deployed all the sarcasm I had in me and said:
Listen, we designers have a tendency to be over-critical of things sometimes. There are all these ideas that we dismiss: phrenology, homeopathy, flat-earthism …blockchain. Haters gonna hate.
I remember somebody asking online a while back, “Why the hate for web3?” And someone I know responded by saying “We hate it because we understand it.” I think there’s a lot of truth to that.
But look, just because blockchains are powering crypto ponzi schemes and N F fucking Ts, it’s worth remembering that it’s also simply a technology. It’s a technological solution in search of a problem.
To be fair, it’s still early days. After all, it’s only been over a decade now.
It’s like the law of instrument says; when all you have is a hammer, everything looks like a nail. Blockchain is like that. Except the hammer is also made of glass.
Anyway, Lola is going to defend the indefensible and talk about blockchain. One thing to keep in mind is this: remember when everyone was talking about “The Cloud”? And then it turned out that you could substitute the phrase “someone else’s server” for “The Cloud?” Well, every time you hear Lola say the word “blockchain”, I’d like you to mentally substitute the phrase “multiple copies of a spreadsheet.”
Please give an open mind and a warm welcome to Lola Oyelayo Pearson!
I got some laughs. I also got lots of gasps and pearl-clutching, as though I were saying something taboo. Welcome to San Francisco.
Lola gave as good as she got. I got a roasting in her talk.
And just to clarify, Lola and I are friends—this was a consensual smackdown.
There was a very serious point to Lola’s talk. Cryptobollocks and other blockchain-powered schemes have historically been very bro-y, and exploitative of non-bro communities. Lola wants to fight that trend.
I get it. But it reminds me a bit of the justifications you hear from people who go to work at Facebook claiming that they can do more good from the inside. Whatever helps you sleep at night.
The crux of Lola’s belief is this: blockchain technology is inevitable, therefore it is uncumbent on us as ethical designers to ensure that the technology is deployed in a way that empowers people instead of exploiting them.
But I take issue with the premise. Blockchain technology is not inevitable. That’s the worst kind of technological determinism. It’s defeatist. It’s a depressing view of “progress” driven not by people, but by technological forces beyond our control.
I refuse to accept that anti-humanist deterministic view.
In any case, for technological determinism to have any validity, there needs to be something to it. At least virtual reality and machine learning are based on some actual technologies. In the case of cryptobollocks, there is no there there. There is nothing except the hype, which is why you’ll see blockchain enthusiasts trying to ride the coattails of trending technologies in a logical fallacy that goes something like this:
Blockchain is bullshit. It isn’t even very clever bullshit. And it certainly isn’t inevitable.
It gives me warm fuzzies to see an indie web building block like
rel="me" getting coverage like this.
AI becomes a stand-in term for whatever technologies and techniques are new, shiny, and just beyond the grasp of our understanding. We use it to gesture at a future we cannot fully comprehend or currently realise. As soon as we do, it will no longer be “AI.”
A terrific piece by Maggie Appleton that starts with a comparison of graphical user interfaces and command line tools—which reminds me of the trade-offs between seamless and seamful design—and then moves into a proposed paradigm for declarative design tools:
Small, scoped areas within a graphical interface that allow users to read and write simple programmes
This chimes with something I’ve been pondering: we anticipate big breakthoughs in software—AI!, blockchain!, metaverse! chatbots!—but in reality the field is relatively stagnant. Meanwhile in areas like biology, there’s been unexpected advances. Or maybe, as Terence indicates, it’s all about the hype.
I really like this experiment that Jim is conducting on his own site. I might try to replicate it sometime!
An account of the mother of all demos, written by Steven Johnson.