Tags: web3

The bedrock of the World Wide Web is solid. Built atop the protocols of the internet (TCP/IP), its fundamental building blocks remain: URLs of HTML files transmitted over HTTP. Baldur Bjarnason writes:

Even today, the web is like living fossil, a preserved relic from a different era. Anybody can put up a website. Anybody can run a business over it. I can build an app or service, send the URL to anybody I like, and most people in the world will be able to run it without asking anybody’s permission.

Still, the web has evolved. In fact, that evolution is something that’s also built into its fundamental design. Rather than try to optimise the World Wide Web for one particular use-case, Tim Berners-Lee realised the power of being flexible. Like the internet, the World Wide Web is deliberately dumb.

(I get very annoyed when people talk about the web as being designed for scientific work at CERN. That was merely the first use-case. The web was designed for everything …and nothing in particular.)

Robin Berjon compares the web’s evolution to the ship of Theseus:

That’s why it’s been so hard to agree about what the Web is: the Web is architected for resilience which means that it adapts and transforms. That flexibility is the reason why I’m talking about some mythological dude’s boat. Altogether too often, we consider some aspects of the Web as being invariants when they’re potentially just as replaceable as any other part. This isn’t to say that there are no invariants on the Web.

The web can be changed. That’s both a comfort and a warning. There’s plenty that we should change about today’s web. But there’s also plenty—at the root level—that we should fight to preserve.

And if you want change, the worst way to go about it is to promulgate the notion of burning everything down and starting from scratch. As Erin says in the fourth and final part of her devastating series on Meta in Myanmar:

We don’t get a do-over planet. We won’t get a do-over network.

Instead, we have to work with the internet we made and find a way to rebuild and fortify it to support the much larger projects of repair—political, cultural, environmental—that are required for our survival.

Though, as Robin points out, that doesn’t preclude us from sharing a vision:

Proceeding via small, incremental changes can be a laudable approach, but even then it helps to have a sense for what it is that those small steps are supposed to be incrementing towards.

I’m looking forward to reading what Robin puts forward, particularly because he says “I’m no technosolutionist.”

From a technical perspective, the web has never been better. We have incredible features in HTML, CSS, and JavaScript, all standardised and with amazing interoperability between browsers. The challenges that face the web today are not technical.

That’s one of the reasons why I have no patience for the web3 crowd. Apart from the ridiculous name, they’re focusing on exactly the wrong part of the stack.

Listening to their pitch, they’ll point out that while yes, the fundamental bedrock of the web is indeed decentralised—TCP/IP, HTTP(S)—what’s been constructed on that foundation is increasingly centralised; the power brokers of Google, Meta, Amazon.

And what’s the solution they propose? Replace the underlying infrastructure with something-something-blockchain.

Would that it were so simple.

The problems of today’s web are not technical in nature. The problems of today’s web won’t be solved by technology. If we’re going to solve the problems of today’s web, we’ll need to do it through law, culture, societal norms, and co-operation.

(Feel free to substitute “today’s web” with “tomorrow’s climate”.)

When I was hosting the DIBI conference in Edinburgh back in May, I moderated an impromptu panel on AI:

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.

Something else that happened at that event was that I met Deborah Dawton from the Design Business Association. She must’ve liked the cut of my jib because she invited me to come and speak at their get-together in Brighton on the topic of “AI, Web3 and design.”

The representative from the DBA who contacted me knew what they were letting themselves in for. They wrote:

I’ve read a few of your posts on the subject and it would be great if you could join us to share your perspectives.

How could I say no?

I’ve published a transcript of the short talk I gave.

• Download the slides

Hello. I was asked by the Design Business Association to talk to you today about “web3 and AI.”

I’d like to explain what those terms mean.

“Web3”

Let’s start with “web3.” Fortunately I don’t have to come up with an explanation for this term because my friend Heydon Pickering has recorded a video entitled “what is web 3.0?”

What is web trois point nought?

Web uno dot zilch was/is a system of interconnected documents traversible by hyperlink.

However, web deux full stop nowt was/is a system of interconnected documents traversible by hyperlink.

On the other hand, web drei dot zilch is a system of interconnected documents traversible by hyperlink.

Should you wish to upgrade to web three point uno, expect a system of interconnected documents traversible by hyperlink.

If we ever get to web noventa y cinco, you can bet your sweet @rse, it will be a system of interconnected documents traversible by f*!king hyperlink.

There you have it. “Web3” is a completely meaningless term. If someone uses it, they’re probably trying to sell you something.

If you ask for a definition, you’ll get a response like “something something decentralisation something something blockchain.”

As soon as someone mentions blockchain, you can tune out. It’s the classic example of a solution in search of a problem (although it’s still early days; it’s only been …more than a decade).

I can give you a defintion of what a blockchain is. A blockchain is multiple copies of a spreadsheet.

I find it useful to be able to do mental substitions like that when it comes to buzzwords. Like, remember when everyone was talking about “the cloud” but no one was asking what that actually meant? Well, by mentally substituting “the cloud” with “someone else’s server” you get a much better handle on the buzzword.

So, with “web3” out of the way, we can move onto the next buzzword. AI.

“AI”

The letters A and I are supposed to stand for Artificial Intelligence. It’s a term that’s almost as old as digital computing itself. It goes right back to the 1950s.

These days we’d use the term Artificial General Intelligence—AGI—to talk about that original vision of making computers as smart as people.

Vision is the right term here, because AGI remains a thought experiment. This is the realm of super intelligence: world-ending AI overlords; paperclip maximisers; Roko’s basilisk.

These are all fascinating thought experiments but they’re in the same arena as speculative technologies like faster-than-light travel or time travel. I’m happy to talk about any of those theoretically-possible topics, but that’s not what we’re here to talk about today.

When you hear about AI today, you’re probably hearing about specific technologies like large language models and machine learning.

Let’s take a look at large language models and their visual counterparts, diffusion models. They both work in the same way. You take a metric shit ton of data and you assign each one to a token. So you’ve got a numeric token that represents a bigger item: a phrase in a piece of text, or an object in an image.

The author Ted Chiang used a really good analogy to describe this process when he said ChatGPT is like a blurry JPEG of the web.

Just as image formats like JPG use compression to smush image data, these models use compression to smush data into tokens.

By the way, the GPT part of ChatGPT stands for Generative Pre-trained Transformer. The pre-training is that metric shit ton of data I mentioned. The generative part is about combining—or transforming—tokens in a way that should make probabalistic sense.

Terminology

Here’s some more terminology that comes up when people talk about these tools.

Overfitting. This is when the output produced by a generative pre-trained transformer is too close to the original data that fed the model. Another word for overfitting is plagiarism.

Hallucinations. People use this word when the output produced by a generative pre-trained transformer strays too far from reality. Another word for this is lying. Although the truth is that all of the output is a form of hallucination—that’s the generative part. Sometimes the output happens to match objective reality. Sometimes it doesn’t.

What about the term AI itself? Is there a more accurate term we could be using?

I’m going to quote Ted Chiang again. He proposes that a more accurate term is applied statistics. I like that. It points to the probabalistic nature of these tools: take an enormous amount of inputs, then generate something that feels similar based on implied correlations.

I like to think of “AI” as a kind of advanced autocomplete. I don’t say that to denigrate it. Quite the opposite. Autocomplete is something that appears mundane on the surface but has an incredible amount of complexity underneath: real-time parsing of input, a massive database of existing language, and on-the-fly predictions of the next most suitable word. Large language models do the same thing, but on a bigger scale.

What’s it good for?

So what is AI good for? Or rather, what is a language or diffusion model good for? Or what is applied statistics or advanced autocomplete good for?

Transformation. These tools are really good at transforming between formats. Text to speech. Speech to text. Text to images. Long form to short form. Short form to long form.

Think of transcripts. Summaries. These are smart uses of this kind of technology.

Coding, to a certain extent, can be considered a form of transformation. I’ve written books on programming, and I always advise people to first write out what they want in English. Then translate each line of English into the programming language. Large language models do a pretty good job of this right now, but you still need a knowledgable programmer to check the output for errors—there will be errors.

(As for long-form and short-form text transformations, the end game may be an internet filled with large language models endlessly converting our written communications.)

When it comes to the design process, these tools are good at quantity, not quality. If you need to generate some lorem ipsum placeholder text—or images—go for it.

What they won’t help with is problem definition. And it turns out that understanding and defining the problem is the really hard part of the design process.

Use these tools for inputs, not outputs. I would never publish the output of one of these tools publicly. But I might use one of these tools at the beginning of the process to get over the blank page. If I want to get a bunch of mediocre ideas out of the way quickly, these tools can help.

There’s an older definition of the intialism AI that dairy farmers would be familiar with, when “the AI man” would visit the farm. In that context, AI stands for artificial insemination. Perhaps thats also a more helpful definition of AI tools in the design process.

But, like I said, the outputs are not for public release. For one thing, the generated outputs aren’t automatically copyrighted. That’s only fair. Technically, it’s not your work. It is quite literally derivative.

Why all the hype?

Everything I’ve described here is potentially useful in some circumstances, but not Earth-shattering. So what’s with all the hype?

Venture capital. With this model of funding, belief in a technology’s future matters more than the technology’s actual future.

We’ve already seen this in action with self-driving cars, the metaverse, and cryptobollocks. Reality never matched the over-inflated expectations but that made no difference to the people profiting from the investments in those technologies (as long as they make sure to get out in time).

By the way, have you noticed how all your crypto spam has been replaced by AI spam? Your spam folder is a good gauge of what’s hot in venture capital circles right now.

The hype around AI is benefiting from a namespace clash. Remember, AI as in applied statistics or advanced autocomplete has nothing in common with AI as in Artificial General Intelligence. But because the same term is applied to both, the AI hype machine can piggyback on the AGI discourse.

It’s as if we decided to call self-driving cars “time machines”— we’d be debating the ethics of time travel as though it were plausible.

For a refreshing counter-example, take a look at what Apple is saying about AI. Or rather, what it isn’t saying. In the most recent Apple keynote, the term AI wasn’t mentioned once.

Technology blogger Om Malik wrote:

One of the most noticeable aspects of the keynote was the distinct lack of mention of AI or ChatGPT.

I think this was a missed marketing opportunity for the company.

I couldn’t disagree more. Apple is using machine learning a-plenty: facial recognition, categorising your photos, and more. But instead of over-inflating that work with the term AI, they stick to the more descriptive term of machine learning.

I think this will pay off when the inevitable hype crash comes. Other companies, that have tied their value to the mast of AI will see their stock prices tank. But because Apple is not associating themselves with that term, they’re well positioned to ride out that crash.

What should you do?

Alright, it’s time for me to wrap this up with some practical words of advice.

Beware of the Law of the instrument. You know the one: when all you have is a hammer, everything looks a nail. There’s a corollary to that: when the market is investing heavily in hammers, everyone’s going to try to convince you that the world is full of nails. See if you can instead cultivate a genuine sense of nailspotting.

It should ring alarm bells if you find yourself thinking “how can I find a use for this technology?” Rather, spend your time figuring out what problem you’re trying to solve and only then evaluate which technologies might help you.

Never make any decision out of fear. FOMO—Fear Of Missing Out—has been weaponised again and again, by crypto, by “web3”, by “AI”.

The message is always the same: “don’t get left behind!”

“It’s inevitable!” they cry. But you know what’s genuinely inevitable? Climate change. So maybe focus your energy there.

Links

I’ll leave you with some links.

I highly recommend you get a copy of the book, The Intelligence Illusion by Baldur Bjarnason. You can find it at illusion.baldurbjarnason.com

The subtitle is “a practical guide to the business risks of generative AI.” It doesn’t get into philosophical debates on potential future advances. Instead it concentrates squarely on the pros and cons of using these tools in your business today. It’s backed up by tons of research with copious amounts of footnotes and citations if you want to dive deeper into any of the issues.

If you don’t have time to read the whole book, Baldur has also created a kind of cheat sheet. Go to needtoknow.fyi and you can a one-page list of cards to help you become an AI bullshit detector.

I keep track of interesting developments in this space on my own website, tagging with “machine learning” at adactio.com/tags/machinelearning

Thank you very much for your time today.

@anildash@mastodon.cloud

When it came time to reckon with social media’s failings, nobody ran to the “web3” platforms. Nobody asked “can I get paid per message”? Nobody asked about the blockchain. The community of people who’ve been quietly doing this work for years (decades!) ended up being the ones who welcomed everyone over, as always.

Letter in Support of Responsible Fintech Policy

A well-written evisceration of cryptobollocks signed by Bruce Scheier, Tim Bray, Molly White, Cory Doctorow, and more.

If you’re a concerned US computer scientist, technologist or developer, you’ve got till June 10th to add your signature before this is submitted to congress.

There’s a lot of emphasis put on decision-making: making sure you’re making the right decision; evaluating all the right factors before making a decision. But we rarely talk about revisiting decisions.

I think perhaps there’s a human tendency to treat past decisions as fixed. That’s certainly true when it comes to evaluating technology.

I’ve been guilty of this. I remember once chatting with Mark about something written in PHP—probably something I had written—and I made some remark to the effect of “I know PHP isn’t a great language…” Mark rightly called me on that. The language wasn’t great in the past but it has come on in leaps and bounds. My perception of the language, however, had not updated accordingly.

I try to keep that lesson in mind whenever I’m thinking about languages, tools and frameworks that I’ve investigated in the past but haven’t revisited in a while.

Andy talks about this as the tech tool carousel:

The carousel is like one of those on a game show that shows the prizes that can be won. The tool will sit on there until I think it’s gone through enough maturing to actually be a viable tool for me, the team I’m working with and the clients I’m working for.

Crucially a carousel is circular: tools and technologies come back around for re-evaluation. It’s all too easy to treat technologies as being on a one-way conveyer belt—once they’ve past in front of your eyes and you’ve weighed them up, that’s it; you never return to re-evaluate your decision.

This doesn’t need to be a never-ending process. At some point it becomes clear that some technologies really aren’t worth returning to:

It’s a really useful strategy because some tools stay on the carousel and then I take them off because they did in fact, turn out to be useless after all.

See, for example, anything related to cryptobollocks. It’s been well over a decade and blockchains remain a solution in search of problems. As Molly White put it, it’s not still the early days:

How long can it possibly be “early days”? How long do we need to wait before someone comes up with an actual application of blockchain technologies that isn’t a transparent attempt to retroactively justify a technology that is inefficient in every sense of the word? How much pollution must we justify pumping into our atmosphere while we wait to get out of the “early days” of proof-of-work blockchains?

Back to the web (the actual un-numbered World Wide Web)…

Nolan Lawson wrote an insightful article recently about how he senses that the balance has shifted away from single page apps. I’ve been sensing the same shift in the zeitgeist. That said, both Nolan and I keep an eye on how browsers are evolving and getting better all the time. If you weren’t aware of changes over the past few years, it would be easy to still think that single page apps offer some unique advantages that in fact no longer hold true. As Nolan wrote in a follow-up post:

My main point was: if the only reason you’re using an SPA is because “it makes navigations faster,” then maybe it’s time to re-evaluate that.

For another example, see this recent XKCD cartoon:

“You look around one day and realize the things you assumed were immutable constants of the universe have changed. The foundations of our reality are shifting beneath our feet. We live in a house built on sand.”

Perhaps the best example of a technology that warrants regular re-evaluation is the World Wide Web itself. Over the course of its existence it has been seemingly bettered by other more proprietary technologies.

Flash was better than the web. It had vector graphics, smooth animations, and streaming video when the web had nothing like it. But over time, the web caught up. Flash was the hare. The World Wide Web was the tortoise.

In more recent memory, the role of the hare has been played by native apps.

I remember talking to someone on the Twitter design team who was designing and building for multiple platforms. They were frustrated by the web. It just didn’t feel as fully-featured as iOS or Android. Their frustration was entirely justified …at the time. I wonder if they’ve revisited their judgement since then though.

In recent years in particular it feels like the web has come on in leaps and bounds: service workers, native JavaScript APIs, and an astonishing boost in what you can do with CSS. Most important of all, the interoperability between browsers is getting better and better. Universal support for new web standards arrives at a faster rate than ever before.

But developers remain suspicious, still prefering to trust third-party libraries over native browser features. They made a decision about those libraries in the past. They evaluated the state of browser support in the past. I wish they would re-evaluate those decisions.

Alas, inertia is a very powerful force. Sticking with a past decision—even if it’s no longer the best choice—is easier than putting in the effort to re-evaluate everything again.

What’s the phrase? “Strong opinions, weakly held.” We’re very good at the first part and pretty bad at the second.

Just the other day I was chatting with one of my colleagues about an online service that’s available on the web and also as a native app. He was showing me the native app on his phone and said it’s not a great app.

“Why don’t you add the website to your phone?” I asked.

“You know,” he said. “The website’s going to be slow.”

He hadn’t tested this. But years of dealing with crappy websites on his phone in the past had trained him to think of the web as being inherently worse than native apps (even though there was nothing this particular service was doing that required any native functionality).

It has become a truism now. Native apps are better than the web.

And you know what? Once upon a time, that would’ve been true. But it hasn’t been true for quite some time …at least from a technical perspective.

But even if the technologies in browsers have reached parity with native apps, that won’t matter unless we can convince people to revisit their previously-formed beliefs.

The technologies are the easy bit. Getting people to re-evaluate their opinions about technologies? That’s the hard part.

Cautionary Tales from Cryptoland

This quote from the brilliant Molly White is about web3/blockchain/cryptobollocks but it applies to evaluating technology in general (like, say, JavaScript frameworks):

I firmly believe that companies first need to identify and research the problem they are trying to solve, and then select the right technology to do it. Those technologies may not be the latest buzzword, and they may not cause venture capitalists to come crawling out of the woodwork, but choosing technologies with that approach tends to be a lot more successful in the long run — at least, assuming the primary goal is to actually solve a problem rather than attract VC money.

🐠 Robin Sloan: describing the emotions of life online

Obviously, no one does this, I recognize this is a very niche endeavor, but the art and craft of maintaining a homepage, with some of your writing and a page that’s about you and whatever else over time, of course always includes addition and deletion, just like a garden — you’re snipping the dead blooms. I do this a lot. I’ll see something really old on my site, and I go, “you know what, I don’t like this anymore,” and I will delete it.

But that’s care. Both adding things and deleting things. Basically the sense of looking at something and saying, “is this good? Is this right? Can I make it better? What does this need right now?” Those are all expressions of care. And I think both the relentless abandonment of stuff that doesn’t have a billion users by tech companies, and the relentless accretion of garbage on the blockchain, I think they’re both kind of the antithesis, honestly, of care.

Web3 - creating problems where we need solutions on Vimeo

This is a great talk from Laura that clearly explains what web3 actually is. It pairs nicely with Molly White’s wb3 is going just great (speaking of which, Casey Newton interviewed Molly White about the site recently).

Make Free Stuff | Max Böck

At its very core, the rules of the web are different than those of “real” markets. The idea that ownership fundamentally means that nobody else can have the same thing you have just doesn’t apply here. This is a world where anything can easily be copied a million times and distributed around the globe in a second. If that were possible in the real world, we’d call it Utopia.

It’s not still the early days

If you’re interested in so-called web3, you should definitely follow Molly White.

How long can it possibly be “early days”? How long do we need to wait before someone comes up with an actual application of blockchain technologies that isn’t a transparent attempt to retroactively justify a technology that is inefficient in every sense of the word? How much pollution must we justify pumping into our atmosphere while we wait to get out of the “early days” of proof-of-work blockchains? How many people must be scammed for all they’re worth while technologists talk about just beginning to think about building safeguards into their platforms? How long must the laymen, who are so eagerly hustled into blockchain-based projects that promise to make them millionaires, be scolded as though it is their fault when they are scammed as if they should be capable of auditing smart contracts themselves?

The more you think about it, the more “it’s early days!” begins to sound like the desperate protestations of people with too much money sunk into a pyramid scheme, hoping they can bag a few more suckers and get out with their cash before the whole thing comes crashing down.

Norton

It me.

Occasionally, I wonder whether I’ve got it all wrong. Is my age, my technical unsophistication, or my fond remembrance of an internet unencumbered by commerce blinding me to the opportunities that crypto offers me? But then I read something terrible and I recant my doubts, meditate for a while and get on with my life.

Blockchain-based systems are not what they say they are

Blockchain technologies have somehow managed to land in the worst of both worlds—decentralized but not really, immutable but not really.

A great analysis of the system of smoke and mirrors that constitutes so-called web3:

Instead of being at the mercy of the “big tech” companies like Amazon and Google that monopolize the traditional way of doing things on the web, you are now at the mercy of a few other tech companies that are rapidly monopolizing the blockchain way of doing things.

Moxie Marlinspike >> Blog >> My first impressions of web3

A balanced, even-handed look at actually using so-called web3 technology. It turns out that even if you leave the ethical and environmental concerns aside, the technological underpinning are, um, troublesome to say the least.

Crypto: the good, the bad and the ugly | Seldo.com

A very even-handed and level-headed assessment by Laurie, who has far more patience than me when it comes to this shit.

Washed Up - Infrequently Noted

The term “web3” is a transparent attempt to associate technologies diametrically opposed to the web with its success; an effort to launder the reputation of systems that have most effectively served as vehicles for money laundering, fraud, and the acceleration of ransomware using the good name of a system that I help maintain.

Perhaps this play to appropriate the value of the web is what it smells like: a desperate move by bag-holders to lure in a new tranche of suckers, allowing them to clear speculative positions. Or perhaps it’s honest confusion. Technically speaking, whatever it is, it isn’t the web or any iteration of it.

A not so gentle intro to web3 | Koos Looijesteijn

Web3 is like a combination of pyramid schemes, scientology and Tamagotchi. There’s the fact that ultimately anything you do on blockchains costs you real money and that once you’ve paid that, you’re one of the people who need to get the next cohort of buyers onboard or lose your money. There’s believing that you’re joining a movement that’s in the know, with all kinds of interesting words and sci-fi stuff that normies just don’t understand. And there’s your portfolio, your pretty JPGs, wallets, apps and everything you spent so much time on understanding and maintaining. Good luck avoiding sunk cost fallacy there.

Wesley Aptekar-Cassels | web3 is Centralized

Ethereum is only decentralized in the way that doesn’t matter — you’re free to join the decentralized system, under the condition that you act in the exact same way as every other actor in that system.

Brian Eno on NFTs and Automaticism

Much of the energy behind crypto arises from the very strong need that some people feel to operate outside of a state, and therefore outside of any sort of democratic communal overview. The idea that Ayn Rand, that Nietzsche-for-Teenagers toxin, should have had her whacky ideas enshrined in a philosophy about money is what is terrifying to me.

The Case Against Crypto | Pervasive Media Studio

The underlying technology of cryptocurrency is based on a world without trust. Its most ardent proponents want to demolish institutions and abolish regulation, reducing the world to a numbers game which they believe they can win. If the wildest fantasies of cryptocurrency enthusiasts were to come true, if all the environmental and technical objections were to fall away, the result would be financial capitalism with all the brakes taken off.

The promotion of cryptocurrencies is at best irresponsible, an advertisement for an unregulated casino. At worst it is an environmental disaster, a predatory pyramid scheme, and a commitment to an ideology of greed and distrust. I believe the only ethical response is to reject it in all its forms.