Kardashev Street
Matt has made a new website for tracking our collective progress levelling up the Kardashev scale:
Maximising energy generation, distribution and usage at street level, for as many people as possible, everyday.
Matt has made a new website for tracking our collective progress levelling up the Kardashev scale:
Maximising energy generation, distribution and usage at street level, for as many people as possible, everyday.
A depressing but accurate description of the economics of web development.
I find my feelings about AI are actually pretty similar to my feelings about blockchains: they do a poor job of much of what people try to do with them, they can’t do the things their creators claim they one day might, and many of the things they are well suited to do may not be altogether that beneficial. And while I do think that AI tools are more broadly useful than blockchains, they also come with similarly monstrous costs.
A very even-handed take.
I’m glad that I took the time to experiment with AI tools, both because I understand them better and because I have found them to be useful in my day-to-day life. But even as someone who has used them and found them helpful, it’s remarkable to see the gap between what they can do and what their promoters promise they will someday be able to do. The benefits, though extant, seem to pale in comparison to the costs.
I don’t believe the greatest societal risk is that a sentient artificial intelligence is going to kill us all. I think our undoing is simpler than that. I think that most of our lives are going to be shorter and more miserable than they could have been, thanks to the unchecked greed that’s fed this rally. (Okay, this and crypto.)
I like this analogy:
AI is like a dancing bear. This was a profitable sideshow dating back to the middle ages: all it takes is a bear, some time, and a complete lack of ethics. Today, our carnival barkers are the AI startups and their CEOs. They’re trying to convince you that if they can show you a bear that can dance, then you’ll believe it can draw, write coherent sentences, and help you with your app’s marketing strategy.
Part of the curiosity of a dancing bear is the implicit risk that it’ll remember at some point that it’s a bear, and maul whoever is nearby. The fear is a selling point. Likewise, some AI vendors have even learned that the product is more compelling if it’s perceived as dangerous. It’s common for AI startup execs to say things like, “of course there’s a real risk that an army of dancing bears will eventually kill us all. Anyway, here’s what we’re working on…” How brave of them.
I really, really like this post from Matt (except for the bit where he breaks Simon’s rule).
The interactive widgets embedded in this article are excellent teaching tools!
Pessimism always sounds smarter than optimism because optimism sounds like a sales pitch while pessimism sounds like someone trying to help you.
I usually hate these kinds of lists of bumper-sticker aphorisms but some of these have me pondering my own work, like this one:
People learn when they’re surprised. Not when they read the right answer, or are told they’re doing it wrong, but when they experience a gap between expectations and reality.
Or this:
There are two types of information: stuff you’ll still care about in the future, and stuff that matters less and less over time. Long-term vs. expiring knowledge.
Hannah Steinkopf-Frank:
At its core, and despite its appropriation, Solarpunk imagines a radically different societal and economic structure.
I do think large tech companies employ JavaScript frameworks because, amongst other things, it saves them money at their scale. And what Big Tech does trickles down in the form of default choices for many others (“they’re doing it and are insanely successful, so mimicking them can’t be a bad idea”). However, the scale at which smaller projects operate doesn’t necessarily translate to the same kind of cost savings.
Science-fiction writers don’t know anything more about the future than anyone else. Human history is too unpredictable; from this moment, we could descend into a mass-extinction event or rise into an age of general prosperity. Still, if you read science fiction, you may be a little less surprised by whatever does happen. Often, science fiction traces the ramifications of a single postulated change; readers co-create, judging the writers’ plausibility and ingenuity, interrogating their theories of history. Doing this repeatedly is a kind of training. It can help you feel more oriented in the history we’re making now.
Kim Stanley Robinson knows the score:
Margaret Thatcher said that “there is no such thing as society,” and Ronald Reagan said that “government is not the solution to our problem; government is the problem.” These stupid slogans marked the turn away from the postwar period of reconstruction and underpin much of the bullshit of the past forty years.
The benchmarks that advertising companies use — intended to measure the number of clicks, sales and downloads that occur after an ad is viewed — are fundamentally misleading. None of these benchmarks distinguish between the selection effect (clicks, purchases and downloads that are happening anyway) and the advertising effect (clicks, purchases and downloads that would not have happened without ads).
It gets worse: the brightest minds of this generation are creating algorithms which only increase the effects of selection.
A terrificly well-written piece on the emperor’s new clothes worn by online advertising. Equal parts economic rigour and Gladwellian anecdata, it’s a joy to read! Kudos to Alana Gillespie for the great translation work (the original article was written in Dutch).
We currently assume that advertising companies always benefit from more data. … But the majority of advertising companies feed their complex algorithms silos full of data even though the practice never delivers the desired result. In the worst case, all that invasion of privacy can even lead to targeting the wrong group of people.
This insight is conspicuously absent from the debate about online privacy. At the moment, we don’t even know whether all this privacy violation works as advertised.
The interaction design of this article is great too—annotations, charts, and more!
Craig writes about reading and publishing, from the memex and the dynabook to the Kindle, the iPhone, and the iPad, all the way back around to plain ol’ email and good old-fashioned physical books.
We were looking for the Future Book in the wrong place. It’s not the form, necessarily, that needed to evolve—I think we can agree that, in an age of infinite distraction, one of the strongest assets of a “book” as a book is its singular, sustained, distraction-free, blissfully immutable voice. Instead, technology changed everything that enables a book, fomenting a quiet revolution. Funding, printing, fulfillment, community-building—everything leading up to and supporting a book has shifted meaningfully, even if the containers haven’t. Perhaps the form and interactivity of what we consider a “standard book” will change in the future, as screens become as cheap and durable as paper. But the books made today, held in our hands, digital or print, are Future Books, unfuturistic and inert may they seem.
Almost every technological innovation over the last 300 years has had side effects which actually increase the number of opportunities for employment. The general trend is that the easier something is to do, the more demand there is for it.
Cameron looks at the historical effects of automation and applies that to design systems. The future he sees is one of increased design democratisation and participation.
This is actually something that designers have been championing for decades – inclusive design at all levels of the company, and an increase in design thinking at all stages of product development. Now that we finally have a chance of achieving that it’s not a time to be scared. It’s a time to be celebrated.
An astoundingly great piece of writing from Paul Ford, comparing the dot-com bubble and the current blockchain bubble. This resonates so hard:
I knew I was supposed to have an opinion on how the web and the capital markets interacted, but I just wanted to write stuff and put it online. Or to talk about web standards—those documents, crafted by committees at the World Wide Web consortium, that defined the contract between a web browser and a web server, outlining how HTML would work. These standards didn’t define just software, but also culture; this was the raw material of human interaction.
And, damn, if this isn’t the best description the post-bubble web:
Heat and light returned. And bit by bit, the software industry insinuated itself into every aspect of global enterprise. Mobile happened, social networks exploded, jobs returned, and coding schools popped up to convert humans into programmers and feed them to the champing maw of commerce. The abstractions I loved became industries.
Oof! That isn’t even the final gut punch. This is:
Here’s what I finally figured out, 25 years in: What Silicon Valley loves most isn’t the products, or the platforms underneath them, but markets.
A brilliant talk by Stuart on how privacy could be a genuinely disruptive angle for companies looking to gain competitive advantage over the businesses currently in the ascendent.
How do you end up shaping the world? By inventing a thing that the current incumbents can’t compete against. By making privacy your core goal. Because companies who have built their whole business model on monetising your personal information cannot compete against that. They’d have to give up on everything that they are, which they can’t do. Facebook altering itself to ensure privacy for its users… wouldn’t exist. Can’t exist. That’s how you win.
The beauty of this is that it’s a weapon which only hurts bad people. A company who are currently doing creepy things with your data but don’t actually have to can alter themselves to not be creepy, and then they’re OK! A company who is utterly reliant on doing creepy things with your data and that’s all they can do, well, they’ll fail. But, y’know, I’m kinda OK with that.
Paul is wondering why good people work for bad companies.
Maybe these designers believe that the respect and admiration they’ve garnered will provide leverage, and allow them to change how a company operates; better to be inside the tent pissing out, than outside pissing in, right? Well, short of burning down the entire piss-drenched campsite. To think you can change an organisation like Facebook – whose leadership has displayed scant regard for the human race beyond its eyeballs – you’re either incredibly naive, or lying to yourself.
The transcript of a talk by Charles Stross on the perils of prediction and the lessons of the past. It echoes Ted Chiang’s observation that runaway AIs are already here, and they’re called corporations.
History gives us the perspective to see what went wrong in the past, and to look for patterns, and check whether those patterns apply to the present and near future. And looking in particular at the history of the past 200-400 years—the age of increasingly rapid change—one glaringly obvious deviation from the norm of the preceding three thousand centuries—is the development of Artificial Intelligence, which happened no earlier than 1553 and no later than 1844.
I’m talking about the very old, very slow AIs we call corporations, of course.
Nobody can afford to volunteer to be extra virtuous in a system where the only rule is quarterly profit and shareholder value. Where the market rules, all of us are fighting for the crumbs to get the best investment for the market. And so, this loose money can go anywhere in the planet without penalty. The market can say: “It doesn’t matter what else is going on, it doesn’t matter if the planet crashes in fifty years and everybody dies, what’s more important is that we have quarterly profit and shareholder value and immediate return on our investment, right now.” So, the market is like a blind giant driving us off a cliff into destruction.
Kim Stanley Robinson journeys to the heart of the Anthropocene.
Economics is the quantitative and systematic analysis of capitalism itself. Economics doesn’t do speculative or projective economics; perhaps it should, I mean, I would love it if it did, but it doesn’t. It’s a dangerous moment, as well as a sign of cultural insanity and incapacity. It’s like you’ve got macular degeneration and your vision of reality itself were just a big black spot precisely in the direction you are walking.
Play the part of an AI pursuing its goal without care for existential threats. This turns out to be ludicrously addictive. I don’t want to tell you how long I spent playing this.
Keep your eye on the prize: remember that money (and superintelligence) is just a means to an end …and that end is making more paperclips.
John makes the point that unless you’re one of the big, big players, your native app is really going to struggle to find an audience. But that’s okay—a progressive web app might be exactly what you need.
In short, using native apps as a path to reaching a large number of potential customers and benefitting from crucial network effects is close to impossible.
But, in the meantime, the Web has responded to the very significant impact that native apps had on user behaviour.
For me, the strength of the web has never been about how it can help big companies—it’s about how it can amplify and connect the niche players.