2026-08-21 08:00:00
These days, the conversation in tech and business, and in a lot of society, is still all AI, all the time. And one of the most fundamental questions boils down to: How do you get people to change what they’re doing in regard to AI? For people who (understandably) have moral or ethical objections to the many harms caused by Big AI, there’s the challenge of how to drive action while lacking the resources and capital of the tech tycoons who’ve driven the broad cultural push towards AI adoption.
As a result of the power differential between those pushing AI and those fighting its advances, the typical rhetorical tactic for AI critics has been to try to attach stigma to the use of AI, and to the outputs of AI systems. There is also little cultural discussion, or even mention, of alternative offerings that aren’t from the Big AI companies, so the entire narrative is framed as either using the most harmful, exploitative, damaging AI tools from the likes of OpenAI, or using nothing at all.
And for the most part, this has been pretty effective for people who have any taste or sense of culture. If you’re a creator, or engaged in creative culture, you probably either can’t stand the AI aesthetic, or feel betrayed when you find out something that was appealing to you was AI-generated or made by someone who used generative AI to create it. The only creative discipline that’s broadly an exception to this is coding, where for the most part people don’t have as many aesthetic objections, but even there, people pretty stridently object to the slop aesthetic in user interfaces and other human-facing aspects.
There are, of course, diehard cohorts of AI advocates who insist that they love the AI aesthetic and don’t mind the hyper-real look to what these systems output, but the mainstream discourse in the arts, design and creative disciplines reached a consensus some time ago, and it’s fairly stringently enforced amongst fan communities.
But shame isn’t an effective strategy for stopping the advance of Big AI as a force in society. I’ve said before that scolding people out of using these tools hasn’t worked and isn’t going to work. What I want to get at here is why it structurally can’t work — and what has to replace it.
I wish shame and stigma were more effective ways of driving or changing behavior in society in general. It has been a project in many social circles over the last 15 years or so to remove shame as a social curb on bad behaviors, and this has largely succeeded; this is why we see the richest man in the world monetizing accounts that share child sexual abuse material on his social network, and the president of the United States having been found liable for sexual abuse, and no one holds these men to account, or is even unwilling to be seen with them. Having grown up fluent in an Asian culture, I’m well aware of how shame can shape entire communities’ functions and norms.
But in the particular case of how new technologies shape society, trying to use shame to drive behavior change isn’t an economically effective tool for curtailing the impact of bad actors. During the rise of the social networks, when we first started seeing the kinds of harms that they could cause, many activists and academics who wanted to champion alternative approaches tried to shame people out of using the then-dominant platforms. That stigma persists — you still see people today who are half-embarrassed when they talk about how they’re “still” on Facebook. But they are on Facebook.
People being embarrassed or ashamed while still using the technology does not bother the authoritarian owners of those platforms in the least, as long as they’re profiting off of those ashamed users.
That pattern repeated with the gig economy. Though the #DeleteUber movement early in the first Trump administration was briefly very effective at scaring Uber’s leadership, they quickly adapted to the criticisms people had, and most people have forgotten they were ever supposed to be angry in the first place. They knew they could weather the brief shame or stigma that was attached to using the app.
In short, the venture capitalists and CEOs of Silicon Valley have priced the costs of shame into their business plans. It may make creative communities feel good to shame people about using AI (and maybe that has some purposes for social cohesion amongst those groups), but it rarely stops people from using the platforms at all — it just makes them quieter about it.
Whenever I say this on social media, a bunch of really angry folks come into my mentions and say “you love AI and slop and why don’t you go give Sam Altman a hug” even though my bona fides of criticizing these tech tycoons go back to when the angry people were still in diapers. But I don’t fault people for having spare reservoirs of rage aimed at the harms that the authoritarian billionaires have done to their world; I just want them to aim their rage more effectively.
We have to care more about being effective than we care about being “right”. We have to care more about power and actually winning than we care about merely dunking on people. (And I mean, dunking on people is fun! It just can’t be the only thing. And it doesn’t win any converts.) I wish we would learn one goddamn lesson from our failures to stop the last several waves of tech adoption, where we’ve just kept repeating the same failing patterns, preaching to the choir with our platitudes while regular people all get fed into the insatiable user acquisition maw of big tech, social stigma be damned.
I’m lucky enough to be the kind of NYC policy nerd who saw Zohran Mamdani’s first campaign video when it came out, right after Donald Trump won a second term. It’s worth a re-watch, but in short, what he does is go to the Bronx and engage with folks in one of the areas of the city that swung hardest toward Trump during the election. And he just starts asking people what they care about, why they voted that way. One of the most remarkable things about the video is, Mamdani doesn’t argue with anybody, he just listens, and then he asks them if their life would be better if their rent were frozen, if buses were free, if childcare were affordable. Perhaps most relevant to this point, he doesn’t shame them, even though they had very obviously made a devastatingly self-defeating choice. He gave them an affirmative alternative to move toward, and in doing so, empowered both those people and himself to do something better.
This is the kind of solution that most AI critics are not allowing for right now when they only picture a shame-based corrective to individual people’s use of AI. It is possible to build human-centric, empowering tools and platforms that are owned by the people instead of by billionaire tycoons, that are responsible about the environment and with people’s data and privacy, that are accountable to the communities that they serve. If we engaged every person who made some AI slop and said, “would you rather have tools that help you make something amazing, and brought you into a community of creators?” I don’t think anybody would say no.
And truthfully, I think two big reasons why critics don’t use that framing instead are due to laziness and arrogance. It takes a lot more time and effort to engage with people over time and to bring them into community. It’s a lot easier to dunk on them, and then return to one’s existing community of peers who will praise you for saying how ugly that person’s slop was. But that won’t stop the Big AI companies.
We need a new theory of change if we care more about stopping the harms of Big AI than we care about feeling righteous. The good news is that it already exists, in pieces: there are tactics for winning the platform war, there are direct actions that ordinary people have already used successfully, and there are alternatives being built right now that are worth pointing people toward. What’s missing isn’t the alternative. It’s our willingness to offer it to people instead of just yelling at them.
2026-08-20 08:00:00
For years, I’ve wanted to have a standalone version of Apple’s Touch ID authentication feature for my Mac, but without having to use an Apple keyboard. (I generally like their keyboards, but my daily driver keyboard these days is a big clicky mechanical beast.) I’d gone down various dead ends of trying to find substitutes, and even checked out the efforts where people had ripped apart expensive Apple keyboards just to scavenge the Touch ID sensors out of them. None of them quite solved the problem.
So today, I’m sharing an open source project called Dashboard Touch, which lets you make your own Touch ID-style sensor for your Mac, using low-cost off-the-shelf part. It’s based on an extensive refactoring of the excellent tinyTouch project by Zimeng Xiong, who recently cracked the code on how to make a useful fingerprint scanner system that’s also reasonably secure for regular Mac users. (You should definitely check out his project and support his new hardware build if you’re interested in this stuff.)
I took my own approach to this work because I wanted to focus a lot on having a friendly web interface for configuring exactly how the fingerprint sensor system works on your computer. When you get Dashboard Touch set up, it presents you with a nice web interface that runs right on your own Mac, letting you do things like set the color of the ring light on the fingerprint sensor, or capture your fingerprints so they’re recorded in the system.
Behind the scenes, the way the system works couldn’t be simpler. You buy a little fingerprint sensor, and a small microcontroller, wire them together (it was actually fun to get back to soldering stuff!), and then plug them into your computer with a regular USB cable. After you run the setup script, you just go to the web interface and add your finger(s) to the system.
Once you’re running, your Mac runs as normal, except any time the system prompts you to type in your password, you can just swipe your fingertip on the sensor and Dashboard Touch will type your password in for you. At a technical level, the device is actually literally pretending to be a keyboard. (You can look over the code on GitHub and get a feel for the approach pretty quickly.)
After it’s installed, it’s basically a set-it-and-forget-it kind of thing. You don’t need to do anything else for it to Just Work. Your password is only ever stored securely on your Mac, and your fingerprints are only ever stored securely on your sensor. You can erase them at any time and nothing talks to the internet at all except the one manual update checker, where you can see if there’s a new version of Dashboard Touch, but only when you intentionally click the button to request it to do so.
Overall, this isn’t the kind of system you should use if you’re protecting a bank vault, but if your computer is physically secure and nobody is going to have extended unsupervised access to your Dashboard Touch setup without your permission, you should be fine.
Personally, it’s been really fun to get back to making things. As you can see in my introductory video, I ended up creating an enclosure for my fingerprint sensor in my woodshop, so that it would match my desk that I recently built. Even creating and editing the intro video was a fun project that took me out of my usual comfort zone.
Nearly every task in this project has had me stretching to do things that I’m pretty bad at, from firmware coding to security review to detailed carpentry to video editing. But I just love the idea of putting things out there again for people to hack on, and there's also something really satisfying about being able to be super-opinionated about the design and user interface of something after so many years of working on teams where I had to collaborate. (Even though I always got to collaborate with brilliant people, it's different when you get to pick every pixel!)
I just also have been missing the era of the web when most of what I saw online was weird and fun things that regular people were building, and I realized that I can't mourn the absence of those kinds of projects unless I invest my own energy into building some of those kinds of things myself. So, here's one! Let me know what you think, and if you've got any ideas for how to make this thing better. Or, of course, if you find any bugs that I should fix.
I hope you have fun touching the blinking lights!
2026-07-24 08:00:00
The vast majority of the documents people use to do business are really quite poor. Presentations that make your eyes glaze over, memos that are inscrutable or unclear, and all kinds of artifacts that say more about how they were created than whatever message they were ostensibly trying to communicate. It's been one of my great frustrations for years, and a big part of why I wrote Make Better Documents a while ago. That post captured a list of the suggestions I've been giving people for years on how to make better, more effective documents that can actually do work for you, instead of fighting at cross purposes to your larger goals.
To my great surprise, that list of suggestions on how to make better documents got a pretty huge response, and a lot of people told me they found it really helpful. So now, I've created a Better Documents skills.md file for people who use LLM tools like Claude to help assist them in creating business documents, to prompt their AI tools to make better documents by default.
If you're not familiar, agent skills are simple text files that describe new capabilities or processes that LLMs can take advantage of when carrying out tasks. (They're Markdown files — more proof of how Markdown is taking over the world!) The way this skill works is that it's distilled the broad principles I outlined in that post into a series of 5 tests, covering areas like whether you've properly considered your target audience, whether the overall structure is correct, if you've overdone things with your formatting, and if things are named clearly, and then either generates a new file that follows those rules, or reviews an existing document to make sure it is obeying best practices.
It's nothing too fancy, but I've been using it for a while, and shared it with a few friends, and people have told me they found it handy and it's improved some of their routine documents. I'm especially glad that people have found it useful even if they're the kind of folks who would never let an LLM generate a document on their behalf, but do think software tools are useful for things like spell check or grammar check. I see this as being a tool in that kind of category.
If you're familiar with skills, the install process is really simple and works just like any other skill. This skill is totally free and open source (if you have improvements, send along a pull request on GitHub, or if you're not a coder type, just email me or hit me up on social media and let me know what fixes/suggestions you've got), so there are no encumbrances or restrictions on its use. I am curious if it's useful to people, especially if you find it handy to use more broadly at a company, so don't be shy to get in touch if you find it valuable.
Here's to us all enduring fewer terrible presentations!
2026-06-23 08:00:00
One aspect of strategy that’s been largely lost in the tech industry in recent years is how to compete against platforms, since the major tech companies have gotten so big that markets are no longer competitive. However, the AI market is still early enough, and users and society are still angry enough, that the Big AI companies can lose.
But for them to lose, everybody else in the ecosystem has to carry out the nearly-lost art of platform strategy. Tech companies (and even open source communities!) used to carry out these tactics in emerging product categories ranging from desktop office suites to operating systems to web browsers, though over the decades, the lesson that big tech learned was, basically, that they should play dirty.
You win platform strategy battles through power and persuasion. We're going to get both.
Historically, we would have relied on regulators or media to help hold bad actors in the tech space accountable, but in the United States, these entities are largely not going to help very much. Some state and local governments may assist, and some independent journalists or smaller media outlets are pushing for accountability, but the most powerful entities are either captured or complicit in many cases, so we don’t have the institutional pushback that had sometimes been present in earlier points of technological change.
The thing that matters right now is that we understand that all of the Big AI companies are extremely vulnerable. The reason they’re making so much noise, and spending so much money, is because they know that they’re vulnerable. Users, and especially users who are developers have an enormous amount of leverage to control where AI goes. And if those communities of users can coordinate, they can put power back into the hands of the people. Today, that means focusing on some technical interventions, along with the cultural and political pushback that’s happening. That’s how we begin to reduce, or even prevent, some of the worst AI harms in the future.
Here are some of the proven tactics that have helped shift the balance of power in prior tech reckonings:
The first and most important technical goal is for everyone to push for all AI usage to be disintermediated — where users access their AI apps or services through open tools or interfaces that aren’t controlled by the Big AI companies. These tools, in the form of “harnesses”, or through text editors or command lines, or just through the familiar chat interfaces that lots of people use, need to move as quickly as possible to being controlled by community-built, open options. The sooner this step happens, the sooner we unlock the ability to shift decision-making power out of the hands of the corporate platforms, and begin to undermine their ability to cement lock-in of users.
Status: Good. There are a number of popular, mature tools in almost every category for users who want to access today’s AI tools through a free, open interface. Most of the work now is to get the word out about these tools, and to continue to polish and improve the user experience so that they offer features and design touches that the commercial tools can’t or won’t.
Another key capability that the open ecosystem must provide is the ability to seamlessly switch between different AI providers on the fly, to reduce costs, to provide better performance, or to get both benefits. In many cases, this will be seamless and automatic, just making the right choice for users so that they get the best option all of the time, but advanced users will want to tweak their settings, like when businesses may want to be very aggressive in minimizing the amount of money that their employees are allowed to spend on AI services.
The important part here is that this forces AI platforms that want to compete to remain compatible with all of their competitors, keeping the market dynamic, and ensuring that all of the big providers are easily replaced with another vendor at any time. Basically, we always have to be able to keep them in their place, and they should know that they could go away at any time. Most companies are aware of these needs, but the more regular consumers are familiar with these kinds of requirements, the more pressure there will be on companies to conform with standards. (This is also what will enable the disintermediation mentioned in point 1.)
Status: Good. This is happening already in business environments, where companies demand this kind of flexibility. Developers have been creating very dynamic systems for switching between AI providers, and the ecosystem encourages this kind of switching by extensively comparing different AI platforms against each other whenever new models are released. The important thing to maintain here is the narrative that none of the individual models matter more than the overall ecosystem — and that even the biggest companies have to conform to the same strict formats and standards as the independent AI systems created by communities around the world.
Another vital concern for shifting power away from the Big AI companies is undermining them economically. Instead of simply following the classic “commoditize the complement” strategy that commercial companies often execute, open source projects created by a community can more straightforwardly pursue a path of enlightened value destruction. Non-commercial LLMs have been roughly keeping pace with the Big AI platforms, following the pattern I described as “frontier minus six”, where free and open models lag about 6 months behind the most cutting-edge AI labs — which means they’re still pretty freaking great for most uses.
In a scenario where there are extremely capable models that cost nothing except for the price of keeping a few servers running, as well as very robust tools that make it effortless to seamlessly switch between models (see point #2!), more and more organizations will shift more and more work away from the Big AI companies, especially as those companies keep raising their prices.
But there’s no reason that these same principles can’t be followed by ordinary consumers as well. Many developers are already using these techniques to switch to free models to save money, and the only barrier to this practice becoming more widespread is that the user experience is still too clunky and technical for most regular people.
Status: Okay. Lots of people are working on this, and in some scenarios, the free AI tools are even pretty great. But for the most part, there are still too many compromises in either the end results or the user experience for this to be a mainstream alternative today. This can change, with the right investments and focus on improving things — and focusing on differentiation in areas where the open community can distinguish itself from all of the Big AI companies.
Pretty much everybody who’s from the 21st century, or anybody who’s a creative person, is pretty furious about AI. Anyone who’s not oblivious to culture is aware of that. Yet all of the Big AI companies keep treating it like some fad that’s going to blow over, or a trend that they can just steamroll with their dollars. This isn’t going to go the way they want.
However, the people who will build the alternatives can actually listen to the values and criticisms of the people who are angry, and make tools that respect and respond to what they’re saying. An Internet of consent is not only possible, it’s all around us, if we choose to respect it. If people hear that they can get some of the conveniences or features that they were previously told were only possible with extractive, exploitative, evil AI tools, but without any of those negatives, they’ll actually be pretty happy to hear it.
Today, usage of AI is high enough that even some of the people who hate AI are using it. Some of this is due to the coercive way that AI is being shoved into everybody’s faces, some of it is due to there being some places that people feel it has utility that they wish they could access without its moral compromises. When people are compelled to use platforms that they object to (as a lot of people feel about using things like social media), the feelings of guilt and resentment that come along with it are deeply toxic.
What we're talking about across these first three points, if taken together, is an entirely new experience for millions of users. And that new set of platforms could respect the consumer backlash against AI and channel it into presenting tools that acknowledge their anger and treat it as legitimate. They might even be tools for fighting back.
Status: This one’s going to be tough. This is the one idea where most people think I’m crazy. People who have a righteous anger about the harms of current Big AI companies say that there couldn’t be any such thing as “good AI”, and I understand their skepticism. People who think AI is an interesting technology but hate the hype (the majority AI view) are usually skeptical that the open community could make offerings that are good enough to compete against the big commercial offerings. And AI enthusiasts are pretty skeptical that AI critics would ever come around to seeing any technology in this category as being acceptable, no matter how thoughtfully it was created or presented.
I think there’s enough anger at the trillionaire predators to go around, though.
It’s been a long time since we succeeded in wresting control of a nascent space away from the tycoons trying to take it over. But it’s pretty clear what the stakes are this time, and it’s also clear that the window for changing the path of the AI world is closing pretty rapidly.
Obviously, this kind of shift won’t be easy, but I think people would be pretty surprised how possible it is. There’s a snowball effect that happens once folks start to understand that there are appealing alternatives to the things that are making them miserable. An entire generation needs to discover that enshittification is not only not inevitable, it is downright preventable, and the power to do so rests in our hands.
If you’re a developer, you have an extra responsibility: are you vetting your work against this list? If nothing else, you need to be doing so just to ensure that you have a chance of having a career over time. But it’s also the right thing to do.
And if you’re not technical in that way, you don’t have to become a developer, but you can familiarize yourself with these concerns broadly — even if you hate AI and never want to touch the stuff! — so that you know what argument to make about how to shift the balance of power.
The most important thing to know is that, as so many people have said, none of this is inevitable. But the way we fight that inevitability is with a more exciting, human, powerful alternative, not merely by repeating what we’re saying no to. We are not simply angrily running away from something, we can all be joyfully running toward something together.
In the early days of tech blogging, one of the biggest reasons that so many people got used to reading Joel Spolsky’s blog was that he’d often write amusing little fables that shared key lessons about product strategy. Strategy Letter V (on commoditizing your complements), or How Microsoft Lost the API War, or Fire and Motion, or… Platforms. If you can squint past the turn-of-the-century mentions of Microsoft Excel, there are lots of interesting lessons there.
2026-06-15 08:00:00
“[T]here can be alternatives. What we can imagine is, rather than the ChatGPT killer, a lot of different little AIs from little responsible players.”
That’s me, in The Guardian a few days ago, trying to distill a message that I’ve been trying to get out as broadly as possible for quite a while now. It's sort of like hoping a comet will take out the major AI players and a bunch of smaller new players will be the smarter, better-adapted mammals that take their place instead.
We’re in another one of those big inflection points for AI. Trump administration policymakers for AI suspended access to Anthropic’s newest product. All of these policymakers have a web of investments in competing players — including SpaceX, which is about to IPO — and the corruption and grift of this cohort are so extensive that it’s impossible to judge what the actual risks and reality are around any of these platforms or technologies, since no one involved is an honest broker.
More broadly, there’s been the widespread pushback against AI culturally, one that is undeniably strongest amongst those who were born in this century. But the adoption patterns and usage data show that even younger people are using some AI tools. And that’s a pattern that we’ve seen before, with social media. We have a significant group of people knowing that a technology contradicts some of their values, preferences, or beliefs, but using it anyway.
Sometimes it’s due to the coercive nature of the platforms themselves, and how they insinuate themselves into our lives, to the point where we don’t even realize we’re using them. Sometimes they are forced upon us by the creators of the platforms, since they have so much power over the devices we use, and the tools that we rely on for things like doing our jobs, or communicating with our loved ones or our communities.
There are millions of people who don’t like that they’re using LLMs provided by the Big AI companies, but end up using them anyway. Just like there are hundreds of millions of people who don’t like that they’re on the giant social networking platforms like Facebook, but end up using them anyway. The feelings that people walk away from those experiences with are often guilt, or shame, or embarrassment, or resentment — all some of the most negative and destructive emotions that humans can experience.
But if people want to get the benefits of some of these technologies, without either the shame of supporting the harms of Big AI, or the unpredictability of being beholden to corrupt billionaires bickering with one another, there are finally starting to be other options. As I mentioned in (One) Good AI Is Here, it’s possible for creators working in their own communities to now make AI tools that serve their specific needs, without causing all the harms that make people object to Big AI.
This feels like the true alternative to the narrative of “inevitability” that so much of the hyper-funded AI industry is trying to push, while also not forcing people into a quiet life of AI guilt if they still find some utility in some aspects of these tools.
Right now, those who (rightly!) object to Big AI due to their platforms’ impact on the environment, or labor, or their extractive use of content without consent, or its many other potential harms, are generally not aware of, or often open to, the idea of there being small, human-scale tools created by and for communities that are accountable for those tools over time. But my suspicion is that it is not only possible to make these tools, there may in fact already be many of these tools in existence, and we’re just not as familiar with them because they’ve been quietly serving their specific niches without having multi-billion-dollar campaigns promoting them.
What I'm unabashedly hoping to do (and I think the Guardian story reflects some momentum in that regard), is shift the narrative from focusing on running away from the bad thing in AI, to finding the good thing that we're running toward. There are alternatives that we could be affirmatively choosing, ones that look at questions like the one I asked more than a year ago, "What Would "Good" AI Look Like?", and offer answers that might give us hope instead of just the righteous rage and anger we feel when we let our imaginations be constrained by the limits of what Big AI offers.
2026-04-30 08:00:00
If you followed along with the recent joyful celebrations of the Artemis cruise around the moon, and took a moment to dive into the photographic archives of the mission, you might have noticed that all of the original images were shared by NASA on the venerable photo sharing service Flickr. What you might not know is… why?
Here’s the TL;DR:
First, some background for folks who might not know what Flickr is, or who may have forgotten. Flickr is a social sharing site for photography which was founded in 2004, and these days people might say that it shares some of its cofounders with Slack, though back when Slack started, everybody said that the company was started by some of the founders of Flickr. That’s because Flickr was arguably the most influential site of the Web 2.0 era, helping define everything from the user interface design to the bright colors to the easy way that developers could access data from the platform. A lot of the things that we take for granted on the modern social internet, like a friendly “voice” used to communicate to users, were pioneered by Flickr, and then quickly came to be considered standard expectations for the apps and sites that followed. It’s hard to imagine that sites from Tumblr to Grindr would have omitted their final “e”s without Flickr’s precedent.
Flickr spun out of a Canadian gaming company called Ludicorp, founded by Stewart Butterfield (later CEO/co-founder of Slack) and Caterina Fake (later an investor and chair of Etsy). The photo-sharing service was extracted from the pieces of a somewhat unsuccessful attempt at multiplayer gaming called “Game Neverending”, but it retained the playfulness of that game even as it became a social app. Flickr also inherited the fine-grained privacy controls and thoughtful community features of earlier social platforms like LiveJournal — along with being actively, intentionally moderated by actual humans who worked diligently to prevent destructive behaviors on the platform. This meant that, more than 20 years ago, this early photo sharing community typically had better social norms than people see on today’s social media apps. (A little side note: Part of Flickr/Ludicorp’s initial funding was with public money. What a remarkable way to fund lasting innovation!)
With all of these groundbreaking features, Flickr didn’t just inspire lots of other entrepreneurs to create a new wave of Web 2.0 startups, it also attracted millions of users who, for the first time, began taking photos with the primary goal of sharing them online. Prior to this moment, the earliest phones with decent cameras were coming to market (it would be years until the iPhone came out), and other photo services of the time were still often oriented towards taking film to processing facilities, and then having the professionals at those facilities scan the resulting images and post them to a clunky online service where you could tediously click through them in a virtual album. Until Flickr, photo sharing online was essentially still analog, even if the experience was technically happening online.
Flickr wasn't a social platform first — it was a photography platform first. That means it was designed to store high-resolution versions of every image, and didn't distort pictures with things like filters. Every image showed details like what kind of camera had taken the photo, and even what specific settings were used to take the shot. People started building communities around the then-new idea of using tags to help them find content by topics online — an idea that would directly influence the creation of hashtags on Twitter a few years later.
Another core idea of the time was a firm belief in open data: people should own and control their own work. Eventually, some experts (including a then-teenage Aaron Swartz, who we'd later talk about in the early days of Markdown) created a set of standards called Creative Commons licenses, now maintained by an organization of the same name. Flickr made it easy for users to describe what permissions people had for reusing or remixing any photos they posted. (I was helping out with a blogging platform back then, and I think we were the first tool to support this stuff. It felt like a big deal at the time!)
People's Flickr images started popping up in corporate PowerPoint presentations or commercial advertising almost immediately. A little sidebar: the incredibly positive and generous intent of these open licenses has since been exploited by extractive Big AI companies, who ransacked all of the images on Flickr that had permissive licenses without any consent from, or compensation to, the creators. That might be legal by most readings of the licenses, but if you have hundreds of billions of dollars and don't think you should at least have a conversation with the photographers whose work you're using, you're probably an asshole.
Our close-knit community of people building the new era of web apps was keenly aware that our users were creating culture. This realization brought a huge amount of responsibility — not just in enabling users to express themselves, but in thinking about the long term for people's ownership of their works. Public institutions had just begun to use these platforms, which meant that the content being shared wasn't just a nice picture to look at: it might be socially or even historically significant.
What happened in the years that followed was… a lot of corporate machinations. Flickr got bought by Yahoo. Flickr's founders left Yahoo. Yahoo got bought by Verizon. You can imagine how all of that went; the details aren't all that important, except to say that by the time Instagram launched, Flickr had begun to fade into obscurity. People were focused on mobile phones instead of the desktop, on sharing square images with filters instead of full-resolution photography, and on connecting socially instead of caring about photos as art or a cultural record. Nobody would post the canonical historical photo of an event with a Valencia filter on it. Most of Flickr's users moved on, rarely checking their old accounts — until a family-owned photo service named SmugMug bought the service from Yahoo. A human-scale operation with some actual heart and a love of photography was a much better home for the platform than some random division of Verizon.
In 2022, the new team at SmugMug that owned Flickr decided to focus on Flickr’s larger place in culture. Many major institutions around the world had chosen to archive their public photos on Flickr because of its superior support for high-resolution imagery, its unique ability to declare explicit legal licenses (including public domain licenses), and its long-term reputation for reliably hosting content without any of the harms or abuses that typical social networks had inflicted on users. Museums around the world had entire catalogs on the platform, and governments routinely used it to document their public events. When I had a photo taken at an official White House event with President Obama, his team sent me the final image afterward by sending me a Flickr link; when Zohran Mamdani met King Charles, the NYC Mayor’s Office shared those pictures on Flickr, too.
The Flickr team at SmugMug did something special with their responsibility about these public works, due to their cultural significance to the world. They made the Flickr Commons, and brought in a team with expertise in digital archiving and community. This is a project of The Flickr Foundation, designed to preserve digital legacies, and begun in collaboration with no less than the U.S. Library of Congress (back before that was an institution under siege.) They are developing a hundred year plan for how to care for these works, which is virtually unheard-of in the digital world. (You should absolutely donate to support the Flickr Foundation in their mission to preserve these vital public resources for many years in the future.)
It’s in this context that NASA has long been sharing its imagery on Flickr, for all of its missions — not just Artemis II. There’s even a special section for NASA on The Commons. And since everything is provided in incredibly high-resolution and has every single detail about the photo and how it was taken, it’s possible to combine the information about the photo with other data and create amazing resources like this beautiful timeline of the entire mission. You can see Hank Green’s wonderful narration of his inspiration and creative journey behind the timeline right here:
Anybody who’s read my site for a while knows that I’m a huge proponent of owning your own website, and having your own content live there. Shouldn’t NASA, of all institutions, have their photos live on their own nasa.gov website? Well, yes! But.
One complication is that many large institutions, especially ones that have developed complex processes for good reasons, like government agencies and big businesses, often have trouble maintaining public-facing web infrastructure over long timeframes. Running a website that millions of people can access requires constant updates and maintenance, guarding against a never-ending onslaught of security challenges (a task that’s rapidly getting more difficult!), and the internal knowledge on how a site was created in the first place often leaves when employees do.
In contrast, platforms that are run by technically fluent, well-intentioned and thoughtful technologists can be very effective in maintaining content over a timescale of decades. The SmugMug team has been very thoughtful in managing both their business and their technical infrastructure in order to sustain Flickr’s public archives for years to come. (Though, as mentioned, you should still donate to ensure they can keep doing so!)
What’s more painful is the more recent threats to public stewardship of this kind of content. The traditional authoritarian impulse to destroy or falsify the public record has not spared the digital realm under the current administration. Wide swaths of the government’s websites have been erased, taken offline, or had their content modified to either delete or adulterate the content. Leaders who regularly post AI slop on their social media accounts, and who have begun posting lies and distortions on major websites like the White House’s, will of course not hesitate to modify or remove photos from public archives as well. By having the public’s images preserved in an independent archive in standard formats, we increase the likelihood of future generations being able to access accurate copies of these historical records.
We’ll be glad to have archives like Flickr’s in the future, and people around the world will be glad for its place in archiving even much more mundane aspects of culture.
I was honored to get to reflect on my long history with Flickr, and with online community, in an interview with my old friend Jessamyn West, for the Flickr Foundation’s blog. In a conversation that unspooled over a few months, I think we covered so many of the themes that resonated in what I’ve mentioned here, and what struck me most was how much I wanted a new generation of people on the internet to have their own version of the communities and experiences that we got to have when sites like Flickr were first being made. People still cherish those values!
The beautiful thing about communities and platforms like Flickr is that they remind us that not everything on the internet has to be ephemeral, not everything on the web has to be hyper-commercial. Sometimes a bunch of decent people can do a good thing for the right reasons, and the result of that work can persevere for decades. Then, others who do some of the most ambitious and astounding things imaginable can build on that work to inspire us. And then, some more regular folks can build on top of that and help us waste a little bit of time just clicking around on something fun. That’s what the internet is supposed to be about!
This isn’t just about recounting old web lore — this is about explaining the internet we have right now. Hank’s timeline site is brand new, entertaining a whole new generation, and probably the majority of the audience who are looking at it weren’t even born when Flickr was first conceived. But the reason he can build that site is because of the values and the inventiveness of the team and community who created a platform like Flickr — and because those kinds of values are durable. They might not be as loud or flashy, but they are still everywhere, quietly enabling a lot of the things we enjoy most every day.
Public dollars helped make a fascinating community, then public dollars enabled a breathtaking journey into space, and then a public commons helped a creator make a novel way to explore that journey. Lots of people chose, over and over, to be generous with their genius. These are all gifts that a bunch of strangers gave each other, over hundreds of thousands of miles, and many years. Inspiration is all around us!
