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Collection of wonders and wanders across the web.

Coin celebrating Border Patrol agent whipping Haitian migrant under investigation by CBP (sacurrent.com)

Coins celebrating the bad behavior of law enforcement have been around for years, according to a report from Mother Jones.

First appearing as “military challenge” coins in 1969, the collectables were to meant to encourage camaraderie in Special Forces units. However, as “cops began equipping themselves and acting more like soldiers, they started minting their own,” the left-leaning magazine reports.

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At the Turning of the Tide : How to Fight Our Way out of the Trump Era (crimethinc.com)

Here, we revisit the structural forces behind Trump’s return to power, review the events of 2025, and propose a strategy for how to fight our way out of the Trump era together.

Today, the world’s ten richest men control considerably more wealth than the poorest three billion people. When wealth becomes this unevenly distributed, the ruling class exerts so much power relative to the rest of the population that representative democracy changes character.

Barring world revolution, the crises inflicted by capitalism will continue to provoke social unrest until the emergence of some massive new mechanism of control or appeasement.

–The Ukrainian Revolution and the Future of Social Movements

Fascism depends on the management of perceptions.

The poet Juvenal wrote that the people of ancient Rome were bribed with bread and circuses to accept the end of democracy and the establishment of the dictatorship known as the Roman Empire. The tried-and-true playbook to accustom people to autocracy is to meet their material needs while channeling their attention towards activities that substitute for self-determination.

The real reason for the tariffs and the deportations is that they are mechanisms of autocracy: they offer ways to maximize the leverage that Donald Trump can exert on governments, corporations, and ordinary people from the Oval Office. The tariffs enable him to negotiate quid pro quo agreements with governments and corporations for his own benefit, the deportations to build up a loyal paramilitary force tasked with attacking whomever he deems an internal enemy.

Above all, the goal is to accustom the general population to suffering—both to others’ suffering and to their own. This is the point of the extrajudicial killings in the Caribbean Sea and eastern Pacific Ocean, of the gratuitously brutal arrests of Mahmoud Khalil and other green card holders, of Trump’s efforts to weaponize the legal system. This explains why they commit their worst atrocities not in secret, but as media stunts.

The movement against Trump must dig deeper and look further than electoral politics. We must center practices that put power in the hands of ordinary people, pursuing a strategy that outflanks and delegitimizes party politics along with capitalism and the violence that sustains it. We have to dismantle the mechanisms that produce billionaires in the first place.

It’s you against the billionaires. At their disposal, they have all the wealth and power of the most formidable empire in the history of the solar system. All you have going for you is your own ingenuity, the solidarity of your comrades, and the desperation of millions like you. The billionaires succeed by concentrating power in their own hands at everyone else’s expense. For you to succeed, you must demonstrate ways that everyone can become more powerful. Two principles confront each other in this contest: on one side, individual aggrandizement at the expense of all living things; on the other, the potential of the individual to increase the self-determination of all human beings, all living creatures.

The Billionaire and the Anarchists

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“Wait, not like that”: Free and open access in the age of generative AI (citationneeded.news)

...there are scenarios that can introduce doubt for those who contribute to free and open projects like the Wikimedia projects, or who independently release their own works under free licenses. I call these “wait, no, not like that” moments.

These reactions are understandable. When we freely license our work, we do so in service of those goals: free and open access to knowledge and education. But when trillion dollar companies exploit that openness while giving nothing back, or when our work enables harmful or exploitative uses, it can feel like we've been naïve. The natural response is to try to regain control.

This is where many creators find themselves today, particularly in response to AI training. But the solutions they're reaching for — more restrictive licenses, paywalls, or not publishing at all — risk destroying the very commons they originally set out to build.

There’s also been an impulse by creators concerned about AI to dramatically limit how people can access their work. Some artists have decided it’s simply not worthwhile to maintain an online gallery of their work when that makes it easily accessible for AI training. Many have implemented restrictive content gates — paywalls, registration-walls, “are you a human”-walls, and similar — to try to fend off scrapers. This too closes off the commons, making it more challenging or expensive for those “every single human beings” described in open access manifestos to access the material that was originally intended to be common goods.

Instead of worrying about “wait, not like that”, I think we need to reframe the conversation to “wait, not only like that” or “wait, not in ways that threaten open access itself”. The true threat from AI models training on open access material is not that more people may access knowledge thanks to new modalities. It’s that those models may stifle Wikipedia and other free knowledge repositories, benefiting from the labor, money, and care that goes into supporting them while also bleeding them dry.

Anyone at an AI company who stops to think for half a second should be able to recognize they have a vampiric relationship with the commons. While they rely on these repositories for their sustenance, their adversarial and disrespectful relationships with creators reduce the incentives for anyone to make their work publicly available going forward (freely licensed or otherwise). They drain resources from maintainers of those common repositories often without any compensation. They reduce the visibility of the original sources, leaving people unaware that they can or should contribute towards maintaining such valuable projects.

There are ways to do it: models like Wikimedia Enterprise, which welcomes AI companies to use Wikimedia-hosted data, but requires them to do so using paid, high-volume pipes to ensure that they do not clog up the system for everyone else and to make them financially support the extra load they’re placing on the project’s infrastructure.

...rather than relying on murky copyright claims or threatening to expand copyright in ways that would ultimately harm creators, we can establish clear legal frameworks around consent and compensation that build on existing labor and contract law. Just as unions have successfully negotiated terms of use, ethical engagement, and fair compensation in the past, collective bargaining can help establish enforceable agreements between AI companies, those freely licensing their works, and communities maintaining open knowledge repositories. These agreements would cover not just financial compensation for infrastructure costs, but also requirements around attribution, ethical use, and reinvestment in the commons.

The future of free and open access isn't about saying “wait, not like that” — it’s about saying "yes, like that, but under fair terms”. With fair compensation for infrastructure costs. With attribution and avenues by which new people can discover and give back to the underlying commons. With deep respect for the communities that make the commons — and the tools that build off them — possible. Only then can we truly build that world where every single human being can freely share in the sum of all knowledge.

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AI bots strain Wikimedia as bandwidth surges 50% (arstechnica.com)

As a result, Wikimedia found that bots account for 65 percent of the most expensive requests to its core infrastructure despite making up just 35 percent of total pageviews. This asymmetry is a key technical insight: The cost of a bot request is far higher than a human one, and it adds up fast.

Making the situation more difficult, many AI-focused crawlers do not play by established rules. Some ignore robots.txt directives. Others spoof browser user agents to disguise themselves as human visitors. Some even rotate through residential IP addresses to avoid blocking, tactics that have become common enough to force individual developers like Xe Iaso to adopt drastic protective measures for their code repositories.

Wikimedia acknowledges the importance of providing “knowledge as a service,” and its content is indeed freely licensed. But as the Foundation states plainly, “Our content is free, our infrastructure is not.”

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