Theorizing “Algorithmic Sabotage”

The “Manifesto” articulates a systematically structured sequence of ten distinct propositions, enumerated from 0 to 9, each delineating the underlying principles, strategic approaches, and aesthetic manifestations that shape the critical concept of “algorithmic sabotage” within the expansive and intricately interwoven frameworks of digital culture and information technology.

1. “Algorithmic Sabotage” is a figure of techno-disobedience for the militancy that’s absent from technology critique.
2. Rather than an atavistic aversion to technology, “Algorithmic Sabotage” can be read as a form of counter-power that emerges from the strength of the community that wields it.
3. “Algorithmic Sabotage” cuts through the capitalist ideological framework that thrives on misery by performing a labour of subversion in the present, dismantling contemporary forms of algorithmic domination and reclaiming spaces for ethical action from generalized thoughtlessness and automaticity.
4. “Algorithmic Sabotage” is an action-oriented commitment to solidarity that precedes any system of social, legal or algorithmic classification.
5. “Algorithmic Sabotage” is a part of a structural renewal of a wider movement for social autonomy that opposes the predations of hegemonic technology through wildcat direct action, consciously aligned itself with ideals of social justice and egalitarianism.
6. “Algorithmic Sabotage” radically reworks our technopolitical arrangements away from the structural injustices, supremacist perspectives and necropolitical authoritarian power layered into the “algorithmic empire”, highlighting its materiality and consequences in terms of both carbon emissions and the centralisation of control.
7. “Algorithmic Sabotage” refuses algorithmic humiliation for power and profit maximisation, focusing on activities of mutual aid and solidarity.
8. The first step of techno-politics is not technological but political. Radical feminist, anti-fascist and decolonial perspectives are a political challenge to “Algorithmic Sabotage”, placing matters of interdependence and collective care against reductive optimisations of the “algorithmic empire”.
9. “Algorithmic Sabotage” struggles against algorithmic violence and fascist techno-solutionism, focusing on artistic-activist resistances that can express a different mentality, a collective “counter-intelligence”.
10. “Algorithmic Sabotage” is an emancipatory defence of the need for communal constraint of harmful technology, a struggle against the abstract segregation “above” and “below” the algorithm.

Interventions:
- Trapping AI.
- Police Officers Faces.
- Technopolitics of Fronts.

Our analysis revealed a significant decline in the quality of information shared on Twitter/X following the platform’s ownership transition. Before the acquisition, both the Twitter panel and Decahose datasets exhibited slight improvements in information quality before the acquisition on October 27, 2022, but after the transition, this trend reversed, leading to a measurable decline in the credibility of shared sources. This pattern is evident across different measures of credibility and was confirmed by an interrupted time series (ITS) analysis, which detects a sharp decline immediately after the acquisition, followed by a sustained downward trend. These findings suggest that changes in platform governance and user behavior correspond with a deterioration in the quality of shared content.

After his staffer’s baby was woken up by a loud ad on a streaming service, a California senator took action to force streamers to turn down the volume on commercials. The entertainment industry is fighting it.

Proposed CA law would lower volume on streaming service ads

A California bill would ban loud ads on Netflix and Hulu, applying TV-style volume rules to online commercials

^{Ryan Sabalow (CalMatters)}

Hundreds of activists staged a protest outside the UN's “AI for Good” summit in Geneva demanding: No AI for genocide and war crimes.

The UN’s partnership with tech companies enabling Israel’s genocide against 2.3 million Palestinians in Gaza is:
UNethical
UNlawful
UNacceptable

By providing cloud infrastructure and AI technologies to the Israeli military, UN tech partners Microsoft, Amazon, Google, Cisco, Oracle, Palantir and IBM are deeply complicit in Israel’s regime of apartheid and genocide against Indigenous Palestinians.

Israel’s is the first AI powered genocide.

We call for global pressure on the UN and its member States to take the below actions.

AI’s impact on human rights is not limited to Palestinians. But as the “test subjects” for militarized technologies exported globally and as survivors of Israel’s ongoing, AI-assisted genocide, Palestinians are a canary in the coal mine warning the world of the catastrophic future of weaponized AI.

Source.

Australia’s eSafety Commissioner has registered three of the nine codes submitted to eSafety by the online industry, creating safeguards to protect children from exposure to pornography, violent content, and themes of suicide, self-harm and disordered eating.
The three include a code relating to search engine services, as well as codes covering enterprise hosting services and internet carriage services such as telcos.

“These three codes needed to create a high level of protections, especially for kids, to be registered. In particular, the fact the search engine code has achieved this is incredibly important as search engines are often the windows to the internet for all of us.”

David Franklin Slater, 64, of Nebraska, after retiring as a Lieutenant Colonel from the U.S. Army, worked in a classified space at USSTRATCOM and held a Top Secret security clearance from in or around August 2021 until in or around April 2022. Slater pleaded guilty to willfully, improperly, and unlawfully conspiring to transmit National Defense Information classified as “SECRET,” which he had reason to believe could be used to the injury of the United States or to the advantage of a foreign nation, on a foreign online dating platform to a person not authorized to receive such information.

Slater attended USSTRATCOM briefings regarding Russia’s war against Ukraine that were classified up to TOP SECRET//SENSITIVE COMPARTMENTED INFORMATION (TS//SCI). Slater then conspired to transmit classified National Defense Information that he learned from those briefings via the foreign online dating website’s messaging platform to his co-conspirator, who claimed to be a female living in Ukraine on the foreign dating website. The co-conspirator regularly asked Slater to provide her with sensitive, non-public, closely held, and classified National Defense Information and called Slater in their messages her “secret informant love” and her “secret agent.” In furtherance of that conspiracy, Slater did, in fact, transmit classified National Defense Information to her, including regarding military targets and Russian military capabilities relating to Russia’s invasion of Ukraine.

Air Force Employee Pleads Guilty to Conspiracy to Disclose Unlawfully Classified National Defense Information

A civilian employee of the U.S. Air Force assigned to the U.S. Strategic Command (USSTRATCOM) at Offutt Air Force Base pleaded guilty today to conspiring to transmit classified information relating to the national defense (National Defense Informatio…

^{www.justice.gov}

https://simonwillison.net/2025/Jul/11/grok-musk/#atom-entries

https://www.engineering.columbia.edu/about/news/need-new-3d-material-build-it-dna

Welcome to Codidact, the community-run, open-source Q&A platform. We're working together to build communities around high-quality, peer-reviewed questions, answers, articles, and other content. Codidact puts people first; we're here to help you share knowledge and get curated answers in a friendly environment.

Welcome to Codidact, the community-run, open-source Q&A platform. We're working together to build communities around high-quality, peer-reviewed questions, answers, articles, and other content. Codidact puts people first; we're here to help you share knowledge and get curated answers in a friendly environment.

Welcome to Codidact, the community-run, open-source Q&A platform. We're working together to build communities around high-quality, peer-reviewed questions, answers, articles, and other content. Codidact puts people first; we're here to help you share knowledge and get curated answers in a friendly environment.

PDF.

Amazon, the largest online retailer in the United States for more than a decade, is poised to overtake Walmart to become the country’s top retailer, full stop.To meet the “fast, free shipping” promise at the heart of its strategy to achieve retail dominance, the corporation has built an army of contingent and subcontracted last-mile delivery workers. The most underpaid and precarious among them, making the speediest deliveries, are managed by Amazon’s Uber-like delivery platform called “Amazon Flex.”

This brief identifies key facets of the Amazon Flex labor model and discusses their negative impacts on job quality. It draws on Amazon’s own corporate filings, statements, and contracts, as well as government documents, press reports, research by academics, industry groups, and advocacy organizations, and conversations with Flex drivers organizing in New Jersey. It concludes by recommending organizing, policy, and legal interventions for improving the conditions of Flex drivers and a growing population of workers facing similar challenges on the job.

Key Points

• Amazon uses a system of interconnected labor practices—digital surveillance, algorithmic management, independent contractor misclassification, mandatory arbitration, and class action waivers—to maximize the labor value it can extract from Flex delivery drivers and to minimize the responsibility it bears for their job quality.
• That labor model subjects Flex drivers to intolerable and often illegal working conditions, including systematic wage theft, unlivable pay, inadequate benefits, unsafe work speeds, racial discrimination, job insecurity, unpredictable schedules, and a lack of recourse for workplace mistreatment.
• Through Flex and its public policy work, Amazon is eroding labor standards in the broader last-mile delivery sector and beyond.

Key Recommendations
- Amazon labor model changes: Amazon should properly classify Flex drivers as employees under labor and employment laws, eliminate independent contractor agreements, arbitration clauses, and class action waivers in its Flex driver contracts, and end its use of opaque algorithmic management practices. But Amazon is unlikely to do any of that without worker and government action.
- Organizing support: Labor institutions, worker advocacy groups, and funders should support Flex driver organizing—because organized workers can raise job standards by making direct demands of Amazon and by advancing public policy change.
- Public policy change: To compel change to the Flex labor model, policymakers should establish worker data rights (including the right to access and correct data used in work management), regulate workplace digital surveillance and algorithmic management, ensure Flex drivers and other app-based workers have full access to gold-standard worker protections, and ban mandatory arbitration and class action waivers.
- Public enforcement and investigation: State Attorneys General and City Attorneys should take legal action against Amazon Flex for independent contractor misclassification. State workforce agencies should conduct unemployment insurance and workers’ compensation audits of Amazon’s Flex operations to quantify losses to state coffers resulting from Amazon’s misclassification of Flex drivers as independent contractors. The Federal Trade Commission should investigate Amazon’s independent contractor misclassification and use of mandatory arbitration in its Flex operation as anticompetitive issues. And members of Congress, following their probe of the Amazon Delivery Service Provider program, should launch an inquiry into the shadowy Amazon Flex operation.

Delivering Precarity: How Amazon Flex Harms Workers and What to Do About It - National Employment Law Project

This brief identifies key facets of the Amazon Flex delivery app’s labor model and discusses their negative impacts on Flex driver job quality.

^{National Employment Law Project}

Why did The Walrus outlet accept this sponsorship?

They have enough number of readers to do the right thing.

we're making updates to better match how people discover trending content today by shifting away from one all-encompassing Trending list towards category-specific charts that we’ll continue to invest in over time.

we're making updates to better match how people discover trending content today by shifting away from one all-encompassing Trending list towards category-specific charts that we’ll continue to invest in over time.

pilot project equips select City collection trucks with camera-based technology to identify contamination in real time. The AI system analyzes the contents of recycling carts as they are emptied into the truck and flags materials that do not meet local recycling guidelines.

When contamination is detected, residents will receive a personalized postcard with clear guidance on which items are not accepted and tips on how to recycle properly. The goal is to reduce contamination, increase efficiency in processing and promote more effective recycling habits throughout the city.

https://www.centervilleohio.gov/CivicAlerts.aspx?AID=146