I want to get back into creating stuff, and so I think I’m going to dedicate Saturdays to making something. I think about how J. Cole mentioned his six minute drill, where he would make a song in six minutes. I’m hoping that I take two or three hours on a Saturday to make some thing from start to finish. If I want to take more time than that then absolutely go ahead with that. But I think making something with such a wonderful use of my time. Even if the thing I made today was a really fucking stupid thirst trap with me data moshing from a cowboy into a cow-boy. No further questions lol.

A zine chronicling the Conquering the Barbarian Altanis D&D campaign.

This issue details sessions 111, 112, and 113.

Adventurers feel the burden of geas.

You can download the issue here.

Overlord's Annals zine is available as part of the Ever & Anon APA, issue 12:

#Zine

Picture, for a moment, the file. It does not exist on paper. It exists as a row in a database held on a server somewhere in the National Police Chiefs' Council estate, on a Home Office machine in Marsham Street, or in the back end of a contractor's analytics platform racked in a data centre on the edge of a Reading business park. The row contains a name, an address, a list of associations and a risk score. The man whose name sits in the first column does not know the row is there. He has not been arrested, charged, cautioned or interviewed. He has not been told that an algorithm has assessed his propensity for predatory violence against women and girls and returned a number high enough to place him in the top one thousand most dangerous men in England and Wales. He cannot ask to see the file. He cannot appeal its conclusions. He may, however, find that the police know his car, his routine and his ex-partner's address before he has met the constable on his doorstep. The file precedes him.

This is V1000, the proposal that broke into the British public sphere in January 2026 when the Telegraph reported that Sir Andy Marsh, head of the College of Policing, was advocating the use of predictive analytics to identify the one thousand men deemed most likely to commit predatory offences against women and girls before any such crime had been committed. The scheme modelled itself on the Met's V100 programme, launched in summer 2023, which uses a points-based scoring system to rank the hundred London men assessed each month as posing the greatest risk to women. By autumn 2025 V100 had produced over 200 convictions with sentences totalling more than 676 years. V1000 is the same logic scaled tenfold and pushed nationwide, embedded in a Home Office white paper that Home Secretary Shabana Mahmood unveiled in late January 2026 as the most significant reorganisation of British policing in two centuries. In the same round Mahmood reached for the line about “the eyes of the state” being “on you at all times,” a sentence that invokes Bentham's panopticon and that, as Silkie Carlo of Big Brother Watch has long argued, does not belong in a healthy democracy.

The panopticon line is not the most consequential thing the British state has said about predictive policing in the past eighteen months. The most consequential thing it has done is build systems that go further than V1000 contemplates, and do so largely without telling the public. In April 2025 Statewatch published freedom-of-information documents showing that the Ministry of Justice had been quietly developing a Homicide Prediction Project, since renamed “sharing data to improve risk assessment.” Commissioned under Rishi Sunak's premiership in January 2023, it draws on records held by the Ministry of Justice, the Home Office, Greater Manchester Police and the Metropolitan Police, ingests data on between 100,000 and 500,000 people, and was designed to model who was most likely to commit murder. The contract documents specifically identified mental health, addiction, self-harm, suicide history, vulnerability and disability as variables expected to give the model “significant predictive power.” Sofia Lyall, the Statewatch researcher who led the work, described it as “the latest chilling and dystopian example” of British state crime-prediction, a tool that would “reinforce and magnify the structural discrimination underpinning the criminal legal system.” A previous Ministry of Justice tool, the Offender Assessment System known as OASys, had already been shown to produce less accurate predictions for Black offenders than for white ones.

A government is framing predictive policing, in public, as a solution to a serious category of violent crime. In practice it is constructing infrastructure that does substantially more than the framing acknowledges, with forces whose underlying data has been repeatedly shown by their own regulators to be racially skewed. The question the Telegraph's January 2026 reporting forces is what kind of legal order can accommodate such systems without ceasing to be a legal order at all.

The Inventory of the American Experiment

Across the Atlantic, the Brennan Center for Justice published on 20 November 2025 a report titled The Dangers of Unregulated AI in Policing, authored by Rachel Levinson-Waldman, director of the Center's Liberty and National Security Program, and Ivey Dyson, counsel in that programme. The report is an inventory of the systems police departments across the United States have adopted, in most cases without public debate, legal frameworks governing accuracy, or mechanisms for the surveilled to contest their inclusion. It names the New York City, Los Angeles, Chicago, Boston, Pasco County Sheriff's Office and Washington DC Metropolitan police departments as forces that have deployed AI-driven data-fusion platforms to compile risk profiles and direct enforcement. It documents that 80 to 90 per cent of investigated ShotSpotter gunfire alerts in the cities where the system has been studied have produced no confirmed gun-related offence. It records that at least eight of the ten wrongful arrests known to have been based on facial recognition involved Black individuals. It notes that over 95 per cent of Suspicious Activity Reports forwarded to the FBI between 2010 and 2017 were never investigated, which means the act of generating, ingesting and storing the report, with all its downstream consequences for the person reported, was sufficient injury in itself.

The Brennan Center's argument is not that any single component is faulty. It is that the combination of components, the absence of accuracy standards, the opacity of procurement, and the inability of the surveilled subject to challenge the conclusions drawn about them, together produce a regime the United States constitutional tradition has no vocabulary for. The November 2025 report extends Levinson-Waldman's decade of work on police surveillance to the data-fusion era, where the question is no longer whether a given algorithm predicts crime accurately but whether the assemblage of inputs, scoring, surveillance and consequence functions as an extralegal apparatus that bypasses the protections the rest of criminal procedure was built to enforce.

The American case studies do not require imagination. Chicago ran the Strategic Subject List, colloquially the heat list, from 2012 onwards, assigning everyone it identified a score representing their assessed risk of involvement in gun violence. Robert McDaniel, a Black man then aged twenty-two and living on the South Side, received an unannounced visit from a police commander in late 2013 warning him not to commit further crimes. McDaniel's prior record consisted of a marijuana-possession charge and an illegal-gambling offence. He had attracted attention not for violent conduct but because of where he lived and whom he knew. The visit was sufficient, in his account and in the record assembled by reporters at the Verge, to mark him in his neighbourhood as a police informant. He was shot and wounded shortly afterwards. He was shot at again years later. The heat list was discontinued in early 2020 after a RAND Corporation audit found the early programme had no measurable preventative impact on gun violence and that its principal observable consequence had been a heightened concentration of police contacts on those whose names appeared on it.

In Pasco County, Florida, the Sheriff's Office ran its Intelligence-Led Policing programme, in which a computer system identified people predicted to commit future crimes, including many under eighteen. Deputies were instructed to make frequent “prolific offender checks,” which in practice meant arriving at the door, photographing the household, citing the resident for minor infractions like uncut grass, and returning at intervals. The Institute for Justice filed a federal lawsuit in 2021 on behalf of four residents, including Dalanea Taylor, Tammy Heilman and Robert A. Jones III. In December 2024 the Sheriff's Office settled, paid $105,000, and accepted that the programme had exceeded officers' implied licence to knock on doors, interfering with the plaintiffs' First, Fourth and Fourteenth Amendment rights. It is one of the few US legal proceedings in which a court extracted a clear finding that a predictive policing programme had violated constitutional rights, and only because the office settled rather than risk a precedent-setting trial.

The COMPAS recidivism-risk algorithm, used in pre-trial bail and sentencing across the United States, was the subject of a 2016 ProPublica investigation by Julia Angwin, Jeff Larson, Surya Mattu and Lauren Kirchner that compared COMPAS scores assigned to more than 7,000 people arrested in Broward County, Florida, with their actual subsequent offending. Black defendants were almost twice as likely as white defendants to be incorrectly flagged as high risk while not actually re-offending; even controlling for criminal history, age and gender, they were 77 per cent more likely to be classified as higher risk of future violent offending. Eric Loomis, whose Wisconsin appeal reached the State Supreme Court in 2016, had no meaningful way to inspect the algorithm or challenge his score because it was a trade secret of a private firm and the court accepted that contention. The court upheld the score's use while cautioning that future cases might raise due-process violations if judges did not understand the tool's limits. The caution was not operationalised in any subsequent precedent. The tool remains in use.

What “Pre-Crime” Means When the Statute Catches Up

In February 2026 the USC Dornsife Scribe published an analysis by Jerry Wood, The Pitfalls of Predictive Policing in the Minority Report, that extended the comparison the Telegraph's coverage had invited. The Philip K. Dick story, first published in 1956 and adapted by Steven Spielberg in 2002, imagines a world in which three precognitive humans foresee murders before they occur and the state arrests the would-be perpetrators on the strength of the forecast. The fictional system's conceit is that it works, in the narrow sense that those arrested would, in the absence of intervention, have committed the crimes attributed to them. Real predictive policing systems carry no such guarantee. They are statistical, probabilistic and unverifiable: the prediction's accuracy cannot be tested without permitting the predicted event to occur, and the prediction's effect on subsequent behaviour cannot be cleanly separated from the effect of the police intervention it triggers.

The Dornsife piece reaches back to scholars including Sarah Brayne, whose 2020 ethnography of the LAPD's use of Palantir Gotham, Predict and Surveil, documented how the platform fused arrest records, license-plate reads, field-interview cards, gang databases, foreclosure records, vehicle registrations and noise complaints into a single interface that extended police gaze into every artefact of municipal life. Brayne's central observation is that the platform did not introduce new biases so much as ratify and amplify the biases already encoded in the underlying records, with the additional property that the ratification appeared, to its users, to be objective and authoritative.

Andrew Guthrie Ferguson, whose 2017 book The Rise of Big Data Policing remains the most thorough legal account of the field, has made a parallel argument about the problem algorithmic policing poses for American criminal procedure. The Fourth Amendment protects against unreasonable searches but does not obviously regulate the construction of a database that renders a person more likely to be searched in future. The Fourteenth Amendment's Due Process Clause protects against the deprivation of liberty without due process, but the liberty interest in not being stigmatised by a state-held risk score has, with the partial exception of the Pasco settlement, not been recognised as cognisable. The Equal Protection Clause demands evidence of discriminatory intent, which is rarely demonstrable in an algorithm's designers, while the discriminatory effect of biased training data is attributed by the algorithm's defenders not to the algorithm but to the world it describes. The American constitutional vocabulary was not built for the problem.

The British position is different in detail and, in some respects, more permissive of executive action. The United Kingdom lacks a single written constitution and operates through a combination of common-law principles, the Human Rights Act 1998, the Data Protection Act 2018, the Equality Act 2010, and the supervisory authority of the Information Commissioner's Office. The Gangs Matrix maintained by the Metropolitan Police, on which 79 per cent of those listed as of late 2021 were Black, was the subject of an ICO enforcement notice in November 2018 finding it in serious breach of data-protection legislation, and a 2022 judicial-review settlement in which the Met accepted that the matrix had been operated unlawfully. The settlement created, for the first time, a right for those listed to request access to their inclusion, but did not extend to a substantive right of challenge, and the matrix continued to operate in modified form. Amnesty International UK's Automated Racism report of 20 February 2025 found that at least thirty-three police forces across the UK were operating predictive profiling or risk-prediction systems in “flagrant breach” of national and international human-rights obligations because they were being used to racially profile people and to undermine the presumption of innocence by targeting them before any crime had been committed.

The Regulator Wakes, Slowly

The AICerts coverage of February 2026 captured a moment in which regulators in multiple jurisdictions began to confront, in coordinated rather than fragmentary fashion, the growing evidence that predictive policing systems were not merely imperfect but structurally biased. The European Union's AI Act, whose Article 5 prohibitions came into force on 2 February 2025, includes at Article 5(1)(d) a categorical ban on AI systems that “assess or predict the risk of a natural person committing a criminal offence, solely on the basis of profiling or assessing personality traits and characteristics.” The operative word is “solely,” which European AI lawyers have read as carving out systems that combine profiling with at least one element of “objective and verifiable” evidence linked to criminal activity. The carve-out, narrow on its face, is wide in practice. Almost any predictive system in operation, including any conceivable V1000 successor, can be characterised by its operators as drawing on objective inputs in addition to profiling. The European Data Protection Supervisor and a coalition of civil-society organisations have called for the carve-out to be tightened. The lobbying continues; the systems continue to operate.

In the United States the regulatory landscape is more fragmented. The White House Office of Management and Budget issued in 2024 a memorandum requiring federal agencies to conduct impact assessments for “rights-impacting” AI uses, including in law enforcement. The memorandum does not apply to state and local police departments, which conduct the overwhelming majority of policing. New York City's POST Act requires the NYPD to publish impact and use policies for surveillance technologies; the Brennan Center has argued that the policies published in compliance are so generic and so devoid of operational detail that they impede rather than enable meaningful public oversight. In February 2026 the Department of Homeland Security signed a blanket purchase agreement, reported by AICerts and several other outlets, valued at up to $1 billion for data-fusion software, an order of magnitude that compresses the federal procurement timeline below the speed of any plausible regulatory response.

The pattern is consistent. Departments procure predictive systems on operational rationales emphasising efficiency. They deploy them before the frameworks that govern them are drafted. They publish, at best, impact assessments after deployment. They reform at the margins in response to litigation. They continue, in substance, to use them. The regulatory pace is slower than procurement by years; procurement is slower than the technology by months. The accumulation is of systems whose operation runs ahead of the legal vocabulary needed to discipline them.

The Feedback Loop Is the Architecture

The most consequential observation in the AICerts February 2026 reporting, and in the wider literature it summarises, is that predictive policing systems do not merely inherit historical bias in their training data. They constitute and reinforce that bias as a feature of their operation. The mechanism is well-documented. Place-based systems, of which PredPol was the most widely deployed in the 2010s, assess the likelihood of crime in a given location by reference to the recorded crime in that location. The recorded crime in a location is the product, in significant part, of the police presence in that location. When the algorithm directs additional police to a high-risk location, the additional observation generates additional recorded crime, which feeds back into the model as confirmation that the location is, indeed, high risk. The loop has been demonstrated mathematically by Kristian Lum and William Isaac, whose 2016 paper modelling PredPol on Oakland drug-arrest data showed that the algorithm would concentrate police attention in neighbourhoods where police had previously concentrated, regardless of the underlying distribution of drug use, which independent survey data showed to be roughly uniform across racial groups.

Person-based systems exhibit a parallel pattern. A score, once assigned, attracts police attention. That attention generates contacts, citations, arrests and intelligence reports, all of which feed the next score. The trajectory is not falsifiable from inside the system, because the system has no access to ground truth about what the person would have done absent the intervention. The USC Dornsife analysis of February 2026 framed the issue as one in which the algorithm “does not predict future behaviour so much as amplify past enforcement patterns.” The system reads the history of policing as the history of crime, the demographics of policed neighbourhoods as the demographics of criminality, and the absence of records from less-policed neighbourhoods as the absence of crime there. The output is not a forecast in any scientific sense. It is a re-presentation, in a vocabulary that carries the unearned prestige of mathematics, of the existing pattern of state attention.

The implications for V1000 are direct. The V100 draws on police records of prior incidents, intelligence reports, calls for service, witness statements and patterns of association. Each is shaped by the prior history of policing in the geographies from which they are drawn. The V100's reported success in producing convictions does not establish that the algorithm has identified the men who pose the greatest risk. It establishes that the algorithm has identified men against whom the police have been able to mount successful prosecutions, a related but distinct quantity. The Met has not disclosed false positive rates. It has not disclosed the demographic composition of the ranked cohort. It has not published an equality impact assessment specific to V100. The infrastructure on which V1000 will be built is one in which the most basic accuracy and fairness metrics are unpublished, the inputs are systematically shaped by the prior pattern of British policing, and the consequences of inclusion are, for the subject, materially significant and procedurally unchallengeable.

The Right Not To Be Predicted

What does due process require in the age of pre-crime prediction? The answer is not, despite the Minority Report comparison V1000 has invited, a categorical prohibition on statistical methods in policing. Police forces have always made resource-allocation decisions on the basis of pattern, intelligence and judgement. The question is what procedural protections must surround the use of automated systems that assign individual risk scores with material consequences for the people scored. A defensible regime requires, at minimum, the following.

The first requirement is notice. A person placed on a predictive watch list, assigned an individual risk score, or otherwise subjected to algorithmic risk assessment by a state agency must be told. The principle is foundational to procedural fairness in every developed legal system. It is, in the case of predictive policing, the requirement most uniformly violated. V1000 contemplates no notice. The Homicide Prediction Project contemplates no notice. The Gangs Matrix did not contemplate notice until the 2022 settlement forced a limited right of subject-access. The American systems documented by the Brennan Center contemplate no notice. The absence of notice forecloses every subsequent procedural protection, because the subject cannot challenge a process they do not know is happening.

The second requirement is access. The subject must be entitled to inspect the inputs used to generate the score, the weights assigned to them, and the reasoning by which the score was reached. The trade-secret defence asserted by Northpointe in the Loomis litigation, accepted by the Wisconsin Supreme Court, is incompatible with this requirement, and the Loomis precedent is increasingly viewed as a failure of judicial nerve. Where the algorithm is the product of a private vendor, the answer is not to defer to the vendor's commercial interest but to require, as a condition of public procurement, the disclosure of the algorithm and the underlying data to the subject and counsel.

The third requirement is challenge. The subject must have a substantive right of appeal, before an independent body, with the power to remove the subject from the list if the inputs are inaccurate, the inferences unjustified, or the algorithm itself shown to be discriminatory. The 2022 Gangs Matrix settlement created a right of subject-access without a meaningful right of substantive challenge. The Pasco settlement extracted a commitment to discontinue the programme but did not establish a generalisable right of challenge for similar programmes elsewhere. The EU AI Act creates rights of explanation for individuals affected by high-risk AI systems but excludes the systems used by law-enforcement and migration agencies in ways that render the protections substantially weaker for precisely the populations most subject to algorithmic harm.

The fourth requirement is audit. Police forces and ministries that deploy predictive systems must publish, on a regular cycle, accuracy and fairness metrics broken down by demographic group, and must subject the systems to independent evaluation by bodies with the technical capacity and legal authority to demand the underlying data. The RAND evaluation of Chicago's heat list is the prototype. It is also, fifteen years into the era of person-based predictive policing in the United States, almost the only such evaluation that has been published. The dearth is not coincidence. Audit threatens the operational autonomy of the agencies deploying the systems and the commercial value of the vendors supplying them. It is, for both reasons, systematically resisted. The remedy is statutory mandate.

The fifth requirement is proportionality. A tool that secures convictions of people who have already offended is a tool for prosecution. A tool that prevents offences before they occur is of a different and more constitutionally fraught character. The Met's V100 has, on the public record, secured convictions. It has not been shown to have prevented offences that would otherwise have occurred. Conflating the two is a category error V1000's public advocates have, throughout the white-paper process, declined to address.

The sixth requirement is reversibility. Where a predictive system has affected a person, the harm must be capable of being undone. A wrongful inclusion on a watch list, once acted upon, can produce harms that no subsequent administrative correction can reach. McDaniel's inclusion on the Chicago heat list, the police visit that announced it to his neighbours, and the shootings that followed are not events the eventual discontinuation of the programme could undo.

The Limits of the Architecture

These requirements, even if implemented in full, would not resolve every problem predictive policing presents. They would leave open the more fundamental question of whether some categories of state action are simply incompatible with a free society regardless of the procedures attached. The argument that V1000, the Homicide Prediction Project, the Pasco programme and the Chicago heat list share a common defect that no procedural architecture can repair is the argument civil-liberties organisations on both sides of the Atlantic have been making for the better part of a decade. The defect is the substitution of statistical inference for the substantive legal process by which a state is permitted to deprive a person of liberty. It is categorically incompatible with the presumption of innocence and with the requirement that punishment follow from the proof of an act rather than the prediction of one.

The Brennan Center, the USC Dornsife scholars, Amnesty International UK, Statewatch and Big Brother Watch have all reached the same operational conclusion. The current predictive-policing infrastructure does not meet the requirements of due process under any plausible reading of either constitutional tradition. The systems are deployed without notice, without access, without challenge, without audit, without demonstrated proportionality, and with effects that cannot be made reversible. The result, on the ground, is a regime in which a person can be placed on a list, surveilled, visited, photographed, cited, harassed and, in the worst cases, killed, on the basis of a model whose accuracy they cannot test, whose inputs they cannot inspect, and whose conclusions they cannot contest. This is not the rule of law. It is something else, wearing the rule of law's clothes.

The choice between V1000 and its alternatives is not a choice between safety and rights. It is a choice about which kind of safety, for which population, secured by which means, at the cost of which rights, for which other population. The men whose names will appear on the V1000 list will not be a representative sample of the men in England and Wales who pose a risk to women. They will be a sample whose composition reflects the patterns of British policing's prior attention. The list will, in the aggregate, generate convictions, because lists drawn from the records of police attention have always been able to generate convictions when police attention is renewed. The convictions will be cited as evidence the list works. The men wrongly included will not appear in the statistics. The crimes the list fails to prevent, by directing attention away from offenders whose patterns do not match the algorithm's training distribution, will not appear in the statistics either. The performance of the system will be measured by its consonance with itself.

The women whom V1000 is designed to protect have a separate set of interests. They have an interest in being protected from the men who pose risks to them, which is the interest the scheme's advocates have placed at the centre of the public case. They have, equally, an interest in a criminal-justice system whose treatment of suspects and convicted persons does not so corrode the legitimacy of state power that its eventual response to actual violence is rendered less, rather than more, effective.

The Standard the Moment Requires

A mature legal order would, faced with the V1000 proposal, have set the conditions of its operation in advance. It would have required the publication of the algorithm and its training data, at least to the Information Commissioner and to designated independent reviewers. It would have required an equality impact assessment, conducted before deployment and refreshed annually. It would have required notice to those placed on the list, with a substantive right of appeal to an independent tribunal. It would have required statutory limits on the actions police could take on the basis of inclusion, with particular protections for inputs derived from third-party data such as health, school or social-services records. It would have required regular external audit of accuracy, bias and operational outcomes. It would have required, before national rollout, evidence of demonstrable preventative effect in the form of a controlled comparison with non-algorithmic alternatives. It would have required, as a backstop, a sunset clause that withdrew the legal authority for the programme if the evidence of effectiveness did not materialise.

None of these conditions, on the public record as of late May 2026, have been set. The white paper announcing V1000 contains no published algorithm, no equality impact assessment, no notice mechanism, no appeal right, no statutory limit on consequential police action, no external audit framework, no controlled pilot evaluation, no sunset clause. The Telegraph's January 2026 reporting captured the moment at which a substantial expansion of British algorithmic policing was announced in advance of the procedural protections that would have rendered it constitutional in either the European or the American sense. The Brennan Center's November 2025 inventory, the USC Dornsife analysis of February 2026 and the AICerts coverage of the same month establish that the British announcement is the latest instance of a pattern, not an outlier.

The constitutional question is not whether the algorithm is accurate. It is whether the people whose lives it rearranges have any meaningful say in the rearrangement. They do not. Until they do, the systems being built in Britain and the United States, and increasingly in the European Union notwithstanding the AI Act's nominal prohibitions, are not predictive instruments in any rigorous sense. They are administrative instruments for the redistribution of state attention, dressed in the prestige of computation, that operate beyond the reach of the procedural protections the rest of the criminal-justice system, at least nominally, requires. The Minority Report comparison, which V1000's public advocates have treated as a rhetorical excess from civil-liberties campaigners, captures something the public advocates have not addressed. In the Dick story, the system worked. In the world the Telegraph described in January 2026, the system does not need to work to do harm. It needs only to be believed. The belief is the architecture, and the architecture is being poured.

What due process requires, then, is the recovery of a principle older than the technology that threatens it. The principle is that the state may act against a person on the basis of what they have done, after a process in which they can know the case against them, see the evidence, and answer it. The principle is not consistent with secret lists, secret scores, secret models and secret consequences. It does not bend because the technology has become sophisticated enough to make the bending operationally efficient. The men on the V1000 list, the people in the Brennan Center's American inventory, the residents whose lives the Pasco programme reorganised, the Black Londoners whose names the Gangs Matrix held, and the future subjects of systems yet to be procured all have the same basic claim. They have the right to know, the right to see, the right to challenge, and the right, before the state visits their door, to a process. The current generation of predictive systems treats that claim as administrative friction. The treatment is the failure. The recovery of the claim is the work.

References

1. Telegraph reporting on UK predictive policing plans, January 2026, as relayed via secondary coverage including GB News, “Police chiefs could trial 'Minority Report policing' to identify and catch criminals before they strike,” January 2026. https://www.gbnews.com/news/police-chiefs-trial-minority-report-policing-identify-catch-criminals-before
2. TechInformed. “Government bets on AI to predict and prevent crime.” 2026. https://techinformed.com/uk-government-bets-on-ai-to-predict-crime/
3. UK Government. From local to national: a new model for policing. White Paper, January 2026. https://assets.publishing.service.gov.uk/media/69779267276692606c013862/260125_White_Paper.pdf
4. Rachel Levinson-Waldman and Ivey Dyson. The Dangers of Unregulated AI in Policing. Brennan Center for Justice, 20 November 2025. https://www.brennancenter.org/our-work/research-reports/dangers-unregulated-ai-policing
5. Jerry Wood. “The Pitfalls of Predictive Policing in the Minority Report.” USC Dornsife Scribe, 27 February 2026. https://dornsife.usc.edu/scribe/2026/02/27/the-pitfalls-of-predictive-policing-in-the-minority-report/
6. AI CERTs News. “Regulators Confront Predictive Policing Bias.” February 2026. https://www.aicerts.ai/news/regulators-confront-predictive-policing-bias/
7. Amnesty International UK. Automated Racism: How police data and algorithms code discrimination into policing. February 2025. https://www.amnesty.org.uk/files/2025-02/Automated%20Racism%20Report%20-%20Amnesty%20International%20UK%20-%202025.pdf
8. Statewatch. “UK: Ministry of Justice secretly developing 'murder prediction' system.” April 2025. https://www.statewatch.org/news/2025/april/uk-ministry-of-justice-secretly-developing-murder-prediction-system/
9. Metropolitan Police. “Groundbreaking technology boosts Met's fight against violence towards women and girls.” https://news.met.police.uk/news/groundbreaking-technology-boosts-mets-fight-against-violence-towards-women-and-girls-498976
10. Metropolitan Police. “V100 Violence Against Women and Girls Programme data and impact assessments.” Disclosure October 2025. https://www.met.police.uk/foi-ai/metropolitan-police/disclosure-2025/october-2025/data-impact-assessments-mps-v100-violence-against-women-girls-programme/
11. Information Commissioner's Office. Enforcement notice issued to the Metropolitan Police Service, Data Protection Act 1998. November 2018. https://www.met.police.uk/SysSiteAssets/media/downloads/force-content/met/about-us/gangs-violence-matrix/ico-enforcement-notice.pdf
12. Youth Justice Legal Centre. “Metropolitan Police to overhaul 'racist' Gangs Matrix after landmark legal challenge.” https://yjlc.uk/resources/legal-updates/metropolitan-police-overhaul-racist-gangs-matrix-after-landmark-legal
13. Julia Angwin, Jeff Larson, Surya Mattu, Lauren Kirchner. “Machine Bias.” ProPublica, 23 May 2016. https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing
14. State v. Loomis, 881 N.W.2d 749 (Wis. 2016).
15. Jessica Saunders, Priscillia Hunt and John S. Hollywood. “Predictions Put Into Practice: A Quasi-Experimental Evaluation of Chicago's Predictive Policing Pilot.” RAND, 2016. https://www.rand.org/pubs/external_publications/EP67204.html
16. Techdirt. “How Predictive Policing Got A Chicago Man Shot Twice.” 3 June 2021. https://www.techdirt.com/2021/06/03/how-predictive-policing-got-chicago-man-shot-twice/
17. Institute for Justice. “Case Closed: Pasco Sheriff Admits 'Predictive Policing' Program Violated Constitution.” Press release. https://ij.org/press-release/case-closed-pasco-sheriff-admits-predictive-policing-program-violated-constitution/
18. Sarah Brayne. Predict and Surveil: Data, Discretion, and the Future of Policing. Oxford University Press, 2020. https://global.oup.com/academic/product/predict-and-surveil-9780190684099
19. Andrew Guthrie Ferguson. The Rise of Big Data Policing: Surveillance, Race, and the Future of Law Enforcement. NYU Press, 2017. https://nyupress.org/9781479892822/the-rise-of-big-data-policing/
20. Kristian Lum and William Isaac. “To predict and serve?” Significance, October 2016. https://rss.onlinelibrary.wiley.com/doi/10.1111/j.1740-9713.2016.00960.x
21. European Union. Regulation (EU) 2024/1689 (the AI Act), Article 5 prohibitions, applicable from 2 February 2025. https://artificialintelligenceact.eu/article/5/
22. Future of Privacy Forum. “Red Lines under the EU AI Act: Unpacking the Prohibition of Individual Risk Assessment for the Prediction of Criminal Offences.” https://fpf.org/blog/red-lines-under-the-eu-ai-act-unpacking-the-prohibition-of-individual-risk-assessment-for-the-prediction-of-criminal-offences/
23. Big Brother Watch. Director profile of Silkie Carlo and campaigns on facial recognition and predictive systems. https://bigbrotherwatch.org.uk/

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Tim Green UK-based Systems Theorist & Independent Technology Writer

Tim explores the intersections of artificial intelligence, decentralised cognition, and posthuman ethics. His work, published at smarterarticles.co.uk, challenges dominant narratives of technological progress while proposing interdisciplinary frameworks for collective intelligence and digital stewardship.

His writing has been featured on Ground News and shared by independent researchers across both academic and technological communities.

ORCID: 0009-0002-0156-9795 Email: tim@smarterarticles.co.uk

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In Summary: * A Saturday which for some strange reason has felt like a Sunday to me starts to wind down. Three special elements to this day have added to my regular chess and prayer work: a very enjoyable brunch this morning with the wife at Golden Corral; a challenging hour spent mowing in the front yard, “real feel” tremperature out there was 108F when I quit work and came inside; watching NASCAR Qualifying at the Michigan Speedway most recently as they set the field for tomorrow's big race. Now I'm ready for the fourth and final special element, the Rangers / Guardians MLB Game. So I'm turning off the TV and moving to the radio broadcast of the Rangers Pregame Show, and I'll stay with 105.3 The Fan for the call of the action. And that will complete my Saturday.

Prayers, etc.: * I have a daily prayer regimen I try to follow throughout the day from early morning, as soon as I roll out of bed, until head hits pillow at night.

Health Metrics: * bw= 234.02 lbs. * bp= 142/81 (71)

Exercise: * morning stretches, balance exercises, kegel pelvic floor exercises, half squats, calf raises, wall push-ups

Diet: * 06:00 – 1 banana * 06:50 – 1 peanut butter sandwich * 10:30 – big buffet meal at Golden Corral * 17:30 – 1 pb&j sandwich

Activities, Chores, etc.: * 05:45 – bank accounts activity monitored. * 06:10 – read, write, pray, follow news reports from various sources, surf the socials, nap * 10:20 to 11:40 – brunch with Sylvia at Golden Corral * 12:00 to 13:00 – yard work, mow on front yard * 13:15 – follow news reports from various sources, surf the socials, nap * 16:00 – watching NASCAR time trials at the Michigan Speedway to set the field for tomorrow's big race

Chess: * 15:10 – have moved in all pending CC games

I am on the edge of falling asleep, and that’s a great time to start writing. My therapist told me “you should keep up with your hobbies. Something nice to keep your hallucinations away.” I wasn’t sure of what hobbies she meant, but i cooked a dessert. i made a churro, heart-shaped. No, nothing romantic. It was the first thing that popped up when i was searching for something to do. a “nice hobby” because everything else wasn’t “nice” and away from my hallucinations. Regarding it, it tastes awesome, and im proud of it. That was the only good thing i did today. most of the day i was just asleep, drunk, staring at nothing for hours. and sick. And that should count as my normal routine now. I don’t care enough to argue back, to stop and change anything. Having my heart lively beating again is more concerning to me than the number of cigarettes I’ve been smoking. Its concerning. Whether it was that lost bride in my dreams or my illness and delusions are taking effect. Its concerning. And sure, this may seem like a silly goose concern, but it’s not when it disappears and comes in times you’d least expect, And that change was never on my “i know it’ll happen” lists. It was never on my list for people who don't follow the script. Usually, everyone acts like boring cattle walking straight into a slaughterhouse, completely predictable. This one jumped the fence. Now the whole plan is ruined. I love it.

I dont know what I’ll do, but I’ll figure it out, well. Maybe Not. I need to sleep and get on “nice hobbies.” I’ll just bake another useless pastry and see if it cures my schizophrenia. A heart-shaped churro won’t fix a broken mind, but at least it tastes better than my daily medication. Or just buy another pack of cigarettes and stare at the wall until the doorway looks empty again.

That sounds like a much more reliable script anyway.

Sincerely, Your Star Patient.

So there I was in 12th grade in my sixth period Spanish class with Ms.Dalfrey – who reminded me of Cameron Diaz’s character in Charlie’s Angels because they were both Blonde and hot despite mentioning how chronically uncool they were their teenage years due to being victimized by braces and their weight, but I digress.

This class was also where I experienced my first as they call it today, “queer awakening”. Set off by a very white, blue eyed blonde girl named Sarah who would also be described as masc. presenting by todays standards. idk about all of that I just know mama set off a fire in me without saying one word. to me despite sitting next to me for half a semester. I know how very gay of me ( I kind of livvveeeee for it though). It was just somethign about her. She was very understated and chill but has such a quiet confidence that we also would now describe as hey mamas energy. I just know she some where to this with a well coifed short hair cut, a wife and a dog and they go hiking every Saturday in Oregon or something.

Anywho, there I sat, in awe of the glossy pamphlet that laid on the table in front of me. Enticing me with pictures of young white students smiling and having the time of their lives in Spain as they stood in front of various Spanish architecture. Their was tons of information on the benefits of cultural immersion and its impact on how well you are able to pick up a new language and the self-reliance that grows when you are able to have new experience in new enviornamnts away from the familiar. And the best part about the program is that you would have been allowed to miss school to gallivant through the streets of Barcelona like the Galleria, Dorinda, Aqua and

At the time I was more excited by the fact that that days Spanish lesson was interrupted by a presentation walking through the contents of the pamphlet but over time with its gloss edges and new paper smell the pamphlet began to burn a whole in the back pocket of my binder and thus a whole right through me.

I was imemdigalye enamored with the idea of traveling not to learn Spanish but to e up out this podunk town on the edges of Alabama called La Grange, GA. I find it interesting that I went from city living in Brooklyn to a town with a population of 2,000 people with an average income of …. and yet this was the first time I heard about studying abroad. I thought this program was bigger than this place admittedly but despite the small town vibes there were several students who came from wealth as their families owned manufacturing companies. I know cause I would pass their large plantation style homes on the way to school in the morning.

But alas this was my first introduction to studying abroad and I was a desire I never let go. Especially considering this trip was well over 2000 and there was was no one either one of my parents were willing to foot the bill. So I sat and I stewed vowing that I would study abroad somehow someway!

I somehow forgot about this desire in trying to honor my social obligation to get into college because the weight of my entire future rested on this moment but was pleasantly reminded about my dream during freshmen orientation where my newfound collegiate home – 2 hours away from po-dunk la grange – boasted about their study abroad programs.

That week I found my way to the global education office where I questioned my newfound study abroad guide within an inch of her life while keeping a smile because she seemed just as happy to be a resource for me. And a resource she was. I asked if I would miss class, would have to share a rom, who pays for the plane ticket, etc. We finally got to the question about cost and I thought this woman would kick me out of her office for the though of mentioning money but without faltering she regaled me with all the options made available to me. It was like she wanted me to study abroad as much as I did. She let me know there were grants and scholarships available – this was my first lesson about accessibility I realize. She also let me know that there were loans that my parents could take out. But as independent as I was I said absolutely not (although that is exactly how I ended up studying abroad the first time, thanks to my mother’s sacrifice and my 8th house stellium that supports my ability to benefit from the resources of other names grants.)

I went home that day and swallowed every suggestion she gave. There was so much to consider – length, what to study, WHERE to study. And I decide a 2 month stay in London over the summer to learn computer science (my major at the time) was what I would do. My study abroad counselor advised me to submit an application that would automatically qualify me for every grant – for studying abroad and any other academic pursuits – that was a fit dependent on the info I provided. I was awarded a $300 grant and was over the moon. I cant remember how much the trip cost but it covered roundtrip intenrantialn airfare, my tuition, room and board (I GOT MY OWN ROOM!), a weekly 20 pound grocer stipend at tescos, public transportation, and tickets to view 3 shows in the west end – Londons world renowed theater district. Which was all a godsend when I eventually did get to London and was broke af where i learned my first travel lesson: exchange rates are a bitch. But that is a story for another day. The details of that trip are extensive so I don’t know if I would do a full recap but I would happily do “these are the things I learned from studying abroad” video if you would be interested I think it would be quite fun.

What wasn’t fun was telling my parents I had this very expensive dream with no wya to pay for it. My mom and Dad and I had a group discussion about the trip and I was scared for my life but they could see how passionate I was. My dad offered to put some money towards the trip and my mother ended up getting a parents PLUS loan to pay for the rest ( I think it ended up being forgiven so she didn’t have to pay it off). And the rest was history. I honestly don’t know who I would be today if it were fro those experiences. I view my 17-18 year old self with such awe because I was committed, focus and fearless in my pursuit to travel and have an experience that I wanted. It is a fire that would follow me throughout my life and it really taught me that I have the power to get exactly what I want even if I didn't know how – which isn’t my business most of the time.

If there’s one thing I regret in my life so far, it’s that I didn’t start smoking at an earlier age.

O corpo que sabe e o poder que o produz

Anthony Vincent está na rua. Já o vimos. Sabemos o que o seu corpo decide antes de pensar. Mas há uma pergunta que o gesto de Vincent abre e que este caderno deixou em suspenso até agora: o que sabe ele, exactamente? E por que é que esse saber — tão preciso, tão situado, tão encarnado — não é reconhecido como conhecimento pelos regimes que produzem verdades sobre discriminação, sobre desigualdade, sobre vidas cuir?

Esta é a pergunta onto-epistemológica que fecha este caderno. Não uma pergunta sobre sentimentos, nem sobre experiências individuais. Uma pergunta sobre poder: quem produz conhecimento legítimo sobre a discriminação? A partir de que corpo? Com que instrumentos? E ao serviço de que interesses?

Fotografia de George Kondylis (2020) — Uso gratuito sob Licença Pexels.

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O olhar que não vê o seu próprio lugar

Donna Haraway colocou esta questão com uma precisão que continua a ser inultrapassável. No seu ensaio sobre conhecimentos situados, Haraway identificou aquilo a que chamou o truque divino, the god trick, — a pretensão, característica da ciência e da epistemologia ocidental moderna, de produzir conhecimento a partir de lugar nenhum. O olhar que se diz neutro, objetivo, universal. O olhar que não precisa de se nomear porque se confunde com o padrão. O olhar que vê tudo porque, ao contrário de todos os outros olhares, não está em parte nenhuma — e, portanto, não está sujeito às distorções que afetam os olhares situados.

Este truque divino é uma ficção política. Não existe conhecimento sem corpo, sem posição, sem história. O olhar que se apresenta como neutro é sempre o olhar de alguém — e esse alguém ocupa uma posição social concreta que o seu discurso de neutralidade trabalha sistematicamente para esconder. A objetividade não é a ausência de perspetiva. É, como Haraway argumenta, a responsabilidade de assumir de onde se olha — de reconhecer a parcialidade do próprio conhecimento como condição de honestidade intelectual.

No campo dos estudos sobre discriminação, este truque tem consequências directas. Os estudos que medem a discriminação LGBT+ em Portugal, as políticas públicas que afirmam combatê-la, os enquadramentos jurídicos que prometem igualdade — todos partem de posições situadas que tendem a reproduzir, nos seus próprios instrumentos, as hierarquias que afirmam querer combater. Quando um estudo usa categorias binárias de sexo e género, está a operar a partir de uma ontologia que já decidiu o que existe e o que não existe. Quando uma política pública trata a discriminação como soma de opressões separadas, está a olhar a partir de uma posição que nunca habitou a interseção. Quando um formulário não tem onde pôr certas existências, não está a ser neutro — está a produzir a inexistência daquilo que não consegue categorizar.

O corpo que sabe porque existe

Karen Barad vai mais longe do que Haraway — ou melhor, aprofunda o gesto de Haraway até às suas consequências ontológicas mais radicais. Para Barad, a separação entre epistemologia e ontologia é ela própria uma ficção. Não é apenas que conhecemos a partir de posições situadas — é que conhecer e existir são processos inseparáveis. O que chamamos realidade é produzido por práticas material-discursivas que são simultaneamente físicas, institucionais, normativas e cognitivas. Não há, de um lado, os corpos que existem, e do outro, os sujeitos que os conhecem. Há intra-ações — encontros entre corpos, instrumentos, normas e discursos — que produzem simultaneamente o que existe e o que pode ser conhecido sobre o que existe.

Aplicado à questão que este texto coloca, isto significa que quem sabe o que dói não sabe por acaso, nem por sensibilidade especial, nem por proximidade afetiva com o sofrimento. Sabe porque o seu corpo foi produzido — pelos mesmos aparelhos que produzem o conhecimento sobre ele — como o lugar onde a dor se inscreve. O corpo de Vincent não preexiste aos aparelhos policiais, médicos e jurídicos que o leem como suspeito, como abjeto, como excesso. É produzido por eles — e é precisamente por ser produzido por eles que sabe, de dentro, como funcionam.

Isto é onto-epistemologia no sentido mais rigoroso: o saber e o ser estão entrelaçados de forma inextricável. Separar a experiência de Vincent do conhecimento que ela produz — tratá-la como anedota pessoal irrelevante para a produção de saber legítimo — é reproduzir exatamente o truque divino que Haraway denunciou. É fingir que o olhar que não habita a interseção é mais confiável do que o olhar que a habita. É confundir distância com objetividade.

Os instrumentos que não veem o que medem

A produção de conhecimento sobre discriminação opera por meio de instrumentos concretos: estudos, inquéritos, bases de dados, relatórios, indicadores. Estes instrumentos não são neutros — são dispositivos material-discursivos, no sentido que Barad dá ao conceito, que participam na produção daquilo que medem. As categorias que usam, as perguntas que fazem, as existências que conseguem capturar e as que deixam escapar — tudo isto é efeito de posições situadas que os instrumentos trabalham para tornar invisíveis.

O Estudo Nacional sobre Necessidades das Pessoas LGBTI em Portugal, que o texto 3 desta série mobilizou, é um esforço sério e rigoroso de tornar visível o que a produção de dados tende a apagar. Mas mesmo os melhores instrumentos têm limites que são também limites ontológicos: as categorias disponíveis determinam o que pode ser dito, e o que não tem categoria disponível tende a desaparecer nos intervalos entre as caixas de verificação.

Pessoas que habitam interseções complexas — negras e cuir e trans e migrantes e precárias — produzem experiências de discriminação que os instrumentos de medição não conseguem captar na sua singularidade. Não porque sejam raras ou marginais, mas porque os instrumentos foram desenhados a partir de posições que não as habitam — e, portanto, não sabem exatamente o que perguntar, nem como perguntar, nem onde procurar. O que não é perguntado não é medido. O que não é medido não existe para a política pública. O que não existe para a política pública não é combatido. É um ciclo de produção de inexistência que começa na epistemologia e termina nos corpos.

O saber das margens como rigor

Há uma tentação, quando se fala de conhecimentos situados e de saberes encarnados, de cair no relativismo — de concluir que todos os saberes são igualmente válidos, ou que a experiência vivida vale tanto quanto a análise estrutural, ou que o pessoal é automaticamente político. Não é isso que Haraway diz, nem é isso que este caderno defende.

O que está em causa não é substituir o conhecimento estrutural pela experiência individual. É reconhecer que certas posições — as que habitam as interseções que o conhecimento dominante não ocupa — produzem saberes sobre o funcionamento do poder que os instrumentos dominantes não conseguem captar. Não porque a margem seja romanticamente mais autêntica do que o centro. Mas, porque a margem vê o centro de um ângulo que o centro não consegue ver a partir de si próprio.

Vincent sabe coisas sobre a interseção de raça, sexualidade e vigilância policial que nenhum estudo académico sobre discriminação consegue capturar inteiramente — não porque o estudo seja mau, mas porque foi desenhado a partir de uma posição que não habita aquela interseção. Esse saber não é subjetivo nem anedótico. É situado — o que, para Haraway, é a condição de qualquer conhecimento rigoroso. A diferença é que o saber de Vincent não pode esconder a sua situação, enquanto o saber que se pretende neutro esconde a sua atrás de uma pretensão de objetividade que é ela própria uma posição política.

Reconhecer isto não é romantizar as margens. É levar a sério a epistemologia — é aplicar ao próprio conhecimento sobre discriminação os critérios críticos que aplicamos a tudo o resto. Quem produz este saber? A partir de que corpo? Com que instrumentos? O que fica de fora? E quem beneficia do que fica de fora?

Escrever desde os corpos

Este caderno começou com uma fábrica. Termina com um corpo na rua.

Entre a fábrica da masculinidade e o gesto de Anthony Vincent, percorremos um trajeto que foi sempre o mesmo: a masculinidade hegemónica como regime material-discursivo que produz corpos, hierarquias e saberes — e que, ao produzi-los, produz também o que fica de fora, o que é descartado, o que é tornado invisível, ou abjeto, ou impossível.

A cuirografia que este caderno propõe não é apenas uma escrita sobre corpos. É uma escrita desde corpos — desde posições situadas, desde margens que veem o centro com uma clareza que o centro não tem sobre si próprio. Escrever desde as margens não é uma limitação nem uma desvantagem epistémica. É uma condição de honestidade intelectual: assumir de onde se olha, reconhecer o que o próprio olhar não consegue ver, e construir conhecimento a partir dessa responsabilidade e não apesar dela.

Que corpos contam? Os que a fábrica reconhece como legítimos. Os que cabem nos formulários. Os que a lei protege. Os que a comunidade acolhe. Os que o conhecimento dominante consegue ver.

E os que não contam? São os que este caderno tentou tornar visíveis — não como vítimas, não como casos de estudo, mas como sujeitos epistémicos cujo saber sobre o funcionamento do poder é politicamente indispensável. Porque é nos corpos que a hegemonia descarta que se vê com mais clareza como a máquina funciona. E é a partir desses corpos que se pode, com mais rigor e com mais honestidade, pensar como a desmontar.

Leituras

Donna Haraway, Situated Knowledges: The Science Question in Feminism and the Privilege of Partial Perspective (1988). O ensaio fundador dos conhecimentos situados, que é simultaneamente uma crítica à pretensão de objetividade universal e uma proposta epistemológica alternativa: o conhecimento parcial, localizado e responsável como condição de rigor. Indispensável para qualquer análise crítica que leve a sério a pergunta sobre quem produz conhecimento e a partir de que posição.

Karen Barad, Meeting the Universe Halfway: Quantum Physics and the Entanglement of Matter and Meaning (2007). O realismo agencial de Barad oferece as ferramentas para pensar a inseparabilidade entre ontologia e epistemologia — entre o que existe e o que pode ser conhecido. Neste texto, Barad é mobilizada para mostrar que o saber encarnado não é menos rigoroso do que o saber que se pretende neutro: é simplesmente mais honesto sobre as suas condições de produção.

Karen Barad, TransMaterialities: Trans*/Matter/Realities and Queer Political Imaginings (2015). Um texto mais curto e mais acessível do que Meeting the Universe Halfway, onde Barad articula o realismo agencial com questões trans e cuir. Uma leitura que mostra como a onto-epistemologia baradiana se aplica diretamente à análise das existências que a hegemonia produz como impossíveis ou abjetas.

Donna Haraway, The Promises of Monsters: A Regenerative Politics for Inappropriate/d Others (1992). Um texto complementar ao ensaio sobre conhecimentos situados, onde Haraway desenvolve a ideia de figuras parciais e conexões inesperadas como estratégia política e epistemológica. A leitura em conjunto com “Situated Knowledges” aprofunda a proposta de uma objetividade encarnada e responsável.

Sandra Saleiro, Nelson Ramalho, Mafalda de Menezes e Jorge Gato, Estudo Nacional sobre Necessidades das Pessoas LGBTI e sobre a Discriminação em Razão da Orientação Sexual, Identidade e Expressão de Género e Características Sexuais (2022). Mobilizado aqui não apenas como fonte de dados, mas como exemplo de um instrumento de produção de conhecimento — com os seus limites e as suas potencialidades — sobre discriminação LGBT+ em Portugal. Uma leitura que ganha em ser feita com olho crítico sobre as categorias que usa e as que não consegue capturar.

Anthony Vincent, Peau noire, masque arc-en-ciel, in Florent Manelli (org.), Pédés (2023). Antologia de testemunhos de homens gays e bissexuais em França, onde se publica o texto de Anthony Vincent que serve de ponto de partida a este ensaio. Uma obra que toma a sério a experiência vivida como matéria política e teórica — e que recusa a separação entre o pessoal e o estrutural.

#cuir #kuir #ontoepistemologia #conhecimentossituados #intersecionalidade #masculinidades #barad #haraway #anthonyvincent #Caderno2 #desdeasmargens

Quando si parla del Ponte Vecchio di Mostar si pensa quasi sempre alla sua storia, alla sua bellezza o alla sua distruzione durante la guerra. Raramente lo si considera un oggetto educativo.

Eppure, osservando il lavoro di una scuola dell'infanzia della città, ho capito che il vero valore del ponte non risiede soltanto nelle sue pietre. Risiede nella sua capacità di formulare domande.

I bambini hanno iniziato portando a scuola fotografie, oggetti e ricordi legati alla città. Hanno osservato manufatti tradizionali, ascoltato racconti, discusso tra loro. Poi sono arrivate le domande: perché il ponte è importante? Cosa c'è sotto il ponte? Chi ci può aiutare a conoscerlo meglio?

Le risposte non provenivano dai libri. Provenivano dalle famiglie, dai musei, dalle esperienze personali, dalla memoria della città. A poco a poco, il ponte è diventato qualcosa di più che un monumento. È diventato un progetto di ricerca.

I bambini lo hanno disegnato, costruito, visitato e reinterpretato. In questo modo hanno imparato storia, osservazione, linguaggio, collaborazione e rappresentazione grafica. Ma soprattutto hanno imparato che la conoscenza nasce dalla relazione con il luogo in cui si vive.

La geopedagogia parte proprio da qui. Ogni territorio custodisce luoghi che raccontano chi siamo. Una montagna, una piazza, un mercato, un fiume o un ponte possono diventare potenti strumenti educativi se la scuola sceglie di ascoltarli.

Per gli adulti il Ponte di Mostar è spesso il simbolo di una ferita e della sua ricostruzione. Per i bambini è qualcosa di più semplice e forse di più importante: un collegamento tra due sponde.

Forse l'educazione dovrebbe fare lo stesso. Prima di trasmettere contenuti dovrebbe costruire ponti. Tra persone, tra generazioni, tra culture e tra visioni del mondo.

In fondo, educare significa proprio questo: aiutare qualcuno a passare da una riva all'altra senza perdere se stesso lungo il cammino.

Qualche anno fa mi trovavo in un piccolo villaggio dell'Uzbekistan occidentale. Avevo trascorso la giornata visitando una scuola dell'infanzia e, come spesso accade, la parte più interessante non era stata quella ufficiale. Non erano stati i documenti, né le presentazioni preparate per la delegazione internazionale. Era successo tutto alla fine della visita, quando alcuni bambini avevano lasciato il giardino della scuola per tornare a casa.

Li osservavo allontanarsi lungo una strada sterrata. Alcuni erano accompagnati dai genitori, altri dai fratelli maggiori, altri ancora dai nonni. Ad un certo punto mi resi conto che quei bambini non stavano semplicemente tornando alle loro abitazioni. Stavano rientrando in un sistema educativo molto più vasto della scuola stessa. Stavano tornando nella mahalla, la comunità di vicinato che ancora oggi rappresenta uno degli elementi fondamentali dell'organizzazione sociale uzbeka.

Fu allora che mi venne in mente una domanda che continua ad accompagnarmi nei miei viaggi professionali: dove comincia davvero l'educazione?

La risposta che spesso diamo nei dibattiti internazionali è semplice. L'educazione comincia nella scuola. Poi discutiamo di curricula, metodologie, formazione degli insegnanti, valutazione e qualità dei servizi. Sono tutti temi importanti. Eppure ogni volta che entro in una scuola dell'infanzia, soprattutto fuori dall'Europa occidentale, ho la sensazione che stiamo osservando soltanto una parte della storia.

I bambini arrivano a scuola già profondamente educati. Non conoscono ancora la matematica o la scrittura, ma hanno già imparato una quantità impressionante di cose sul mondo. Hanno imparato come ci si rivolge agli adulti, cosa significa rispettare qualcuno, quali emozioni si possono mostrare in pubblico, come si affronta un conflitto, chi si prende cura dei più piccoli, quale rapporto esiste tra individuo e comunità. Hanno imparato tutto questo molto prima di incontrare il primo insegnante.

In Kosovo ho visto bambini crescere all'interno di reti familiari estese dove il concetto di appartenenza supera largamente il nucleo familiare ristretto. In Eswatini ho incontrato comunità nelle quali le nonne svolgono un ruolo educativo essenziale per intere generazioni di bambini. In Laos ho osservato quanto il buddhismo continui a influenzare il modo in cui vengono interpretati il rispetto, la disciplina e la relazione con la natura. In Palestina ho visto famiglie che educano i figli all'interno di una quotidianità segnata dall'incertezza politica e dalla necessità di costruire speranza anche quando il futuro appare fragile.

Ogni volta emerge la stessa evidenza. L'infanzia non è una categoria universale che assume semplicemente forme diverse nei vari paesi. L'infanzia è essa stessa una costruzione culturale. Ogni società produce una propria idea di bambino, una propria immagine di ciò che significa crescere, imparare e diventare adulti.

Questo non significa che non esistano bisogni universali. Tutti i bambini hanno bisogno di affetto, sicurezza, nutrizione adeguata e opportunità di apprendimento. Ma il modo in cui questi bisogni vengono interpretati e soddisfatti varia enormemente da un luogo all'altro. Ed è proprio qui che molte politiche educative incontrano le loro maggiori difficoltà.

Troppo spesso immaginiamo che un curriculum possa essere trasferito da un paese all'altro come si esporta un prodotto industriale. Si traduce il documento, si organizzano alcuni corsi di formazione e si presume che il cambiamento avverrà automaticamente. Nella realtà le cose funzionano diversamente. Ogni riforma entra in relazione con una storia, con una geografia, con una religione, con una memoria collettiva. Se non comprende questi elementi, rischia di rimanere una sovrastruttura amministrativa incapace di modificare davvero le pratiche educative.

È da questa constatazione che nasce ciò che ho iniziato a chiamare geopedagogia. Non una nuova teoria educativa e nemmeno una metodologia. Piuttosto un esercizio di ascolto. Un tentativo di comprendere come i popoli immaginano l'infanzia prima ancora di proporre come educarla.

Perché forse la prima domanda che dovremmo porci non è quale curriculum adottare o quali competenze sviluppare. Forse la domanda più importante è molto più semplice: chi è il bambino che abbiamo davanti e da quale mondo proviene?

Finché non saremo in grado di rispondere a questa domanda, continueremo a progettare scuole per bambini immaginari, dimenticando quelli reali.

When we were in Lisbon, we had to take a cab because of a transit strike. Elke asked the driver whether he spoke English, and indeed, like most people in Lisbon, he did. From there, we had a lively conversation about life in the city, with its ups and downs.

This reminded me of a science fiction story we both read in the early 90s, in which the narrator instructed a robotic driver “with conversation.” Curiously, both a self-driving car and a chatting computer are no longer science fiction in 2026.

“With conversation” has since become a running gag between Elke and me in these situations. But which story is it from?

Surely, ChatGPT knows, so I asked when we stopped at a street café later that day. Aside from the quote, I remember quite a few story details: The narrator visited a friend who had become incredibly rich by inventing a universal material based on water. I also recalled that it had a Russian angle (like many SF stories).

ChatGPT rattled off a series of stories, none of which matched. One was The Water Statues by Fletcher Pratt from New York. While not Russian, it was close to Russian sci-fi of that era. That sounded specific enough that I let it be and moved on.

Back home, I followed up and learned that Fletcher Pratt had never written a story titled The Water Statues. There is a book with that title by Swiss author Fleur Jaeggy, but it is not science fiction.

So back to square one. I remembered that the book containing the story was called Das Mädchen am Abhang (“The girl at the slope”). A Google search revealed the author’s name. From there, ChatGPT finally identified the story as Die Flüssige Materie (The Liquid Substance) by Ilja Warszawski, which has never been translated into English and hence eluded the internet and AI.

It’s fascinating that a published story that has become so ingrained in Elke’s and my memory is largely obscure to the rest of the world. 

Building on American cloud is the easy choice, which is exactly why almost everyone makes it. One account at Amazon, Google, or Microsoft and you get the whole stack in one place: compute, database, storage, DNS, email, all of it wired together, billed on one invoice, documented to death. It is a genuinely excellent product. It is also where PlantLab started.

It doesn't run there anymore. The diagnosis API, the database that holds your history, and the services around them now run on European infrastructure, and the live path a request travels – upload, inference, response, storage – never leaves the EU. That was not the easy choice. I want to explain why I think the easy choice and the right one were two different things here.

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The all-in-one pitch is real, and it's the trap

The reason a hyperscaler is so easy to build on is that it has already solved the hard part for you: integration. You don't think about how your database talks to your storage, or whether your email provider and your DNS provider have ever heard of each other. One vendor owns all of it, so it all just fits. For a solo founder with limited hours, that convenience is worth a lot.

The catch is what you hand over in exchange. Your data, and the rules that govern it, now live inside one American company's estate, under one country's legal reach, no matter which “region” you tick in the console. An EU region of a US cloud is still a US cloud. The convenience and the loss of sovereignty are the same decision – you can't take one without the other.

For a lot of software that trade is fine. For a tool that gets handed photos from real, often licensed, grow rooms, I didn't think it was.

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Europe is fractured, and that's the whole point

Here is the honest part nobody puts in the brochure: there is no European hyperscaler. There is no single EU console where you tick a box and get a sovereign, all-in-one stack. So you build it the hard way – you assemble it.

You host compute with one provider in one country. You find a separate DNS and content-delivery company in another. You put your database and transactional email with providers in a third. And before you trust any of them you do the unglamorous research: is this company actually European-owned and European-hosted, or is it a US firm with an EU postcode? Where does the data physically sit? Who can be compelled to hand it over, and under whose law? More vendors, more contracts, more reading, more things that can break.

That fragmentation is real, and it is the cost of sovereignty. The single invoice is convenient precisely because one entity controls everything. The moment you insist that no single entity should, you inherit the work of stitching independent pieces together yourself. I think that work is the point, not a bug to be engineered away.

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What the assembling actually produced

Here is where things stand now. Three countries, several independent European providers, deliberately not one console:

Layer	Where it runs now
Diagnosis API (the inference itself)	Germany
Database (your history, account, keys)	France
Transactional email	France
DNS and content delivery	Slovenia
Web analytics	EU-hosted, cookieless
Uptime monitoring	France

The cutover was the careful kind. I ran the new European stack alongside the old one, sent real traffic through it, and verified end to end that a diagnosis written on the new infrastructure could be read back correctly, including the parts that are encrypted at rest. Only then did production point at it. The old environment is still sitting there, frozen, as a rollback target for a while longer, because turning the lights off the same day you cut over is how you turn a migration into an incident.

In an earlier post on data privacy I said this move was in progress and was careful not to overclaim it – the core diagnosis API still ran on a US cloud at the time. That caveat is gone now. The whole live path is European.

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Why the hard road

I didn't do this for a marketing line, and I'm wary of anyone who treats “EU-hosted” as a badge. I did it because of what a plant photo actually is.

A photo of a flowering plant gives things away – that you grow, the kind of setup you run, and across enough images, the scale of it. For a licensed European operation that is commercially sensitive information sitting inside a regulatory frame. The question that operator asks before sending anything real is simple: where does my data live, and whose rules govern it? “On servers in Germany, under EU law, with no single foreign company holding the whole stack” is a different answer than “somewhere in a US cloud's European region.”

There is a regulatory tailwind too. Europe's high-risk AI obligations come into force in August 2026, and the broader direction on privacy keeps moving toward stronger consent and more transparency, not less. Building here now, while PlantLab is small and the change is cheap, beats retrofitting it under a deadline later. But the regulation is the tailwind, not the reason. None of this makes PlantLab a compliance product, and you should distrust any small tool that claims a certificate.

The reason is plainer than that. Data sovereignty, privacy, and digital rights belong to the person whose data it is – not to whichever cloud happens to be cheapest to build on. Most companies build on US infrastructure because it's easy and it works, and I understand why. I took the harder, more fragmented road because, for a tool handling this kind of data, the user is the one who matters most. The convenience was mine to give up. The data was never mine to be casual with.

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What this changes for you

For most people using the API, the answer is: nothing you have to do, which is the point. The endpoints are the same, your API key is the same, the response format is the same. Inference still runs in milliseconds – the model didn't change, only the building it runs in. A migration you have to think about is a migration done badly.

What it changes is what's true underneath:

• Your diagnosis data is processed and stored in the EU. The live request path stays inside European infrastructure from upload to response, across providers that no single foreign entity controls.
• Sovereignty is distributed on purpose. No one company holds your data, your DNS, and your delivery layer at once. That's harder to run and harder to compromise wholesale.
• The privacy controls travel with it. Bounded, opt-in retention and encryption of the sensitive diagnosis fields ride on top of the move. Where your data lives and how it's held now point the same way.

If you opt in to contributing diagnoses on the free tier, those images are kept in EU storage as well. The default is still minimization: opt-in, bounded, then deleted.

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Stated accurately, not stretched

“EU-based” is a phrase that gets stretched until it means a billing address. I'd rather it mean something concrete. Here it does: the request that carries your plant photo is served from Germany, your history is stored in the EU, traffic is measured by cookieless EU analytics, and uptime is watched by EU monitoring – each from an independent European provider. The live path your data travels, in real time, is European end to end. That's the claim, and it's a specific one.

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PlantLab is free to try at plantlab.ai. Three diagnoses a day, results in milliseconds. The full API documentation, including data handling details, lives at plantlab.ai/docs.

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FAQ

Where does PlantLab run now?

The diagnosis API is served from Germany, the database and transactional email are in France, and DNS and content delivery run from Slovenia. Analytics are cookieless and EU-hosted, and uptime monitoring runs from France – each from an independent European provider rather than a single all-in-one cloud. A diagnosis request stays inside the EU from upload to response.

Why not just use a US cloud's European region?

Because an EU region of a US company is still governed by that company and, ultimately, by US legal reach over it. Using independent European providers keeps the data physically in the EU and out of any single foreign entity's control. It's more work to run, which is the trade I chose to make.

Did the API change? Do I need to update anything?

No. The endpoints, your API key, and the response format are unchanged. Inference still runs in milliseconds. The move was designed to be invisible to integrators – nothing in your code needs to change.

Why does this matter for cannabis growers specifically?

A plant photo can reveal that you grow, the kind of operation you run, and at scale, how large it is. For a licensed European operation that's commercially sensitive and sits inside a regulatory frame. Data stored in the EU under EU law, across providers no single foreign company controls, is a stronger answer to “where does my grow data live” than data in a US cloud.

Does this make PlantLab GDPR or EU AI Act compliant?

EU-based infrastructure supports those goals but isn't a certificate, and no honest small tool should claim one. PlantLab pairs EU hosting with bounded opt-in retention, encryption of sensitive fields at rest, and cookieless analytics – controls that move in the same direction the regulation does.

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Related reading: – A Plant Photo Says More Than You Think: Privacy by Design at PlantLab – What we keep, for how long, and why – How PlantLab Knows When It Might Be Wrong: The reliability_score Field – The trust signal on every diagnosis – What's Wrong With My Cannabis Plant? A Visual Diagnosis Guide – The grower-facing diagnostic hub

Today's MLB Game of Choice...

...in the Roscoe-verse, weather permitting of course, will have my Texas Rangers playing the Cleveland Guardians. This game is scheduled to start at 6:35 PM CDT. I'll be following the radio call of the game on 105.3 The Fan, DFW's Sports Station.

And the adventure continues.

Dionne Brand writes that every map a Black person makes begins at the door of no return — the rupture where the connection to origin was severed, where the Atlantic became the site of a dispossession so total that what it organized was not a journey with a destination but a navigation from a breaking that has no other side. The door does not draw you back through it. There is no back. What it produces instead is a particular structure of navigation: the body moving through geographies it did not choose, on land it arrived to under conditions not of its choosing, making maps from a point of irresolvable loss rather than from a legible origin. The water is where this structure is felt most honestly — not because it holds what was lost or promises what was severed, but because it is where the breaking happened and keeps happening, the ongoing condition of dispossession that the body is inside whether or not it has language for it. The St. Lawrence running east toward the Atlantic is not pulling the body toward something waiting on the other side. It is the body registering, near this specific water in this specific diaspora geography, the structure that has been organizing its navigation all along — the triangular piece of ice that pointed east from this river on a blustery February morning, the eastward orientation I keep returning to without deciding to, the body finding the water cities not because they were calling but because it is navigating from a rupture that makes every geography partial, every belonging conditional, every map a document of what cannot be returned to as much as of where you are. The body near Tiohtià:ke’s water, carrying what Kjipuktuk drew out of it, living inside Sharpe’s weather, navigating from Brand’s door — these are not separate conditions pressing on the same body but one condition, the structure of Black life in diaspora, felt here at the water’s edge.

I was thinking back to around the time that the very first COVID lockdown came into effect. I recall seeing a government person on a video talking about the moment when he first realized how serious of a problem it was. He said that moment came for him when there was a meeting with health officials, and they had showed him the numbers and projections and things.

For me back then, that moment came prior to the first lockdown. It was when I saw images online of streets in a city in China being hosed down with disinfectant by crews wearing hazmat suits. That disturbed me at the time, and I suspected it was going to be a huge deal. And it was.

I had a similar moment more recently when I became aware of bad things coming. I saw video of a moron on a stage with a chainsaw. My thought was, “nice to see that they are taking the leadership job seriously.” I just knew right then that the regime would take the shit show from swirling in the bowl, to gurgling down the pipes into the sewer. And their incompetence is dragging the rest of the world down with them.

How can I view it otherwise when news around the world shows that the race between absurdity like that, and hope for a better future is still a close race?

And just think, that same chainsaw wielding idiot is soon going to be the world's first trillionaire. My spellcheck doesn't even know the word. I agree with you, spellcheck. That word should not exist. The word billionaire should also not exist. Both are ridiculous. If my yearly wage was fifty thousand dollars a year, and if every cent could be saved, it would take twenty million years to reach a trillion dollars.

What are we supposed to feel about one 'person' worth a trillion dollars? Are we supposed to envy it? Are we supposed to view this as a great human milestone or accomplishment? This is no accomplishment. It is disgusting, a fail, when one gets to have so much while billions struggle to survive. It symbolizes a failure of a society with a failure of an economic system that allows things like him, and other ultra wealthy losers, to exist.

Mitte Mai wollte ich sagen, wie es rollenspielerisch mit mir weitergeht. Der Mai ist vorbei, also Zeit, Tacheles zu reden. Ich ziehe mich weitestgehend aus allen Sachen zurück. Damit sind alle Runden und auch mein Engagement auf WE20 gemeint. Eigentlich werde ich in den nächsten Monaten mehr freie Zeit haben als vorher, ABER ich werde sie nicht frei planen können. Das heißt, ich würde unzuverlässig sein, Runden kurzfristig absagen und Deadlines nicht einhalten. Ist ungeil!

Trotzdem will ich spielen, und wo ein Wille ist, findet sich mitunter auch ein Weg. Ich werde spontanere Runden anbieten. Gerade bei PbtA-Sachen geht das ja klar. Cthulhu-Szenarien werde ich auch wieder anbieten, nur eben nicht Wochen im Voraus.

Gut, so weit dazu. Thema Blog und Bloggen. Seit ich wieder angefangen habe zu bloggen, hatte ich Schwierigkeiten. WordPress fühlte sich behäbig an, und auch die Themen, über die ich schreiben wollte, passten für mich nicht in (m)einen Blog, fand ich. Auf WE20 habe ich dann einfach mal gefragt, wie andere Blogger oder Blogleser das so sehen. Und Clawdeen hat mich an etwas erinnert: Blogs sind eigentlich persönliche Weblogbücher. Sie dokumentieren meine Streifzüge durchs Web oder eben meinen Spaßkosmos (Pen & Paper, Horror und so weiter). Diese Sichtweise macht viel aus, beim Schreiben, aber auch beim Lesen, denke ich zumindest.

Das Schreiben eines Blogs soll Spaß machen und sich nicht anfühlen, als müsse man am nächsten Tag ein Referat halten – sofern Referate halten nichts ist, das euch Spaß macht! Und das Lesen eines Blogs sollte auch unterhaltend sein. Ich habe zum Beispiel immer mal wieder fefes oder Anke Gröners Blog gelesen, obwohl ich weder ITler noch Kunsthistoriker bin, eben weil mich die Blogs unterhalten haben (beide derzeit nicht erreichbar).

Langer Rede, kurzer Sinn: Ich werde hier künftig kurze Beiträge posten und auch nicht themenagnostisch sein, wobei ein großer Teil meines privaten Lebens mit Horror zu tun hat … Also, ähm … ich mag das Genre. Türlich auch Pen & Paper und ja, vielleicht auch Bücher aus anderen Bereichen. Auf WE20 gibt es einen nigelnagelneuen Buchclub, und ich überlege, auch hier darüber zu schreiben oder einen neuen Blog über write.as zu machen. Was man als Leser nämlich vielleicht nicht wahrnimmt: Eigentlich sind Blogs hier nur einen Klick voneinander entfernt, fast wie Kategorien in WordPress, nur anders.

Aber ich möchte natürlich auch tiefer in die Materie von Rollenspielen eintauchen. Ich werde weniger spielen, aber trotzdem nicht das Hobby aufgeben. Für die umfangreicheren Artikel habe ich mir einen Digital Garden zugelegt, ein Obsidian-Vault, das ich mit GitHub, Vercel und einem Plugin öffentlich mache. Das Ganze ist noch im Werden.