Crime is a subject surrounded by myths. Serious offences that receive particularly frequent media coverage trigger strong emotions in many people—especially when the victims are perceived as defenceless and the perpetrators as foreign. A majority of the population therefore believes that crime has increased in the recent past. To the extent that this can be objectively established, however, the opposite is the case. With regard to important indicators of public safety (homicide rate; frequency of robberies, burglaries and motor-vehicle theft; violence in schools; and juvenile delinquency in general), the available trend curves for the last two or three decades clearly point downward. This does not contradict the fact that there are, in some respects, genuinely unpleasant new phenomena (e.g. forms of cybercrime made possible by technology, or the youth gangs in Vienna that have recently attracted much attention in Austria) and countervailing trends in specific areas of offending (such as sexual offences or hate crime). The latter, however, is due to the creation of new offences and to more careful detection and statistical recording. This long-term decline can be observed not only in Austria or Germany, but in most Western countries. There is still no explanation for it that is consistently accepted within the scientific community. Most academics assume that demographic shifts play an important role. This is plausible: in ageing societies there are simply fewer young people and therefore fewer young men, who, for as long as statistical records have existed, have shown a far above-average risk of offending in all cultures and at all times. Another important role is likely to be played by the considerable expansion of crime-prevention efforts, which successfully prevent offences at many levels—from awareness campaigns in schools and technical security measures for homes and cars or video surveillance to reintegrative programmes supporting people who have committed offences.
Schmiede26 · Hallein, Austria
As-If Science Jam
When Science Becomes Play — and Suddenly Makes Sense
- 16–26 Sep
- 2026
- Hallein
- Schmiede, Austria
- 11
- datasets, all licensed
- subnet
- a format by Michael Hackl
Why crime
Crime Data as a Subject for an “As-if Science Jam”
Walter Fuchs · Professor of Criminology, Berlin School of Economics and Law
Examples
Four folders you can copy and run
Each one is a real dataset with a claim attached that is not true, and everything needed to
argue it: the data already in place, the task, and an .Rproj
to open. Two of them are written up here.
Worked all the way through
Fell the oaks, fund the theatre
A poster with an R² of 0.906 in which every number is correct and the conclusion is nonsense. The chain is published and signed — and refuted on the same page.
The hard one
Inequality and homicide
Forty-six countries and a relationship that is genuinely there, which is exactly what makes it difficult to argue honestly. Compiled by Walter Fuchs.
We live in a world saturated with data. Studies, statistics, models — they shape political decisions, public debates, and personal beliefs. And yet genuine data-based discourse rarely takes place. Instead, two extremes dominate: blind trust (“the study says…”) and reflexive rejection (“I don’t understand this”).
The As-If Science Jam intervenes precisely at this point.
Developed by Michael Hackl for subnet, the format will be initiated at Schmiede Hallein in 2026. It deliberately turns the scientific process upside down. Teams work with real datasets and apply methods from statistics and data science, but with an unexpected goal: to “prove” the most absurd hypothesis as convincingly as possible.
What initially appears to be a game is, in fact, a precise intervention. Through deliberate exaggeration, simplification, and distortion, the mechanisms that also shape real-world research, media reporting, and politics become visible: selective data sampling, misleading visualizations, and statistical tricks.
In a multi-day process — from hypothesis generation to analysis and finally a public “Offensio/Defensio” — participants learn not only how to read data, but how to question it. The boundary between knowledge and interpretation is not explained theoretically, but experienced directly in practice.
The concept is carried by an interdisciplinary team around Michael Hackl, Erik Zepka, and Walter Fuchs, who combine art, science, and critical reflection. Their shared goal is to make data literacy accessible — not through simplification, but through experience.
The As-If Science Jam demonstrates that science is not merely a collection of correct answers, but a process shaped by decisions, interpretation, and responsibility. And that precisely through playful engagement with data, a new understanding can emerge: one that neither believes naively nor rejects prematurely.
Lab leaders
Michael Hackl — Systems philosopher and co-creator of Schmiede Hallein (recipient of the Austrian Art Prize 2016), Process & Innovation Engineer at Scinteco (pharmaceutical software). Works at the intersection of art, technology, and science. His improVerse vision revolves around verifiable scientific workflows. His philosophical project Asifism questions placebo effects, ritual, and the construction of meaning. Experienced facilitator of hackathons and experimental formats.
Erik Zepka — Conceptual media artist, curator, poet, scientist, educator, and theorist. Years of interdisciplinary laboratory work in immunology, pathology, environmental health, and chemistry have given him first-hand experience with institutional scientific practice. Co-founder of the Open Science Network in Vancouver — a laboratory for democratizing and rethinking scientific communication. His artistic work interrogates the cultural products of technoscience and has been exhibited at institutions including Tate Modern, the Whitney Museum, and ISEA.
Prof. Dr. Walter Fuchs — Professor of Criminology at HWR Berlin. Research focuses include hate crime, white-collar crime, migration and crime, and sociology of law. Explicit expertise in quantitative research methods and data visualization.