Bruno Mortier | Investigating Fraud & Crime

20 Jahre OSINT. Viele Fehler. Noch mehr gelernt. Auf der GOSINTCON 2026 nehme ich euch mit durch Einblicke aus zwei Jahrzehnten Ermittlungsarbeit: Learnings, Aha-Momente und ein paar Warnschilder. Seid ihr dabei? 2026.gosintcon.de #OSINT #GOSINTCon26 #GOSINTCon

(comic) Shoutout to Kevin

Bragging about how much software you’re shipping with AI is like holding down the shutter button and bragging about how many photos you took.

This is the the quote I've been citing a lot recently.

When the training data becomes the battlefield: reflexive control and LLM poisoning ino.to/EAltpvK

Wir stellen Proton Meet vor: Videokonferenzen mit Privatsphäre an erster Stelle proton.me/de/business/bl… via @ProtonPrivacy

We build the first crosscountry database of kleptocratic regimes-governments organized around the personal enrichment of the ruler and the movement of stolen wealth offshore. papers.ssrn.com/sol3/papers.cf…

Due diligence is not prohibited in China. But information-gathering that touches sensitive supply chain, labor, market, or business-information questions can be reframed as an illegal foreign investigation harris-sliwoski.com/chinalawblog/c…

A European Commission proposal could create one of Europe’s largest privacy and national-security risks in decades. techletters.substack.com/p/the-european… Through DMA enforcement, it may compel Google to hand over sensitive search data about millions of Europeans to third parties, including entities that could be used as fronts by hostile actors. The privacy risk is serious. The national-security risk is real.

Journalists reporting on China should be aware of ways the authorities may respond to their work. Here's what happened to @ICIJorg and its network following a 2025 exposé on Beijing’s tactics to threaten, coerce and intimidate regime critics overseas. icij.org/investigations…

Law & AI Stuff #14 Flesh / silicon distinctions, and epistemic pollution artificialauthority.ai/p/law-and-ai-s…

(comic) The estimate game

Put it in the Louvre

"It all comes down to compute." @DAlperovitch from @SilveradoPolicy explains: "The single most important input to winning is compute the processing power used to train and run AI models. Let me say that plainly, because it is defining that everything that congress and this committee do on AI policy. The binding constraint in this competition is not talent, it is not data, and it is not cash. Both the United States and China have talented researchers and financial resources, and we have learned that frontier models trained on generic data routinely outperform smaller models, trained on more specialized inputs. It all comes down to compute."

FNF OSINT Investigation Competition 2026 freiheit.org/global-innovat…

France is transitioning government desktops to Linux, with each ministry required to formalize its implementation plan by autumn 2026. linuxiac.com/france-launche… #Linux #OpenSource

🦔A researcher invented a fake eye condition called bixonimania, uploaded two obviously fraudulent papers about it to an academic server, and watched major AI systems present it as real medicine within weeks. The fake papers thanked Starfleet Academy, cited funding from the Professor Sideshow Bob Foundation and the University of Fellowship of the Ring, and stated mid-paper that the entire thing was made up. Google's Gemini told users it was caused by blue light. Perplexity cited its prevalence at one in 90,000 people. ChatGPT advised users whether their symptoms matched. The fake research was then cited in a peer-reviewed journal that only retracted it after Nature contacted the publisher. My Take The researcher made the papers as obviously fake as possible on purpose. The AI systems didn't catch it. Neither did the human researchers who cited it in real journals, which means people are feeding AI-generated references into their work without reading what they're actually citing. I've covered the FDA using AI for drug review, the NYC hospital CEO ready to replace radiologists, and ChatGPT Health launching this year. All of that is happening in the same environment where a condition funded by a Simpsons character and endorsed by the crew of the Enterprise was being presented as emerging medical consensus. The people making these deployment decisions seem to believe the pipeline from research to AI to patient is more supervised than it actually is. This experiment suggests it isn't supervised much at all. Hedgie🤗 nature.com/articles/d4158…

(comic) The Cost of Learning