The opening of the conference will take place in the Aula Hanswijk (Z1.13, on the first floor), and will be streamed into the Aula Donche (Z1.15, first floor).
Over the past three years, the Guardian Data Projects team has revealed how private equity firms have increased their share in the childcare sector as well as in the provision of children’s care homes in England. We have also investigated how taxpayers’ money for services that provide support for rape and sexual assault victims ends up in private equity companies. And we have estimated that the UK government has spent billions of pounds in companies that are owned by a private equity group.
Attendees to this session will learn about two methodologies the Guardian built to track down the involvement of private equity firms in the country’s economy and specific sectors. They will also learn about specific resources to find out company data, as well as understand how the Guardian built an automated system to analyse thousands of company records to find the ultimate controlling party for each company group. We will also show how an LLM helped to identify companies owned by a private equity firm, as well as the limitations of using this type of technique.
Zeke is a Senior Software Engineer on the Guardian’s Digital Investigations team. The team contributes to journalistic research and builds secure tools to enable investigative journalism.
Data journalist at The Guardian Data Project team. I work on a variety of subjects - always finding the data angle in every story. Scraping, cleaning, data analysis, but above all JOURNALISM!
Everyone listens to audio all the time, yet investigators rarely think of it. This session introduces audio forensics as an often-overlooked OSINT skill. We’ll explore how frequencies, compression, spectrograms, and a touch of physics can be used to authenticate media, detect edits, determine locations, and even prove war crimes. Participants will learn how to calculate a shooter’s distance using bullet speed and the speed of sound, analyse electrical network frequencies, and recognise platform-specific compression. No prior experience in OSINT or extensive knowledge of audio is required — this session is suitable for beginners.
Seit 2021 bei der NZZ tätig. Seit Beginn des Ukraine-Kriegs Fokus auf OSINT-Recherchen. Gefolgt von diversen Weiterbildungen in Digitaler Forensik, Spezialisierung auf Audio- & Videoforensik. Teil des OSINT-Teams der NZZ.
Large language models (LLMs) have become a common tool in most investigative newsrooms. But what do you do when prudish language models refuse to process what you are investigating? Or you have so much sensitive information that it makes your stomach hurt to send it to Big Tech?
Enter local AI models!
Norwegian Broadcasting Corporation (NRK) has used AI models running on their own machines or leased ones to carry out several projects. Together with Lighthouse Reports, we exposed a hidden class divide in Norwegian courtrooms – revealing that the wealthy receive more lenient sentences than the poor – by analyzing 9,000 verdicts. The NRK team then turned its attention to the adult industry, reviewing over 1,000 films to document a sharp rise in choking incidents.
While the subjects differ vastly, the projects share a common thread: the controlled use of local AIs to process massive datasets. We want to share our methodology, our findings, and insights along the way – but most of all demonstrate how to get you started with using the latest local models for your specific investigative needs.
In the presentation, we will show concrete examples of how to run the latest local models and invite the audience to think with us about how these models can enhance investigative workflows.
