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Sergey Pesterev / Wikimedia Commons

Benh LIEU SONG (Flickr), CC BY-SA 4.0, via Wikimedia Commons

Markus Trienke, CC BY-SA 2.0, via Wikimedia Commons

JohnDarrochNZ, CC BY-SA 4.0, via Wikimedia Commons

NASA Goddard Space Flight Center from Greenbelt, MD, USA, Public domain, via Wikimedia Commons

Charles J. Sharp, CC BY-SA 4.0, via Wikimedia Commons

Michael S Adler, CC BY-SA 4.0, via Wikimedia Commons

Stefan Krause, Germany, FAL, via Wikimedia Commons

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Machine Learning/Artificial Intelligence

Open letter: Harnessing open source AI to advance digital sovereignty

November 13, 2025 Dear Presdent Macron,Dear Chancellor Merz,Dear President von der Leyen, Europe is at a crossroads. The Summit on European Digital Sovereignty marks an important milestone for the EU and its member states in aligning on a shared strategy for achieving real and lasting European digital sovereignty. As the EU pursues the goal of digital sovereignty, we urge you to harness open source — that is, technology that is free to use, inspect, adapt, and share — as a key enabler of this strategy.  Europe cannot buy sovereignty off a shelf, it has to build it. In an age of geopolitical volatility and rapid innovation Europe must play to its strengths, including world-leading researchers and a rich history of open source development. It faces a choice: use these strengths to carve out its distinct place in the global AI ecosystem or settle for copying the playbooks of already dominant actors.  At their heart, closed systems create dependency, open systems create capacity. Investment into the full open source AI stack, from AI models to data and software tooling, is a strategic lever. If digital sovereignty means creating a Europe that is resilient and benefits from choice, security, and self-determination, then open source is a critical force multiplier that enables Europe to do more with less.  Open source AI, and open source technology more broadly, is not just a strategic asset benefiting governments, businesses, and people. If underpinned by a clear commitment to values that are at the heart of the European project — including cultural diversity, fundamental rights, environmental sustainability, and people’s privacy and security — open source can help embed these into the technologies that will shape our future.  We, the undersigned, represent a diverse coalition of organisations across industry, the open source community,… Read More »Open letter: Harnessing open source AI to advance digital sovereignty

Wikipedia & AI Competition: Biases, Mistakes, Omissions

A model to predict pixel colour values, based on an original photograph. The work illustrates a popular type of machine learning model: the decision tree. Decision trees work by splitting the data into ever smaller segments. It shows that models are simplifications of reality, but can still be useful. Authors: Rens Dimmendaal and David Clode, License: CC-BY, Source: BBC, Better Images of AI

Competition is a good thing. Wikipedia’s free licences explicitly welcome it. We have seen other platforms and encyclopaedias appear in the past, and we will see more in the future. 

The latest batch of competition that wants to harness AI technology to generate better compendiums of knowledge. These projects criticise things like gaps in coverage, reliable or alleged political biases. Let’s have a look at what’s out there and discuss some of the aspects!

Read More »Wikipedia & AI Competition: Biases, Mistakes, Omissions

Meet “ClueBot NG”, an AI Tool to tackle Wikipedia vandalism

Mishaps happen. The question is how to deal with them. (Image: "The crashed B-2 at Guam", Federal Aviation Administration, 2008, public domain)

There are many bots on Wikipedia, computer-controlled  “user accounts” that perform simple, repetitive, maintenance-related tasks. Most are simple, trained to fix typos or using a list of blacklisted words to determine vandalism. ClueBot NG uses a combination of different detection methods which use machine learning at their core.

Bots on Wikipedia

A bot (a common nickname for a software robot) is an automated tool that carries out repetitive and mundane tasks. Bots are used to maintain different Wikimedia projects across language versions. Bots are able to make edits very rapidly, but can disrupt Wikipedia if they are incorrectly designed or operated. False positives are an issue as well. For these reasons, a bot policy has been developed.There are currently 2,534 bot tasks approved for use on the English Wikipedia; however, not all approved tasks involve actively carrying out edits. Bots will leave messages on user talk pages if the action that the bot has carried out is of interest to that editor. There are 323 bots flagged with the “bot” flag right now (and over 400 former bots) on English Wikipedia. On Bulgarian Wikipedia, a much smaller language version, there are currently 106 bot accounts, but only a number of them are active. Projects by smaller communities sometimes need to rely more on machines for page maintenance.

Read More »Meet “ClueBot NG”, an AI Tool to tackle Wikipedia vandalism

Wikimedia Projects & AI: Designing a “Section Recommendation” tool without reinforcing biases

Graffiti in Vitoria-Gasteiz, Zarateman, Creative Commons Zero, Public Domain Dedication

There is an idea to use a  “section recommendation” feature to help editors write articles by suggesting possible sections to be added. But it is possible that its recommendations inadvertently increase gender bias. Here’s how we could deal with it.

Read More »Wikimedia Projects & AI: Designing a “Section Recommendation” tool without reinforcing biases

Wikimedia Projects & AI Tools: Vandalism Detection

Al-Jazari's programmable automata (1206 CE): Realistic humanoid automata were built by craftsman from many civilizations and were believed to be capable of wisdom and emotion. [Public Domain, via Wikimedia Commons]

There is a machine learning service available to interested Wikimedia projects and communities called ORES. It aims to recognise if an edit, for instance on Wikipedia, is damaging or done in good faith. Of course, false predictions cannot be avoided and thus remain a major risk. Here’s how we try to handle it.  

Read More »Wikimedia Projects & AI Tools: Vandalism Detection