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The web was designed to make it possible for information - data - to transfer conveniently no matter where you are or what device you are using. Today data is used as a bargaining chip to lock you in. Solid is a standard that describes how to build storage, apps, and identification in such a way that you can conveniently connect and switch without losing data. If you are interested in the standardisation process, contributions are welcome."

"Stop manipulating us, and give us real choices," says Katarzyna Szymielewicz, a technology and human rights expert, lawyer and activist who advocates for people to have more control over how their data is processed and used.

aTrain is a tool for automatically transcribing speech recordings utilizing state-of-the-art machine learning models without uploading any data to the internet. It was developed by researchers at the Business Analytics and Data Science-Center at the University of Graz and tested by researchers from the Know-Center Graz.

Challenges of a digital society and response of Dutch universities. One programme, seven themes: Citizenship & Democracy, Responsible Data Science, Health & Well-Being Learning & Education, Work & Organisations, Digital Cities & Communities, Safety & Security

Of je een baan krijgt of een hypotheek, wie er vervroegd wordt vrijgelaten uit de gevangenis: algoritmes bepalen steeds vaker de grote beslissingen in ons leven. Want algoritmes zijn sneller en efficiënter dan mensen. Maar nemen ze ook altijd betere beslissingen? En hoe ziet een samenleving eruit waarin we gestuurd worden door big data en computercode?

In 2018 the Netherlands started the development of a new curriculum framework for primary, lower and upper secondary education. New themes in curriculum are Digital Literacy, citizenship and a strong focus on 21st century skills. Digital Literacy is defined as a combination of ICT skills, media literacy, information literacy and Computational Thinking. Starting with a vision on a theme such as Digital Literacy and using this vision as a starting point for describing big ideas. For Digital Literacy eight big ideas were described: data and information, safety and privacy, using and controlling, communication and cooperation, digital citizenship, digital economy, applying and designing, and sustainability. Computational Thinking is integrated in each of these big ideas. The underlying framework for Computational Thinking is based on ISTE and CSTA and each big idea is specified as a learning trajectory describing learning objectives leading to a new legal curriculum framework in 2022.

Revelations that digital consultants to the Trump campaign misused the data of millions of Facebook users set off a furor on both sides of the Atlantic. This is how The Times covered it.

The Society for Learning Analytics Research (SoLAR) is an inter-disciplinary network of leading international researchers who are exploring the role and impact of analytics on teaching, learning, training and development. SoLAR has been active in organizing the International Conference on Learning Analytics & Knowledge (LAK) and the Learning Analytics Summer Institute (LASI), launching multiple initiatives to support collaborative and open research around learning analytics, promoting the publication and dissemination of learning analytics research, and advising and consulting with state, provincial, and national governments.

AI systems are already capable of deceiving humans. Deception is the systematic inducement of false beliefs in others to accomplish some outcome other than the truth. Large language models and other AI systems have already learned, from their training, the ability to deceive via techniques such as manipulation, sycophancy, and cheating the safety test.

AI systems are already capable of deceiving humans. Deception is the systematic inducement of false beliefs in others to accomplish some outcome other than the truth. Large language models and other AI systems have already learned, from their training, the ability to deceive via techniques such as manipulation, sycophancy, and cheating the safety test.

Terwijl onderwijstechnologie zich blijft ontwikkelen, zijn veel instellingen steeds meer op zoek naar mogelijkheden om learning analytics (LA) en artificial intelligence (AI) te integreren om leerresultaten te verbeteren. De grenzen tussen LA en AI zijn soms echter vaag, wat leidt tot verwarring over hoe deze twee gebieden elkaar overlappen en aanvullen.

Kunstmatige intelligentie die bluft tijdens een kaartspelletje om de tegenstander om de tuin te leiden. Een chatbot die een afspraak met een vriendin voorwendt om onder een andere afspraak uit te komen. En zelfs een AI-systeem dat 'voor dood' speelt om niet ontdekt te worden tijdens een controle. Kunstmatige intelligentie misleidt en manipuleert, concluderen wetenschappers in een nieuwe studie.

Frontier models are increasingly trained and deployed as autonomous agent. One safety concern is that AI agents might covertly pursue misaligned goals, hiding their true capabilities and objectives - also known as scheming. We study whether models have the capability to scheme in pursuit of a goal that we provide in-context and instruct the model to strongly follow. We evaluate frontier models on a suite of six agentic evaluations where models are instructed to pursue goals and are placed in environments that incentivize scheming