These guidelines from AlgorithmWatch outline ethical principles for using generative AI, including transparency, accountability, and safeguards against harm, with a focus on practical policy and governance measures for organizations.
A comic essay that narratively explores AI and sustainability, showing how data-intensive technologies intersect with environmental concerns and inviting readers to think critically about technologically mediated futures.
Wem vertrauen wir mehr: Mensch oder KI? Nicht nur Schülerinnen und Schüler können Opfer des “Automation Bias” werden – auch Lehrkräfte sollten die Ergebnisse von KI-Tools reflektieren. A short educational resource explaining automation bias, the tendency to trust suggestions and decisions made by machines more than one’s own judgement. It uses the example of a […]
Künstliche Intelligenz ist nur so “smart” wie die Daten, mit denen sie trainiert wurde. Aber: Diese Daten spiegeln häufig gesellschaftliche Vorurteile. A short educational resource explaining how bias can arise in AI systems through training data, algorithms and their use. It introduces examples of racist, sexist and class-based bias, explains debiasing approaches, and provides suggestions […]
A report on a national research conducted in Croatia on the topic of mental health and AI use. Research on the relationship between artificial intelligence, mental health and Generation Z. The study explores how young people perceive and use AI, including its potential benefits, risks and impact on wellbeing, providing insights into the attitudes and […]