The increase in fake news, the growing influence on elections, increasing false reports and targeted disinformation campaigns are not least a consequence of advancing digitalisation. Information technology is needed to put a stop to these undesirable developments. With intelligent algorithms and refined data analysis, fakes must be detected more quickly in the future and their spread prevented. However, in order to meaningfully recognize and filter fakes by means of artificial intelligence, it must be possible to distinguish fakes from facts, facts from fictions, and fictions from fakes. This book therefore also asks questions about the distinctions of fake, factual and fictional. The underlying theories of truth are discussed, and practical-technical ways of differentiating truth from falsity are outlined. By taking into account the fictional as well as the assumption that information-technical advancements can benefit from humanities knowledge, the authors hope that content-related, technical and methodological challenges of the present and future can be met. Peter Klimczak (Dr. phil. et Dr. rer. nat. habil.) teaches media, cultural and technical sciences as a private lecturer at the Brandenburg University of Technology and conducts research as part of a Feodor Lynen Research Fellowship at the University of Wroclaw. He is the author of numerous publications on the use of artificial languages in media and cultural studies, on digital and social media, and on cognitive systems and artificial intelligence. Thomas Zoglauer (Dr. phil. habil.) teaches philosophy as an adjunct professor at the Brandenburg University of Technology and as a lecturer at the Universities of Freiburg and Stuttgart. He is the author of numerous books on the philosophy of technology, logic and applied ethics. This book is a translation of an original German edition. The translation was done with the help of artificial intelligence (machine translation by the service DeepL.com). A subsequent human revision was done primarily in terms of content, so that the book will read stylistically differently from a conventional translation.