Model checkingIn computer science, model checking or property checking is a method for checking whether a finite-state model of a system meets a given specification (also known as correctness). This is typically associated with hardware or software systems, where the specification contains liveness requirements (such as avoidance of livelock) as well as safety requirements (such as avoidance of states representing a system crash). In order to solve such a problem algorithmically, both the model of the system and its specification are formulated in some precise mathematical language.
Evidence-based policyEvidence-based policy is a concept in public policy that advocates for policy decisions to be grounded on, or influenced by, rigorously established objective evidence. This concept presents a stark contrast to policymaking predicated on ideology, 'common sense,' anecdotes, or personal intuitions. The approach mirrors the effective altruism movement's philosophy within governmental circles. The methodology employed in evidence-based policy often includes comprehensive research methods such as randomized controlled trials (RCT).
Fact-checkingFact-checking is the process of verifying the factual accuracy of questioned reporting and statements. Fact-checking can be conducted before (ante hoc) or after (post hoc) the text or content is published or otherwise disseminated. Internal fact-checking is such checking done in-house by the publisher to prevent inaccurate content from being published; when the text is analyzed by a third party, the process is called external fact-checking.
Synthetic mediaSynthetic media (also known as AI-generated media, media produced by generative AI, personalized media, and colloquially as deepfakes) is a catch-all term for the artificial production, manipulation, and modification of data and media by automated means, especially through the use of artificial intelligence algorithms, such as for the purpose of misleading people or changing an original meaning.
Fake newsFake news is false or misleading information presented as news. Fake news often has the aim of damaging the reputation of a person or entity, or making money through advertising revenue. Although false news has always been spread throughout history, the term "fake news" was first used in the 1890s when sensational reports in newspapers were common. Nevertheless, the term does not have a fixed definition and has been applied broadly to any type of false information.
EvidenceEvidence for a proposition is what supports the proposition. It is usually understood as an indication that the supported proposition is true. What role evidence plays and how it is conceived varies from field to field. In epistemology, evidence is what justifies beliefs or what makes it rational to hold a certain doxastic attitude. For example, a perceptual experience of a tree may act as evidence that justifies the belief that there is a tree. In this role, evidence is usually understood as a private mental state.
DeepfakeDeepfakes (portmanteau of "deep learning" and "fake") are synthetic media that have been digitally manipulated to replace one person's likeness convincingly with that of another. Deepfakes are the manipulation of facial appearance through deep generative methods. While the act of creating fake content is not new, deepfakes leverage powerful techniques from machine learning and artificial intelligence to manipulate or generate visual and audio content that can more easily deceive.
MisinformationMisinformation is incorrect or misleading information. It differs from disinformation, which is deliberately deceptive and propagated information. Rumors are information not attributed to any particular source, and so are unreliable and often unverified, but can turn out to be either true or false. However, definitions of the terms might vary between cultural contexts. Even if later retracted, misinformation can continue to influence actions and memory.
Generative adversarial networkA generative adversarial network (GAN) is a class of machine learning framework and a prominent framework for approaching generative AI. The concept was initially developed by Ian Goodfellow and his colleagues in June 2014. In a GAN, two neural networks contest with each other in the form of a zero-sum game, where one agent's gain is another agent's loss. Given a training set, this technique learns to generate new data with the same statistics as the training set.
Information warfareInformation warfare (IW) (different from cyberwarfare that attacks computers, software, and command control systems) is a concept involving the battlespace use and management of information and communication technology (ICT) in pursuit of a competitive advantage over an opponent. Information warfare is the manipulation of information trusted by a target without the target's awareness so that the target will make decisions against their interest but in the interest of the one conducting information warfare.
