AIsammanhang

AIsammanhang is a term used in Swedish-language AI discourse to describe the contextual frame in which an artificial intelligence system operates. It encompasses data provenance and quality, the specific task and goals, user expectations, the physical and digital environment, and normative constraints such as laws, regulations, and ethical guidelines. The concept emphasizes that AI behavior and outcomes are shaped by the surrounding context as much as by the underlying algorithms.

The word combines AI with sammanhang, meaning context or setting. It is used across domains to guide design, evaluation, and governance, and to highlight that performance and safety can vary when data, users, or environments change. This makes AIsammanhang a tool for discussing domain specificity, robustness, and transferability of AI solutions.

In practice, AIsammanhang informs evaluation and deployment practices by promoting context-aware testing, domain adaptation, and risk assessment. It supports planning for transparency, accountability, and user- and environment-specific constraints. By foregrounding context, developers and researchers aim to anticipate biases, unintended consequences, and governance needs that arise only when AI interacts with real-world settings.

Relation to other concepts includes context-aware computing, deployment strategies, and socio-technical systems, where technology and human actors co-evolve within a surrounding context. The term is primarily used in Swedish-language literature and discussions and is not an official standard, but rather a framework for considering how context shapes AI behavior and decision-making.