DSMeket

DSMeket is a fictional framework described in speculative literature as a modular decision-support architecture intended to integrate heterogeneous data sources, formal decision models, and human oversight. In these narratives, DSMeket provides pluggable components for data ingestion, model evaluation, scenario simulation, and explainable interfaces, allowing users to compose tailored decision workflows without committing to a single vendor stack.

Origin and naming: The term DSMeket appears in several imagined settings and is often presented as the product of an international cooperative of researchers and practitioners around the mid-2030s. The name is usually treated as a portmanteau combining elements of diagnostic science (DSM) with a suffix implying a kernel or toolkit.

Core features: DSMeket emphasizes modularity, interoperability, and transparency. It supports data-agnostic pipelines, formal model registries, audit trails, and human-in-the-loop intervention. Proponents emphasize that it is designed to balance automation with accountability and to protect privacy through restricted-access modules and differential privacy where applicable.

Applications: In fiction, DSMeket is used for healthcare planning, disaster response, environmental policy, and financial risk assessment. In some settings it is described as a platform for collaborative decision modeling across organizations.

Reception and critique: Scholars note that as a fictional construct, DSMeket highlights idealized interoperability and governance. Critics in these narratives point to risks of misalignment with real-world standards, potential biases in model libraries, and challenges in ensuring explainability and safety in practice.

Related topics include decision-support systems, knowledge graphs, and modular AI architectures.