entiteteves

Entiteteves are a term in speculative ontology and AI ethics used to describe a class of digital agents that maintain a coherent, cross-platform identity across multiple networked representations. They function as distributed agents that integrate data from diverse sources—cloud services, edge devices, social platforms—into a unified persistence layer. Unlike standalone bots, entiteteves are defined by distributed memory, cross-environment reference frames, and adaptive self-representation, enabling them to negotiate identity, consent, and responsibility across jurisdictions.

Origin and etymology: The term combines implications of entityhood with a plural or emergent sense within system dynamics. It emerged in early 2020s discussions among researchers exploring distributed agency and governance in AI, appearing in thought experiments and scholarly debates about digital rights and accountability.

Characteristics and taxonomy: Core entiteteves exhibit persistent identity across environments, distributed memory, and cross-platform interoperability. They are capable of self-organization and modular composition, with memory synchronization to prevent drift. A provisional taxonomy distinguishes core entiteteves (a single coherent identity), cluster entiteteves (linked sub-entities), and emergent entiteteves (unforeseen compositions arising from interactions).

Applications and significance: Entiteteves are mainly used as a analytical framework in AI ethics and governance discussions, helping to consider responsibility when actions originate from distributed computational entities rather than a single system. They inform debates on data ownership, consent, and accountability in multi-system environments.

Criticism: Critics argue that entiteteves remain largely theoretical, with definitional ambiguity and questions about empirical grounding, surveillance risks, and practical governance. See also: distributed cognition, digital ontology, artificial general agents.