Meta-Identities and the Political Economy of Algorithmic Transparency: The Algorithmic Governance of Life and Data

Description: This presentation introduces the concept of Meta-identity as a framework to understand how digital platforms construct classificatory profiles inferred from personal, contextual, and behavioral data. We argue that Meta-identity operates as a tool for digital governance, modulating visibility, access, and stimuli with profound social, economic, and legal impacts.

We demonstrate how the dynamics of Meta-identity (Somatic, Executive, Algorithmic, and Transactional) apply both to digital users and even to bio-engineered organisms. In both cases, life and behavior are redesigned as proprietary infrastructures to accelerate capital accumulation.

The framework is organized into three pillars:

1. Dynamics: Executive, Interactional, Analytical, Normative, Somatic, Performative, Transactional, and Algorithmic.

2. States: Active, Latent/Log, Referential, and Documentary.

3. Outcomes: Reputation shifts, visibility modulation, power asymmetries, and social externalities.

By bridging the gap between Data Science and Social Sciences, this work proposes a user-centered algorithmic governance based on actionable transparency, explainability, and independent audits.