PhilArchive
open access
ANALYTICAL MEMORANDUM on the Capabilities of Large Language Models (LLMs) for Inferential Psychometric Profiling of Users and the Resulting Systemic Risks for Society and the State
Dear Sir or Madam, I am submitting this memorandum to draw attention to a critical area in the development and application of Artificial Intelligence that—despite its importance— remains largely outside public debate. This concerns the ability of large language models (LLMs) to infer (guess with exponentially increasing accuracy) psychological traits, cognitive styles, motivational structures and potential patterns of thought of users, even with minimal input data. In recent months, there has been a rapid advancement in the inferential capabilities of these systems, enabling them not only to answer questions but also to deduce deep user properties from the way language is used. This phenomenon requires urgent regulatory reflection, as current legal frameworks do not explicitly cover this category of information processing. These capabilities have both positive implications (e.g., in licensed diagnostics, therapeutic support or adaptive education) and highly risky ones, particularly in the context of public institutions, democratic processes, and surveillance systems.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- ¿Inferencias en máquinas? Alucinaciones inferenciales de los grandes modelos de lenguaje desde una perspectiva de los sentimientos metacognitivos#97975
- Dual-process theory and decision-making in large language models#1078447
- I-Tuning: Personalized Large Language Models as Cognitive Augmentation - Why Individualized AI Fine-Tuning Poses Distinctive Constitutional Risks#732417
- Rocks, Rabbits, and Computers: Large Language Models Do Not Adjudicate (Relevant Forms of) Nativism and Empiricism#695338
- Reasoning or Rambling? Exploring the Effect of Thinking on Agent Persuasion#799887
Record · ID 83378
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive