User-Owned AI: A Shift from Rental Models to True Control

Ownership of AI assistants raises critical questions about control and data privacy. Most digital assistants are rented, leaving users dependent on providers who dictate functionality and access. Key points include:

Users face risks if providers change terms or monetize data unexpectedly.
Centralized AI models lack transparency; user data can be logged or misused.
Recent events, like Italy's temporary ban on ChatGPT, highlight vulnerabilities in relying on third-party AI.
True ownership involves controlling an AI agent’s core logic and decision-making parameters.
User-owned agents can operate independently, manage resources, and safeguard sensitive data.

Web3 infrastructures and neobanking systems enable programmable asset management, shifting AI from passive tools to proactive systems tailored to individual needs. An example is Pearl, an app store for autonomous AI agents that allows users to retain full ownership while managing various tasks, including DeFi portfolio oversight and content generation.

The movement towards user-owned AI seeks to decentralize power from dominant platforms, promoting security through open-source models. This paradigm shift emphasizes the importance of retaining control over personal data and decisions in a rapidly evolving digital landscape.