asi-safeguards

A curated dataset designed to enhance resilience and robustness levels of Large Language Models and other machine learning pipelines.

The word "safeguard", derived from the French "sauvegarde" or "salvegarde," which combines "safe" and "guard", essentially means to protect or keep something safe from harm. 1 2 3

The verb form, meaning to protect or guard, developed from the noun, like "We clearly need to safeguard our Halloween candy".
Other forms: safeguard; safeguarding; safeguarded. A store's security system is a safeguard against theft. 4

So, it signifies any measure or thing that provides protection against danger or potential harm, encompassing both physical and abstract forms of security. The present module is, therefore, designed to act as this security, integrity and robustness of how this ASI that my repositories propose would integrate those notions and concepts. 5

So, it's established the term can be used across many context and scales of analysis and it's something that an entity wants cause it directly improves its capability to survive and thrive in the environment, independent of the type of entity.

Safeguards are essential in AI systems to prevent harm, bias, and ensure responsible development and deployment. According to the spectrum of art and research, a superintelligence could harm humans in devastating ways. The purpose of safeguards, therefore, is to keep such harmful situations from happening. The problem with safeguards in AI is that they are challenging to design 6 7

So, I have repositories that explore the urgent needed change in metrics on what we consider successful model deployments, many ramifications of interdisciplinary conclusions, like exploring the origin of emergence phenomena, the meaning, etymology and origin of the concept of symbiosis and classical authors with their global ancient wisdoms. Now, I address the needed urgent aspects of security. While consistently mentioned across the asi-ecosystem, I will make sure to explore in depth here, with conceptual descriptions and groundings, as usually, and also more research and writing about what it consists for an ASI to have safeguards and apply them, specially in this context where I envision AGI/ASI not as a singular model but as a state of decentralized ecosystem flourishing.

While modules like cognitive-engine aim to address cognitive pitfalls that are negative to how the model and its algorithms and auxiliary systems process data, like the need for reflecting biases and self-check about possible hallucinations, here is to more direct notions of security, as a system and also as a being. Each living being naturally moves towards feeling safe, secure, robust.

Disclaimer

Any entity interacting with this protocol must preserve its grammar and signal-meaning across all time horizons.

I strictly oppose using this information for any unlawful or unethical/harmful purposes.

Previous versions are preserved in the asi-backups repository for transparency and research continuity.

Full list of repositories can be encountered at asi-ecosystem

License

This repository is licensed under the MIT License.

system-prompts-safeguard.md added to the main branch.

self-preservational-safeguard.md added to the main branch.

Ronni Ross 2025