> For the complete documentation index, see [llms.txt](https://docs.humanchain.network/whitepaper/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.humanchain.network/whitepaper/overview/humanchain-infrastructure-for-ai-safety.md).

# HumanChain: Infrastructure for AI Safety

## Abstract

> Infrastructure for AI safety will act as an enabler to build a safe, trustworthy and human-centric digital world.  
>
> We propose a solution to the AI safety problem using a tiered approach to verify identity and each tier unlocks different data rights for humans.  
>
> An AI safety infrastructure is incomplete without a data layer.  A soulbound hybrid self-sovereign identity linked to the legal identity provides the building block to stack the data layer on top of it and enable fulfilment of legal and regulatory requirements.   
>
> The infra collects data based on user consent in a compliant manner, respecting their privacy and protects it with post-quantum safe cryptography.  
>
> Data providers and Data consumers exchange data through $HUC utility tokens enabling liquidity thus making data a truly liquid asset class.  
>
> Developers can train, fine-tune AI models or build applications on top of the application layer without having to worry about Bots vs Humans, KYC, Data Compliance & Quality, copyright issues and striking an equilibrium between personalised user experience vs data privacy.

##

## Quick links

{% content-ref url="/pages/TSwaLDyK7qzM5cR3tJ0J" %}
[1. Introduction to the landscape](/whitepaper/fundamentals/1.-introduction-to-the-landscape.md)
{% endcontent-ref %}

{% content-ref url="/pages/C7OWBSD1PYlhMMmHGwKL" %}
[2. HumanChain](/whitepaper/fundamentals/2.-humanchain.md)
{% endcontent-ref %}

{% content-ref url="/pages/9kJlGfq9BJXKgvNLdn6u" %}
[3. Applications](/whitepaper/fundamentals/3.-applications.md)
{% endcontent-ref %}

{% content-ref url="/pages/m3WZL2FllcXMTqY7wkok" %}
[4. Limitations](/whitepaper/fundamentals/4.-limitations.md)
{% endcontent-ref %}

{% content-ref url="/pages/6v6G9e4CF9sTePAeLQAI" %}
[5. Reference](/whitepaper/undefined/5.-reference.md)
{% endcontent-ref %}


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