At Responsible AI Labs, we believe that AI should be transparent, fair, safe, and accountable.
Last Updated: November 10, 2025
This Responsible AI Policy outlines our commitment to developing, deploying, and maintaining AI systems that respect human rights, promote fairness, and contribute positively to society. We recognize the significant impact that AI technologies can have on individuals and communities, and we take our responsibility seriously.
Our policy applies to all AI products, services, and research activities conducted by Responsible AI Labs, including our RAIL Score API, content generation tools, and safety evaluation frameworks.
These principles guide every decision we make in AI development and deployment
We design AI systems to treat all individuals and groups equitably, actively working to identify and mitigate bias across demographics, cultures, and contexts.
AI systems must be safe, secure, and robust against misuse. We implement rigorous testing and safeguards to prevent harmful outputs and protect users.
Users have the right to understand how AI systems make decisions. We provide clear explanations of our models' capabilities, limitations, and decision-making processes.
We respect user privacy and implement strong data protection measures. Personal data is collected, processed, and stored in accordance with privacy regulations.
AI should augment human capabilities, not replace human judgment in critical decisions. We prioritize human well-being and autonomy in our design choices.
We maintain clear accountability for our AI systems and their impacts. Our governance structures ensure responsible development and deployment.
How we implement our responsible AI principles
Before deploying any AI system, we conduct comprehensive risk assessments to identify potential harms, biases, or negative impacts. This includes:
We explicitly prohibit the use of our AI systems for purposes that violate human rights or cause harm, including but not limited to:
We are committed to transparency about our AI systems' capabilities, limitations, and impacts. This includes:
We provide detailed documentation for our AI models, including training data sources, intended use cases, known limitations, and performance metrics across different demographic groups.
We publish regular reports on the societal impact of our AI systems, including metrics on fairness, safety incidents, and steps taken to address identified issues.
In the event of significant safety or fairness incidents, we commit to transparent disclosure and communication about the issue, its impact, and our response.
We welcome feedback, questions, and concerns about our responsible AI practices. Your input helps us improve.