Center for Responsible AI

Designing AI to empower

Collaboration and commitment to build the next generation of AI products. Empowering AI for the greater good with responsibility at the core.

Building AI that is transparent, accountable, and ethical

What is Responsible AI?

Responsible AI: where innovation meets ethics

Responsible AI is the ethical and reliable development and deployment of artificial intelligence systems that minimize harm, ensure transparency, and accountability. By considering ethical and societal implications responsible AI can help mitigate potential risks and promote trust in AI technologies.

Responsible AI
AI Consortium
Building AI for a better tomorrow, today!

World's largest responsible AI consortium

The Center for Responsible AI is the largest consortium ever dedicated to Responsible AI, bringing together eleven startups, including two unicorns, eight research centers, a law firm, and also five industry leaders in Life Sciences, Tourism, and Retail. 

With an investment of almost 80 million euros, the consortium will be responsible for 21 new AI projects by 2030. The goal of this project is to develop a fair artificial intelligence system and to solve questions that, up to this moment, were too challenging due to the danger involved. 

YData, a responsible AI-focused company

Everything starts with your data

Data is the raw material of artificial intelligence. The way we work with them determines the success of each project and each company's decisions. Responsible AI comes as a result of responsible data.

YData will be in charge of data understanding, data democratization, bias mitigation, and data causality. Easy data access and quality control will help approach problems such as gender and ethnic discrimination.

Data is the raw material

AI that works for everyone


Reducing biases and their negative consequences


Transparency about how technology works


Tackling the environmental implications of AI development

Start your journey in Responsible AI!

Enhance the performance and efficacy of your data-drive initiatives across a broader distribution of population with fair and unbiased data.

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