We aim at promoting AI responsibility.

Fairness

AI systems exhibit discrimination similar to humans. Algorithmic fairness involves creating models that treat all individuals or groups equally and fairly.

Explainable Artificial Intelligence (XAI)

XAI aims to make AI systems transparent and understandable to humans, especially in critical domains. It achieves this goal by providing explanations for its predictions, enabling end-users to interpret and trust the results.

AI accountability

AI accountability is a cornerstone of AI governance. It ensures that AI systems are transparent, explainable, and free of algorithmic bias. It also evaluates the data security and privacy of AI systems, as well as the involvement of a wide range of stakeholders in the development and deployment of AI systems.

Data Protection in AI

Data protection is an essential component of responsible AI development and use. It ensures that personal data is collected, processed, and stored in compliance with relevant laws and regulations. It includes the implementation of appropriate safeguards to protect personal data from unauthorized access, corruption, or adversarial attacks.

Team

This could be you!

We are always looking for people who are passionate about advancing AI responsibility. You can get in touch with us by using one of the following methods.

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