Towards Trustworthy AI in Europe
The objective of the EU is to secure the uptake of algorithmic systems in Europe, especially those based on artificial intelligence (AI), while ensuring the protection of the safety and fundamental rights of European citizens.
AI made in Europe should be trustworthy: transparent, fair and human-centred, with a positive societal impact.
Understanding the social impact of AI
In this research topic, the JRC:
- advances the scientific understanding of machine and human intelligence,
- studies the societal and ethical impact of algorithms,
- defines methodologies for trustworthy AI,
- and provides scientific contributions to EU AI policies.
This work addresses different types of AI systems, such as recommender systems, facial processing systems, conversational systems or automated driving systems. The JRC maps the opportunities these systems offer to different application domains, assesses risks that these systems bring to safety, fundamental rights and mental well-being, develops practical methodologies for trustworthy AI, evaluating and ensuring transparency, fairness and human oversight of those systems and studies the long-term impact of algorithms, such as the impact on children or mental health.
Related policy initiatives
This topic allows the JRC a direct contribution to two core policy initiatives in the different stages of the policy making process:
The AI Act
Our work also supports AI policies in specific sectors such as transport, education or culture.
Research topics: Trustworthy AI, diversity, non-discrimination and fairness in AI, transparency of algorithmic systems, human-centric machine learning, recommender systems, facial processing, automated driving, children-AI interaction, music and culture.
Teachers and students should be prepared to better understand and engage in the ethical use of AI and data.
Researchers, policymakers and industry should involve children and their caregivers when designing new policies and initiatives dealing with artificial intelligence (AI)-based technologies
A recent study in Nature Machine Intelligence, analyses how benchmarking is transforming the Artificial Intelligence (AI) scientific research and its concrete applications in different fields.