Research

How to make AI explainable?

• Have you ever wondered how AI reaches its decisions? The challenge is crucial: to enable humans to understand the results of an Artificial Intelligence system.
• Explainable AI techniques combine methods and processes designed to show the operating logic of an algorithm and provide clear explanations to users of how AI makes decisions.
• There are already myriad techniques depending on context, target audience and the impact of the algorithm. And that’s without factoring in the development of generative AI systems, which raises new challenges in terms of explainability techniques.
Read the article

Explainability of artificial intelligence systems: what are the requirements and limits?

Read the article

Data and AI Ethics Council, guarantor of responsible AI at Orange

Read the article
A person checks their heart rate on a smartwatch while holding a smartphone. The setting is natural, with trees in the background.

Wireless Power Transfers: ERWPT breaks new ground with electric fields

Read the article
Crowdsourcing cacatoès

Smartphone data to map the outer atmosphere and monitor urban wildlife

Read the article

Institutional funding and interpersonal solidarity in Senegal

Read the article

Mobile money: an alternative to a bank account for small businesses in Senegal?

Read the article