Substra Foundation becomes Labelia Labs with the mission to develop the positive impacts of Data Science by equipping and promoting collaborative, responsible and trustworthy approaches!
Towards trustworthy data science
As of today, it is difficult to trust AI
AI technologies require massive amounts of data to achieve high predictive performances. The circulation, processing and compilation of datasets by multiple actors raises concerns about privacy issues and risks of sensitive information leaks. Further, many in the tech industry, research sector, and public organizations are growing more preoccupied with AI standards, such as how algorithms are trained and tested, and how to measure the significance and robustness of AI performance. As of today, with clear risks and work-in-progress regulations, it is difficult to trust AI.
Simultaneously, ML and data science keep expanding into research, business processes, marketing and advertising, products and services in countless industries. Whether presented as new techniques, specialised tools, or general capabilities, this diffusion of ML fuels a multiplicity of projects aimed at gaining new insights and opens up many possible fields where AI could stimulate innovations. The potential of AI is immense.
The potential of AI is immense
Trustworthy AI BY-DESIGN is needed
The two trends, the growing concerns about privacy, transparency and quality of AI, and its expansion into many sectors and organizations, won’t disappear in the coming years. We believe that we need to address both, and in reconciling and combining them we can foster a sound development of trustworthy AI. New technical and organizational solutions are required for this endeavor, to build up trust, to enable large scale collaborations of citizens, companies and institutions; ultimately, to create the conditions for responsible, privacy-preserving, and quality data science. In short, trustworthy AI by-design is needed, and Labelia Labs (ex Substra Foundation) is entirely committed to contributing to it.
We are an independent non-profit organization dedicated to fostering the development of trustworthy data science ecosystems (Learn more about us).
Our projects and consortiums
HealthChain - AI on clinical data (concluded end of 2021)
The HealthChain consortium gathers French hospitals, research centers and start-up organisations together with Labelia Labs (ex Substra Foundation) to develop AI models on clinical data. Substra framework enables the training and validation of AI models and, in doing so, secures the remote analysis of sensitive data. This project will provide the first proof of concept of the Substra framework and will prove its compliance with GDPR.
(9 partners, 10M€ funding)
More details
MELLODDY - Drug discovery (concluded mid-2022)
The MELLODDY project aims to develop a platform for creating more accurate models to predict which chemical compounds may be most promising in the later stages of drug discovery and development. It demonstrates a new model of collaboration between traditional competitors in drug discovery and involves an unprecedented volume of competitive data. The platform aims to address the need for security and privacy preservation while allowing for enough information exchange to boost predictive performance.
(17 partners, 18M€ funding)
More details
Responsible and trustworthy data science
We animate a serie of open and collaborative workshops to define ‘responsible and trustworthy data science’.
The objective? Establish together an open source framework of risks and best practices enabling organizations to assess their maturity level. Have a look on GitHub at the current release and ongoing work of the ”responsible and trustworthy AI assessment”.
Towards trustworthy data science
