ELSA’s approach to safe and secure AI by design
ELSA is based on the understanding that safe and secure AI can only be achieved by building on foundational research. Relying on heuristics alone is susceptible to arms races and will not yield appreciable, reliable or sustainable levels of safety or security and is prone to fail overcoming the key obstacles in shaping AI in compliance with our European values. ELSA will overcome this by combining rigorous approaches such as robustness certification and differential privacy with machine learning and deep learning that are ubiquitous in applications. Hence, ELSA is based on a research agenda that encompasses the key research directions and fosters vital research by bringing together researchers across communities as well as different stakeholders. The research community is unified and directed towards addressing grand challenges that reach across use-cases by benchmarks that will drive innovation and provide measurable progress. The use-cases call for different, domain-specific requirements and risk analysis that require solutions, tools, and software that overcome obstacles in a trustworthy approach that conforms with legal and ethical principles grounded on European values. Our investigations emphasize state of the art methodology and technology (with a particular focus on Deep Learning techniques) in order to ensure practical relevance of the solutions.
Excellence needs to be the foundation of the Lighthouse.
Grand Challenges of secure and safe AI are of fundamental nature.
To overcome the obstacles hampering AI deployment, we need to build a lighthouse on solid foundations. In order to develop secure and safe-by-design solutions, we need rigorous formulation built on the latest advance in science and technology. Latest advances in robustness certification and differential privacy are just two examples of how rigorous approaches have provided solutions that escape arms-race-issues - an essential property in safe and secure systems.
Building a Lighthouse that is future proof. Identifying solutions to meet current demands requires both a foundational approach that is sustainable and future-oriented, capable of addressing unanticipated novel challenges that differ from existing needs. Accordingly, the lighthouse must be equipped to address the needs of both current and future generations. This requires outstanding academic research that will advance foundational, principled knowledge that will endure as technology advances.
ELLIS - a backbone for AI in Europe built on excellence.
ELLIS (European Laboratory for Learning and Intelligent Systems) is a network of leading machine learning researchers in Europe. It is based on the maxim of excellence in research and has created an operational, highly successful and internationally visible network, with members from over 100 organizations. The ELLIS network has greatly contributed to overcoming fragmentation and brought together key players across Europe under a common vision. It is built on 3 pillars:
ELLIS Fellowship/Research Programs: ELLIS Fellowship Programs currently link 337 carefully selected leading researchers and outstanding junior researchers (with 113 ERC grants) into 13 thematic Research Programs. The fellows in each program meet several times a year for intensive scientific exchange on high-impact questions. The topics of the Programs cover different areas of machine learning methodology and application domains.
ELLIS Units: In parallel with the Fellowship Programs, 30 ELLIS Units represent localised groups of best AI researchers in 13 European countries. ELLIS Units are selected by an international selection committee based on scientific excellence criteria. The Units provide continuity and link the best research institutions to an active and productive network.
ELLIS PhD/Postdoc Program: ELLIS PhD and Postdoc program supports young researchers through joint supervision and mobility support. Each young researcher is supervised by two academic ELLIS supervisors from different countries with at least 6 month mobility, or in collaboration between academia and industry. The first open PhD call attracted over 1300 applications from over 70 countries and over 90 nationalities, thereby promoting the next generation of AI/ML experts in Europe.