At no time has trust been more tested or valued in leaders and each other than today. Trust is the basis for connection. Trust is all-encompassing: physical, emotional, digital, financial, and ethical. New technology adds another dimension to the concept of trust. Not only do we need to trust people, we also need to trust systems that are increasingly making decisions for us. How can we be sure an algorithm is trustworthy?
Knowing that trust is a central component of the interaction between people and systems based on artificial intelligence, we need to understand and advance the technology that trustworthy systems are based on. The ROBUST LTP focuses on advancing the technological underpinnings of these systems, in terms of accuracy, reliability, repeatability, resilience, and safety. Only if these are guaranteed, we can realize one of the promises of artificial intelligence: to contribute to solving today’s societal challenges.
The ROBUST vision is to address the challenge of trustworthy AI-based systems in a multi-disciplinary, multistakeholder set-up, with knowledge institutes, industrial partners, governmental organizations, and societal stakeholders. ROBUST combines the creation of economic opportunities with social progress. We operationalize this ambition by explicitly aligning our research agenda on robust AI with the United Nation’s sustainable development goals.
The project is funded in a public private partnership by NWO/NLAIC and the private partners. We do this as a network of labs in which knowledge institutes and industrial stakeholders pursue collaborative research agendas. Three of these labs have landed at JADS.
The objective of SAFEGUARD is auditing of AI software by exploring, developing and validating novel auditing theories, tools, and methodologies. The aim is to monitor and audit whether AI applications adhere in terms of fairness (no bias), explainability, transparency (easy to explain), robustness and reliability (delivering same results under various execution environments), respect of privacy (respecting GDPR), and safety and security (with no vulnerabilities).
ILUSTRE will be a living lab in the Caribbean with the objective to develop, implement and test AI innovations that will accelerate the use of clean energy and advance solutions in water treatment and wastewater recycling/purification. Alongside with these sustainable development objectives, the innovation partners aim at establishing an education platform for AI and data science for the Caribbean region.
How can AI contribute to the functioning of the media along the entire production chain (sourcing, production, distribution, engagement), and even fundamentally change aspects of the media as we know it? The lab will explore the potential of AI-driven solutions for the media, their professional role, opportunities for new business models and new ways of engaging with users, while taking into account professional values and the emerging regulatory framework for AI. The lab seeks to develop AI-based methods and solutions that facilitate more diverse news offerings to readers, working alongside human journalists.
For more information about PhD positions for the ROBUST labs, check our vacancies page.
We do cool stuff that matters, with data. The Jheronimus Academy of Data Science (JADS) is a unique cooperation between Eindhoven University of Technology (TU/e) and Tilburg University (TiU). At JADS, we believe that data science can provide answers to society’s complex issues. We provide innovative educational programs, data science research, and support for business and society. With a team of lecturers, students, scientists and entrepreneurs – from a wide range of sectors and disciplines – we work on creating impact with data science. We do this by connecting people, sectors and industries: in the past 5 years we have been working with 300+ organizations on data-related projects. Our main drivers? Doing cool stuff that matters with data. Our location at the former monastery Mariënburg in Den Bosch houses a vibrant campus fully dedicated to data science.