JADS: PhD on Fairness of AI Software Systems (0,8 – 1,0 fte)

Jheronimus Academy of Data Science (JADS) Den Bosch, isproud to start with three large Robust AI labs together with:

JADS is seeking enthusiastic colleagues for the position of PhD students. We operationalize the huge ambition around AI 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. This position is part of the Deloitte project.

Short Description

The next generation of enterprise applications is quickly becoming AI-enabled, providing novel functionalities with unprecedented levels of automation and intelligence. As we recover, reopen, and rebuild, it is time to rethink the importance of trust. At no time has it been more tested or valued in leaders and each other. Trust is the basis for connection. Trust is all-encompassing: physical, emotional, digital, financial, and ethical. A nice-to-have is now a must-have; a principle is now a catalyst; a value is now invaluable.
Are you an enthusiastic and ambitious researcher with a completed master's degree in a field related to machine learning (Computer science, AI, Data Science) or in Electrical Engineering with an affinity for AI and deep learning? Does the idea of working on real-world problems and with industry partners excite you? Are you passionate about using trustworthy AI methods for the next generation of auditing processes, which are increasingly AI-enabled and data-driven? And are you interested in delivering new tools to ascertain the fairness of the next generation of AI software?
We are recruiting a Ph.D. candidate who will develop and validate novel concepts, methods, and tools for monitoring, auditing, and fostering fairness of AI software systems and trial them with industrial partners who work with Deloitte.

Job Description

This vacancy falls under the auspices of the JADE lab, which is the data/AI engineering and governance research UNIT of the Jheronimus Academy of Data Science (JADS), and DELOITTE. In particular, this position is associated with JADE's ROBUST program on Auditing for Responsible AI Software System (SAFE-GUARD), which is financed under the NWO LTP funding scheme with Deloitte as the key industry partner.
The overall objective of SAFE-GUARD is auditing of AI software, it may be further refined in the following more elaborated goal: "Explore, develop and validate novel auditing theories, tools, and methodologies that will be able to monitor and audit whether AI applications adhere in terms of fairness (no bias), explainability, and 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)."
The industrial setting of the deep involvement of Deloitte will balance the rigour with relevance and ascertain fit with societal requirements and trends, validation with industrial case studies.

Scientific Challenge

Application software developers cannot train-, test- and deploy AI models independent of socio-political, ethical, cultural, and personal context. At the same time, data is not objective: it is inherently reflective of pre-existing social and cultural biases, thus implying that AI (and AI-induced applications) may lead to (unintended) negative consequences and inequitable outcomes in practical settings. This project will develop novel methodologies, including techniques and tools, that can be exploited during audit activity when detecting AI software bias, possibly predicting those conditions and recommending ways to triage them. These aspects render important aspects when developing trustworthy AI software.