New master in Responsible Data Science: for ethical and sustainable AI developments.
As of September 2026, the new Responsible Data Science master’s programme at Maastricht University prepares students to become professionals who deploy artificial intelligence and other digital technologies with respect for both people and the planet.
As data science and artificial intelligence techniques mature, so too must the responsibility that accompanies their use. Experience shows that the responsible application of these technologies often falls short, whether through ignorance or intent. Maastricht University’s Faculty of Science and Engineering aims to address this gap with its new Responsible Data Science programme. No organisation wants to face a scandal like the Dutch childcare benefits affair, nor do users wish to be misled by biased AI-algorithms.
Industry and student demand
“In discussions with partners in business and government, we’ve observed a clear need for professionals who can critically assess the societal impacts of data science and AI, ensuring these technologies are integrated responsibly into operations,” says Mark Winands, chair of the Department of Advanced Computing Sciences.
Students, too, are increasingly interested in the ethical, legal, social, and ecological dimensions of their future work, Winands notes. “They want to approach their field in a more holistic way.” Students in Responsible Data Science are trained IT specialists who can bridge the gap between technical experts and their non-technical colleagues.
Curriculum Focus
“Throughout the programme, we delve deeper into techniques that enable responsible data use,” explains Visara Urovi, associate professor. “This includes explainable AI, where the reasoning behind AI models is made transparent, and privacy-preserving techniques applied to protect individual’s data.” The curriculum covers cutting-edge topics such as machine learning, generative AI, blockchain, federated learning, FAIR data principles.
A Responsible Approach
“We do not train students to be innovators who solely develop new AI technologies,” Urovi clarifies. “Instead, we prepare them to ensure responsible data science practices across various domains, keeping innovations within ethical, legal, social, and ecological boundaries.”
Graduates of Responsible Data Science will enter the workforce as academically trained IT professionals who know how to deploy data science and AI responsibly ensuring these technologies serve humanity, not undermine it.
For more information, please visit the Responsible Data Science website
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