In our aim to create a Human-Centred AI Master’s programme, the HCAIM Consortium follows the definition of AI HLEG: “The human-centric approach to AI strives to ensure that human values are central to how AI systems are developed, deployed, used and monitored, by ensuring respect for fundamental rights.”
To answer the requirements of this definition, the programme covers the technical, ethical and practical elements of artificial intelligence.
We have designed our content around the three phases of the MLOps lifecycle – development, deployment and maintenance of machine learning models. The three phases of MLOps are each subdivided into several topics that cover the technical (AI/ML), ethical and practical elements of that part of the MLOps lifecycle: modelling (the exploration of the data and the design of the AI/ML models), deployment (taking AI/ML models into production and connecting to existing systems), and evaluation (maintenance of an AI/ML model in production).
We created three core modules in alignment with the above-mentioned ML-Ops phases: Modelling (Module A), Deployment (Module B), and Evaluation (Module C). We added a fourth module – (D) Graduation, to enable students to show that they can independently solve challenges proposed by the industry based on current needs and requirements related to human-centred artificial intelligence. To support the students herewith, the lesson plan Research in Practice runs parallel to the other Modules and guides the students from the start of the programme in their thesis process. This covers the core of the Human-centered AI master.
The structure of the programme is visualised in the table below.