The surge in data availability and processing power has made it possible for Artificial Intelligence (AI) / Machine Learning (ML) to advance at a faster rate. However, the different nature of AI/ML systems has posed significant new challenges to Requirements Engineering (RE). Literature has shown that AI/ML system does not use current RE methods. It was also found that data scientists are taking the role of the requirements engineers resulting in software that does not focus on users needs. Building AI/ML software with a human-centric approach has proven to produce more ethical, transparent, inclusive and non-bias outcomes. This research will look into how to adjust current RE methodologies to fit into AI/ML systems from a human-centric perspective. The project will establish human-centric AI/ML requirements and map them into a modeling language tool. A platform will be built to model and display the requirements visually. Finally, a case study will be conducted to evaluate the newly developed language, as well as a final survey to finalize our findings. To date, I have conducted a Systematic Literature Review (SLR) to find current RE methodologies and challenges in AI/ML and currently in the planning phase of a survey to find adopted practices in the industry.

I am currently studying my PhD at Deakin University. My research aims to identify the different approaches used in managing Requirements Engineering techniques for Artificial Intelligence systems from a human-centric approach.