Citizen Science Research with the Square Kilometre Array Observatory (SKAO)

Over the past two decades, internet-enabled citizen science research (CSR) has contributed to significant discoveries while involving millions of people in the research process. Our review highlights CSR in extragalactic radio astronomy and emphasises that such approaches will become increasingly relevant across radio astronomy in the era of the Square Kilometre Array (SKA). As astronomical data volumes grow, CSR is converging with Artificial Intelligence and Machine Learning (AI/ML), creating hybrid human-machine frameworks suited to big-data challenges. Two CSR platforms, Radio Galaxy Zoo and RAD@home, demonstrate success: the former excels in large-scale, web-based catalogue creation, while the latter combines structured training with collaborative discovery. Following this, we propose CSR with the SKA, namely SKA@home, with two modes: one purely web-based and the other in collaboratory mode with national training programmes. We argue that CSR can complement, and at times surpass, automated AI/ML pipelines, particularly in identifying rare, intricate, or unexpected features. Illustrative CSR discoveries include an episodic wide-angle-tailed radio galaxy, a jet-galaxy interaction, a collimated synchrotron thread, a twin-ring odd radio circle, and a large-scale shock ahead of a cluster-infalling galaxy. Consistent with the IAU's recognition of CSR as a driver of Astronomy for Development and the United Nations' affirmation of participation in science as a universal human right, both the SKA construction proposal and outreach strategies show commitment to enabling CSR with SKA. The proposed SKA@home would not only enhance the early discovery potential of SKA data but also initiate a deeper and more meaningful connection with society at large.