Traditional iris recognition systems rely on dedicated sensors, typically using near-infrared illumination, which demand a high degree of user cooperation. Recent studies have demonstrated the feasibility of performing iris recognition on samples captured from uncooperative users in uncontrolled environments, including ocular images cropped from high-resolution facial portraits posted on websites and social media. These advancements are largely driven by novel artificial intelligence techniques and the availability of datasets containing ocular samples collected under non-ideal conditions. Nevertheless, the improved accuracy and robustness of iris recognition methods introduce new challenges related to privacy protection. This chapter examines recent advancements in iris recognition using samples obtained from websites and social media, focusing on algorithms, public datasets, privacy concerns, and potential mitigation strategies.