 The study provides an overview of digital approaches in automated and machine learning assessments of hearing using pure tone audiometry, focusing on accuracy, reliability, and time efficiency. The results show that machine learning approaches require fewer trials than conventional threshold seeking approaches, and personal digital devices make assessments more affordable and accessible. Validity can be enhanced using digital technologies for quality surveillance, including noise monitoring and detecting inconclusive results. The study concludes that automated assessments using digital devices can support task shifting, self-care, telehealth, and clinical care pathways. This article was authored by Jan Willem Wozman, Leontine Pragt, Robert Eichelboom, and others.