  Integrating Artificial Intelligence (AI) into mobile and wearables offers
numerous benefits at individual, societal, and environmental levels. Yet, it
also spotlights concerns over emerging risks. Traditional assessments of risks
and benefits have been sporadic, and often require costly expert analysis. We
developed a semi-automatic method that leverages Large Language Models (LLMs)
to identify AI uses in mobile and wearables, classify their risks based on the
EU AI Act, and determine their benefits that align with globally recognized
long-term sustainable development goals; a manual validation of our method by
two experts in mobile and wearable technologies, a legal and compliance expert,
and a cohort of nine individuals with legal backgrounds who were recruited from
Prolific, confirmed its accuracy to be over 85\%. We uncovered that specific
applications of mobile computing hold significant potential in improving
well-being, safety, and social equality. However, these promising uses are
linked to risks involving sensitive data, vulnerable groups, and automated
decision-making. To avoid rejecting these risky yet impactful mobile and
wearable uses, we propose a risk assessment checklist for the Mobile HCI
community.
