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.

翻译：将人工智能（AI）集成到移动和可穿戴设备中，为个人、社会及环境层面带来了诸多益处。然而，这也凸显了人们对新兴风险的担忧。传统的风险与效益评估往往是零散的，且通常需要昂贵的专家分析。我们开发了一种半自动方法，该方法利用大型语言模型（LLMs）来识别移动和可穿戴设备中的AI应用，根据欧盟《人工智能法案》对其风险进行分类，并确定其与全球公认的长期可持续发展目标相一致的效益；通过两位移动与可穿戴技术专家、一位法律与合规专家，以及从Prolific平台招募的九位具有法律背景的人员对我们的方法进行人工验证，确认其准确率超过85%。我们发现，移动计算的具体应用在提升福祉、安全和社会平等方面具有巨大潜力。然而，这些前景广阔的应用也关联着涉及敏感数据、弱势群体和自动化决策的风险。为了避免拒绝这些具有风险但影响深远的移动与可穿戴应用，我们为移动人机交互（Mobile HCI）领域提出了一份风险评估清单。