AI 中文总结
针对欧盟人工智能法案下高风险人工智能系统在算法招聘领域缺乏标准的情况，本文提出特定标准化建议，构建垂直、特定领域框架，映射法案要求到具体建议，关注招聘系统多方面风险及治理，且不依赖特定项目技术工件。
AI 中文摘要
根据近期欧洲立法，高风险人工智能系统须适应以符合如风险管理、数据质量与治理、日志记录与可追溯性、技术文档、透明度、人工监督和准确性等特定领域要求。由于人工智能标准化进程预计仍具迭代性，且目前尚无完全涵盖算法招聘挑战的欧洲人工智能标准，我们针对欧盟委员会指定的相关人工智能领域提出了特定的面向标准化的建议。对于每个领域，我们阐述了高风险领域尤其是招聘领域的人工智能系统应满足的要求，以及为确保其合理使用和理想性能应开展的活动。与现有的人工智能治理和标准化水平方法不同，本文通过将人工智能法案的要求映射到具体的标准化建议，为算法招聘尤其是基于排名的招聘系统贡献了一个垂直的、特定领域的框架，重点关注招聘系统中的生命周期歧视风险、公平感知数据治理、可解释性、人工监督和部署后监测。尽管我们的建议受欧洲项目FINDHR成果的启发，但它们并不依赖于该项目的技术工件，可使用替代方法、工具或治理机制来实施。
英文摘要
According to the recent European legislation, high-risk AI systems will have to adapt in order to comply with requirements related to specific areas, like risk management, data quality and governance, logging and traceability, technical documentation, transparency, human oversight, and accuracy, as outlined in the European Artificial Intelligence (AI) Act. As the standardisation process for AI is expected to remain iterative and, so far, there are no European standards on AI fully covering the challenges of algorithmic hiring, we propose specific standardisation-oriented recommendations related to the relevant AI areas specified by the European Commission. For each of these areas, we set the context by describing the requirements that AI systems in high-risk domains, and especially in recruitment, should fulfil, as well as the activities that should be carried out to ensure their appropriate use and desired performance, in line with the requirements deriving from the AI Act. Unlike existing horizontal approaches to AI governance and standardisation, this paper contributes a vertical, domain-specific framework for algorithmic hiring, and especially ranking-based recruitment systems, by mapping the requirements of the AI Act to concrete standardisation recommendations, focusing on lifecycle discrimination risks, fairness-aware data governance, explainability, human oversight, and post-deployment monitoring in recruitment systems. Even though our recommendations were informed by the outcomes of the European project FINDHR, they are not tied to the project's technical artefacts and could be implemented using alternative methods, tools, or governance mechanisms.
