AI建议强化传统性别角色
AI Advice Reinforces Traditional Gender Roles
AI总结：
该研究通过两项含四款领先LLM的大规模审计实验，发现AI职业建议会向女性求职者推荐更低薪资、更侧重照护相关内容，向男性推荐更高薪资、更侧重职业发展，从而强化传统性别角色。
摘要：
专业人士越来越多地向人工智能（AI）寻求职业建议。我们在职业谈判情境中测试了大型语言模型（LLM）是否会向女性和男性求职者提供不同的建议。通过两项大规模审计实验，涉及四款领先模型，LLM不仅向女性角色推荐的薪资目标低于男性角色，还构建了不同的谈判议程：对女性候选人更优先考虑灵活性、照护责任和福祉，对男性候选人则更优先考虑经济回报、流动性和晋升。这些差异分别与独立人员对主要照护者和养家糊口者角色相关雇佣条款的评分密切对应。我们的研究发现了一条微妙路径，个性化AI建议可能通过该路径强化职场性别不平等：引导原本条件相当的用户走向传统性别角色。
英文摘要：
Professionals are increasingly turning to artificial intelligence (AI) for career advice. We tested whether large language models (LLMs) provide different advice to female and male job candidates in the context of career negotiations. Across two large-scale audit experiments, including four leading models, the LLMs not only recommended lower salary targets for female than male personas, but also constructed distinct negotiation agendas, prioritizing flexibility, caregiving, and well-being more highly for female candidates, and financial rewards, mobility, and advancement more highly for male candidates. These differences closely tracked independent human ratings of employment terms associated with primary caregiver and breadwinner roles, respectively. Our findings identify a subtle pathway through which personalized AI advice may reinforce gender inequality at work: steering otherwise equivalent users toward traditional gender roles.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
