安妮，你还好吗？基于风格和上下文的个性化如何塑造AI辅助决策
Annie, Are You Okay? How Style- and Context-Based Personalization Shape AI-Assisted Decision-Making
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中文总结 AI 辅助
本研究通过预注册实验发现，基于上下文的个性化（而非风格个性化）能可靠改变用户对股票排序的决策，使其向AI推荐靠拢，且影响在低专业知识用户中更强，引发对个性化决策支持治理的担忧。
中文摘要 AI 辅助
随着人们转向生成式AI寻求财务建议，这些系统可以个性化其沟通方式和内容。这些个性化形式是否以不同方式影响决策仍不清楚。我们进行了一项预注册的2×2被试间因子实验（N=240）：参与者对三只可行性相当的股票进行排序，与AI讨论后重新排序。参与者感知到了两种形式的个性化，但只有基于上下文的个性化可靠地改变了排序行为：它增加了重新考虑，并使排序向AI指定的推荐靠拢。参与者感到更受影响，但并未认为AI更正确、更值得信赖、更智能、更讨人喜欢或质量更高。那些初始排序远离其推荐的参与者更向推荐靠拢，同时认为其建议正确性较低；探索性分析表明，专业知识较低的参与者更容易受影响。这些发现表明，个性化AI可以在仅留下最小评估痕迹的情况下引导人们在可辩护选项中的决策，引发了对个性化决策支持设计和治理的担忧。
英文摘要
As people turn to generative AI for financial advice, these systems can personalize how they communicate and what they say. Whether these forms of personalization shape decisions differently remains unclear. We conducted a preregistered 2 x 2 between-subjects factorial experiment (N=240): participants ranked three comparably viable stocks, discussed them with an AI, and reranked them. Participants perceived both forms of personalization, but only context-based personalization reliably changed ranking behavior: it increased reconsideration and moved rankings toward the AI's assigned recommendation. Participants felt more influenced without judging the AI as more correct, trustworthy, intelligent, likeable, or high-quality. Those initially farther from its recommendation moved more toward it while judging its advice less correct; exploratory analyses suggest greater susceptibility among lower-expertise participants. These findings show how personalized AI can steer decisions among defensible options with only a minimal evaluative trace, raising concerns for the design and governance of personalized decision support.
发表机构
- Northeastern University（东北大学）
- University College Dublin（都柏林大学学院）
机构由 AI 辅助整理，请以论文原文为准。
