工作记忆和需要可解释的人工智能 - 从医疗保健,社交媒体和保险的场景
M Liebherr1,2, E Gößwein1,2, C Kannen3
1Department of General Psychology: Cognition, University Duisburg-Essen, Duisburg, Germany.
Heliyon
|February 10, 2025
概括
当人工智能系统与个人相关时,人们更需要可解释性AI (XAI),特别是在健康和保险决策方面. 像工作记忆能力这样的认知能力并没有显著影响这种需求.
科学领域:
- 人与计算机的交互
- 人工智能伦理学 人工智能伦理学
- 认知心理学 认知心理学
背景情况:
- 可解释AI (XAI) 对于专业,伦理和商业原因至关重要,特别是对于"黑子"AI系统.
- 对XAI的感知需求可以受到个人相关性,个性特征和认知功能的影响.
研究的目的:
- 调查个人相关性和个人的认知差异如何影响人们对XAI的感知需求.
- 在不同的AI应用场景中探索工作记忆容量,人格特征 (智力) 和XAI需求之间的关系.
主要方法:
- 一个在线实验,有215名参与者评估客观工作记忆能力和"智力"的人格特质.
- 参与者在三个场景中评估了他们对XAI的需求:皮肤癌检测,社交媒体个性化和汽车保险定价.
主要成果:
- 与社交媒体个性化相比,在个人投资 (健康,保险) 较高的场景中报告了对XAI的更高需求.
- 客观工作记忆容量与XAI需求没有关联.
- 自我报告的智力表明,与XAI的需求有轻微的积极关联,特别是在汽车保险方面.
结论:
- 对人工智能系统的个人投资是确定对可解释人工智能的感知需求的关键因素.
- 虽然像工作记忆这样的认知功能可能不会直接影响XAI的需求,但像智力这样的个性方面可能在特定情况下发挥着微妙的作用.
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