首页|Investigators from Fudan University Release New Data on ArtificialIntelligence (Artificial Intelligence Products and Their Influence OnIndividuals’ Objectific ation: a Narrative Review)
Investigators from Fudan University Release New Data on ArtificialIntelligence (Artificial Intelligence Products and Their Influence OnIndividuals’ Objectific ation: a Narrative Review)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Current study results on Artificial In telligence have been published. According to newsreporting originating from Sha nghai, People’s Republic of China, by NewsRx correspondents, researchstated, “W ith the advancement of technology, artificial intelligence (AI) has permeated va rious aspects ofour social lives. AI products exhibit significant gender biases that may contribute to both self-objectificationand the sexual objectification of others.”Our news editors obtained a quote from the research from Fudan University, “Desp ite this, the impactof AI products on individuals’ objectification and self-obj ectification has not been thoroughly examined,with the mechanisms involved and potential moderating factors remaining unclear. This paper offers aconcise synt hesis and review of the extensive literature on gender bias in AI and sexual obj ectification,covering research up to October 2023. Synthetic analysis indicates that AI products exhibit pronouncedgender biases and cues of sexual objectific ation in both internal attributes, such as algorithms, and externalattributes, such as voice and appearance. These biases may affect an individual’s self-objec tification andthe sexual objectification of others. Internalization, social com parison, and dehumanization are identified askey mechanisms through which AI pr oducts affect individuals’ objectification. Factors like the performancecharact eristics of AI products, individual psychological traits, and human-AI interacti on characteristics mayplay a moderating role. Finally, this paper suggests futu re research directions, including focusing on howto reduce gender bias in AI de sign, exploring the mechanisms through which AI influences objectification,and identifying protective factors involved in this process, as well as addressing t he limitations of existingresearch.”
ShanghaiPeople’s Republic of ChinaAs iaArtificial IntelligenceEmerging TechnologiesMachine LearningFudan Univ ersity
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