不可替代代币（NFT）市场中发现的性别和种族差异

在一项新研究中，卡内基梅隆大学的研究人员研究了虚拟化身的性别和种族对不可替代代币（NFT）市场交易价格的影响。

Researchers from Carnegie Mellon University, New York University, and Harvard University have conducted a new study examining the impact of avatars' gender and race on transaction prices in the non-fungible token (NFT) marketplace. Their findings, published in the International Journal of Research in Marketing, reveal pronounced gender and racial disparities in NFT prices, challenging the expectation that these disparities would be diminished in the emerging digital marketplace.

来自卡内基梅隆大学、纽约大学和哈佛大学的研究人员进行了一项新研究，探讨虚拟人物的性别和种族对不可替代代币（NFT）市场交易价格的影响。他们的研究结果发表在《国际营销研究杂志》上，揭示了 NFT 价格中明显的性别和种族差异，挑战了这些差异将在新兴数字市场中缩小的预期。

The study, led by Yuan Yuan, a Ph.D. student in marketing at CMU, sought to investigate the presence of gender and racial biases in the NFT marketplace, given the younger, wealthier, and more politically progressive demographic of NFT investors. As the NFT market continues to grow and digital communities are increasingly leveraged as brand assets, understanding such biases becomes crucial.

该研究由博士袁媛领导。鉴于 NFT 投资者更年轻、更富有、政治上更进步，卡内基梅隆大学市场营销专业的学生试图调查 NFT 市场中是否存在性别和种族偏见。随着 NFT 市场不断增长，数字社区越来越多地被用作品牌资产，理解这种偏见变得至关重要。

In the NFT marketplace, avatar headshots represent individuals' digital identities. The researchers aimed to identify the effects of avatars' gender and race on NFT prices, how these effects varied over time, and what NFT providers could do to mitigate disparities.

在 NFT 市场中，头像头像代表了个人的数字身份。研究人员旨在确定化身的性别和种族对 NFT 价格的影响、这些影响如何随时间变化，以及 NFT 提供商可以采取哪些措施来缩小差异。

Their analysis of CryptoPunks avatars, a popular NFT collection, revealed that female CryptoPunks were sold at a 37% lower price than their male counterparts (i.e., avatars with similar image attributes), while Black CryptoPunks were sold at a 31% lower price than their white counterparts. Furthermore, a controlled lab experiment causally confirmed both gender and race price premiums, as well as the presence of racial bias in these purchasing behaviors.

他们对流行的 NFT 系列 CryptoPunks 头像的分析显示，女性 CryptoPunk 的售价比男性同行（即具有相似图像属性的头像）低 37%，而黑色 CryptoPunk 的售价比男性同行低 31%。白人同行。此外，一项受控实验室实验证实了性别和种族价格溢价的因果关系，以及这些购买行为中存在种族偏见。

Interestingly, the study also found that certain attributes of the avatars, such as those linked to high-tech or higher education (e.g., 3D virtual reality headsets or nerd glasses), were associated with countering the disparities. Incorporating these attributes into avatars could potentially counteract bias in the NFT marketplace.

有趣的是，研究还发现化身的某些属性，例如与高科技或高等教育相关的属性（例如 3D 虚拟现实耳机或书呆子眼镜），与消除差异有关。将这些属性纳入化身可能会抵消 NFT 市场中的偏见。

These findings challenge the notion that gender and racial biases are diminished in the emerging, technologically advanced marketplace. Instead, the study highlights deep-seated and persistent societal stereotypes and prejudices in the digital marketplace, particularly in the devaluation of Black avatars across demographics, showcasing the complexity of biases in digital marketplaces.

这些发现挑战了性别和种族偏见在新兴的、技术先进的市场中减少的观念。相反，该研究强调了数字市场中根深蒂固且持续存在的社会刻板印象和偏见，特别是在人口统计数据中黑人化身的贬值，展示了数字市场中偏见的复杂性。

"NFT creators and platforms can promote a more balanced marketplace by introducing attributes that counteract bias," said Kannan Srinivasan, professor of management, marketing, and business technology at CMU, who co-authored the study. "NFT platforms that want to harmonize efficiency with fairness can also adopt policies that discourage bias, providing more equitable guidelines for the creation and transaction of NFTs."

该研究的合著者、卡内基梅隆大学管理、营销和商业技术教授 Kannan Srinivasan 表示：“NFT 创作者和平台可以通过引入抵消偏见的属性来促进更加平衡的市场。” “想要协调效率与公平的 NFT 平台也可以采取阻止偏见的政策，为 NFT 的创建和交易提供更公平的指导方针。”

The authors also acknowledged some limitations of their study, such as the difficulty in distinguishing between factors perceived as more valuable and those that are personally preferred, and the exclusive focus on human avatars. Additionally, they noted that the diversity of their database might not fully represent the general population.

作者还承认他们的研究存在一些局限性，例如难以区分被认为更有价值的因素和个人偏好的因素，以及仅关注人类化身。此外，他们指出，他们的数据库的多样性可能无法完全代表一般人群。