算法歧视比人类歧视引起更少道德惩罚欲

doi:10.3724/SP.J.1041.2022.01076

摘要/Abstract

摘要：

算法歧视屡见不鲜, 人们对其有何反应值得关注。6个递进实验比较了不同类型歧视情境下人们对算法歧视和人类歧视的道德惩罚欲, 并探讨其潜在机制和边界条件。结果发现：相对于人类歧视, 人们对算法歧视的道德惩罚欲更少(实验1~6), 潜在机制是人们认为算法(与人类相比)更缺乏自由意志(实验2~4), 且个体拟人化倾向越强或者算法越拟人化, 人们对算法的道德惩罚欲越强(实验5~6)。研究结果有助于更好地理解人们对算法歧视的反应, 并为算法犯错后的道德惩罚提供启示。

关键词: 算法, 算法歧视, 道德惩罚, 自由意志信念, 拟人化

Abstract:

The application of algorithms is believed to contribute to reducing discrimination in human decision-making, but algorithmic discrimination still exists in real life. So is there a difference between folk responses to human discrimination and algorithmic discrimination? Previous research has found that people's moral outrage at algorithmic discrimination is less than that at human discrimination. Few studies, however, have investigated people's behavioral tendency towards algorithmic discrimination and human discrimination, especially whether there is a difference in their desire for moral punishment. Therefore, the present study aimed at comparing people's desire to punish algorithmic discrimination and human discrimination as well as finding the underlying mechanism and boundary conditions behind the possible difference.
To achieve the research objectives, six experiments were conducted, which involved various kinds of discrimination in daily life, including gender discrimination, educational background discrimination, ethnic discrimination and age discrimination. In experiment 1 and 2, participants were randomly assigned to two conditions (discrimination: algorithm vs. human), and their desire for moral punishment was measured. Additionally, the mediating role of free will belief was tested in experiment 2. To demonstrate the robustness of our findings, the underlying mechanism (i.e., free will belief) was further examined in experiment 3 and 4. Experiment 3 was a 2 (discrimination: algorithm vs. human) × 2 (belief in free will: high vs. low) between-subject design, and experiment 4 was a single-factor (discrimination: human vs. algorithm with free will vs. algorithm without free will) between-subject design. Experiment 5 and 6 were conducted to test the moderating role of anthropomorphism. Specifically, participants’ tendency to anthropomorphize was measured in experiment 5, and the anthropomorphism of algorithm was manipulated in experiment 6.
As predicted, the present research found that compared with human discrimination, people have less desire to punish algorithmic discrimination. And the robustness of this result was demonstrated by the diversity of our stimuli and samples. In addition, we found that free will belief played a mediating role in the effect of discrimination (algorithm vs. human) on the desire to punish. That is to say, the reason why people had less desire to punish when facing algorithm discrimination was that they thought algorithms had less free will than humans. Finally, the results also demonstrated the moderating effect of anthropomorphism.
These results enrich literature regarding algorithm discrimination as well as moral punishment from the perspective of social psychology. First, this research explored people's behavioral tendency towards algorithmic discrimination by focusing on the desire for moral punishment, which contributes to a better understanding of people's responses to algorithmic discrimination. Second, the results are consistent with previous studies on people’s mind perception of artificial intelligence. Third, it adds evidence that free will has a significant impact on moral punishment.

Key words: algorithm, algorithmic discrimination, moral punishment, free will belief, anthropomorphism

中图分类号:

B849: C91

许丽颖, 喻丰, 彭凯平. (2022). 算法歧视比人类歧视引起更少道德惩罚欲. 心理学报, 54(9), 1076-1092.

XU Liying, YU Feng, PENG Kaiping. (2022). Algorithmic discrimination causes less desire for moral punishment than human discrimination. Acta Psychologica Sinica, 54(9), 1076-1092.

图/表 5

图1 自由意志信念的中介作用

图2 不同自由意志信念组对人类和算法歧视的道德惩罚欲评分注：*p < 0.05, **p < 0.01.

图3 不同歧视主体组的道德惩罚欲评分注：*p < 0.05, ***p < 0.001.

图4 拟人化倾向的调节作用

图5 不同歧视主体组的道德惩罚欲评分注：*p < 0.05, ***p < 0.001.

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