A possibility of inappropriate use of gender studies in human-robot Interaction

In 2018, it was reported that male students were given priority over female students in exams at some Japanese medical universities. The underlying reason for this controversial priority is thought to be the assumption that female doctors experience more difficulties than male doctors in the clinical field. One of the universities involved justified setting their admissions criteria higher for women based on an academic paper in the field of psychology that claimed women had better communication skills than men (Mainichi Japan 2018). The officials of the university explained that women tend to reach psychological maturity earlier and have relatively higher communication skills than men; therefore, they adjusted their test scoring in an attempt to correct the disadvantage for male test takers. The paper referenced in their statement (Cohn 1991) investigated sex differences in maturity, but not sex differences in communication skills. Nevertheless, it was used to justify gender bias in the exam without referring to actual gender bias in the clinical field or the higher unemployment rate of female doctors than male doctors, which suggests a discriminatory labor environment against female doctors. In response to this situation, some Japanese psychologists published a statement denouncing the university’s action as justifying sexism by unsophisticatedly quoting the research. The statement gained the support of over 60 others in the field. Moreover, one academic society on psychological research, the Japan Society of Personality Psychology (https ://jspp.gr.jp/en/), held an academic seminar where one of the statement’s authors was invited to discuss how psychologists should interpret gender studies and present the results of such studies to society. During the academic seminar, an evolutionary psychologist and social psychologist explained the current research environment on gender studies in each of their research fields: (1) gender differences tend to be used to justify the maintenance of the present status in communities; (2) it is hard to interpret gender differences in a strictly statistical sense (both significant probability and effect size); and (3) there have been no guidelines or standards on how researchers should state their results when they find gender effects in their studies (note: these statements are based on a report by the author of the paper, Nomura, who participated to the seminar). Many studies on gender effects have recently been reported in the fields of human–machine interaction, including affective computing. In particular, researchers in the field of human–robot interaction (HRI) have conducted several studies on gender effects (Nomura 2017). HRI involves the characteristic of the embodiment of robots, which leads to easier assignment of gender-specific properties with robots (so-called “gendered robots”). Moreover, interaction effects of gendered robots with other factors, including the user’s gender, can be explicitly investigated in HRI. However, these studies may be used to design daily-life applications of robots that entrench existing gender biases. Whether men or women are more likely to prefer or dislike robots is an important issue in HRI (Nomura 2017). Some studies found that females had more negative attitudes toward interactions with robots than males in general (Nomura et al. 2006, 2008), and other studies reported that males had a more positive attitude than females towards the usefulness of a specific type of robot (Kuo et al. 2009; Lin et al. 2012). Effects of user gender in perception of and feelings about robots may depend on other factors such as the type of robots, and the situations and contexts under which robots are used. There are existing studies comparing males and females under different conditions with respect to the existence and absence of various factors related to robots, such as politeness in behaviors (Strait et al. 2015), machinelike or human-like appearance (Tung 2011), and task structure on cooperation or competition with robots (Mutlu et al. 2006). * Tatsuya Nomura nomura@rins.ryukoku.ac.jp