Are Machines Gender Neutral? Gender‐Stereotypic Responses to Computers With Voices

Abstract

This study tested whether computers embedded with the most minimal gender cues will evoke gender‐based stereotypic responses. Using an experimental paradigm (N = 40) that involved computers with voice output, the study tested 3 gender‐based stereotypes under conditions in which all suggestions of gender were removed, with the sole exception of vocal cues. In all 3 cases, gender‐stereotypic responses were obtained. Because the experimental manipulation involved no deception regarding the source of the voices. this study presents evidence that the tendency to gender stereotype is extremely powerful, extending even to stereotyping of machines.

Trusting in Machines: How Mode of Interaction Affects Willingness to Share Personal Information with Machines

“…If people apply human gender stereotypes to machines, as some research suggests [31], the machine's perceived gender could influence users' trust as well. Therefore our field experiment had eight conditions in a 2 (user's expression modality: talk, type) × 2 (machine's response modality: talk, type) × 2 (machine's gender: male, female) between-participants fully randomized experimental design.…”

Response to Assessment Feedback: The Effects of Grades, Praise, and Source of Information

“…These researchers described themselves as functioning within the Computers as Social Actors (CASA) paradigm and argued that people may be unconsciously perceiving computers and other media as being intentional social agents (Nass, Moon, & Carney, 1999). Some studies showed that people often attributed human characteristics to computers: People were polite to machines (Nass et al, 1999), perceived machines as competent teammates (Nass, Fogg, & Moon, 1996), ascribed gender and personalities to machines (Nass, Moon, & Green, 1997), and got angry and punished them (Ferdig & Mishra, 2004). Responding socially to a computer was also quite common and typical for people of all ages and levels of expertise (Mishra, 2006).…”

A Comparison of Avatar-, Video-, and Robot-Mediated Interaction on Users’ Trust in Expertise

“…Since gender can influence trust in computer recommendation systems (Nass et al, 1997), we ensured that the advisors are female for all media representations (e.g., the same female audio tracks, female names). The sizes of the representations of the actor were made consistent in each media, by making sure that the video and avatar clips were projected at the same size, and at the same eye level, as the robot.…”