Asking for Help from a Gendered Robot

Asking for Help from a Gendered Robot Emma Alexander, Caroline Bank, Jie Jessica Yang, Bradley Hayes, Brian Scassellati Department of Computer Science, Yale University 51 Prospect St, New Haven, CT 06511 {caroline.bank,emma.alexander,jiejessica.yang,bradley.h.hayes,brian.scassellati}@yale.edu Abstract This project investigates the effects of gender in a human-robot collaboration interaction. In the experiment, participants com- pleted four Sudoku-like puzzles with a robot from which they could verbally elicit help. The robot was given the gendered characteristics of a gendered computer generated voice and ei- ther the name Charlotte (female condition) or Charley (male condition). Contrary to expectations from psychology, male participants asked the robot for help more frequently regardless of its assigned gender. Participants of both genders reported feeling more comfortable with a robot assigned the other gen- der and preferred the male robot’s help. Findings indicate that gender effects can be generated in human-robot collab- oration through relatively unobtrusive gendering methods and that they may not align with predictions from psychology. Background Gender effects are present and well-studied in human-human interaction and collaboration. When presented with the de- scription of a potential helper, men have been seen to be more likely to seek help from a woman than from a man (Nadler, Maler, & Friedman, 1984). On the other hand, mixed-gender groups working on collaborative computer-based tasks ex- hibit less collaborative behavior (Collazos, Guerrero, Llana, & Oetzel, 2002) and lower performance (Underwood, Mc- Caffrey, & Underwood, 1990) than same-sex groups in iden- tical circumstances. Women were also more likely to seek help in general (Nadler et al., 1984). Women and men also show differences in asking for help from attractive versus unattractive members of the same or different gender (Nadler, Shapira, & Ben-Itzhak, 1982). These effects also carry over to perceived helpfulness: Menzel and Carrell (1999) found a strongly mediated but nonetheless significant effect on per- ceived learning where students believed they learned more when taught by a professor of the same gender. Existing literature suggests that helpfulness is not the only quality that people perceive through a lens of gender. In 1968, Rosenkrantz et al found that over 75% of participants of both genders associated a number of attributes to one gen- der or the other. In particular, participants associated compe- tence, dominance, independence, and logic with males, and emotion, subjectiveness, submission, and tact with females (1968). These stereotypes were reaffirmed in a survey by Hosoda and Stone (2000). Biernat and Kobrynowicz found that these biases can affect other behavior, as subjects that were asked to evaluate candidates in a mock job interview setting rated woman and minorities against a lower standard for baseline competence but more stringent standards for high levels of competence (1997; 2010). Even gendered voices with no other stimuli evoke different responses in the brain (Lattner, Meyer, & Friederici, 2005; Decasper & Prescott, After interacting with a robot, people will often bring up comments on robot gender unprompted, demonstrating that its strength as a social cue is still highly relevant (Carpenter et al., 2009). In another study, participants used more complex language when describing the stereotypically female domain of relationships to a female robot than a male robot (Powers et al., 2005). Men have also been shown to be more will- ing to make donations when asked by a female robot (Siegel, Breazeal, & Norton, 2009). This study also demonstrated that after the interaction, participants saw robots of the other gen- der as more credible, trustworthy, and engaging, indicating an other-gender preference in the case of a robot asking a human for a help. It has been found that in particular situ- ations, people prefer interaction with an other-gender robot (Park, Kim, & del Pobil, 2011) and will consider a robot dis- playing other-gender characteristics more attractive, interest- ing, and trustworthy than one displaying same-gender char- acteristics (Siegel et al., 2009). In many studies, gender was conferred to the robot using only a single, relatively subtle cue: a gendered name and introduction (Nomura & Takagi, 2011), voice modulation (Siegel et al., 2009), a combination of the two (Crowelly, Villanoy, Scheutzz, & Schermerhornz, 2009), or voice modulation accompanied by variation in lip color (Powers et al., 2005). These results indicate that even with limited gender cues behavioral responses can be elicited from humans by robotic stimulus. This study explores the shaping of perceptions within the specific case of a human seeking help from a gendered robot collaborator. Methods To study gender effects on human-robot collaboration we de- signed a 2x2 study on robot and participant gender. Robot gender was assigned with a name/pronoun cue and a voice cue. Past studies have shown that these cues alone are suffi- ciently strong to elicit a gender response. Changes in appear- ance were avoided as they could confound results. We picked a puzzle-based task because it provided a way for the robot to contribute to the participant’s success while allowing the variety of interaction to be limited, ensuring that participants shared a standard experience. The puzzle chosen was sudoku, with the numbers 1-9 replaced with the letters A-I so that both analytical and verbal skills would be indicated and the robot perception would not be affected by stereotypes of numeri- cal intelligence. Participants were given four puzzles in or- der of increasing difficulty to control for differences in their previous experience with the activity. Each puzzle was in-