| OCR Text |
Show 102 David Gerritsen college of social & behavioral science Entire industries are based on the physiological, cognitive, and economic demands of technology on end users. Designers think deeply about the size and weight of the computer, the complexity of the software, and the cost of the distribution. There is not, however, much research into the social aspects of human-computer interaction (HCI). This includes, for example, research into how friendly a computer program should be, or to what degree a user may attribute independence of will and thought to the machine. Both constructs emphasize the importance of appraisal processes. To understand this issue better, it is necessary to study the unique qualities of HCI when computers are programmed to mimic natural social behavior. The Computers are Social Actors paradigm (Reeves & Nass, 1996) began this exploration, and the current research expands it. We begin by replicating a study on acts of reciprocity toward a computer (Fogg, 1997), then consider two additional social constructs. First, we collect the participants' agreeable-ness rating as it may predict the number of favors performed for the computer. Second, we look at individ-ual differences in expressions of altruism and whether or not a strange computer is treated similarly to an unknown human. The guiding hypotheses are that people who are high in agreeableness should be more generous to a software agent than people who are low in agreeableness (Eisenberger, Cotterell, & Marvel, 1987), and that a positive correlation exists between the number of favors performed and an individual's trait of reciprocal altruism (Ashton, 1998). Results contradict the original study, and show that the help-fulness of the computer does not predict how many favors a user will perform. Of greater interest, users who ranked low in agreeableness performed more favors than those who ranked high in agreeableness when the computer was helpful. Finally, kin altruists performed more favors than reciprocal altruists, but only when the computer was unhelpful. From an applied perspective, the results could have implications for software design. From a theoretical perspective, the social cognition literature would benefit from a deeper understanding of the humanity which users attribute to artificial agents. Ashton, M. (1998).Kin Altruism, Reciprocal Altruism, and the Big Five Personality Factors.Evolution and Human Behavior, 19(4), 243-255. doi:10.1016/S1090-5138(98)00009-9 Eisenberger, R., Cotterell, N., & Marvel, J. (1987).Reciprocation ideology.Journal of Personality and Social Psychology, 53(4), 743-750. doi:10.1037//0022-3514.53.4.743 Fogg, B. J. (1997). Charismatic computers: creating more likable and persuasive interactive technologies by leveraging principles from social psychology. Stanford University, Stanford, CA, USA. Reeves, B. & Nass, C. (1996).The Media Equation: How people treat computers, television, and new media like real people and places. New York: Cambridge University Press. DECISION MAKING AND JUDGMENTS WITH A COMPUTER David Gerritsen, Kyle Gagnon, (Jeanine Stefanucci, Frank Drews) Department of Psychology University of Utah UNDERGRADUATE RESEARCH ABSTRACTS Kyle Gagnon Frank Drews The computer either puts partial effort or full effort into helping the participant with a task the participant cares about. After offering either good or bad advice, the computer asks the participant for help on a color sorting task which is important to the computer. Jeanine Stefanucci |
