Combating Identity Threat of Machine: The effect of group-affirmation on humans' intellectual performance loss

기계의 정체성 위협에 대항하기: 집단 가치 확인이 인간의 지적 수행 저하에 미치는 효과

  • Cha, Young-Jae (Interdisciplinary Program in Cognitive Science, Seoul National University) ;
  • Baek, Sojung (Interdisciplinary Program in Cognitive Science, Seoul National University) ;
  • Lee, Hyung-Suk (Program in History and Philosophy of Science, Seoul National University) ;
  • Bae, Jonghoon (Graduate School of Business, Seoul National University) ;
  • Lee, Jongho (Department of Electrical and Computer Engineering, Seoul National University) ;
  • Lee, Sang-Hun (Department of Brain and Cognitive Science, Seoul National University) ;
  • Kim, Gunhee (Department of Computer Science and Engineering, Seoul National University) ;
  • Jang, Dayk (College of Liberal Studies, Seoul National University)
  • 차영재 (서울대학교 인지과학 협동과정) ;
  • 백소정 (서울대학교 인지과학 협동과정) ;
  • 이형석 (서울대학교 과학사 및 과학철학 협동과정) ;
  • 배종훈 (서울대학교 경영전문대학원) ;
  • 이종호 (서울대학교 전기.정보공학부) ;
  • 이상훈 (서울대학교 뇌인지과학과) ;
  • 김건희 (서울대학교 컴퓨터공학부) ;
  • 장대익 (서울대학교 자유전공학부)
  • Received : 2019.10.04
  • Accepted : 2019.10.04
  • Published : 2019.09.30


Motivation of human individuals to perform on intellectual tasks can be hampered by identity threat from intellectual machines. A laboratory experiment examined whether individuals' performance loss on intellectual tasks appears under human identity threat. Additionally, by affirming alternative attributes of human identity, researchers checked whether group-affirmation alleviate the performance loss on intellectual tasks. This research predicted that under high social identity threat, individuals' performance loss on the intellectual tasks would be moderated by valuing alternative attributes of human identity. Experiment shows that when social identity threat is increased, human individuals affirmed alternative human attributes show higher performance on intellectual tasks than individuals non-affirmed. This effect of human-group level affirmation on performance loss did not appear in the condition of low social identity threat. Theoretical and practical implications were discussed.


Social Identity;Identity Threat;Performance Loss;Human-Machine Competition;Group Affirmation;Intergroup Relations


Supported by : Seoul National University


  1. Bae, J., Cha, Y.-J., Lee, H., Lee, B., Baek, S., Choi, S., & Jang, D. (2017). Social networks and inference about unknown events: A case of the match between Google's AlphaGo and Sedol Lee. PloS One, 12(2), e0171472.
  2. Becker, J. C. (2012). The system-stabilizing role of identity management strategies: Social creativity can undermine collective action for social change. Journal of Personality and Social Psychology, 103(4), 647-662.
  3. Branscombe, N. R., Ellemers, N., Spears, R., & Doosje, B. (1999). The context and content of social identity threat. In N. Ellemers, R. Spears, & B. Doosje (Eds.), Social identity: Context, commitment, content (pp. 35-58). Oxford: Blackwell Science.
  4. British Science Association. (n.d.). One in three believe that the rise of artificial intelligence is a threat to humanity. Retrieved from
  5. Burt, R. S. (2009). Structural holes: The social structure of competition. Harvard university press.
  6. Crocker, J., Major, B., & Steele, C. (1998). Social stigma: The psychology of marked relationships. In The handbook of social psychology (Vol. 2, pp. 504-553). Boston: McGraw-Hill.
  7. Deligianis, C., Stanton, C. J., McGarty, C., & Stevens, C. J. (2017). The impact of intergroup bias on trust and approach behaviour towards a humanoid robot. Journal of Human-Robot Interaction, 6(3), 4-20.
  8. Derks, B., Scheepers, D., Van Laar, C., & Ellemers, N. (2011). The threat vs. challenge of car parking for women: How self-and group affirmation affect cardiovascular responses. Journal of Experimental Social Psychology, 47(1), 178-183
  9. Derks, B., van Laar, C., & Ellemers, N. (2006). Striving for success in outgroup settings: Effects of contextually emphasizing ingroup dimensions on stigmatized group members' social identity and performance styles. Personality and Social Psychology Bulletin, 32(5), 576-588.
  10. Eyssel, F., & Kuchenbrandt, D. (2012). Social categorization of social robots: Anthropomorphism as a function of robot group membership. British Journal of Social Psychology, 51(4), 724-731.
  11. Ferrari, F., Paladino, M. P., & Jetten, J. (2016). Blurring human-machine distinctions: Anthropomorphic appearance in social robots as a threat to human distinctiveness. International Journal of Social Robotics, 8(2), 287-302.
  12. Fraune, M. R., Nishiwaki, Y., Sabanovic, S., Smith, E. R., & Okada, M. (2017). Threatening flocks and mindful snowflakes: How group entitativity affects perceptions of robots. In Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot Interaction (pp. 205-213). New York: ACM.
  13. Gunn, G. R., & Wilson, A. E. (2011). Acknowledging the skeletons in our closet: The effect of group affirmation on collective guilt, collective shame, and reparatory attitudes. Personality and Social Psychology Bulletin, 37(11), 1474-1487.
  14. Hogg, M. A., Abrams, D., Otten, S., & Hinkle, S. (2004). The social identity perspective: Intergroup relations, self-conception, and small groups. Small Group Research, 35(3), 246-276.
  15. Kim Eui-Joong et al. (2003). Standardization, Reliability, and Validity Evaluation of the Korean Version of Mood Scale(K-POMS). swu-myen-ps ceng-sin-sayng-li, 10(1), 39-51.
  16. Kim Ji-min. (2016. 3. 8). AlphaGo Developer "First Steps on Long Journey... Medical AI Coming Soon". Moneytoday. URL:
  17. Krastev, S., McGuire, J. T., McNeney, D., Kable, J. W., Stolle, D., Gidengil, E., & Fellows, L. K. (2016). Do political and economic choices rely on common neural substrates? A systematic review of the emerging neuropolitics literature. Frontiers in psychology, 7, 264.
  18. Lalonde, R. N. (1992). The dynamics of group differentiation in the face of defeat. Personality and Social Psychology Bulletin, 18(3), 336-342.
  19. Lee Hyun-hee et al. (2003). Validation of the Korean Version of Positive Affect and Negative Affect Schedule. Korean Journal of Clinical Psychology, 22(4), 935-946.
  20. Lee, P & Gurnkl, D & Dusentrieb, Daniela. (2015). Why Truly Intelligent Machines Need Emotions. International Journal of Artificial Intelligence. 3.
  21. Lee Kwang-hyung et al. (2015). Future Issue Analysis Report. Ministry of Science, ICT and Future Planning.
  22. Lin, N. (2002). Social capital: A theory of social structure and action (Vol. 19). Cambridge university press.
  23. Picard, R. W. (2004). Toward Machines With Emotional Intelligence. In The Science of Emotional Intelligence: Knowns and Unknowns. 29-30. 10.1093/acprof:oso/9780195181890.003.0016.
  24. Sherman, D. K., Kinias, Z., Major, B., Kim, H. S., & Prenovost, M. (2007). The group as a resource: Reducing biased attributions for group success and failure via group affirmation. Personality and Social Psychology Bulletin, 33(8), 1100-1112.
  25. Silver, D., Huang, A., Maddison, C. J., Guez, A., Sifre, L., Van Den Driessche, G., ... Lanctot, M. (2016). Mastering the game of Go with deep neural networks and tree search. Nature, 529(7587), 484-489.
  26. Steele, C. M. (1988). The psychology of self-affirmation: Sustaining the integrity of the self. In L. Berkowitz (Ed.), Advances in experimental social psychology (Vol. 21, pp. 261-302). San Diego, CA: Academic Press.
  27. Tajfel, H. (1981). Human groups and social categories: Studies in social psychology. CUP Archive.
  28. Tajfel, H., & Turner, J. C. (1979). An integrative theory of intergroup conflict. In W. G. Austin, & S. Worchel (Eds.), The social psychology of intergroup relations (pp. 33-37). Monterey, CA: Brooks/Cole.
  29. Tajfel, H., & Turner, J. C. (1986). The social identity theory of intergroup behavior. In S. Worchel & W. Austin (Eds.), Psychology of intergroup relations (pp. 7-24). Chicago: Nelson-Hall.
  30. Tajfel, H., & Wilkes, A. L. (1963). Classification and quantitative judgement. British journal of psychology, 54(2), 101-114.
  31. Van Laar, C., Derks, B., & Ellemers, N. (2013). Motivation for education and work in young Muslim women: The importance of value for ingroup domains. Basic and Applied Social Psychology, 35(1), 64-74.
  32. Yeo, I. (2017). Human perception on artificial intelligence: Blessing or threat? (Master's thesis). Seoul National University.
  33. Yogeeswaran, K., Zlotowski, J., Livingstone, M., Bartneck, C., Sumioka, H., & Ishiguro, H. (2016). The interactive effects of robot anthropomorphism and robot ability on perceived threat and support for robotics research. Journal of Human-Robot Interaction, 5(2), 29-47.
  34. Fraune, M. R., Sabanovic, S., & Smith, E. R. (2017). Teammates first: Favoring ingroup robots over outgroup humans. In 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), 2017 (pp. 1432-1437). Lisbon: IEEE.