İLERİ TEKNOLOJİLER, YAPAY ZEKÂ TEMELLİ ÇÖZÜMLER: DUYGU ODAKLI BİR YAKLAŞIM

Year 2023, Volume: 18 Issue: 60, 367 - 395, 27.07.2023

Ömer Faruk Çelebi , Nilşah Cavdar Aksoy , Alev Kocak Alan , Ebru Tümer Kabadayı

https://doi.org/10.14783/maruoneri.1189209

Cited By: 2

Abstract

Yapay zekâ teknolojisinin ilerlemesiyle birlikte, bireylerin yaşamlarına dâhil olan yeni nesil ürün ve hizmetlerin çeşitliliği her geçen gün artmaktadır. Bu çeşitlilik, bireylerin yapay zekâ teknolojisi ile temas ettiği alanları da genişletmektedir. Bu nedenle, bireylerin yapay zekâ teknolojisine yönelik duygularının anlaşılması araştırmaya değer konular arasında öne çıkmaktadır. Bu çalışmanın amacı, bireylerin yapay zekâ teknolojisi ve yapay zekâ destekli ürün ve hizmetler ile etkileşimlerinde açığa çıkan duyguları keşfetmektir. Bu doğrultuda, bu çalışmada nitel araştırma yöntemi benimsenmiş ve 10 katılımcı ile derinlemesine mülakat gerçekleştirilmiştir. Bulgulara göre temel duygu tipolojileri şu şekildedir: mutluluk, memnuniyet, şaşırma, merak, heyecan, umut, rahatlık, hayal kırıklığı, öfke, sinirlilik, korku, ürkütücülük, uyarılmama (canlandırılmama), rahatsızlık, endişe, umutsuzluk ve memnuniyetsizlik. Ayrıca bulgular, katılımcıların yapay zekâ teknolojisine yönelik olarak birden fazla duyguyu birlikte yaşayabildiğini (memnuniyet-korku, rahatlık-korku gibi) göstermektedir. Çalışma bulgularının, bireylerin yapay zekâ teknolojisine ve yapay zekâ destekli ürün ve hizmetlere yönelik duygularının anlaşılmasına katkı sağlayacağı düşünülmektedir.

Keywords

Duygu Tipolojileri, Yapay Zekâ Uygulamaları, Temel Duygular, Olumlu Duygular, Olumsuz Duygular

ADVANCED TECHNOLOGIES, ARTIFICIAL INTELLIGENCE-BASED SOLUTIONS: AN EMOTION-FOCUSED APPROACH

Abstract

With the advancement of artificial intelligence technology, the diversity of new-generation products and services included in individuals’ life is increasing day by day. This diversity also expands the areas where individuals come into contact with artificial intelligence technology. Therefore, understanding emotions toward artificial intelligence technology stands out among the topics worth researching. This study aims to explore the emotions that emerge in the interactions of individuals with artificial intelligence technology and artificial intelligence- based products and services. In doing this, a qualitative research method was adopted in this study, and an in-depth interview technique was applied with 10 participants. According to the findings, the basic emotion typologies are as follows: happiness, pleased, astonished, curiosity, excitement, hope, comfort, disappointment, anger, nervousness, fear, frightened, unaroused, discomfort, anxiety, hopelessness and unpleased. Furthermore, the findings show that participants can experience more than one emotion simultaneously (such as pleased- fear or comfort-fear) for artificial intelligence technology. It is thought that the study’s results will contribute to the understanding of individuals’ emotions towards artificial intelligence technology and artificial intelligence- based products and services.

Keywords

Emotion Typologies, Artificial Intelligence Applications, Basic Emotions, Positive Emotions, Negative Emotions

References

• Abd Aziz, S. (2016). Does fear of new car technologies influence brand loyalty relationship?. Journal of Marketing Management, 4(1), 125-136.
• Adams-Hutcheson, G., & Longhurst, R. (2017). ‘At least in person there would have been a cup of tea’: interviewing via Skype. Area, 49(2), 148–155. https://doi.org/10.1111/area.12306
• Airenti, G. (2015). The cognitive bases of anthropomorphism: from relatedness to empathy. International Journal of Social Robotics, 7(1), 117-127.
• Arastaman, G., FİDAN, İ. Ö., & Fidan, T. (2018). Nitel araştırmada geçerlik ve güvenirlik: Kuramsal bir inceleme. Van Yüzüncü Yıl Üniversitesi Eğitim Fakültesi Dergisi, 15(1), 37-75.
• Arsenijevic, U., & Jovic, M. (2019). Artificial Intelligence Marketing: Chatbots. 2019 International Conference on Artificial Intelligence: Applications and Innovations (IC-AIAI), 19–193. https://doi.org/10.1109/IC-AIAI48757.2019.00010
• Başkale, H. (2016). Nitel araştırmalarda geçerlik, güvenirlik ve örneklem büyüklüğünün belirlenmesi. Dokuz Eylül Üniversitesi Hemşirelik Fakültesi Elektronik Dergisi, 9(1), 23-28.
• Bagozzi, R. P., Gopinath, M., & Nyer, P. U. (1999). The role of emotions in marketing. Journal of the academy of marketing science, 27(2), 184-206.
• Barrett, L. F. (2017). Categories and their role in the science of emotion. Psychological inquiry, 28(1), 20-26.
• Beaudry, A., & Pinsonneault, A. (2010). The other side of acceptance: Studying the direct and indirect effects of emotions on information technology use. MIS quarterly, 689-710.
• Beedie, C., Terry, P., & Lane, A. (2005). Distinctions between emotion and mood. Cognition & Emotion, 19(6), 847-878.
• Castillo, D., Canhoto, A. I., & Said, E. (2021). The dark side of AI-powered service interactions: exploring the process of co-destruction from the customer perspective. Service Industries Journal, 41(13–14), 900–925. https://doi.org/10.1080/02642069.2020.1787993
• Chuah, S. H. W., & Yu, J. (2021). The future of service: The power of emotion in human-robot interaction. Journal of Retailing and Consumer Services, 61(January), 102551. https://doi.org/10.1016/j.jretconser.2021.102551
• Cohen, J. B., Pham, M. T., & Andrade, E. B. (2018). The nature and role of affect in consumer behavior. In Handbook of consumer psychology (pp. 306-357). Routledge.
• Conrad, A. M., & Munro, D. (2008). Relationships between computer self-efficacy, technology, attitudes and anxiety: Development of the computer technology use scale (CTUS). Journal of Educational Computing Research, 39(1), 51-73.
• Corbo, L., Costa, S., & Dabi, M. (2022). The evolving role of artificial intelligence in marketing : A review and research agenda. 128(March 2020), 187–203. https://doi.org/10.1016/j.jbusres.2021.01.055
• Cowan, B. R., Pantidi, N., Coyle, D., Morrissey, K., Clarke, P., Al-Shehri, S., Earley, D., & Bandeira, N. (2017). “What can i help you with?”: Infrequent users’ experiences of intelligent personal assistants. Proceedings of the 19th International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2017. https://doi.org/10.1145/3098279.3098539
• Creswell, J. W. (2013). Nitel araştırma yöntemleri. Ankara: Siyasal Kitabevi.
• Das S, Das I, Shaw RN, Ghosh A (2021) Advance machine learning and artificial intelligence applications in service robot. Artif Intell Fut Gener Robot 83–91. https://doi.org/10.1016/B978-0-323-85498-6.00002-2
• Du, S., & Xie, C. (2021). Paradoxes of artificial intelligence in consumer markets: Ethical challenges and opportunities. Journal of Business Research, 129(August 2020), 961–974. https://doi.org/10.1016/j.jbusres.2020.08.024
• Elo, S., Kääriäinen, M., Kanste, O., Pölkki, T., Utriainen, K., & Kyngäs, H. (2014). Qualitative content analysis: A focus on trustworthiness. SAGE open, 4(1), 2158244014522633.
• Erbuğ, E., & Özalkan, G. Ş. (2022) Pandemi Süresince Nitel Araştırma: Çevrimiçi Platformlar Üzerinden Derinlemesine Görüşmelerin İmkân Ve Sınırlılıkları. Sosyoloji Araştırmaları Dergisi, 25(1), 36-46.
• Gaur, S. S., Herjanto, H., & Makkar, M. (2014). Journal of Retailing and Consumer Services Review of emotions research in marketing , 2002 – 2013. Journal of Retailing and Consumer Services, 21(6), 917–923. https://doi.org/10.1016/j.jretconser.2014.08.009
• Gardner, M. P. (1985). Mood states and consumer behavior: A critical review. Journal of Consumer research, 12(3), 281-300.
• Gillath, O., Ai, T., Branicky, M. S., Keshmiri, S., Davison, R. B., & Spaulding, R. (2021). Attachment and trust in artificial intelligence. Computers in Human Behavior, 115(September 2020), 106607. https://doi.org/10.1016/j.chb.2020.106607
• Gkinko, L., & Elbanna, A. (2022). The appropriation of conversational AI in the workplace: A taxonomy of AI chatbot users. International Journal of Information Management, 102568.
• Guo, F., Li, M., Qu, Q., & Duffy, V. G. (2019). The effect of a humanoid robot’s emotional behaviors on users’ emotional responses: Evidence from pupillometry and electroencephalography measures. International Journal of Human–Computer Interaction, 35(20), 1947-1959.
• Hohenberger, C., Spörrle, M., & Welpe, I. M. (2016). How and why do men and women differ in their willingness to use automated cars? The influence of emotions across different age groups. Transportation Research Part A: Policy and Practice, 94, 374-385.
• Holthöwer, J., & van Doorn, J. (2022). Robots do not judge: service robots can alleviate embarrassment in service encounters. Journal of the Academy of Marketing Science, 1-18.
• Hornung, O., & Smolnik, S. (2022). AI invading the workplace: negative emotions towards the organizational use of personal virtual assistants. Electronic Markets, 32(1), 123-138.
• Horstmann, A. C., & Krämer, N. C. (2019). Great expectations? Relation of previous experiences with social robots in real life or in the media and expectancies based on qualitative and quantitative assessment. Frontiers in psychology, 10, 939.
• Huang, M. H. (2001). The theory of emotions in marketing. Journal of Business and Psychology, 16(2), 239-247.
• Huang, M. H., & Rust, R. T. (2018). Artificial Intelligence in Service. Journal of Service Research, 21(2), 155–172. https://doi.org/10.1177/1094670517752459
• Huang, M., Rust, R., & Maksimovic, V. (2019). The Feeling Economy: 1–23. https://doi.org/10.1177/0008125619863436
• Izard, C. E. (1977). Differential emotions theory. In Human emotions (pp. 43-66). Springer, Boston, MA.
• Janiesch, C., Zschech, P., & Heinrich, K. (2021). Machine learning and deep learning. Electronic Markets, 31(3), 685-695.
• Kim, S. Y., & Schmitt, B. H. (2019). Eliza in the uncanny valley : anthropomorphizing consumer robots increases their perceived warmth but decreases liking. 1–12.
• Koc, E., & Boz, H. (2014). Psychoneurobiochemistry of tourism marketing. Tourism Management, 44, 140-148.
• Lazarus, R. S., & Folkman, S. (1984). Stress, appraisal, and coping. Springer publishing company.
• Lee, H., Lee, J., Chung, N., & Koo, C. (2018). Tourists’ happiness: are there smart tourism technology effects?. Asia Pacific Journal of Tourism Research, 23(5), 486-501.
• Li, S., Scott, N., & Walters, G. (2015). Current and potential methods for measuring emotion in tourism experiences: a review. Current Issues in Tourism, 18(9), 805-827.
• Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. Sage.
• Liang, Y., & Lee, S. A. (2017). Fear of Autonomous Robots and Artificial Intelligence : Evidence from National Representative Data with Probability Sampling. International Journal of Social Robotics, 9(3), 379–384. https://doi.org/10.1007/s12369-017-0401-3
• Liddy, E. D. (2003). Natural language processing, encyclopedia of library and information science (2nd ed.). New York: Marcel Decker.
• Loderer, K., Pekrun, R., & Lester, J. C. (2020). Beyond cold technology: A systematic review and meta-analysis on emotions in technology-based learning environments. Learning and instruction, 70, 101162.
• Loureiro, S.M.C., Guerreiro, J., Eloy, S., Langaro, D. and Panchapakesan, P. (2019), “Understanding the use of virtual reality in marketing: a text-mining based review”, Journal of Business Research, Vol. 100, pp. 514-530.
• Lu, Y. (2019). Artificial intelligence: a survey on evolution, models, applications and future trends. Journal of Management Analytics, 6(1), 1-29.
• Martin, D., Neill, M. O., Hubbard, S., & Palmer, A. (2008). The role of emotion in explaining consumer satisfaction and future behavioural intention. 3(July 2006), 224–236. https://doi.org/10.1108/08876040810871183
• Mori, M. (1970). The uncanny valley: the original essay by Masahiro Mori. IEEE Spectrum.
• Moustakas, C. (1994). Phenomenological research methods. Sage publications.
• Mozafari, N., Weiger, W. H., & Hammerschmidt, M. (2022). Trust me, I’m a bot – repercussions of chatbot disclosure in different service frontline settings. Journal of Service Management, 33(2), 221–245. https://doi.org/10.1108/JOSM-10-2020-0380
• Murphy, J., Gretzel, U., & Pesonen, J. (2019). Marketing robot services in hospitality and tourism: the role of anthropomorphism. Journal of Travel & Tourism Marketing, 36(7), 784-795.
• Müller, V. C. (2021). Ethics of artificial intelligence 1. In The Routledge social science handbook of AI (pp. 122-137). Routledge.
• Oksanen, A., Savela, N., Latikka, R., & Koivula, A. (2020). Trust toward robots and artificial intelligence: An experimental approach to human–technology interactions online. Frontiers in Psychology, 11, 568256.
• Olgun, C. K. (2008). Nitel Araştırmalarda İçerik Analizi Tekniğİ. Sosyoloji Notları, 66.
• Oluwalola, F. K. (2015). Effect of emotion on distance e-learning—The fear of technology. International Journal of Social Science and Humanity, 5(11), 966-970.
• Ostern, N. (2018). Do you trust a trust-free transaction? Toward a trust framework model for blockchain technology.
• Pai, C. K., Liu, Y., Kang, S., & Dai, A. (2020). The role of perceived smart tourism technology experience for tourist satisfaction, happiness and revisit intention. Sustainability, 12(16), 6592.
• Palinkas, L. A., Horwitz, S. M., Green, C. A., Wisdom, J. P., Duan, N., & Hoagwood, K. (2015). Purposeful sampling for qualitative data collection and analysis in mixed method implementation research. Administration and policy in mental health and mental health services research, 42(5), 533-544.
• Park, J., & Yang, S. (2006). The moderating role of consumer trust and experiences: Value driven usage of mobile technology. International Journal of Mobile Marketing, 1(2).
• Plutchik, R. (1980). A general psychoevolutionary theory of emotion. In Theories of emotion (pp. 3-33). Academic press.
• Polkinghorne, D. E. (1989). Phenomenological research methods. In Existential-phenomenological perspectives in psychology (pp. 41-60). Springer, Boston, MA.
• Rapp, A., Curti, L., & Boldi, A. (2021). The human side of human-chatbot interaction: A systematic literature review of ten years of research on text-based chatbots. International Journal of Human Computer Studies, 151(March), 102630. https://doi.org/10.1016/j.ijhcs.2021.102630
• Rauschnabel, P. A., Felix, R., & Hinsch, C. (2019). Augmented reality marketing: How mobile AR-apps can improve brands through inspiration. Journal of Retailing and Consumer Services, 49, 43-53.
• Rejeb, A., Rejeb, K., El, S., Abou, R., El, R., Ariana, B., & Keogh, J. G. (n.d.). Potential of Big Data for Marketing : A Literature Review.
• Richins, M. L. (1997). Measuring emotions in the consumption experience. Journal of consumer research, 24(2), 127-146.
• Russell, J. A. (1980). A circumplex model of affect. Journal of personality and social psychology, 39(6), 1161.
• Russell, S., & Norvig, P. (2010). Artificial intelligence: a modern approach. 3rd. Upper Saddle River, EUA: Prentice-Hall.
• Saadé, R. G., & Kira, D. (2007). Mediating the impact of technology usage on perceived ease of use by anxiety. Computers & education, 49(4), 1189-1204.
• Salles, A., Evers, K., & Farisco, M. (2020). Anthropomorphism in AI. AJOB neuroscience, 11(2), 88-95.
• Shank, D. B., Graves, C., Gott, A., Gamez, P., & Rodriguez, S. (2019). Computers in Human Behavior Feeling our way to machine minds : People ’ s emotions when perceiving mind in arti fi cial intelligence. 98(November 2018), 256–266. https://doi.org/10.1016/j.chb.2019.04.001
• Shankar, V., & Parsana, S. (2022). An overview and empirical comparison of natural language processing (NLP) models and an introduction to and empirical application of autoencoder models in marketing. Journal of the Academy of Marketing Science, 1-27.f
• Song, X., Xu, B., & Zhao, Z. (2022). Can people experience romantic love for artificial intelligence? An empirical study of intelligent assistants. Information & Management, 59(2), 103595.
• Steinert, S., & Roeser, S. (2020). Emotions, values and technology: illuminating the blind spots. Journal of Responsible Innovation, 7(3), 298-319.
• Storm, C., & Storm, T. (1987). A taxonomic study of the vocabulary of emotions. Journal of personality and social psychology, 53(4), 805.
• Straregic Market Research, (2022). Robotic Industry Statistics-2022. https://www.strategicmarketresearch.com/blogs/robotics-industry-statistics adresinden alındı.
• Taylor, M., Reilly, D., & Wren, C. (2020). Internet of things support for marketing activities. Journal of Strategic Marketing, 28(2), 149-160.
• Tekin, H. H., & TEKİN, H. (2006). Nitel Araştirma Yönteminin Bir Veri Toplama Tekniği Olarak Derinlemesine Görüşme. İstanbul University Journal of Sociology, 3(13), 101-116. The International Federation of Robotic, (2021). Executive Summary World Robotics 2021-Service Robots.
• https://ifr.org/img/worldrobotics/Executive_Summary_WR_Service_Robots_2021.pdf adresinden alındı.
• Tsai, W. H. S., Lun, D., Carcioppolo, N., & Chuan, C. H. (2021). Human versus chatbot: Understanding the role of emotion in health marketing communication for vaccines. Psychology & marketing, 38(12), 2377-2392.
• Verma, S., Sharma, R., Deb, S., & Maitra, D. (2021). Artificial intelligence in marketing: Systematic review and future research direction. International Journal of Information Management Data Insights, 1(1), 100002.
• Van Pinxteren, M. M., Wetzels, R. W., Rüger, J., Pluymaekers, M., & Wetzels, M. (2019). Trust in humanoid robots: implications for services marketing. Journal of Services Marketing.
• Vlačić, B., Corbo, L., Costa e Silva, S., & Dabić, M. (2021). The evolving role of artificial intelligence in marketing: A review and research agenda. Journal of Business Research, 128(February 2021), 187–203. https://doi.org/10.1016/j.jbusres.2021.01.055
• Wang, P., & Shao, J. (2022, January). Escaping Loneliness Through Tourist-Chatbot Interactions. In ENTER22 e-Tourism Conference (pp. 473-485). Springer, Cham.
• Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: the PANAS scales. Journal of personality and social psychology, 54(6), 1063.
• Watson, L., & Spence, M. T. (2007). Causes and consequences of emotions on consumer behaviour: A review and integrative cognitive appraisal theory. European Journal of Marketing.
• Wirtz, J., Patterson, P.G., Kunz, W.H., Gruber, T., Lu, V.N., Paluch, S. and Martins, A. (2018), "Brave new world: service robots in the frontline", Journal of Service Management, Vol. 29 No. 5, pp. 907-931. https://doi.org/10.1108/JOSM-04-2018-0119
• Yang, Q., Fu, S., Wang, H., & Fang, H. (2021). Machine-learning-enabled cooperative perception for connected autonomous vehicles: Challenges and opportunities. IEEE Network, 35(3), 96-101.
• Yıldırım, A., & Simsek, H. (1999). Sosyal Bilimlerde Nitel Araştırma Yöntemleri (11 baski: 1999-2018).