Memória P&D Design

14º Congresso Brasileiro de Pesquisa e Desenvolvimento em Design

ESDI/UERJ; ESPM-Rio — Rio de Janeiro (RJ)

Outubro/2022

"a Realidade Nem Sempre É Frustrante": Alinhando os Modelos Mentais de Usuários com as Reais Capacidades de Assistentes de Voz (avs)

"reality Is Not Always Frustrating": Towards Aligning Users' Mental Models with Voice Assistants' (vas) Real Capabilities

Isabela Motta
Manuela Quaresma

Como citar

Motta, Isabela; Quaresma, Manuela; ""a Realidade Nem Sempre É Frustrante": Alinhando os Modelos Mentais de Usuários com as Reais Capacidades de Assistentes de Voz (avs)", p. 2897-2911. In: CONGRESSO BRASILEIRO DE PESQUISA E DESENVOLVIMENTO EM DESIGN, 14., 2022, Rio de Janeiro. Anais [...]. São Paulo: Blucher, 2022, DOI 10.5151/ped2022-1943537

Resumo

Assistentes de Voz (AVs), como Alexa, estão cada vez mais populares, mas os modelos mentais dos usuários são incompatíveis com as reais capacidades desses sistemas. Para melhorar as interações, alinhar as percepções dos usuários com o real funcionamento dos AVs é necessário, e, para isso, é essencial considerar as percepções dos designers desses produtos. Assim, foram conduzidas entrevistas exploratórias semi-estruturadas com profissionais experientes em interfaces conversacionais, visando explorar suas opiniões sobre as causas para as lacunas nos modelos mentais dos usuários e identificar soluções para o problema. Os resultados indicaram que as características antropomórficas dos AVs e a apresentação de informações foram considerados influentes para as percepções dos usuários, assim como marketing, ficção científica e as características dos usuários. Ainda, aumentar a transparência do sistema foi considerada uma solução adequada, mas os designers precisam ter as habilidades e conhecimento para aplicar a solução, considerando as necessidades dos usuários e de usabilidade.
Palavras-chave:

Assistentes de Voz, Modelos Mentais, Usabilidade

Abstract

Voice Assistants (VAs) such as Siri and Alexa are growing in popularity, but users' mental models of VAs are not in line with the reality of these systems' functioning. To improve interactions, aligning users' perceptions with the VAs' capabilities may be beneficial, and for such a work, it is essential to consider the perceptions of these products' designers. Thus, we conducted exploratory semi-structured interviews with professionals experienced with conversational interfaces to explore their opinions on the causes for misalignments in users' mental models and survey solutions to address this issue. The results indicate that VAs' anthropomorphic features and information-related outputs (e.g., feedback) were considered influential for users' perceptions, as well as marketing, science fiction, and user backgrounds. To address misperceptions, increasing VAs' transparency was considered an adequate solution, but designers must possess the skills and knowledge to apply such a solution, considering users' needs and usability requirements.
Keywords:

Voice Assistants, Mental Models, Usability

Referências bibliográficas

  • E., D.; MORRISSEY, K.; CLARKE, P.; AL-SHEHRI, S.; EARLEY, D.; BANDEIRA, N. "What can i help you with?" 4 Sep. 2017. Proceedings of the 19th International Conference on Human-Computer Interaction with Mobile Devices and Services. New York, NY, USA: ACM, 4 Sep. 2017. p. 1–12. DOI 10.1145/3098279.3098539.

  • FESTERLING, J.; SIRAJ, I. Alexa, What Are You? Exploring Primary School Children's Ontological Perceptions of Digital Voice Assistants in Open Interactions. Human Development, vol. 64, no. 1, p. 26–43, 2020. DOI 10.1159/000508499.

  • HOLZINGER, A. From Machine Learning to Explainable AI. Aug. 2018. 2018 World Symposium on Digital Intelligence for Systems and Machines (DISA). [S. l.]: IEEE, Aug. 2018. p. 55–66. DOI 10.1109/DISA.2018.8490530.

  • KIM, J.; JEONG, M.; LEE, S. C. "Why did this voice agent not understand me?" 21 Sep. 2019. Proceedings of the 11th International Conference on Automotive User Interfaces and Interactive Vehicular Applications: Adjunct Proceedings. New York, NY, USA: ACM, 21 Sep. 2019. p. 146–150. DOI 10.1145/3349263.3351513.

  • KIRSCHTHALER, P.; PORCHERON, M.; FISCHER, J. E. What Can i Say?: Effects of Discoverability in VUIs on Task Performance and User Experience. 2020. ACM International Conference Proceeding Series. [S. l.: s. n.], 2020. DOI 10.1145/3405755.3406119.

  • KISELEVA, J.; WILLIAMS, K.; JIANG, J.; HASSAN AWADALLAH, A.; CROOK, A. C.; ZITOUNI, I.; ANASTASAKOS, T. Understanding User Satisfaction with Intelligent Assistants. 2016. Proceedings of the 2016 ACM on Conference on Human Information Interaction and Retrieval. New York, NY, USA: Association for Computing Machinery, 2016. p. 121–130. DOI 10.1145/2854946.2854961.

  • KUZMINYKH, A.; SUN, J.; GOVINDARAJU, N.; AVERY, J.; LANK, E. Genie in the Bottle. 21 Apr. 2020. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. New York, NY, USA: ACM, 21 Apr. 2020. p. 1–13. DOI 10.1145/3313831.3376665.

  • LAU, J.; ZIMMERMAN, B.; SCHAUB, F. Alexa, Are You Listening? Proceedings of the ACM on Human-Computer Interaction, New York, NY, USA, vol. 2, no. CSCW, p. 1–31, Nov. 2018. DOI 10.1145/3274371.

  • LOPATOVSKA, I.; GRIFFIN, A. L.; GALLAGHER, K.; BALLINGALL, C.; ROCK, C.; VELAZQUEZ, M. User recommendations for intelligent personal assistants. Journal of Librarianship and Information Science, vol. 52, no. 2, p. 577–591, 8 Jun. 2020. DOI 10.1177/0961000619841107.

  • LOPATOVSKA, I.; RINK, K.; KNIGHT, I.; RAINES, K.; COSENZA, K.; WILLIAMS, H.; SORSCHE, P.; HIRSCH, D.; LI, Q.; MARTINEZ, A. Talk to me: Exploring user interactions with the Amazon Alexa. Journal of Librarianship and Information Science, vol. 51, no. 4, p. 984–997, 7 Dec. 2019. DOI 10.1177/0961000618759414.

  • LUGER, E.; SELLEN, A. "Like Having a Really Bad PA": The Gulf between User Expectation and Experience of Conversational Agents. 2016. Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. New York, NY, USA: Association for Computing Machinery, 2016. p. 5286–5297. DOI 10.1145/2858036.2858288.

  • MCLEAN, G.; OSEI-FRIMPONG, K. Hey Alexa ... examine the variables influencing the use of artificial intelligent in-home voice assistants. Computers in Human Behavior, vol. 99, p. 28–37, 2019. DOI https://doi.org/10.1016/j.chb.2019.05.009.

  • MOAR, J.; ESCHERICH, M. Hey Siri, how will you make money? 2020. Available at: https://www.juniperresearch.com/whitepapers/hey-siri-how-will-you-make-money. Accessed on April 18th 2022.

  • MORIUCHI, E. Okay, Google!: An empirical study on voice assistants on consumer engagement and loyalty. Psychology & Marketing, vol. 36, no. 5, p. 489–501, 15 May 2019. DOI 10.1002/mar.21192.

  • MOTTA, I.; QUARESMA, M. OPPORTUNITIES AND ISSUES IN THE ADOPTION OF VOICE ASSISTANTS BY BRAZILIAN SMARTPHONE USERS. Ergodesign & HCI, vol. 7, no. Especial, p. 138, 31 Dec. 2019. DOI 10.22570/ergodesignhci.v7iEspecial.1312.

  • MOTTA, I; QUARESMA, M; "Explorando desafios e oportunidades para aumentar a transparência de Assistentes de Voz (AVs)", p. 983-994. In: Anais do 18º Congresso Internacional de Ergonomia e Usabilidade de Interfaces Humano-Tecnologia e o 18º Congresso Internacional de Ergonomia e Usabilidade de Interfaces e Interação Humano-Computador. São Paulo: Blucher, 2022.

  • MYERS, C.; FURQAN, A.; NEBOLSKY, J.; CARO, K.; ZHU, J. Patterns for how users overcome obstacles in Voice User Interfaces. 2018-April. Conference on Human Factors in Computing Systems - Proceedings. [S. l.: s. n.], 2018. vol. 2018-April, p. 1–7. https://doi.org/10.1145/3173574.3173580.

  • MYERS, C. M.; FURQAN, A.; ZHU, J. The Impact of User Characteristics and Preferences on Performance with an Unfamiliar Voice User Interface. 2 May 2019. Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems. New York, NY, USA: ACM, 2 May 2019. p. 1–9. DOI 10.1145/3290605.3300277.

  • NASS, C.; MOON, Y. Machines and Mindlessness: Social Responses to Computers. Journal of Social Issues, vol. 56, no. 1, p. 81–103, 2000.

  • NORMAN, D. The design of everyday things. Revised an. New York, NY, USA: Basic books, 2013.

  • PORCHERON, M.; FISCHER, J. E.; REEVES, S.; SHARPLES, S. Voice Interfaces in Everyday Life. 2018-April. 21 Apr. 2018. Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. New York, NY, USA: ACM, 21 Apr. 2018. vol. 2018-April, p. 1–12. DOI 10.1145/3173574.3174214.

  • PORCHERON, M.; FISCHER, J. E.; SHARPLES, S. "Do Animals Have Accents?" 25 Feb. 2017. Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing. New York, NY, USA: ACM, 25 Feb. 2017. p. 207–219. DOI 10.1145/2998181.2998298.

  • PRIDMORE, J.; ZIMMER, M.; VITAK, J.; MOLS, A.; TROTTIER, D.; KUMAR, P. C.; LIAO, Y. Intelligent Personal Assistants and the Intercultural Negotiations of Dataveillance in Platformed Households. Surveillance & Society, vol. 17, no. 1/2, p. 125–131, 31 Mar. 2019. DOI 10.24908/ss.v17i1/2.12936.

  • PURINGTON, A.; TAFT, J. G.; SANNON, S.; BAZAROVA, N. N.; TAYLOR, S. H. "Alexa is my new BFF": Social roles, user satisfaction, and personification of the Amazon Echo. Conference on Human Factors in Computing Systems - Proceedings, vol. Part F1276, p. 2853–2859, 2017. https://doi.org/10.1145/3027063.3053246.

  • STATISTA. Total number of Amazon Alexa skills in selected countries as of January 2020. 2020. Available at: https://www.statista.com/statistics/917900/selected-countries-amazon-alexa-skill-count/. Accessed on: 2 Nov. 2021.

  • WEST, M.; KRAUT, R.; HAN EI, C. I'd blush if I could, 2019. Available at: https://unesdoc.unesco.org/ark:/48223/pf0000367416.page=1. Accessed on: 2 Nov 2021.

  • WICKENS, C. D.; LEE, J.; LIU, Y.; BECKER, S. G. Cognition. An Introduction to Human Factors Engineering. second. London: Pearson, 2014. p. 100–134.

  • WILSON, J. R.; RUTHERFORD, A. Mental models: Theory and application in human factors. Human Factors, vol. 31, no. 6, p. 617–634, 1989. https://doi.org/10.1177/001872088903100601.