Do Analógico ao Algoritmo
uma revisão abrangente da intersecção da inteligência artificial com a literatura de gestão e a Teoria Ator-Rede
DOI:
https://doi.org/10.36311/1981-1640.2024.v18.e024013Palavras-chave:
Inteligência Artificial, Teoria Ator-Rede, Ciência de Dados, Administração, Revisão Sistemática de LiteraturaResumo
Na era digital, a literatura atual sobre Administração continua fortemente enraizada em perspectivas antropocêntricas e analógicas, muitas vezes negligenciando a profunda influência dos algoritmos e da inteligência artificial (IA) na dinâmica organizacional moderna. Para isso, esta revisão sistemática de literatura procura preencher essa lacuna ao explorar o cenário em evolução da IA nas organizações e o papel da Teoria Ator-Rede (ANT) como uma lente teórico-metodológica para entender o impacto da IA na Administração. Por meio de uma revisão sistemática da literatura, abordamos pesquisas sobre a utilização da IA na Administração na última década, as aplicações da ANT em estudos de gestão que não sejam de TI ou de IA e estudos que expliquem conceitos de TI ou IA por meio da ANT. Nossas descobertas destacam uma lacuna de pesquisa significativa na compreensão das interações homem-máquina e da Gestão de Negócios em organizações que usam IA. Além disso, identificamos possíveis caminhos para futuras contribuições acadêmicas, enfatizando a necessidade de uma abordagem mais integrada que considere os atores humanos e mecânicos em contextos organizacionais.
Downloads
Métricas
Referências
Akhtar, P., Frynas, J. G., Mellahi, K., & Ullah, S. (2019, APR). Big data-savvy teams’ skills, big data-driven actions and business performance. British Journal of Management, 30(2, SI), 252-271. doi: https://doi.org/10.1111/1467-8551.12333
Alonso Trillo, R., & Poliks, M. (2023). Debris: Machine learning, archive archaeology, digital audio waste. Organised Sound. doi: https://doi.org/10.1017/S1355771823000249
Andersen, L. B., Danholt, P., Halskov, K., Hansen, N. B., & Lauritsen, P. (2015). Participation as a matter of concern in participatory design. CoDesign, 11(3-4), 250 – 261. doi: https://doi.org/10.1080/15710882.2015.1081246
Andersson, R. (2016). Hardwiring the frontier? The politics of security technology in Europe’s ‘fight against illegal migration’. Security Dialogue, 47(1), 22 – 39. doi: https://doi.org/10.1177/0967010615606044
Armour, J., & Sako, M. (2020, Mar). AI-enabled business models in legal services: from traditional law firms to next-generation law companies? Journal of Professions and Organization, 7(1), 27-46. doi: https://doi.org/10.1093/jpo/joaa001
Bag, S., Pretorius, J. H. C., Gupta, S., & Dwivedi, Y. K. (2021). Role of institutional pressures and resources in the adoption of big data analytics powered artificial intelligence, sustainable manufacturing practices and circular economy capabilities . Technological Forecasting and Social Change, 163. doi: https://doi.org/10.1016/j.techfore.2020.120420
Bajde, D. (2013). Consumer culture theory (re)visits actor-network theory: Flattening consumption studies. Marketing Theory, 13(2), 227 – 242. doi: https://doi.org/10.1177/1470593113477887
Bartlett, L., & Vavrus, F. (2014). Transversing the vertical case study: A methodological approach to studies of educational policy as practice. Anthropology and Education Quarterly, 45(2), 131 – 147. doi: https://doi.org/10.1111/aeq.12055
Bartrolí, M. A. (2021). The university social responsibility framework by the international federation of catholic universities: A case of “intelligent” co-creation. Springer. doi: https://doi.org/10.1007/978-3-030-70013-3_2
Belanche, D., Casalo, L., V, Flavian, C., & Schepers, J. (2020). Robots or frontline employees? Exploring customers’ attributions of responsibility and stability after service failure or success. Journal of Service Management, 31(2, SI), 267-289. doi: https://doi.org/10.1108/JOSM -05-2019-0156
Bellanova, R. (2017). Digital, politics, and algorithms: Governing digital data through the lens of data protection. European Journal of Social Theory, 20(3), 329 – 347. doi: https://doi.org/10.1177/1368431016679167
Bittner, C., Glasze, G., & Turk, C. (2013). Tracing contingencies: Analyzing the political in assemblages of web 2.0 cartographies. GeoJournal, 78(6), 935 – 948. doi: https://doi.org/10.1007/s10708-013-9488-8
Blok, A. (2013, NOV). Pragmatic sociology as political ecology: On the many worths of nature(s). European Journal Of Social Theory, 16(4), 492-510. doi: https://doi.org/10.1177/1368431013479688
Borch, C. (2023). Machine learning and postcolonial critique: Homologous challenges to sociological notions of human agency. Sociology. doi: https://doi.org/10.1177/00380385221146877
Brougham, D., & Haar, J. (2018). Smart technology, artificial intelligence, robotics, and algorithms (STARA): Employees’ perceptions of our future workplace. Journal of Management & Organization, 24(2), 239-257. doi: https://doi.org/10.1017/jmo.2016.55
Buhalis, D., Harwood, T., Bogicevic, V., Viglia, G., Beldona, S., & Hofacker, C. (2019). Technological disruptions in services: lessons from tourism and hospitality. Journal of Service Management, 30(4, SI), 484-506. doi: https://doi.org/10.1108/JOSM-12-2018-0398
Burga, R., & Rezania, D. (2017). Project accountability: An exploratory case study using actor-network theory. International Journal of Project Management, 35(6), 1024-1036. doi: https://doi.org/10.1016/j.ijproman.2017.05.001
Campbell-Verduyn, M., Goguen, M., & Porter, T. (2017). Big data and algorithmic governance: the case of financial practices. New Political Economy, 22(2), 219 – 236. doi: https://doi.org/10.1080/13563467.2016.1216533
Caputo, F., Cillo, V., Candelo, E., & Liu, Y. (2019, SEP 12). Innovating through digital revolution the role of soft skills and big data in increasing firm performance. Management Decision, 57(8, SI), 2032-2051. doi: https://doi.org/10.1108/MD-07-2018-0833
Cecez-Kecmanovic, D., Kautz, K., & Abrahall, R. (2014). Reframing success and failure of information systems: A performative perspective. MIS Quarterly: Management Information Systems, 38(2), 561 – 588. doi: https://doi.org/10.25300/MISQ/2014/38.2.11
Contini, F. (2020). Artificial intelligence and the transformation of humans, law and technology interactions in judicial proceedings. Law, Technology and Humans, 2(1), 4–18. doi: https://doi.org/10.5204/lthj.v2i1.1478
Cooper, D. J., Ezzamel, M., & Qu, S. Q. (2017). Popularizing a management accounting idea: The case of the balanced scorecard. Contemporary Accounting Research, 34(2), 991 – 1025. doi: https://doi.org/10.1111/1911-3846.12299
Dery, K., Hall, R., Wailes, N., & Wiblen, S. (2013, SEP). Lost in translation? An actor-network approach to HRIS implementation. Journal of Strategic Information Systems, 22(3), 225-237. doi: https://doi.org/10.1016/j.jsis.2013.03.002
Domingo, D., Masip, P., & Costera Meijer, I. (2015). Tracing digital news networks: Towards an integrated framework of the dynamics of news production, circulation and use. Digital Journalism, 3(1), 53 – 67. doi: https://doi.org/10.1080/21670811.2014.927996
Elbanna, A. (2013, May). Top management support in multiple-project environments: an in-practice view. European Journal of Information Systems, 22(3), 278-294. doi: https://doi.org/10.1057/ejis.2012.16
Eze, S. C., Duan, Y., & Chen, H. (2014). Examining emerging ICT’s adoption in SMEs from a dynamic process approach. Information Technology and People, 27(1), 63–82. doi: https://doi.org/10.1108/ITP-03-2013-0044
Fleming, P. (2019, JAN). Robots and organization studies: Why robots might not want to steal your job. Organization Studies, 40(1), 23-37. doi: https://doi.org/10.1177/0170840618765568
Flyverbom, M. (2015). Sunlight in cyberspace? On transparency as a form of ordering . European Journal of Social Theory, 18(2), 168 – 184. doi: https://doi.org/10.1177/1368431014555258
Frauenberger, C. (2019). Entanglement HCI the next wave? . ACM Transactions on Computer-Human Interaction, 27(1). doi: https://doi.org/10.1145/3364998
Fuenfschilling, L., & Binz, C. (2018, MAY). Global socio-technical regimes. Research Policy, 47(4), 735-749. doi: https://doi.org/10.1016/j.respol.2018.02.003
Füller, J., Hutter, K., Wahl, J., Bilgram, V., & Tekic, Z. (2022). How AI revolutionizes innovation management – perceptions and implementation preferences of AI-based innovators . Technological Forecasting and Social Change, 178. doi: https://doi.org/10.1016/j.techfore.2022.121598
Greenhalgh, T., Wherton, J., Shaw, S., Papoutsi, C., Vijayaraghavan, S., & Stones, R. (2019). Infrastructure revisited: An ethnographic case study of how health information infrastructure shapes and constrains technological innovation . Journal of Medical Internet Research, 21(12). doi: https://doi.org/10.2196/16093
Gregory, R. W., Henfridsson, O., Kaganer, E., & Kyriakou, S. H. (2021, JUL). The role of artificial intelligence and data network effects for creating user value. Academy of Management Review, 46(3), 534-551. doi: https://doi.org/10.5465/amr.2019.0178
Gunawong, P., & Gao, P. (2017). Understanding e-government failure in the developing country context: a process-oriented study. Information Technology for Development, 23(1), 153 – 178. doi: https://doi.org/10.1080/02681102.2016.1269713
Hansen, H. K., & Flyverbom, M. (2015). The politics of transparency and the calibration of knowledge in the digital age. Organization, 22(6), 872 – 889. doi: https://doi.org/10.1177/1350508414522315
Iskanderov, Y., & Pautov, M. (2020). Agents and multi-agent systems as actor-networks. In A. Rocha, L. Steels, & J. VanDenHerik (Eds.), ICAART: Proceedings of the 12th International Conference on Agents and Artificial Intelligence, vol 1 (p. 179-184). doi: https://doi.org/10.5220/0008935601790184
Islam, A. K. M. N., Mantymaki, M., & Turunen, M. (2019, Nov). Why do blockchains split? An actor-network perspective on bitcoin splits. Technological Forecasting and Social Change, 148. doi: https://doi.org/10.1016/j.techfore.2019.119743
Johnson, D. G., & Verdicchio, M. (2019, SEP). AI, agency and responsibility: the VW fraud case and beyond. AI & Society, 34(3), 639-647. doi: https://doi.org/10.1007/s00146-017-0781-9
Kaasinen, E., Anttila, A.-H., Heikkilä, P., Laarni, J., Koskinen, H., & Väätänen, A. (2022). Smooth and resilient human–machine teamwork as an industry 5.0 design challenge . Sustainability (Switzerland), 14(5). doi: https://doi.org/10.3390/su14052773
Karmakar, S. (2022). Artificial intelligence: the future of medicine, or an overhyped and dangerous idea? . Irish Journal of Medical Science, 191(5), 1991–1994. doi: https://doi.org/10.1007/s11845 -021-02853-3
Kitchenham, B. A., & Charters, S. (2007). Guidelines for performing systematic literature reviews in software engineering (Tech. Rep.). Keele, United Kingdom: School of Computer Science and Mathematics, Keele University.
Kumar, N., & Rangaswamy, N. (2013). The mobile media actor-network in urban India. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (p. 1989–1998). doi: https://doi.org/10.1145/2470654.2466263
Law, J., & Lien, M. E. (2013). Slippery: Field notes in empirical ontology. Social Studies of Science, 43(3), 363 – 378. doi: https://doi.org/10.1177/0306312712456947
Law, J., & Singleton, V. (2013). Ant and politics: Working in and on the world. Qualitative Sociology, 36(4), 485 – 502. doi: https://doi.org/10.1007/s11133-013-9263-7
Law, J., & Singleton, V. (2014). ANT, multiplicity and policy . Critical Policy Studies, 8(4), 379–396. doi: https://doi.org/10.1080/19460171.2014.957056
Lawrence, T. B., & Dover, G. (2015, SEP). Place and institutional work: Creating housing for the hard-to-house. Administrative Science Quarterly, 60(3), 371-410. doi: https://doi.org/10.1177/0001839215589813
Lee, F., & Bjorklund Larsen, L. (2019). How should we theorize algorithms? Five ideal types in analyzing algorithmic normativities. Big Data and Society, 6(2). doi: https://doi.org/10.1177/2053951719867349
Martin, D. M., & Schouten, J. W. (2014, FEB). Consumption-driven market emergence. Journal Of Consumer Research, 40(5), 855-870. doi: https://doi.org/10.1086/673196
Missonier, S., & Loufrani-Fedida, S. (2014). Stakeholder analysis and engagement in projects: From stakeholder relational perspective to stakeholder relational ontology . International Journal of Project Management, 32(7), 1108 – 1122. doi: https://doi.org/10.1016/j.ijproman.2014.02 .010
Modell, S., Vinnari, E., & Lukka, K. (2017, Jul). On the virtues and vices of combining theories: The case of institutional and actor-network theories in accounting research. Accounting Organizations and Society, 60, 62-78. doi: https://doi.org/10.1016/j.aos.2017.06.005
Murray, A., Rhymer, J., & Sirmon, D. G. (2021, Jul). Humans and technology: Forms of conjoined agency in organizations. Academy of Management Review, 46(3), 552-571. doi: https://doi.org/10.5465/amr.2019.0186
Onno, J., Khan, F. A., Daftary, A., & David, P. M. (2023, Jun). Artificial intelligence-based computer aided detection (AI-CAD) in the fight against tuberculosis: Effects of moving health technologies in global health. Social Science & Medicine, 327. doi: https://doi.org/10.1016/j.socscimed .2023.115949
Pan, Y., Froese, F., Liu, N., Hu, Y., & Ye, M. (2022, Mar 26). The adoption of artificial intelligence in employee recruitment: The influence of contextual factors. International Journal of Human Resource Management, 33(6, SI), 1125-1147. doi: https://doi.org/10.1080/09585192.2021.1879206
Piekut, B. (2014). Actor-networks in music history: Clarifications and critiques . Twentieth Century Music, 11(2), 191 – 215. doi: https://doi.org/10.1017/S147857221400005X
Pillai, R., & Sivathanu, B. (2020, Nov 9). Adoption of artificial intelligence (AI) for talent acquisition in IT/ITES organizations. Benchmarking: an International Journal, 27(9), 2599-2629. doi: https://doi.org/10.1108/BIJ-04-2020-0186
Pinto, M. F., Leal, A., Lopes, F., Pais, J., Dourado, A., Sales, F., ... Teixeira, C. A. (2022). On the clinical acceptance of black-box systems for EEG seizure prediction. Epilepsia Open, 7(2), 247–259. doi: https://doi.org/10.1002/epi4.12597
Pollack, J., Costello, K., & Sankaran, S. (2013). Applying actor-network theory as a sensemaking framework for complex organisational change programs . International Journal of Project Management, 31(8), 1118–1128. doi: https://doi.org/10.1016/j.ijproman.2012.12.007
Prado, A. B., & Calani Baranauskas, M. C. (2014). Capturing semiotic and social factors of organizational evolution. In S. Hammoudi, J. Cordeiro, L. Maciaszek, & J. Filipe (Eds.), Enterprise information systems, ICEIS 2013 (Vol. 190, p. 264-279). doi: https://doi.org/10.1007/978-3-319 -09492-2
Raisch, S., & Krakowski, S. (2021, Jan). Artificial intelligence and management: The automation-augmentation paradox. Academy of Management Review, 46(1), 192-210. doi: https://doi.org/10.5465/amr.2018.0072
Sarlak, M. A., Salamzadeh, Y., & Farzad, F. S. (2020). Actor-network theory and networked organizations, proposing a conceptual framework. Springer. doi: https://doi.org/10.1007/978-981-15-7066-7_11
Sayes, E. (2014). Actor-network theory and methodology: Just what does it mean to say that nonhumans have agency? . Social Studies of Science, 44(1), 134 – 149. doi: https://doi.org/10.1177/0306312713511867
Shmargad, Y. (2017). Network perspectives on privacy and security in the internet of things: From actor-network theory to social network analysis. In: 2017 AAAI Spring Symposium – No 3 - Computational Context: Why It Is Important, What It Means, and Can It Be Computed? Technical Report SS-17-03, p. 351 – 353. https://cdn.aaai.org/ocs/15243/15243-68241-1-PB.pdf
Sidorova, A. (2018). Interests and agency in ai: The case of image recognition with inception 3 model completed research papers. In AMCIS 2018 Proceedings. (24th Americas Conference on Information Systems (AMCIS) - Digital Disruption, New Orleans, LA, Aug 16-18, 2018)
Sperling, K., Stenliden, L., Nissen, J., & Heintz, F. (2022). Still w(AI)ting for the automation of teaching: An exploration of machine learning in Swedish primary education using actor-network theory . European Journal of Education, 57(4), 584 – 600. doi: https://doi.org/10.1111/ejed.12526
Van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523-538.
van Rijmenam, M., & Logue, D. (2021). Revising the ‘science of the organisation’: theorising AI agency and actorhood . Innovation: Organization and Management, 23(1), 127–144. doi: https://doi.org/10.1080/14479338.2020.1816833
Waeraas, A., & Nielsen, J. A. (2016, Jul). Translation theory ‘translated’: Three perspectives on translation in organizational research. International Journal Of Management Reviews, 18(3, SI), 236-270. doi: https://doi.org/10.1111/ijmr.12092
Warner, K. S. R., & Waeger, M. (2019, Jun). Building dynamic capabilities for digital transformation: An ongoing process of strategic renewal. Long Range Planning, 52(3), 326-349. doi: https://doi.org/10.1016/j.lrp.2018.12.001.
Williams, I. (2020). Contemporary applications of actor network theory. Springer. doi: https://doi.org/10.1007/978-981-15-7066-7.
Downloads
Publicado
Como Citar
Edição
Seção
Licença
Copyright (c) 2024 Wellington Rodrigo Monteiro, Eduardo Ayrosa
Este trabalho está licenciado sob uma licença Creative Commons Attribution-ShareAlike 4.0 International License.
Ao submeter um artigo os autores mantêm os direitos autorais do mesmo, cedendo ao Brazilian Journal of Information Science plenos direitos para publicação do referido texto.
O (s) autor (es) concorda(m) que o artigo, se aceito editorialmente para publicação, deve ser licenciado sob a licença Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) (http://creativecommons.org/licenses/by-sa /4.0) Os leitores / usuários são livres para: - Compartilhar - copiar e redistribuir o material em qualquer meio ou formato - Adaptar - remixar, transformar e desenvolver o material para qualquer finalidade, mesmo comercialmente. O licenciante não pode revogar essas liberdades desde que você siga os termos da licença. Sob os seguintes termos: - Atribuição - Você deve dar o crédito apropriado, fornecer um link para a licença e indicar se foram feitas alterações. Você pode fazê-lo de qualquer maneira razoável, mas não de maneira que sugira que o licenciante endossa você ou seu uso. - ShareAlike - Se você remixar, transformar ou desenvolver o material, deverá distribuir suas contribuições sob a mesma licença que o original. Sem restrições adicionais - Você não pode aplicar termos legais ou medidas tecnológicas que restrinjam legalmente outras pessoas a fazer o que a licença permitir. Avisos: - Você não precisa cumprir a licença para elementos do material em domínio público ou nos casos em que seu uso é permitido por uma exceção ou limitação aplicável. - Não há garantias. A licença pode não fornecer todas as permissões necessárias para o uso pretendido. Por exemplo, outros direitos, como publicidade, privacidade ou direitos morais, podem limitar a maneira como você usa o material.
Creative Commons Attribution-ShareAlike 4.0 International License
