Are hybrid-human-AI-systems a more humane and responsible version of AI? Empirical inquiries into the conundrums of value-by-design in language technology
DOI:
https://doi.org/10.15346/hc.v12i1.160Abstract
The development of hybrid human–artificial intelligence approaches offers the prospect of creating a more humane and responsible form of AI. However, technological anthropologists question whether these approaches represent a significant shift. The idea that good and bad, humane and inhumane, or responsible and irresponsible versions of AI can be achieved through hybrid human–AI systems oversimplifies the complexity of technological design and implementation. Focusing on 'intelligence performance' is too narrow, distracting from the conundrum of value-oriented design and the crucial dimensions of socio-technical systems. These systems intertwine the various socio-technical layers of AI technology design with specific stakeholders and practices in social reality. Value orientation requires practices at all layers involved in technology design and implementation, and is therefore a continuous technological activity rather than emerging from a particular AI system architecture. Furthermore, the development of a humane and responsible version of AI requires a fundamental realignment of AI technology and research paradigms, challenging the concept of superior intelligence and power for the purpose of providing a rational and reflective evaluation of technology that goes beyond Turing's black boxing.References
Akrich, M. (1992). The de-scription of technical Objects. In shaping technology/building society. Studies in sociotech-nical change (pp. 205–224). MIT Press. https://shs.hal.science/halshs-00081744/
Araujo de Aguiar, C. H., Pinch, T., & Green, K. (2022). De-scription at early phases of artifact design. In Proceedings of the 25th International Academic Mindtrek Conference (pp. 179–191). ACM. https://doi.org/10.1145/3569219.3569380
Batool, A., Zowghi, D., & Bano, M. (2023). Responsible AI governance: a systematic literature review. arXiv. https://arxiv.org/abs/2401.10896v1
Blodgett, S. L., Barocas, S., Daumé, H., III, & Wallach, H. (2020). Language (technology) is power: A critical survey of "bias" in NLP. In D. Jurafsky, J. Chai, N. Schluter, & J. Tetreault (Eds.), Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (pp. 5454–5476). Association for Computational Linguistics. https://doi.org/10.18653/v1/2020.acl-main.485
Bruun, M. H., Wahlberg, A., Douglas-Jones, R., Hasse, C., Hoeyer, K., Kristensen, D. B., & Winthereik, B. R. (Eds.). (2022). The Palgrave handbook of the anthropology of technology. Palgrave Macmillan. https://doi.org/10.1007/978-981-16-7084-8
Bryant, A., & Charmaz, K. (2019). The SAGE handbook of current developments in grounded theory. SAGE.
Butot, V., & van Zoonen, L. (2024). Contesting infrastructural futures: 5g opposition as a technological drama. Sci-ence, Technology, & Human Values, 49(5), 1017–1044. https://doi.org/10.1177/01622439221147347
Callon, M. (2004). The role of hybrid communities and socio-technical arrangements in the participatory design. Journal of the Center of Information Studies, 5(3), 3–10. https://www.comm.tcu.ac.jp/cisj/05/5_01.pdf
Constantinescu, M., Voinea, C., Uszkai, R., & Vică, C. (2021). Understanding responsibility in Responsible AI. Diano-etic virtues and the hard problem of context. Ethics and Information Technology, 23(4), 803–814. https://doi.org/10.1007/s10676-021-09616-9
Coupaye, L. (2022). Making ‘technology’ visible: technical activities and the Chaîne Opératoire. In The Palgrave Handbook of the anthropology of technology (pp. 37–60). Palgrave Macmillan. https://doi.org/10.1007/978-981-16-7084-8_2
Eiser, I., Fischer, T., Schneider, F., Koch, G., Biemann, C., & Petersen Frey, F. (Eds.) (2023). Open Science Prinzipien und interdisziplinäre Kollaboration in D-WISE: Zwischen Hermeneutik und Digitaler Methode in der Diskursanalyse. Zenodo.
Escobar, A. (Ed.). (2018). New ecologies for the twenty-first century. Designs for the pluriverse: Radical interdepend-ence, autonomy, and the making of worlds. Duke University Press. https://doi.org/10.1215/9780822371816
Fischer, T., Schneider, F., Petersen-Frey, F., Haque, A. S. M., Eiser, I., Koch, G., & Biemann, C. (2024). Extending the Discourse Analysis Tool Suite with whiteboards for visual qualitative analysis. In N. Calzolari, M.-Y. Kan, V. Hoste, A. Lenci, S. Sakti, & N. Xue (Eds.), Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) (pp. 7017–7022). ELRA and ICCL. https://aclanthology.org/2024.lrec-main.615/
Gianni, R., Lehtinen, S., & Nieminen, M. (2022). Governance of responsible AI: From ethical guidelines to coopera-tive Policies. Frontiers in Computer Science, 4, Article 873437, 873437. https://doi.org/10.3389/fcomp.2022.873437
Giunchiglia, F., Batsuren, K., & Bella, G [Gabor] (2017). Understanding and exploiting language diversity. In Pro-ceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization. https://doi.org/10.24963/ijcai.2017/560
Gorman, M. E. (2002). Levels of expertise and trading zones. Social Studies of Science, 32(5-6), 933–938. https://doi.org/10.1177/030631270203200511
Gurumurthy, A., & Chami, N. (2019). The wicked problem of AI governance (Artificial Intelligence in India, No. 2). Friedrich-Ebert-Stiftung India Office. https://doi.org/10.13140/RG.2.2.14753.22886
Halpern, M. (2006). The trouble with the Turing test. The New Atlantis(11), 42–63.
Helm, P., Bella, G [Gábor], Koch, G., & Giunchiglia, F. (2023). Diversity and language technology: How techno-linguistic bias can cause epistemic injustice. arXiv. https://doi.org/10.48550/arXiv.2307.13714
Himmelreich, J. (2019). Responsibility for killer robots. Ethical Theory and Moral Practice, 22(3), 731–747. https://doi.org/10.1007/s10677-019-10007-9
Himmelreich, J., & Köhler, S. (2022). Responsible AI through conceptual engineering. Philosophy & Technology, 35(3). https://doi.org/10.1007/s13347-022-00542-2
Hovy, D., & Prabhumoye, S. (2021). Five sources of bias in natural language processing. Language and Linguistics Compass, 15(8), e12432. https://doi.org/10.1111/lnc3.12432
Jarrahi, M. H., Lutz, C., & Newlands, G. (2022). Artificial intelligence, human intelligence and hybrid intelligence based on mutual augmentation. Big Data & Society, 9(2), Article 20539517221142824. https://doi.org/10.1177/20539517221142824
Khalilia, H., Bella, G., Freihat, A. A., Darma, S., & Giunchiglia, F. (2023). Lexical diversity in kinship across lan-guages and dialects. Frontiers in Psychology, 14, 1229697. https://doi.org/10.3389/fpsyg.2023.1229697
Koch, G. (2005). Zur Kulturalität der Technikgenese: Praxen, Policies und Wissenskulturen der künstlichen Intelligenz. Röhrig.
Koch, G., Bella, G [Gábor], Helm, P., & Giunchiglia, F. (2024). Layers of technology in pluriversal design decolonis-ing language technology with the live language initiative. CoDesign, 20(1), 77–90. https://doi.org/10.1080/15710882.2024.2341799
Koch, G., Biemann, C., Eiser, I., Fischer, T., Schneider, F., Stumpf, T., & Tijerina García, A. (2022). D-WISE Tool Suite for the sociology of knowledge approach to discourse analysis. In M. Rauterberg (Ed.), Culture and Computing: 10th International Conference, C&C 2022, Held as Part of the 24th HCI International Confer-ence, HCII 2022, Virtual Event, June 26 – July 1, 2022, Proceedings (1st ed. 2022, Vol. 13324, pp. 68–83). Springer International Publishing; Imprint Springer. https://doi.org/10.1007/978-3-031-05434-1_5
Koch, G., Stumpf, T., & Haque, A. S. M. (2026). Grounded Theory geleitetes Strukturieren in KI-gestützten Forschungsprozessen am Beispiel digitaler Diskursanalysen. In C. Pentzold, N. Heise, & Bischof Andreas (Eds.), Praxis Grounded Theory (2. edition). Springer VS.
Lavi, E., & Reich, Y. (2024). Cross-disciplinary system value overview towards value-oriented design. Research in Engineering Design, 35(1), 1–20. https://doi.org/10.1007/s00163-023-00418-2
Lazem, S., Giglitto, D., Nkwo, M. S., Mthoko, H., Upani, J., & Peters, A. (2022). Challenges and paradoxes in decol-onising HCI: a critical discussion. Computer Supported Cooperative Work (CSCW), 31(2), 159–196. https://doi.org/10.1007/s10606-021-09398-0
Lowenhaupt Tsing, A. (2005). Friction: An ethnography of global connection. Princeton University Press. https://doi.org/10.1515/9781400830596
Lu, Q., Zhu, L., Xu, X., Whittle, J., Zowghi, D., & Jacquet, A. (2024). Responsible AI pattern catalogue: A collection of best practices for AI governance and engineering. ACM Computing Surveys, 56(7), 1–35. https://doi.org/10.1145/3626234
Ong, A., & Collier, S. (Eds.). (2005). Global assemblages: technology, politics, and ethics as anthropological problems. Blackwell Publishing.
Papagiannidis, E., Mikalef, P., & Conboy, K. (2025). Responsible artificial intelligence governance: A review and research framework. The Journal of Strategic Information Systems, 34(2), 101885. https://doi.org/10.1016/j.jsis.2024.101885
Pfaffenberger, B. (1992). Technological dramas. Science, Technology, & Human Values, 17(3), 282–312. https://doi.org/10.1177/016224399201700302
Reddyhoff, D. (2022). Dependency, data and decolonisation: a framework for decolonial thinking in collaborative AI research. arXiv. https://doi.org/10.48550/arXiv.2206.03212
Reichert, R., & Richterich, A. (2015). Introduction: Digital materialism. Digital Culture & Society(1), 5–18. https://www.degruyter.com/document/doi/10.14361/dcs-2015-0102/html
Rismani, S., & Moon, A. (2023). What does it mean to be a responsible AI practitioner: An ontology of roles and skills. In Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society (pp. 584–595). ACM. https://doi.org/10.1145/3600211.3604702
Ropohl, G. (1999). Philosophy of socio-technical systems. Society for Philosophy and Technology Quarterly Electronic Journal, 4(3), 186–194. https://doi.org/10.5840/techne19994311.
Shneiderman, B. (2020). Human-centered artificial intelligence: reliable, safe & trustworthy. International Journal of Human–Computer Interaction, 36(6), 495–504. https://doi.org/10.1080/10447318.2020.1741118
Siapera, E. (2022). AI content moderation, racism and (de)coloniality. International Journal of Bullying Prevention, 4(1), 55–65. https://doi.org/10.1007/s42380-021-00105-7
Spiekermann, S., & Winkler, T. (2020). Value-based engineering for ethics by design. SSRN Electronic Journal. Advance online publication. https://doi.org/10.2139/ssrn.3598911
Stahl, B. C. (2023). Embedding responsibility in intelligent systems: From AI ethics to responsible AI ecosystems. Scientific Reports, 13(1), 7586. https://doi.org/10.1038/s41598-023-34622-w
Tzachor, A., Devare, M., King, B., Avin, S., & Ó hÉigeartaigh, S. (2022). Responsible artificial intelligence in agricul-ture requires systemic understanding of risks and externalities. Nature Machine Intelligence, 4(2), 104–109. https://doi.org/10.1038/s42256-022-00440-4
Zembylas, M. (2023). A decolonial critique of ‘diversity’: Theoretical and methodological implications for meta-intercultural education. Intercultural Education, 34(2), 118–133. https://doi.org/10.1080/14675986.2023.2177622.
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