Philosophical Inquiry into Computer Intentionality: Machine Learning and Value Sensitive Design
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Dmytro Mykhailov
Abstract
Intelligent algorithms together with various machine learning techniques hold a dominant position among major challenges for contemporary value sensitive design. Self-learning capabilities of current AI applications blur the causal link between programmer and computer behavior. This creates a vital challenge for the design, development and implementation of digital technologies nowadays. This paper seeks to provide an account of this challenge. The main question that shapes the current analysis is the following: What conceptual tools can be developed within the value sensitive design school of thought for evaluating machine learning algorithms where the causal relation between designers and the behavior of their computer systems has been eroded? The answer to this question will be provided through two levels of investigation within the value sensitive design methodology. The first level is conceptual. Within the conceptual level, we will introduce the notion of computer intentionality and will show how this term may be used for solving an issue of non-causal relation between designer and computer system. The second level of investigation is technical. At this level the emphasis will be given to machine learning algorithms.
Funding source: National Social Science Fund of China
Award Identifier / Grant number: 19ZDA040
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Research funding: The work on this paper has been supported financially by the Major Project of the National Social Science Fund of China: “The philosophy of technological innovations and the practical logic of Chinese independent innovation” (技术创新哲学与中国自主创新的实践逻辑研究). Grant number: 19ZDA040.
References
Benjamin, J. J., Berger, A., Merrill, N., & Pierce, J. (2021). Machine learning uncertainty as a design material: A post-phenomenological inquiry. In ACM 2021 CHI Conference on Human Factors in Computing Systems.10.1145/3411764.3445481Suche in Google Scholar
Berkich, D. (2017). The problem of original agency. Southwest Philosophy Review, 33(1), 75–82. https://doi.org/10.5840/swphilreview20173318Suche in Google Scholar
Binns, R. (2017). Fairness in machine learning: Lessons from political philosophy. ArXiv, 81, 1–11. http://arxiv.org/abs/1712.03586Suche in Google Scholar
Boyd, D., & Crawford, K. (2012). Critical questions for big data: Provocations for a cultural, technological, and scholarly phenomenon. Information, Communication & Society, 15(5), 662–679. https://doi.org/10.1080/1369118X.2012.678878Suche in Google Scholar
Brey, P. (2010). Philosophy of technology after the empirical turn. Techné: Research in Philosophy and Technology, 14(1 PLISS), 36–48. https://doi.org/10.5840/TECHNE20101416Suche in Google Scholar
Burrell, J. (2016). How the machine ‘thinks’: Understanding opacity in machine learning algorithms. Big Data and Society, 3, 1–12.10.1177/2053951715622512Suche in Google Scholar
Flanagan, M., Howe, D., & Nissenbaum, H. (2008). Embodying values in technology: Theory and practice. In J. van den Hoven, & J. Weckert (Eds.), Information Technology and Moral Philosophy (pp. 322–353). Cambridge University Press. https://philpapers.org/rec/FLAEVI10.1017/CBO9780511498725.017Suche in Google Scholar
Floridi, L. (2013). The Ethics of information. Oxford University Press.10.1093/acprof:oso/9780199641321.001.0001Suche in Google Scholar
Floridi, L., & Sanders, J. W. (2004). On the morality of artificial agents. Minds and Machines, 14(3), 349–379. https://doi.org/10.1023/B:MIND.0000035461.63578.9d10.1023/B:MIND.0000035461.63578.9dSuche in Google Scholar
Friedman, B., Harbers, M., Hendry, D. G., van den Hoven, J., Jonker, C., & Logler, N. (2021). Eight grand challenges for value sensitive design from the 2016 Lorentz workshop. Ethics and Information Technology, 23, 5–16. https://doi.org/10.1007/s10676-021-09586-y.Suche in Google Scholar
Friedman, B., & Hendry, D. (2019). Value sensitive design: Shaping technology with moral imagination. MIT Press.10.7551/mitpress/7585.001.0001Suche in Google Scholar
Friedman, B., Kahn, P., & Borning, A. (2006). Value sensitive design and information systems. In P. Zhang, & D. Galletta (Eds.), Human–computer interaction in management information systems: Foundations (pp. 348–372). M. E. Sharpe.Suche in Google Scholar
Gillespie, T. (2014). The relevance of algorithms. In Media Technologies (pp. 167–194). The MIT Press.10.7551/mitpress/9780262525374.003.0009Suche in Google Scholar
Hoffmann, A. L. (2019). Where fairness fails: Data, algorithms, and the limits of antidiscrimination discourse. Information, Communication & Society, 22(7), 900–915. https://doi.org/10.1080/1369118X.2019.1573912.Suche in Google Scholar
Hoven, J. (2013). Value sensitive design and responsible innovation. In R. Owen, J. Bessant, & M. Heintz (Eds.), Responsible innovation (pp. 75–83). Wiley.10.1002/9781118551424.ch4Suche in Google Scholar
Johnson, D. G. (2006). Computer systems: Moral entities but not moral agents. Ethics and Information Technology, 8(4), 195–204. https://doi.org/10.1007/s10676-006-9111-5Suche in Google Scholar
Johnson, D. G., & Powers, T. M. (2008). Computers as surrogate agents. In Information Technology and Moral Philosophy (pp. 251–269). Cambridge University Press.10.1017/CBO9780511498725.014Suche in Google Scholar
Jordan, M., & Bishop, C. (2004). Neural networks. In A. B. Tucker (Ed.), Handbook of Computer Science. CRC Press. https://leeway.tistory.com/950Suche in Google Scholar
Lepri, B., Oliver, N., Letouzé, E., Pentland, A., & Vinck, P. (2018). Fair, transparent, and accountable algorithmic decision-making processes: The premise, the proposed solutions, and the open challenges. Philosophy and Technology, 31(4), 611–627. https://doi.org/10.1007/s13347-017-0279-xSuche in Google Scholar
Liberati, N. (2020). The Borg–eye and the We–I. The production of a collective living body through wearable computers. AI & Society, 35(1), 39–49. https://doi.org/10.1007/s00146-018-0840-xSuche in Google Scholar
Matthias, A. (2004). The responsibility gap: Ascribing responsibility for the actions of learning automata. Ethics and Information Technology, 6(3), 175–183. https://doi.org/10.1007/s10676-004-3422-1Suche in Google Scholar
Matthias, A. (2011). From coder to creator. In Handbook of Research on Technoethics (pp. 635–650). IGI Global.10.4018/978-1-60566-022-6.ch041Suche in Google Scholar
Mykhailov, D. (2020). The phenomenological roots of technological intentionality: A postphenomenological perspective. Frontiers of Philosophy in China, 15(4), 612–635. https://doi.org/10.3868/s030-009-020-0035-6Suche in Google Scholar
Mykhailov, D. (2021). A moral analysis of intelligent decision-support systems in diagnostics through the lens of Luciano Floridi’s information ethics. Human Affairs, 31(2), 149–164. https://doi.org/10.1515/humaff-2021-0013Suche in Google Scholar
Mykhailov, D. (2022). Postphenomenological variation of instrumental realism on the “problem of representation”: fMRI imaging technology and visual representations of the human brain. Prometeica – Journal of Philosophy and Science, Special, 64–78. https://doi.org/10.34024/prometeica.2022.Especial.13520Suche in Google Scholar
Mykhailov, D., & Liberati, N. (2022). A study of technological intentionality in C++ and generative adversarial model: Phenomenological and postphenomenological perspectives. Foundations of Science, 2022, 1–17. https://doi.org/10.1007/S10699-022-09833-5Suche in Google Scholar
Pasquale, F. (2015). The black blox society: The secret algorithms that control money and information. Harvard University Press.10.4159/harvard.9780674736061Suche in Google Scholar
Powers, T. M. (2013). On the moral agency of computers. Topoi, 32(2), 227–236. https://doi.org/10.1007/s11245-012-9149-4Suche in Google Scholar
Primiero, G. (2017). Algorithmic iteration for computational intelligence. Minds and Machines, 27(3), 521–543. https://doi.org/10.1007/S11023-017-9423-8Suche in Google Scholar
Schmidhuber, J. (2015). Deep Learning in neural networks: An overview. Neural Networks, 61, 85–117. https://doi.org/10.1016/j.neunet.2014.09.003Suche in Google Scholar
Simon, J., Wong, P. H., & Rieder, G. (2020). Algorithmic bias and the value sensitive design approach. Internet Policy Review: Journal on Internet Regulation, 9(4), 1–16. https://doi.org/10.14763/2020.4.1534. https://ideas.repec.org/a/zbw/iprjir/233110.htmlSuche in Google Scholar
Umbrello, S., & van de Poel, I. (2021). Mapping value sensitive design onto AI for social good principles. AI and Ethics, 1, 3. https://doi.org/10.1007/s43681-021-00038-3Suche in Google Scholar
van den Hoven, J. (2017). Ethics for the digital age: Where are the moral specs? In H. Werthner, & F. van Harmelen (Eds.), Informatics in the Future (pp. 65–76). Springer International Publishing.10.1007/978-3-319-55735-9_6Suche in Google Scholar
van de Poel, I. (2020). Embedding values in artificial intelligence (AI) systems. Minds and Machines, 30(3), 385–409. https://doi.org/10.1007/s11023-020-09537-4Suche in Google Scholar
Verma, S., & Rubin, J. (2018). Fairness definitions explained. Proceedings - International Conference on Software Engineering, 1–7. https://doi.org/10.1145/3194770.3194776.Suche in Google Scholar
Wong, P. H. (2020). Democratizing algorithmic fairness. Philosophy and Technology, 33(2), 225–244. https://doi.org/10.1007/s13347-019-00355-wSuche in Google Scholar
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Artikel in diesem Heft
- Frontmatter
- Research Articles
- Against Gender: The Anti-Gender Movements and the Socio-Cultural and Moral Deconstructions in Europe
- Into the Black Box: Sex and Gender in the Study on Decision-Making – An Evidence from a Slovak Sample
- Cultural Differences in the Construction of Gender: A Thematic Analysis of Gender Representations in American, Spanish, and Czech Children’s Literature
- Different Minority Groups Elicit Different Safety, Economic, Power, and Symbolic Threats
- Social Representations of Political Polarization through Traditional Media: A Study of the Brazilian Case between 2015 and 2019
- Terrorists’ Violence Threats and Coping Strategies: A Phenomenological Approach of Former FATA, Pakistan
- Genealogy, Immanent Critique and Forms of Life: A Path for Decolonial Studies
- Philosophical Inquiry into Computer Intentionality: Machine Learning and Value Sensitive Design
- National Identity and Belonging of Yemenite Jews in The Journey of Buried Secrets
