Reassembling Agency
Epistemic Practices in the Age of Artificial Intelligence
DOI:
https://doi.org/10.37062/sf.62.27824Nyckelord:
agencing, machine agency, practice, epistemic configurationsAbstract
This article reflects on how sociology can analyse the role of artificial intelligence (AI) in scientific practice without buying into the current AI hype. Drawing on sensibilities developed in actor-network theory (ANT) it introduces the concept of agencing (agency as a verb) which refers to how scientists debate and configure the human and machine agency. It suggests that we can come to a more nuanced understanding of the effects of AI in science by attending to actors’ agencing practices. By discussing three ideal types of agencing, the article argues that AI should not be regarded as a rupture in the tooling and practices of science, but rather as a continuation of long-standing patterns of practice. That is, agency, and the space for action and judgement, is organised differently in the AI-driven laboratory; however, this is not a new configuration of epistemic agency. Rather we might understand these changes as building on statistical epistemic configurations going back to the birth of statistics in sociology in the 1700s and 1800s.
Referenser
Amelang, K. & S. Bauer (2019) "Following the algorithm: How epidemiological risk-scores do accountability”, Social Studies of Science 49 (4): 476–502. https://doi.org/10.1177/0306312719862049
Callon, M. (1984) “Some elements of a sociology of translation: Domestication of the scallops and the fishermen of St Brieuc Bay”, Sociological Review 32 (1): 196–233. https://doi.org/10.1111/j.1467-954x.1984.tb00113.x
Callon, M. & B. Latour (1992) “Don’t throw the baby out with the Bath School! A reply to Collins and Yearley”, 343–368 in A. Pickering (Ed.) Science as practice and culture. University of Chicago Press.
Callon, M. & J. Law (1995) “Agency and the hybrid collectif”, South Atlantic Quarterly 94 (2): 481–507.
Callon, M. & F. Muniesa (2005) “Peripheral vision: Economic markets as calculative collective devices”, Organization Studies 26 (8): 1229–1250. https://doi.org/10.1177/0170840605056393
Campolo, A. & K. Crawford (2020) “Enchanted determinism: Power without responsibility in artificial intelligence”, Engaging Science, Technology, and Society 6: 1–19. https://doi.org/10.17351/ests2020.277
Cochoy, F. (2008) “Calculation, qualculation, calqulation: shopping cart arithmetic, equipped cognition and the clustered consumer”, Marketing Theory 8 (1): 15–44. https://doi.org/10.1177/1470593107086483
Daston, L. (1995) “The moral economy of science”, Osiris 10: 2–24.
“Data-Driven Life Science (DDLS)” (n.d.) SciLifeLab. https://www.scilifelab.se/data-driven/
“DDLS What is data-driven life science?” (n.d.) SciLifeLab. https://www.scilifelab.se/data-driven/what-is-ddls/
Deleuze, G. & F. Guattari (1987) A thousand plateaus: Capitalism and schizophrenia. London and New York: Continuum.
Dussauge, I., C.-F. Helgesson, F. Lee & S. Woolgar (2015) “On the omnipresence, diversity, and elusiveness of values in the life sciences and medicine”, 1–28 in I. Dussauge, C.-F. Helgesson & F. Lee (Eds) Value Practices in the Life Sciences and Medicine. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199689583.003.0001.
Edwards, P.N., M.S. Mayernik, A.L. Batcheller, G.C. Bowker & C.L. Borgman (2011) “Science friction: Data, metadata, and collaboration”, Social Studies of Science 41 (5): 667–690. https://doi.org/10.1177/0306312711413314.
Fujimura, J.H. & D.Y. Chou (1994) “Dissent in science: Styles of scientific practice and the controversy over the cause of AIDS”, Social Science & Medicine 38 (8): 1017–1036. https://doi.org/10.1016/0277-9536(94)90219-4
Garfinkel, H. (1967) Studies in ethnomethodology. New Jersey: Prentice-Hall.
Gigerenzer, G. et al. (1989) The empire of chance: How probability changed science and everyday life. Cambridge [UK] , New York: Cambridge University Press (Ideas in context).
Gitelman, L. (2013) “Raw data” is an oxymoron. Boston: MIT Press.
Jaton, F. (2017) “We get the algorithms of our ground truths: Designing referential databases in digital image processing”, Social Studies of Science 47 (6): 811–840. https://doi.org/10.1177/0306312717730428
Jaton, F. (2021) “Assessing biases, relaxing moralism: On ground-truthing practices in machine learning design and application”, Big Data & Society, 8 (1): 20539517211013569. https://doi.org/10.1177/20539517211013569
Jülich, S. (2002) Skuggor av sanning : tidig svensk radiologi och visuell kultur. Linköping University. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-34996
Keller, E.F. (1984) A feeling for the organism, 10th Aniversary edn: The Life and Work of Barbara McClintock. Illustrated edn. New York: Times Books.
Knorr Cetina, K.D. (1999) Epistemic cultures: How the sciences make knowledge. Cambridge: Harvard University Press.
Krig, S. (2014a) “Ground truth data, content, metrics, and analysis”, 283–311 in S. Krig (Ed.) Computer vision metrics: Survey, taxonomy, and analysis. Berkeley: Apress. https://doi.org/10.1007/978-1-4302-5930-5_7
Krig, S. (2014b) “Survey of ground truth datasets”, 401–410 in S. Krig (Ed.) Computer vision metrics: Survey, taxonomy, and analysis. Berkeley: Apress, https://doi.org/10.1007/978-1-4302-5930-5_10
Latour, B. (1987) Science in action. Cambridge: Harvard University Press.
Latour, B. (1999) “On recalling ANT”, 15–25 in J. Law & J. Hassard (Eds.) Actor network theory and after. Oxford: Blackwell.
Latour, B. (2005) Reassembling the social: An introduction to actor-network-theory. Oxford University Press.
Latour, B. & S. Woolgar. (1986) Laboratory life: The construction of scientific facts. 2nd edn. Princeton University Press.
Law, J. (2002a) Aircraft stories: Decentering the object in technoscience. Durham: Duke University Press (Science and Cultural Theory).
Law, J. (2002b) “Complexities: Social studies of knowledge practices”. https://doi.org/10.1215/9780822383550.
Law, J. & J. Hassard (1999) Actor-network theory and after. Oxford: Blackwell.
Lee, F. (2015) “Purity and interest: On interest work and epistemic value”, 207–223 in I. Dussauge, C.-F. Helgesson & F. Lee (Eds) Value Practices in the Life Sciences and Medicine. Oxford University Press.
Lee, F. (2016) “Skattkarta eller atlas: om förväntningar och kunskapens värde i biovetenskapen”, in A. Tunlid & S. Widmalm (Eds) Det forskningspolitiska laboratoriet: Förväntningar på vetenskapen 1900–2010. Lund: Nordic Academic Press.
Lee, F. (2021) “Enacting the pandemic: Analyzing agency, opacity, and power in algorithmic assemblages”, Science & Technology Studies 34 (1): 65–90. https://doi.org/10.23987/sts.75323
Lee, F. (2023) “Ontological overflows and the politics of absence: Zika, disease surveillance, and mosquitos”, Science as Culture 33 (3): 1–26. https://doi.org/10.1080/09505431.2023.2291046
Lee, F. (2024) “The Practices and Politics of Machine Learning: A Fieldguide for Analyzing Artificial Intelligence”. OSF. https://doi.org/10.31235/osf.io/vmzfu
Lee, F. & C.-F. Helgesson (2020) “Styles of Valuation: Algorithms and Agency in High-throughput Bioscience”, Science, Technology, & Human Values 45 (4): 659–685. https://doi.org/10.1177/0162243919866898
Lee, F., M. Boman & A. Ostrowska, A. (2021) “Data work in biomedical AI: The hidden challenges of data, pre-training, and ground truths”, 90 in V. Dignum (Ed.) Community reference meeting healthcare. Umeå: WASP-HS. https://wasp-hs.org/wp-content/uploads/2021/05/WASP-HS-CRM-Report-Healthcare-May-2021-1.pdf
Lynch, M. (2012) “Revisiting the cultural dope”, Human Studies 35 (2): 223–233. https://doi.org/10.1007/s10746-012-9227-z
Mackenzie, A. (2015) “The production of prediction: What does machine learning want?”, European Journal of Cultural Studies [Preprint]. https://doi.org/10.1177/1367549415577384
Marcus, G.E. (1998) Ethnography through thick and thin. Berkeley: University of California.
Marx, K. (1992) Capital Volume 1. 1st edn. London: Penguin Classics.
Mol, A. (1999) “Ontological politics: A word and some questions”, 74–89 in J. Law & J. Hassard (Eds.) Actor-network theory and after. Oxford: Blackwell.
Mol, A. (2002) The body multiple: Ontology in medical practice. Durham: Duke University Press.
Star, S.L. (1990) “Power, technology and the phenomenology of conventions: On being allergic to onions”, The Sociological Review 38 (1 Supplement): 26–56. https://doi.org/10.1111/j.1467-954X.1990.tb03347.x
Strum, S.S. & B. Latour (1987) “Redefining the social link: From baboons to humans”, Social Science Information 26 (4): 783–802. https://doi.org/10.1177/053901887026004004
Suchman, L. (2023) “The uncontroversial ‘thingness’ of AI”, Big Data & Society 10 (2): 20539517231206794. https://doi.org/10.1177/20539517231206794
Thevenot, L. (2002) “Which road to follow? The moral complexity of an ‘equipped’ humanity”, 53–87 in John Law & Annemarie Mol (Eds) Complexities: Social Studies of Knowledge Practices. Durham: Duke University Press.
Ziewitz, M. (2016) “Governing algorithms: Myth, mess, and methods”, Science, Technology, & Human Values 41 (1): 3–16. https://doi.org/10.1177/0162243915608948
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