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      The repression of mètis within digital organizations

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            Abstract

            Numerous organizations are placing great emphasis on such techniques as evidence-based protocols to automation and artificial intelligence (AI) with the aim of improving efficiency and maximizing profitability. Such instrumental techniques attempt to formalize all manner of environmental phenomena through abstraction and categorization. They have also reduced organizational capability to deal with dynamic environmental complexities, uncertainties and ambiguities. The aim of this paper is to examine organizational approaches relying heavily on formalized/automated protocols in aviation, medicine and other professional domains targeted by AI development. Such approaches repress the human capability known as mètis, which organizations require to deal successfully with dynamic ambiguities in the form of unexpected emergencies. Mètis is briefly explained, and examples of organizational barriers preventing its manifestation are given.

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            Author and article information

            Contributors
            Journal
            10.2307/j50022063
            prometheus
            Prometheus
            Pluto Journals
            0810-9028
            1470-1030
            1 September 2020
            : 36
            : 3 ( doiID: 10.13169/prometheus.36.issue-3 )
            : 253-276
            Affiliations
            School of Management Sciences, Université du Québec à Montréal
            Author notes
            Article
            prometheus.36.3.0253
            10.13169/prometheus.36.3.0253
            03ef9ffc-56ca-4271-ba35-16257e3b27cc
            © 2020 Pluto Journals

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            eng

            Computer science,Arts,Social & Behavioral Sciences,Law,History,Economics

            References

            1. Alavi, M. and Tiwana, A. (2003) ‘Knowledge management: the information technology dimension’ in Easterby-Smith, M. and Lyles, M. (eds) Handbook of Organizational Learning and Knowledge Management, Blackwell Publishing, Malden MA, pp.104–21.

            2. Alexander, J. (2008) The Mantra of Efficiency: From Waterwheel to Social Control, John Hopkins University Press, Baltimore.

            3. Ananny, M. (2016) ‘Toward an ethics of algorithms: convening, observation, probability, and timeliness’, Science, Technology and Human Values, 41, 1, pp.93–117.

            4. Au, W. (2011) ‘Teaching under the new Taylorism: high-stakes testing and the standardization of the 21st century curriculum’, Journal of Curriculum Studies, 43, 1, pp.25–45.

            5. Autor, D. (2015) ‘Why are there still so many jobs? The history and future of workplace automation’, Journal of Economic Perspectives, 29, 3, pp.3–30.

            6. Barad, K (2007) Meeting the Universe Halfway: Quantum Physics and the Entanglement of Matter and Meaning, Duke University Press, Durham NC.

            7. Baumard, P. (1999) Tacit Knowledge in Organizations, Sage, London.

            8. Benvéniste, E. (1980) Problèmes de Linguistique Générale, vol. 2, Gallimard, Paris.

            9. Brown, P., Lauder, H. and Ashton, D. (2011) The Global Auction: The Broken Promise of Education, Jobs and Incomes, Oxford University Press, New York.

            10. Buchanan, B. and Miller, T. (2017) Machine Learning for Policymakers, Belfer Center for Science and International Affairs, available at https://www.belfercenter.org/sites/default/files/files/publication/MachineLearningforPolicymakers.pdf (accessed August 2020).

            11. Carlile, P. (2002) ‘A pragmatic view of knowledge and boundaries: boundary objects in new product development’, Organization Science, 13, 4, pp.442–55.

            12. Carrette, J. (1999) Religion, and Culture Michel Foucault, Routledge, New York.

            13. Carter, C., Clegg, S. and Kornberge, M. (2008) A Very Short, Interesting and Reasonably Cheap Book about Studying Strategy, Sage, London.

            14. Clair, M. (2016) ‘The limits of neoliberalism: how writers and editors use digital technologies in the literary field’, Communication and Information Technologies Annual, 11, pp.169–201.

            15. Clegg, S., Courpasson, D. and Phillips. N. (2006) Power and Organizations, Sage, London.

            16. Cohen, D. (2013) ‘FDA official: “Clinical trial system is broken”‘. BMJ, 347, f6980.

            17. Collins, H. (2007) ‘Bicycling on the moon: collective tacit knowledge and somatic-limit tacit knowledge’, Organization Studies, 28, 2, pp.257–62.

            18. Collins, H. (2010) Tacit and Explicit Knowledge, University of Chicago Press, Chicago.

            19. Cook, S. and Brown, J. (1999) ‘Bridging epistemologies: the generative dance between organizational knowledge and organizational knowing’, Organization Science, 6, 4, pp.350–72.

            20. Couric, K. (2009) ‘Capt. Sully worried about airline industry’, CBS Evening News, 10 February, available at https://www.cbsnews.com/news/capt-sully-worried-about-airline-industry/ (accessed August 2020).

            21. Crossley, N. (2011) Towards Relational Sociology, Routledge, New York.

            22. Dane, E. (2013) ‘Things seen and unseen: investigating experience-based qualities of attention in a dynamic work setting’, Organization Studies, 34, 1, pp.45–78.

            23. De Certeau, M. (1984) Practice of Everyday Life, University of California Press, Berkeley CA.

            24. Dejoux, C. and Léon, E. (2018) Métamorphose des Managers, Pearson, Paris.

            25. Détienne, M. and Vernant, J. (1978) Les Ruses de l'Intélligence. La Mètis des Grecs, Flammarion, Paris.

            26. Dewey, J. (1927) The Public and its Problems, Holt Publishers New York.

            27. Dewey, J. (1929) The Quest for Certainty: A Study of the Relation of Knowledge and Action, Putnam, New York.

            28. Dewulf, A., Craps, M., Bouwen, R., Taillieu, T. and Pahl-Wostl, C. (2005) ‘Integrated management of natural resources: dealing with ambiguous issues, multiple actors and diverging frames’, Water Science and Technology, 52, 6, pp.115–24.

            29. Dolmage, J. (2009) ‘Metis, mêtis, mestiza, Medusa: rhetorical bodies across rhetorical traditions’, Rhetoric Review, 28, 1, pp.1–28.

            30. Dreyfus, H. (1996) ‘Being and power: Heidegger and Foucault’, International Journal of Philosophical Studies, 4, 1, pp.1–16.

            31. Dreyfus, H. and Dreyfus, S. (2005) ‘Peripheral vision expertise in real world contexts’, Organization Studies, 26, 5, pp.779–92.

            32. Elish, M. and Boyd, D. (2018) ‘Situating methods in the magic of Big Data and AI’, Communication Monographs, 85, 1, pp.57–80.

            33. Ellul, J. (1980) The Technological System, Continuum, New York.

            34. Emirbayer, M. (1997) ‘Manifesto for a relational sociology’, American Journal of Sociology, 103, 2, pp.281–317.

            35. Every-Palmer, S. and Howick, J. (2014) ‘How evidence-based medicine is failing due to biased trials and selective publications’, Journal of Evaluation in Clinical Practice, 20, pp.908–14.

            36. Falconer, L. (2006) ‘Organizational learning, tacit information, and e-learning: a review’, The Learning Organization, 13, 2, pp.140–51.

            37. Faraj, S., Pachidi, S. and Sayegh, K. (2018) ‘Working and organizing in the age of the learning algorithm’, Information and Organization, 28, pp.62–70.

            38. Feenberg, A. (1999) Questioning Technology, Routledge, London.

            39. Ferrucci, D. (2012) ‘Introduction to “This is Watson”‘, IBM Journal of Research and Development, 56, 3.4, pp.1:1–1:15.

            40. Foucault, M. (1982) The Archaeology of Knowledge and the Discourse on Language, Pantheon Books, New York.

            41. Gerdes, A. (2008) ‘The clash between standardisation and engagement’, Journal of Information, Communication and Ethics in Society, 6, 1, pp.46–59.

            42. Gherardi, S. (2012) How to Conduct a Practice-based Study: Problems and Methods, Edward Elgar, Cheltenham.

            43. Glasersfeld, E. von (1995) Radical Constructivism: A Way of Knowing and Learning, Falmer, London.

            44. Glasziou, P., Moynihan, R., Richards, T. and Godlee, F. (2013) ‘Too much medicine; too little care’, BMJ, 347, f4247.

            45. Greenhalgh, T., Howick, J. and Maskrey, N. (2014) ‘Evidence based medicine: a movement in crisis?‘, BMJ, 348, g3725.

            46. Groves, C., Henwood, K., Shirani, F., Butler, C., Parkhill, K. and Pidgeon, N. (2016) ‘The grit in the oyster: using energy biographies to question socio-technical imaginaries of “smartness”‘, Journal of Responsible Innovation, 3, 1, pp.4–25.

            47. Grunwald, A. (2014) ‘The hermeneutic side of responsible research and innovation’, Journal of Responsible Innovation, 1, 3, pp.274–91.

            48. Guiette, A. and Vandenbempt, K. (2016) ‘Learning in times of dynamic complexity through balancing phenomenal qualities of sensemaking’, Management Learning, 47, 1, pp.83–99.

            49. Hagan, M., Demuth, H., Beale, M. and Jesús, O. (2014) Neural Network Design, Martin Hagan Publisher, Oklahoma State University, Stillwater OK.

            50. Harford, T. (2016) ‘Crash: how computers are setting us up for disaster’, Guardian, 11 October, available at https://www.theguardian.com/technology/2016/oct/11/crash-how-computers-are-setting-us-up-disaster (accessed August 2020).

            51. Harkins, A. (2005) ‘Too much guidance?‘, Lancet, 365, 1768.

            52. Harrison, S. and Checkland, K. (2009) Evidence-Based Practice in UK Health Policy, Routledge, New York.

            53. Hatt, B. (2016) ‘Street smarts vs book smarts: the figured world of smartness in the lives of marginalized urban youth’, Urban Review, 39, 2, pp.145–66.

            54. Heidegger, M. (1977) The Question Concerning Technology and Other Essays, Garland Publishing, New York.

            55. Hernes, T. (2014) A Process Theory of Organization, Oxford University Press, Oxford.

            56. Holford, W. and Hadaya, P. (2017) ‘Addressing the tacit knowledge gap in knowledge systems across agential realism’, Proceedings of 50th Hawaii International Conference on System Sciences (HICSS-50), IEEE, Computer Society Press, Wakoloa, Hawaii, pp.4465–74.

            57. Irani, L. (2015) ‘Difference and dependence among digital workers: the case of Amazon Mechanical Turk’, South Atlantic Quarterly, 11, 4, 1, pp.225–34.

            58. James, W. (1950) The Principles of Psychology, Dover, New York.

            59. Jarrahi, M. (2018) ‘Artificial intelligence and the future of work: human-AI symbiosis in organizational decision making’, Business Horizons, 61, 14, pp.577–86.

            60. Jasanoff, S. and Kim, S-H. (2009) ‘Containing the atom: sociotechnical imaginaries and nuclear power in the United States and South Korea’, Minerva, 47, 2, pp.119–46.

            61. Kahneman, D. and Klein, G. (2009) ‘Conditions for intuitive expertise’, American Psychologist, 64, 6, pp.515–26.

            62. Kaplan, A. and Haenlein, M. (2019) ‘Siri, Siri, in my hand: who's the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence’, Business Horizons, 62, 1, pp.15–25.

            63. Kittur, A., Nickerson, J., Bernstein, M., Gerber, E., Shaw, A., Zimmerman, J., Lease, M. and Horton, J. (2013) ‘The future of crowdwork’, CSCW 2013 Conference, February, San Antonio TX.

            64. Kupers, W. (2008) ‘Embodied “inter-learning” – an integral phenomenology of learning in and by organizations’, The Learning Organization, 15, 5, pp.388–408.

            65. Langer, E. (2000) ‘Mindful learning’, Current Directions in Psychological Science, 9, 2, pp.220–3.

            66. LeCun, Y., Bengio, Y. and Hinton, G. (2015) ‘Deep learning’, Nature, 521, 7553, pp.436–44.

            67. Leonard, D. and Swap, W. (2004) ‘Deep smarts’, Harvard Business Review, 30, 2, pp.157–69.

            68. Leyden, J. et al. (1999) ‘Finasteride in the treatment of men with frontal male pattern hair loss’, Journal of the American Academy of Dermatology, 40, pp.930–7.

            69. Liu, H., Chai, K-H. and Nebus, J. (2013) ‘Balancing codification and personalization for knowledge reuse: a Markov decision process approach’, Journal of Knowledge Management, 17, 5, pp.755–72.

            70. Lorino P., Tricard, B. and Clot Y. (2011) ‘Research methods for non-representational approaches to organizational complexity: the dialogical mediated inquiry’, Organization Studies, 32, 6, pp.769– 801.

            71. Lowrie, I. (2017) ‘Algorithmic rationality: epistemology and efficiency in the data sciences’, Big Data & Society, January–June, pp.1–13.

            72. Llewelyn, H., Ang, H., Lewis, D. and Al-Abdullah, A. (2014) Oxford Handbook of Clinical Diagnosis, Oxford University Press, Oxford.

            73. Macnaghten, P. and Szerszynski, B. (2013) ‘Living the global social experiment: an analysis of public discourse on solar radiation management and its implications for governance’, Global Environmental Change, 23, 2, pp.465–74.

            74. Maddieson, I. (1984) Patterns of Sounds, Cambridge University Press, Cambridge.

            75. Marneffe, M.-C., Manning, C. and Potts, C. (2012) ‘Did it happen? The pragmatic complexity of veridicality assessment’, Computational Linguistics, 38, pp.301–33.

            76. Marwala, T. (2015) Causality, Correlation and Artificial Intelligence for Rational Decision Making, World Scientific, Singapore.

            77. McComb, K. and Semple S. (2005) ‘Coevolution of vocal communication and sociality in primates’, Biology Letters, 1, pp.381–5.

            78. McLoughlin, I. (2002) Creative Technological Change: The Shaping of Technology and Organisations, Routledge, London.

            79. McMillan, J. and Buhle, P. (2003) New Left Revisited, Temple University Press, Philadelphia.

            80. Merleau-Ponty, M. (1962) Phenomenology of Perception, Routledge & Kegan Paul, London.

            81. Meshkati, N. and Khashe, Y. (2015) ‘Operators’ improvisation in complex technological systems: successfully tackling ambiguity, enhancing resiliency and the last resort to averting disaster', Journal of Contingencies and Crisis Management, 23, 2, pp.90–6.

            82. Mitchell, T. (2006) The Discipline of Machine Learning, report CMU-ML-06-108, Machine Learning Department, Carnegie Melon University, Pittsburgh PA, available at http://reports-archive.adm.cs.cmu.edu/anon/ml/CMU-ML-06-108.pdf (accessed August 2020).

            83. Moore, P. and Robinson, A. (2015) ‘The quantified self: what counts in the neoliberal workplace’, New Media and Society, 18, 11, pp. 2774–92.

            84. Mukherjee, S. (2017) ‘AI versus MD: what happens when diagnosis is automated?‘, New Yorker, 27 March, available at https://www.newyorker.com/magazine/2017/04/03/ai-versus-md (accessed August 2020).

            85. Nafus, D. (2014) ‘Stuck data, dead data, and disloyal data: the stops and starts in making numbers into social practice’, Distinktion: Scandanavian Journal of Social Theory, 15, 2, pp.208–22.

            86. Nonaka, I. and Takeuchi, H. (2004) Hitotsubashi on Knowledge Management, John Wiley & Sons (Asia), Singapore.

            87. Nonaka, I. and von Krogh, G. (2009) ‘Tacit knowledge and knowledge conversion: controversy and advancement in organizational knowledge creation theory’, Organization Science, 20, 3, pp.635–52.

            88. OECD (2018) Science, Technology and Innovation Outlook 2018: Adapting to Technological and Societal Disruption, OECD Publishing, Paris.

            89. Orlikowski, W. (2002) ‘Knowing in practice: enacting a collective capability in distributed organizing’, Organization Science, 13, 3, pp.249–73.

            90. Orlikowski, W. and Scott, S. (2015) ‘Exploring material-discursive practices’, Journal of Management Studies, 52, 5, pp.696–705.

            91. Palit, A. and Popovic, D. (2005) Computational Intelligence in Time Series Forecasting: Theory and Engineering Applications, Springer, New York.

            92. Polanyi, M. (1962) Personal Knowledge, University of Chicago Press, Chicago.

            93. Polanyi, M. and Prosch, H. (1975) Meaning, University of Chicago Press, Chicago.

            94. Pomerol, J. (1997) ‘Artificial intelligence and human decision making’, European Journal of Operational Research, 99, pp.3–25.

            95. Pope, S. (2014) ‘Fly by wire: fact versus science fiction’, Flying Magazine, 23 April, available at https://www.flyingmag.com/aircraft/jets/fly-by-wire-fact-versus-science-fiction/ (accessed August 2020).

            96. Proudfoot, D. (2011) ‘Anthropomorphism and AI: Turing's much misunderstood imitation game’, Artificial Intelligence, 175, 5–6, pp.950–7.

            97. Ray, T. and Clegg, S. (2007) ‘Can we make sense of knowledge management's tangible rainbow? A radical constructivist alternative’, Prometheus: Critical Studies in Innovation, 25, 2, pp.161–85.

            98. Ribeiro, R. and Collins, H. (2007) ‘The bread-making machine: tacit knowledge and two types of action’, Organization Studies, 28, 9, pp.1417–33.

            99. Russell, S. and Norvig, P. (2010) Artificial Intelligence: A Modern Approach, Prentice Hall, Upper Saddle River NJ.

            100. Sanzogni, L., Guzman, G. and Busch, P. (2017) ‘Artificial intelligence and knowledge management: questioning the tacit dimension’, Prometheus: Critical Studies in Innovation, 35, 1, pp.37–56.

            101. Schmiz, A. (2013) ‘Migrant self-employment between precariousness and self-exploitation’, Ephemera, 13, 1, pp.53–74.

            102. Schrader, S., Riggs W. and Smith, R. (1993) ‘Choice over uncertainty and ambiguity in technical problem solving’, Journal of Engineering and Technology Management, 10, pp.13–99.

            103. Scott, J. (1998) Seeing like a State: How Certain Schemes to Improve the Human State have Failed, Vail-Ballou Press, Binghamton NY.

            104. Searle, J. (1980) ‘Minds, brains, and programs’, Behavioral and Brain Sciences, 3, 3, pp.417–57.

            105. Selamat, M. and Choudrie, J. (2004) ‘The diffusion of tacit knowledge and its implications on information systems: the role of meta-abilities’, Journal of Knowledge Management, 8, 2. pp.128–39.

            106. Shotter, J. (2011). Reflections on sociomateriality and dialogicality in organization studies: from “inter-” to “intra-thinking” in performing practices', 3rd International Symposium on Process Organization Studies, June, Corfu, pp.1–14.

            107. Silver, D., Schrittwieser, J., Simonyan, K., Antonoglou, I., Huang, A., Guez, A. and Hassabis, D. (2017) ‘Mastering the game of Go without human knowledge’, Nature, 550, 7676, pp.354–9.

            108. Suchman, L. (1994) ‘Do categories have politics? The language/action perspective reconsidered’, Computer Supported Cooperative Work, 2, pp.177–90.

            109. Swap, W., Leonard, D., Shields, M. and Abrams, L. (2001) ‘Using mentoring and storytelling to transfer knowledge in the workplace’, Journal of Management Information Systems, 18, 1, pp.95– 114.

            110. Szulanski, G. (2000) ‘The process of knowledge transfer: a diachronic analysis of stickiness’, Organizational Behavior and Human Decision Processes, 82, 1, pp.9–27.

            111. Till, C. (2014) ‘Exercise as labour: quantified self and the transformation of exercise into labour’, Societies, 4, 3, pp.446–62.

            112. Timmermans, S. and Berg, M. (2003) The Gold Standard: The Challenge of Evidence-based Medicine and Standardization in Health Care, Temple University Press, Philadelphia.

            113. Tsoukas, H. (1996) ‘The firm as a distributed knowledge system: a constructivist approach’, Strategic Management Journal, 17, pp.11–25.

            114. Tsoukas, H. (2003) ‘Do we really understand tacit knowledge?‘ in Easterby-Smith, M. and Lyles, M. (eds) Blackwell Handbook of Organizational Learning and Knowledge Management, Blackwell, Oxford, pp.410–27.

            115. Tsoukas, H. (2005) Complex Knowledge: Studies in Organizational Epistemology, Oxford University Press, Oxford.

            116. Tsoukas, H. (2009) ‘A dialogical approach to the creation of new knowledge in organizations’, Organization Science, 20, 6, pp.941–53.

            117. Turing, Alan (1950) ‘Computing machinery and intelligence’, Mind, 49, pp.433–60.

            118. Turner, E., Matthews, A., Linardatos, E., Tell, R. and Rosenthal, R. (2008) ‘Selective publication of antidepressant trials and its influence on apparent efficacy’, New England Journal of Medicine, 358, pp.252–60.

            119. Van Mannen, J. (1988) Tales of the Field, University of Chicago Press, Chicago.

            120. Vartabedian, R. and Masunaga, S. (2019) ‘Lion Air crash shows cockpit computers are no substitute for pilot skills’, Los Angeles Times, 4 February, available at https://www.latimes.com/business/la-fi-lion-air-crash-20190204-story.html (accessed August 2020).

            121. Virtanen, I. (2013) ‘In search for a theoretically firmer epistemological foundation for the relationship between tacit and explicit knowledge’, Electronic Journal of Knowledge Management, 11, 2, pp.118–26.

            122. Wachter, R. (2015a) ‘My interview with Capt. Sully Sullenberger: on aviation, medicine and technology’, Hospital Leader, 23 February, available at https://thehospitalleader.org/my-interview-with-capt-sully-sullenberger-on-aviation-medicine-and-technology/ (accessed August 2020).

            123. Wachter, R. (2015b) The Digital Doctor: Hope, Hype, and Harm at the Dawn of Medicine's Computer Age, McGraw-Hill Education, New York.

            124. Walker, W., Harremoës, P., Rotmans, J., Van der Sluijs, J., Van Asselt, M., Jansen, P. and Krayer von Krauss, M. (2003) ‘Defining uncertainty: a conceptual basis for uncertainty management in model-based decision support’, Journal of Integrated Assessment, 4, 1, pp.5–17.

            125. Wallén, J. (2008) The History of the Industrial Robot, Technical Report from Automatic Control, report LiTH-ISY-R-2853, Linköping University, Sweden.

            126. Weick, K. (2009) Making Sense of the Organization: The Impermanent Organization, John Wiley & Sons, Chichester.

            127. Weick, K. (2015) ‘Ambiguity as grasp: the reworking of sense’, Journal of Contingencies and Crisis Management, 23, 2, pp.117–23.

            128. Winther, R. (2014) ‘James and Dewey on abstractions’, The Pluralist, 9, 2, pp.1–28.

            129. Wittgenstein L (1972) Philosophical Investigations, Blackwell, Oxford.

            130. Zilber, T. (2007) ‘Stories and the discursive dynamics of institutional entrepreneurship: the case of Israeli high-tech after the bubble’, Organization Studies, 28, pp.1035–54.

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