Abstract
In this chapter, I provide an overview of the changes that big data is rendering in biomedicine, through a brief analysis of the term “big data” and its relationship to biomedical paradigms. I explore how emerging trends like personalized medicine intersect with the broader politics and practices of data, such as the various forms of expertise and power that are involved in making and making sense of data. Ultimately, I set out an agenda for an “anthropology of data,” as a means to question the norms, politics, and values that get wrapped up in data.
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References
Ackerman, Sara L., Katherine Weatherford Darling, Sandra Soo-Jin Lee, Robert A. Hiatt, and Janet K. Shim. 2015. Accounting for Complexity: Gene–Environment Interaction Research and the Moral Economy of Quantification. Science, Technology & Human Values 41 (2): 194–218.
Ali, Hamid Raza, M. Irwin, L. Morris, S.J. Dawson, F.M. Blows, E. Provenzano, B. Mahler-Araujo, et al. 2013. Astronomical Algorithms for Automated Analysis of Tissue Protein Expression in Breast Cancer. British Journal of Cancer 108 (3): 602–612.
Appadurai, Arjun. 1996. Modernity at Large: Cultural Dimensions of Globalization. Vol. 1. Minneapolis, MN: University of Minnesota Press.
Arribas-Ayllon, Michel, A. Bartlett, and K. Featherstone. 2010. Complexity and Accountability: The Witches’ Brew of Psychiatric genetics. Social Studies of Science 40 (4): 499–524.
Balog, Júlia, László Sasi-Szabó, James Kinross, Matthew R. Lewis, Laura J. Muirhead, Kirill Veselkov, Reza Mirnezami, et al. 2013. Intraoperative Tissue Identification Using Rapid Evaporative Ionization Mass Spectrometry. Science Translational Medicine 5 (194): 1–11.
Barnes, Tom. 2015. Science Shows Why Drum Machines Will Never Replace Live Drummers. https://mic.com/articles/113504/science-shows-why-drum-machines-will-never-replace-live-drummers#.or0xf9jMa
Bateson, Gregory, Don D. Jackson, Jay Haley, and John Weakland. 1956a. The Double Bind. Behavioral Science 1 (4): 251–254.
———. 1956b. Toward a Theory of Schizophrenia. Behavioral Science 1 (4): 251–264.
Bateson, Gregory, Don D. Jackson, Jay Haley, and John H. Weakland. 1963. A Note on the Double Bind—1962. Family Process 2 (1): 154–161.
Beaulieu, Anne. 2001. Voxels in the Brain: Neuroscience, Informatics and Changing Notions of Objectivity. Social Studies of Science 31 (5): 635–680.
———. 2002. Images are Not the (Only) Truth: Brain Mapping, Visual Knowledge, and Iconoclasm. Science, Technology & Human Values 27 (1): 53–86.
———. 2004. From Brainbank to Database: The Informational Turn in the Study of the Brain. Studies in History and Philosophy of Science Part C 35 (2): 367–390.
Bender, Eric. 2015. Big Data in Biomedicine. Nature 527 (7576): S1–S1.
Boyd, Danah, and Kate Crawford. 2012. Critical Questions for Big Data: Provocations for a Cultural, Technological, and Scholarly Phenomenon. Information, Communication & Society 15 (5): 662–679.
Braun, Bruce. 2007. Biopolitics and the Molecularization of Life. Cultural Geographies 14 (1): 6–28.
Butler, Declan. 2013. When Google got Flu Wrong. Nature 494 (7436): 155.
Caduff, Carlo. 2014. Sick Weather Ahead: On Data-Mining, Crowd-Sourcing and White Noise. Cambridge Anthropology 32 (1): 32–46.
Carruth, Allison. 2014. The Digital Cloud and the Micropolitics of Energy. Public Culture 26 (2): 339–364.
Cook, Samantha, Corrie Conrad, Ashley L. Fowlkes, and Matthew H. Mohebbi. 2011. Assessing Google Flu Trends Performance in the United States During the 2009 Influenza Virus A (H1N1) Pandemic. PloS One 6 (8): e23610.
Crawford, Kate. 2013. The Hidden Biases in Big Data. HBR Blog Network. https://hbr.org/2013/04/the-hidden-biases-in-big-data
Darnton, Robert. 2000. An Early Information Society: News and the Media in Eighteenth-Century Paris. American Historical Review 105 (1): 1–35.
Daston, Loren, and P. Galison. 2007. Objectivity. New York: Zone Books.
Davies, Gail. 2012. What is a Humanized Mouse? Remaking the Species and Spaces of Translational Medicine. Body & Society 18 (3–4): 126–155.
Diebold, Francis X. 2012. On the Origin (s) and Development of the Term ‘Big Data’. https://economics.sas.upenn.edu/pier/working-paper/2012/origins-and-development-term-%E2%80%9Cbig-data
Doctorow, Cory. 2013. Correlation Between Autism Diagnosis and Organic Food Sales. BoingBoing. http://boingboing.net/2013/01/01/correlation-between-autism-dia.html
Dougherty, Conor. 2015. Google Photos Mistakenly Labels Black People ‘Gorillas’. The New York Times. http://bits.blogs.nytimes.com/2015/07/01/google-photos-mistakenly-labels-black-people-gorillas/
Dumit, Joe. 2003. Picturing Personhood: Brain Scans and Biomedical Identity. Princeton: Princeton University Press.
Edwards, Paul. 2010. A Vast Machine: Computer Models, Climate Data, and the Politics of Global Warming. Cambridge: MIT Press.
Fortun, Kim. 2001. Advocacy after Bhopal: Environmentalism, Disaster, New Global Orders. Chicago: University of Chicago Press.
Fortun, Kim, and M. Fortun. 2005. Scientific Imaginaries and Ethical Plateaus in Contemporary US Toxicology. American Anthropologist 107 (1): 43–54.
Foucault, Michel. 1977. In Discipline & Punish: The Birth of the Prison, ed. Allen Lane. Sheridan: Vintage.
———. 2003. The Birth of the Clinic. London: Routledge.
Ginsberg, Jeremy, Matthew H. Mohebbi, Rajan S. Patel, Lynnette Brammer, Mark S. Smolinski, and Larry Brilliant. 2009. Detecting Influenza Epidemics Using Search Engine Query Data. Nature 457 (7232): 1012–1014.
Gitelman, Lisa. 2013. Raw Data Is an Oxymoron. Cambridge, MA: MIT Press.
Good, Byron. 1994. Medicine, Rationality, and Experience: An Anthropological Perspective. Cambridge: Cambridge University Press.
Hacking, Ian. 1990. The Taming of Chance. Cambridge: Cambridge University Press.
Hagen, J.B. 1998. The Origins of Bioinformatics. Nature Medicine 2: 231–236.
Halpern, Orit. 2015. Beautiful Data: A History of Vision and Reason Since 1945. Durham: Duke University Press.
Harford, Tim. 2014. Big Data: Are We Making a Big Mistake? FT Magazine. http://www.ft.com/intl/cms/s/2/21a6e7d8-b479-11e3-a09a-00144feabdc0.html
Hayden, Erika Check. 2014. The $1,000 Genome. Nature 507 (7492): 294–295.
Hern, Alex. 2016. 2016: The Year AI Came of Age. https://www.theguardian.com/technology/2016/dec/28/2016-the-year-ai-came-of-age
Hotz, Robert Lee. 13 August 2012. Here’s an Omical Tale: Scientists Discover Spreading Suffix. The Wall Street Journal. http://online.wsj.com/article/SB10000872396390444840104577551433143153716.html
IBM. 2015. IBM Watson. http://www.ibm.com/smarterplanet/us/en/ibmwatson/
Imperial NIHR Biomedical Research Centre. 2011. An ‘Intelligent Knife’ That Tells the Surgeon Where to Cut. http://imperialbrc.org/our-impact/case-studies/intelligent-knife-surgery
Kay, Lily. 2000. Who Wrote the Book of Life?: A History of the Genetic Code. Palo Alto: Stanford University Press.
Kayyali, Basel, David Knott, and Steve Van Kuiken. 2013. The Big-Data Revolution in US Health Care: Accelerating Value and Innovation. McKinsey & Company. http://www.mckinsey.com/industries/healthcare-systems-and-services/our-insights/the-big-data-revolution-in-us-health-care
Keller, Evelyn Fox. 2000. Models of and Models For: Theory and Practice in Contemporary Biology. Philosophy of Science 67: 72–86.
———. 2002. The Century of the Gene. Cambridge: Harvard University Press.
Kitchin, Rob, and Gavin McArdle. 2016. What Makes Big Data, Big Data? Exploring the Ontological Characteristics of 26 Datasets. Big Data & Society 1: 1–10.
Kleinman, Arthur. 1982. Neurasthenia and Depression: A Study of Somatization and Culture in China. Culture, Medicine and Psychiatry 6 (2): 117–190.
Krenchel, Mikkel, and Christian Madsbjerg. 2014. Your Big Data Is Worthless if You Don’t Bring It Into the Real World. Wired. http://www.wired.com/2014/04/your-big-data-is-worthless-if-you-dont-bring-it-into-the-real-world/
Lakoff, Andrew. 2015. Real-time Biopolitics: The Actuary and the Sentinel in Global Public Health. Economy and Society 44 (1): 40–59.
Landecker, Hannah. 2011. Food as Exposure: Nutritional Epigenetics and the New Metabolism. BioSocieties 6 (2): 167–194.
———. 2015. Being and Eating: Losing Grip on the Equation. BioSocieties 10 (2): 253–258.
Laney, Douglas. 2001. 3D Data Management: Controlling Data Volume, Velocity and Variety. META Group Research Note 6.
Latour, B., and S. Woolgar. 1986. Laboratory Life: The Construction of Scientific Facts. Princeton: Princeton University Press.
Leonelli, Sabina. 2012. When Humans are the Exception: Cross-Species Databases at the Interface of Biological and Clinical Research. Social Studies of Science 42 (2): 214–236.
———. 2016. Data-Centric Biology: A Philosophical Study. Chicago: University of Chicago Press.
Levin, Nadine. 2014a. Multivariate Statistics and the Enactment of Biological Complexity in Metabolic Science. Social Studies of Science 44 (4): 555–578.
———. 2014b. What’s Being Translated in Translational Research? Making and Making Sense of Data between the Laboratory and the Clinic. TECNOSCIENZA: Italian Journal of Science & Technology Studies 5 (1): 91–114.
Lock, Margaret. 1995. Encounters with Aging: Mythologies of Menopause in Japan and North America. London: University of California Press.
Lohr, Steve. 2013. The Origins of ‘Big Data’: An Etymological Detective Story. The New York Times. http://bits.blogs.nytimes.com/2013/02/01/the-origins-of-big-data-an-etymological-detective-story/?_r=0
———. 2014. The New Thing in Google Flu Trends Is Traditional Data. The New York Times. http://bits.blogs.nytimes.com/2014/10/31/the-new-thing-in-google-flu-trends-is-traditional-data/
Löwy, Ilona. 2009. Preventive Strikes: Women, Precancer, and Prophylactic Surgery. Baltimore: Johns Hopkins University Press.
Lupton, Deborah. 2015. Health Promotion in the Digital Era: A Critical Commentary. Health Promotion International 30 (1): 174–183.
M’charek, Amade. 2005. The Human Genome Diversity Project: An Ethnography of Scientific Practice. Cambridge: Cambridge University Press.
MacKenzie, Adrian. 2015. Machine Learning and Genomic Dimensionality: From Features to Landscapes. In Postgenomics, ed. S. Richardson and H. Stevens, 73–102. Durham: Duke University Press.
MacKenzie, Donald, and Taylor Spears. 2014. ‘The Formula That Killed Wall Street’? The Gaussian Copula and the Material Cultures of Modelling. Social Studies of Science 44 (3): 393–417.
Madrigal, Alex C. 2014. In Defense of Google Flu Trends. The Atlantic Monthly. http://www.theatlantic.com/technology/archive/2014/03/in-defense-of-google-flu-trends/359688/
Manyika, J., M. Chui, P. Bisson, J. Woetzel, R. Dobbs, J. Bughin, and D. Aharon. 2015. Unlocking the Potential of the Internet of Things. McKinsey Global Institute.
Miller, Claire Cain. 2015. When Algorithms Discriminate. The New York Times. http://www.nytimes.com/2015/07/10/upshot/when-algorithms-discriminate.html
Morgan, Mary S., and Margaret Morrison. 1999. Models as Mediators: Perspectives on Natural and Social Science. Cambridge: Cambridge University Press.
Myers, Natasha. 2015. Rendering Life Molecular: Models, Modelers, and Excitable Matter. Durham: Duke University Press.
Naughton, John. 2014. Google and the Flu: How Big Data Will Help Us Make Gigantic Mistakes. The Guardian. https://www.theguardian.com/technology/2014/apr/05/google-flu-big-data-help-make-gigantic-mistakes
Note to Self. 2015. Why Online Shoppers See Different Prices for the Same Item. http://www.wnyc.org/story/dynamic-pricing-price-optimization-discrimination/
November, Joseph A. 2012. Biomedical Computing: Digitizing Life in the United States. Baltimore: Johns Hopkins University Press.
Prentice, Rachel. 2012. Bodies in Formation: An Ethnography of Anatomy and Surgery Education. Durham: Duke University Press.
Rajan, K.S., and S. Leonelli. 2013. Biomedical Trans-actions. Public Culture 25 (3): 463–475.
Rapp, Raina. 1999. Testing Women, Testing the Fetus: The Social Impact of Amniocentesis in America. New York: Routledge.
Räsänen, Minna, and James M. Nyce. 2013. The Raw is Cooked: Data in Intelligence Practice. Science, Technology & Human Values 38 (5): 655–677.
Ruths, Derek, and Jürgen Pfeffer. 2014. Social Media for Large Studies of Behavior. Science 346 (6213): 1063–1064.
Saini, Angela. 2012. Olympic Drug Testing Lab to Become National Phenome Center. Science. http://news.sciencemag.org/europe/2012/08/olympic-drug-testing-lab-become-national-phenome-center
Silver, Nate. 2012. The Signal and the Noise: Why So Many Predictions Fail-But Some Don’t. London: Penguin.
Starosielski, Nicole. 2015. The Undersea Network. Durham: Duke University Press.
Stevens, Hallam. 2013. Life Out of Sequence: A Data-Driven History of Bioinformatics. Chicago: University of Chicago Press.
Strasser, Bruno J. 2012. Data-Driven Sciences: From Wonder Cabinets to Electronic Databases. Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 43 (1): 85–87.
Taleb, Nassim M. 2013. Beware the Big Errors of ‘Big Data’. Wired. http://www.wired.com/2013/02/big-data-means-big-errors-people/
TechRepublic. 2015. Why Your Urine Could Usher in an Era of Personalised Medicine. http://www.techrepublic.com/blog/european-technology/why-your-urine-could-usher-in-an-era-of-personalised-medicine/
Topol, Eric J. 2012. The Creative Destruction of Medicine: How the Digital Revolution will Create Better Health Care. New York: Basic Books.
Turkle, Sherry. 2012. Alone Together: Why We Expect More from Technology and Less From Each Other. New York: Basic Books.
Tutton, Richard. 2012. Personalizing Medicine: Futures Present and Past. Social Science & Medicine 75: 1721–1728.
UK Department of Health. 2012. A Phenomenal Legacy for London 2012. http://mediacentre.dh.gov.uk/2012/08/01/a-phenomenal-legacy-for-london-2012/
University of Cambridge. 2013. Astronomers and Cancer Researchers Team Up to Beat Cancer. http://www.ast.cam.ac.uk/content/astronomers.and.cancer.researchers.team.beat.cancer
Vigen, Tyler. 2015. Spurious Correlations. New York: Hachette Books.
Walter, Patrick. 2012. Phenomenal Olympic Science Legacy (Or is that Sustainability?). http://www.rsc.org/chemistryworld/2012/07/phenomenal-olympic-science-legacy-or-sustainability
Whitmarsh, Ian. 2011. American Genomics in Barbados: Race, Illness, and Pleasure in the Science of Personalized Medicine. Body & Society 17 (2–3): 159–181.
Wynne, Brian. 2005. Reflexing Complexity. Theory, Culture & Society 22 (5): 67–94.
Zickuhr, Kathryn, and Aaron Smith. 2012. Digital Differences. http://www.pewinternet.org/2012/04/13/digital-differences/
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Levin, N. (2018). Big Data and Biomedicine. In: Meloni, M., Cromby, J., Fitzgerald, D., Lloyd, S. (eds) The Palgrave Handbook of Biology and Society. Palgrave Macmillan, London. https://doi.org/10.1057/978-1-137-52879-7_28
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