When digital health meets digital capitalism, how many common goods are at stake?

In recent years, all major consumer technology corporations have moved into the domain of health research. This ‘Googlization of health research’ (‘GHR’) begs the question of how the common good will be served in this research. As critical data scholars contend, such phenomena must be situated within the political economy of digital capitalism in order to foreground the question of public interest and the common good. Here, trends like GHR are framed within a double, incommensurable logic, where private gain and economic value are pitted against public good and societal value. While helpful for highlighting the exploitative potential of digital capitalism, this framing is limiting, insofar as it acknowledges only one conception of the common good. This article uses the analytical framework of modes of justification developed by Boltanksi and Thévenot to identify a plurality of orders of worth and conceptualizations of the common good at work in GHR. Not just the ‘civic’ (doing good for society) and ‘market’ (enhancing wealth creation) orders, but also an ‘industrial’ (increasing efficiency), a ‘project’ (innovation and experimentation), and what I call a ‘vitalist’ (proliferating life) order. Using promotional material of GHR initiatives and preliminary interviews with participants in GHR projects, I ask what moral orientations guide different actors in GHR. Engaging seriously with these different conceptions of the common good is paramount. First, in order to critically evaluate them and explicate what is at stake in the move towards GHR, and ultimately, in order to develop viable governance solutions that ensure strong ‘civic’ components.

[1]  Terra Graziani,et al.  Data Justice , 2020, Child Data Citizen.

[2]  R. Krohn Laboratory Life , 2019, Bridging the Seas.

[3]  I. Kohane,et al.  Biases in electronic health record data due to processes within the healthcare system: retrospective observational study , 2018, British Medical Journal.

[4]  Julia E. Powles,et al.  Response to DeepMind , 2018 .

[5]  G. Rees,et al.  Letter in response to Google DeepMind and healthcare in an age of algorithms , 2018 .

[6]  J. Kvedar,et al.  Artificial intelligence powers digital medicine , 2018, npj Digital Medicine.

[7]  M. Pratt Are Apple and Amazon tech ‘saviors’ or same old story? , 2018 .

[8]  Michael V. McConnell,et al.  Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning , 2017, Nature Biomedical Engineering.

[9]  Industrial Strategy Industrial strategy: building a Britain fit for the future , 2017 .

[10]  L. Taylor What is data justice? The case for connecting digital rights and freedoms globally , 2017, Big Data Soc..

[11]  Hal Hodson,et al.  Google DeepMind and healthcare in an age of algorithms , 2017, Health and Technology.

[12]  B. Prainsack Research for personalised medicine: Time for solidarity , 2017 .

[13]  Eeva Luhtakallio,et al.  Justifications Analysis: Understanding Moral Evaluations in Public Debates , 2016 .

[14]  Tamar Sharon,et al.  The Googlization of health research: from disruptive innovation to disruptive ethics. , 2016, Personalized medicine.

[15]  John P. A. Ioannidis,et al.  Routinely collected data and comparative effectiveness evidence: promises and limitations , 2016, Canadian Medical Association Journal.

[16]  Neil Savage,et al.  Mobile data: Made to measure , 2015, Nature.

[17]  Jennifer Jardine,et al.  Apple’s ResearchKit: smart data collection for the smartphone era? , 2015, Journal of the Royal Society of Medicine.

[18]  Michael Causey Apple’s ResearchKit , 2015 .

[19]  Shoshana Zuboff,et al.  Big other: surveillance capitalism and the prospects of an information civilization , 2015, J. Inf. Technol..

[20]  D. Lupton,et al.  The commodification of patient opinion: the digital patient experience economy in the age of big data. , 2014, Sociology of health & illness.

[21]  J. Dijck Datafication, dataism and dataveillance: Big Data between scientific paradigm and ideology , 2014 .

[22]  C. Waldby,et al.  Book review symposium: Authors’ response to reviews of Clinical Labor: Tissue Donors and Research Subjects in the Global Bioeconomy , 2014 .

[23]  I. Huys,et al.  “Trust is not something you can reclaim easily”: patenting in the field of direct-to-consumer genetic testing , 2012, Genetics in Medicine.

[24]  S. Wyatt,et al.  THE GIFT OF SPIT (AND THE OBLIGATION TO RETURN IT) , 2013 .

[25]  Andrzej K. Koźmiński,et al.  The Entrepreneurial State , 2013 .

[26]  D. Boyd,et al.  CRITICAL QUESTIONS FOR BIG DATA , 2012 .

[27]  David E Frost,et al.  All of us. , 2011, Journal of oral and maxillofacial surgery : official journal of the American Association of Oral and Maxillofacial Surgeons.

[28]  Turo-Kimmo Lehtonen,et al.  Justifications for commodified security: The promotion of private life insurance in Finland 1945-90 , 2010 .

[29]  Ken R. Roy There's No Such Thing as a Free Gift , 2008 .

[30]  A. Taegtmeyer Personalized Medicine , 2007, McGill journal of medicine : MJM : an international forum for the advancement of medical sciences by students.

[31]  Luc Boltanski,et al.  The New Spirit of Capitalism , 2005 .

[32]  Trevor Darrell,et al.  Privacy in Context , 2001, Hum. Comput. Interact..

[33]  Tiziana Terranova Free Labor: Producing Culture for the Digital Economy , 2000 .

[34]  Ferial J. Ghazoul,et al.  Madness and civilization , 1994 .

[35]  Laurent Thévenot,et al.  Une justification écologique? Conflits dans l'aménagement de la nature , 1993 .

[36]  R. Crawford Healthism and the Medicalization of Everyday Life , 1980, International journal of health services : planning, administration, evaluation.

[37]  J. Olsen,et al.  The European Commission , 2020, The European Union.