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The Digital Phenotype: a Philosophical and Ethical Exploration

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Abstract

The concept of the digital phenotype has been used to refer to digital data prognostic or diagnostic of disease conditions. Medical conditions may be inferred from the time pattern in an insomniac’s tweets, the Facebook posts of a depressed individual, or the web searches of a hypochondriac. This paper conceptualizes digital data as an extended phenotype of humans, that is as digital information produced by humans and affecting human behavior and culture. It argues that there are ethical obligations to persons affected by generalizable knowledge of a digital phenotype, not only those who are personally identifiable or involved in data generation. This claim is illustrated by considering the health-related digital phenotypes of precision medicine and digital epidemiology.

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Notes

  1. I wish to thank Prof. Ernst Hafen, who inspired me to work on this topic, participants to the ethics panel of the MyData 2017 Conference (Tallin-Helsinki) and Paul-Olivier Dehaye, for co-organizing that panel and providing feedback on a previous draft of this article. Special gratitude is owed to the two anonymous reviewers of this journal, who enriched the paper with their inputs, and in several rounds of review very patiently helped me to give shape to these views and to remove at least the worst sources of unclarity. All remaining problems in the paper are solely the author’s responsibility.

  2. Twitter followers include bots (software programmed by paid professionals) whose goal is to enhance the perception of popularity of politicians, celebrities and companies (Freelon 2014). Freelon cites the so-called “Karpf’s rule”: “any metric of digital influence that becomes financially valuable, or is used to determine newsworthiness, will become increasingly unreliable over time”. See David Karpf, “Social Science Research Methods in Internet Time,” Information, Communication & Society 15, no. 5 (June 1, 2012): 650.

  3. These feedback loops take place across the offline-online boundary. The philosopher Luciano Floridi uses the concept of onlife to indicate the porous nature of the offline-online boundary (The Onlife initiative 2015).

  4. They do not exhaust the range of possible moral theories (or even of European Enlightenment-inspired moral theories). For example four-principlism (Beauchamp and Childress 1994) is influential in bioethics and can be stretched to develop an ethics of health-related data (Mittelstadt 2017a).

  5. For example, the “biotrust model” has been proposed to govern genetic biobanks (David E. Winickoff and Winickoff 2003; D. E. Winickoff and Neumann 2005), the solidarity model for research biobanks (Prainsack and Buyx 2013).

  6. This is suggested by indicating shared traits of the genome as part of the reasons to adopt a biotrust model (D. E. Winickoff and Neumann 2005, 9). A similar line of argument appears in Widdows's work on the Connected Self (2013, chap. 3).

  7. Floridi’s account of this issue describes the problem as one of group privacy (Floridi 2014, 2016b). My treatment makes no such commitment.

  8. See also (Floridi 2011). Notice that Floridi here talks about personal information, e.g. a person’s Facebook profile is an extension of the self, but this is, arguably, not essential to the argument. I can recognize my informational extensions produced by participating to internet conversations in an anonymous form as mine, even though others cannot recognize me.

  9. This recommendation corresponds to ethical principle #1 in (Mittelstadt 2017a, 2).

  10. Another example of platform effect is the “People You May Know” function in Facebook, which caused a spike in the observed rate of triadic closures (the phenomenon by which two nodes in a network are more likely to establish a link between each other if they each already share a link with another node) in Facebook friendships (Zignani et al. 2014). Platform effects are especially important for the epistemology of online sociology but they are problematic also for epidemiology.

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  1. University of Zurich, Zurich, Switzerland

    Michele Loi

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  1. Michele Loi
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Correspondence to Michele Loi.

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Part of this work was done while ML was a scientific collaborator at ETH Zurich.

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Loi, M. The Digital Phenotype: a Philosophical and Ethical Exploration. Philos. Technol. 32, 155–171 (2019). https://doi.org/10.1007/s13347-018-0319-1

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