Nonnatural Personal Information. Accounting for Misleading and Non-misleading Personal Information

Abstract

Personal information is key to informational privacy and the algorithmically generated profiles of individuals. However, the concept of personal information and its nature is rarely discussed. The concept of personal information thus seems to be based on an idea of information as objective and truthful—as natural information—that is depicted as digital footprints in the online and digital realm. I argue that the concept of personal information should exit the realm of natural information and enter the realm of nonnatural information—grounded in meaning, intention, and convention—as this will provide us with a concept that can account for potential misleadingness, inaccuracies, and mistakes.

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Fig. 1

Notes

  1. 1.

    In the present article, when talking about natural information, it may mean either of the two different varieties, depending on the context. Most often, it is a reference to Dretske-information, as it is this conception of information that is most often at play in the privacy literature when personal information is mentioned.

  2. 2.

    The concepts of nonnatural personal information, unintentionally non-misleading personal information, intentionally non-misleading personal information, personal misinformation, and personal disinformation have not previously been developed and are thus not present within the privacy literature.

  3. 3.

    It should be noted that I am only committing myself to the phrasing of the legal definition in terms of the relation between some information and an identifiable natural person. I am not tying the definition of nonnatural personal information to any of the specifications of the elements of the original legal definition as laid out in the opinion published by the Data Protection Working Party (2007).

  4. 4.

    In the “all-or-nothing” interpretation equivalent to Dretske’s (1981) concept of information.

  5. 5.

    The Data Protection Working Party (2007) does not distinguish between data and information. As seen in the quotation, personal data is defined in terms of information, and the document does not offer a general definition of information.

  6. 6.

    It should be noted that a footprint in principle can be generated with the intention to mislead. For instance, it is possible to walk backwards in the snow in order to mislead about the direction one has taken. However, this possibility is not reflected in the idea of the digital footprint, which is treated as something objective, truthful, and accurate.

  7. 7.

    The idea that information is something one can control and/or restrict access to seems to be bound to an idea of information as property—i.e., something which can be owned and thereby controlled by some specific individual, company, or government. For a discussion of ownership of information (data), see Hummel, Braun, and Dabrock (2020).

  8. 8.

    In fact, we might need to question the profiling business as such.

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Acknowledgements

I wish to thank my colleagues in the project “Don't Take it Personal” Jens-Erik Mai, Rikke Frank Jørgensen, Bjarki Valtysson, Taina Bucher, Johan Lau Munkholm, and Jesper Pagh for fruitful discussions along the way. Furthermore, I would like to thank Mike Katell and Irina Shklovski for very thorough and useful comments on an earlier draft, as well as all the attendees at the Information Ethics Roundtable in Copenhagen in 2018 (IER2018).

Funding

This research was conducted within the project “Don’t Take it Personal”: Privacy and Information in an Algorithmic Age, which is generously funded by the Independent Research Fund Denmark, grant number: 8018-00041B.

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Correspondence to Sille Obelitz Søe.

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Søe, S.O. Nonnatural Personal Information. Accounting for Misleading and Non-misleading Personal Information. Philos. Technol. (2021). https://doi.org/10.1007/s13347-021-00457-4

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Keywords

  • Personal information
  • Nonnatural information
  • Misleadingness
  • Personal misinformation
  • Personal disinformation
  • Algorithmic profiles
  • Privacy
  • Information