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The Image is Openness, the Practice is Data: Notes on Conceptual Obscurity and Some of Its Implications for Privacy

Larsson, Stefan LU (2016) AOIR 2016
Abstract (Swedish)
Internet Metaphors and Norms

To what extent is digital “openness” also creating a modern “Panopticon”? I.e. to what extent is the conceptual imaginary of relevance for the legitimacy of modern data practices in terms of privacy? This paper argues that conceptual battles around what the Internet is and the digital development means are significant battles. The metaphorical descriptions of the internet and the significance of digitization are not just part of rhetoric or poetic language but are an outcome of how we understand this complex socio-technological phenomenon and how this understanding can be negotiated, over time and cultures, with strong discursive relevance (cf Larsson, 2013; 2014; forthcoming).

“The Internet”... (More)
Internet Metaphors and Norms

To what extent is digital “openness” also creating a modern “Panopticon”? I.e. to what extent is the conceptual imaginary of relevance for the legitimacy of modern data practices in terms of privacy? This paper argues that conceptual battles around what the Internet is and the digital development means are significant battles. The metaphorical descriptions of the internet and the significance of digitization are not just part of rhetoric or poetic language but are an outcome of how we understand this complex socio-technological phenomenon and how this understanding can be negotiated, over time and cultures, with strong discursive relevance (cf Larsson, 2013; 2014; forthcoming).

“The Internet” used to be an “information superhighway”, a “cyberspace”, or a “world wide web” often described as an empowering structure, that now has transformed to be understood in terms of “layers”, a generator of big data for a number of “platform” ventures and preferably consisting of “open” attributes.

Open Platforms, Collecting Data

There have been a number of thorough expositions of big data benefits in a digitized world conducted from a multitude of perspectives. However, one of the major concerns put forward regards individual privacy, and to what extent, and how, it needs to be protected from overly aggressive information collectors, often framed in terms of how to balance utility against privacy (Rubinstein, 2013; Tene & Polonotsky, 2012).

Predictive analytics and phenomena such as machine learning, artificial intelligence and cognitive computing all depend on massive amounts of human information, which according to critics, leads to a commodification of the private sphere (Taylor, 2014), a lack of insight into where the information travels and what it is used for (Pasquale, 2015), as well as creating a deeply asymmetric power relationship between the individuals and the data collectors, in what has been described as a “regime of compulsory self-disclosure” (Andrejevic & Gates, 2014, p. 7).

“Open [fill in blank]”

Metaphorically, it is of interest to see what type of values that may be hidden beneath the “open” concept for what it hides as much as it highlights. The debates on freedom, control, and regulation for a number of digitally related innovative fields are related to or framed in the terminology of the importance of openness. The open source movement is a clear example, pushing for the benefits of being able to co-work in primarily software development, as in a movement of “free and open source” (cf Söderberg, 2007). Open access on the other hand has underscored some of the imbalances of conventional academic publishing, and more, where some of the tax-funded research is “locked” into the proprietary models of the publishers, sometimes with the twist of being sold back to the research community through massive license agreements. Similarly, there has in the last few years been what can be called an open data movement that has taken on international significance, with government agencies around the world committing to releasing data through government and non-government websites. As a means to promote government accountability, civil participation or innovation based on public sector information (PSI). Openness, it seems, comes in many forms.

Critique

Some quite substantial critique concerning the appraisal for “openness” in a digital context is also relevant for how we understand data collection, and has been voiced the last few years. This is in this study contrasted to metaphors for both data as such (cf Puschmann & Burgess, 2014) as well as notions of surveillance, such as the Foucauldian Panopticon or the more ubiquitous and invisible “Cryptopticon” (Vaidhyanathan, 2015), enabling “pan-analytics” through what has been called “panspectric surveillance” (Palmås, 2011).

Evgeny Morozov, for example, points out the concept of “open” itself as troublesome: “the ambiguity of a term like ‘openness’ in part explains the confusion, excitement and disappointment generated by various recent campaigns to promote ‘open government’ and liberate ‘open government data’” (2013, p. 93), and discusses the normative content that follows in terms of “openness and its messiahs.” Similarly, Astra Taylor, in The People’s Platform, describes open as a concept “capacious enough to contain both the communal and capitalistic impulses central to Web 2.0 while being thankfully free of any socialist connotations”, adding that new-media thinkers have “claimed openness as the appropriate utopian ideal for our time, and the concept has caught on” (Taylor, 2014, p. 21). Further, she argues, “in tech circles, open systems – like the Internet itself – are always good, while closed systems – like the classic broadcast model – are bad.” Therefore, open, being an embodied concept, carries with it normativity for both digital architecture and business models.

Taylor develops her critique that new media players, now grown into mega corporations, share similar monopolist traits to traditional mass media, but with the rhetorical advantages brought by the “openness” metaphor. We should by no means be tricked, she argues, into thinking that open by necessity means free. Instead, this business model is not built around selling specific products but around measuring us, storing and selling our data to the advertising industry. She argues that this “open model” leads to the distinction between commercial and non-commercial having ’melted away’: “Where there is no distinction between inner and outer, our bonds with family and friends, our private desires and curiosities, all become commodities” (2014, p. 212).

One of the common features of metaphors, however, is that just as they highlight some aspects of a phenomenon they also hide other aspects of it. “Open” comes with culturally embedded positive connotations, sometimes in connection with “free”, which may downplay any notion of surveillance that the exact same practices sometimes are understood as in other contexts.


References
Andrejevic, M. and K. Gates. 2014. Editorial. Big Data Surveillance: Introduction. Surveillance & Society 12(2): 185-196.
Larsson, S. (2013) Metaphors, Law and Digital Phenomena: The Swedish Pirate Bay Court Case. International Journal of Law and Information Technology 21(4): 329–353.
Larsson, S. (2014) Karl Renner and (Intellectual) Property – How Cognitive Theory Can Enrich a Socio-legal Analysis of Contemporary Copyright. Law & Society Review 48(1): 3–33.
Larsson, S. (Forthcoming) Conceptions in the Code. How Metaphors Explain Legal Challenges in Digital Times. Oxford Studies in Language and Law: Oxford University Press.
Morozov, E. (2013) To Save Everything, Click Here: The Folly of Technological Solutionism. New York: Public Affairs.
Palmås, K. (2011) Predicting what you’ll do tomorrow: Panspectric surveillance and the contemporary corporation. Surveillance & Society 8(3): 338–354.
Puschmann, C., & Burgess, J (2014) Big Data, Big Questions. Metaphors of Big Data, International Journal of Communication, vol 8.
Rubinstein, I. (2013) Big Data: The End of Privacy or a New Beginning?, 3 INT’L DATA PRIVACY L. 74, 77-78.
Söderberg, J. (2008) Hacking Capitalism – The Free and Open Source Software Movement. Routledge.
Taylor, A. (2014) The People’s Platform. Taking Back Power and Culture in the Digital Age. Metropolitan Books/Henry Holt & Company.
Tene, O. & Polonetsky, J. (2012) Privacy in the Age of Big Data: A Time for Big Decisions, 64 Stanford Law Review 63.
Vaidhyanathan, S. (2015) The Rise of the Cryptopticon, The Hedgehog Review 17(1). (Less)
Abstract
Internet Metaphors and Norms. To what extent is digital “openness” also creating a modern “Panopticon”? I.e. to what extent is the conceptual imaginary of relevance for the legitimacy of modern data practices in terms of privacy? This paper argues that conceptual battles around what the Internet is and the digital development means are significant battles. The metaphorical descriptions of the internet and the significance of digitization are not just part of rhetoric or poetic language but are an outcome of how we understand this complex socio-technological phenomenon and how this understanding can be negotiated, over time and cultures, with strong discursive relevance (cf Larsson, 2013; 2014; forthcoming). “The Internet” used to be... (More)
Internet Metaphors and Norms. To what extent is digital “openness” also creating a modern “Panopticon”? I.e. to what extent is the conceptual imaginary of relevance for the legitimacy of modern data practices in terms of privacy? This paper argues that conceptual battles around what the Internet is and the digital development means are significant battles. The metaphorical descriptions of the internet and the significance of digitization are not just part of rhetoric or poetic language but are an outcome of how we understand this complex socio-technological phenomenon and how this understanding can be negotiated, over time and cultures, with strong discursive relevance (cf Larsson, 2013; 2014; forthcoming). “The Internet” used to be an “information superhighway”, a “cyberspace”, or a “world wide web” often described as an empowering structure, that now has transformed to be understood in terms of “layers”, a generator of big data for a number of “platform” ventures and preferably consisting of “open” attributes. 
Open Platforms, Collecting Data. There have been a number of thorough expositions of big data benefits in a digitized world conducted from a multitude of perspectives. However, one of the major concerns put forward regards individual privacy, and to what extent, and how, it needs to be protected from overly aggressive information collectors, often framed in terms of how to balance utility against privacy (Rubinstein, 2013; Tene & Polonotsky, 2012). Predictive analytics and phenomena such as machine learning, artificial intelligence and cognitive computing all depend on massive amounts of human information, which according to critics, leads to a commodification of the private sphere (Taylor, 2014), a lack of insight into where the information travels and what it is used for (Pasquale, 2015), as well as creating a deeply asymmetric power relationship between the individuals and the data collectors, in what has been described as a “regime of compulsory self-disclosure” (Andrejevic & Gates, 2014, p. 7). 
“Open [fill in blank]”. Metaphorically, it is of interest to see what type of values that may be hidden beneath the “open” concept for what it hides as much as it highlights. The debates on freedom, control, and regulation for a number of digitally related innovative fields are related to or framed in the terminology of the importance of openness. The open source movement is a clear example, pushing for the benefits of being able to co-work in primarily software development, as in a movement of “free and open source” (cf Söderberg, 2007). Open access on the other hand has underscored some of the imbalances of conventional academic publishing, and more, where some of the tax-funded research is “locked” into the proprietary models of the publishers, sometimes with the twist of being sold back to the research community through massive license agreements. Similarly, there has in the last few years been what can be called an open data movement that has taken on international significance, with government agencies around the world committing to releasing data through government and non-government websites. As a means to promote government accountability, civil participation or innovation based on public sector information (PSI). Openness, it seems, comes in many forms. 
Critique. Some quite substantial critique concerning the appraisal for “openness” in a digital context is also relevant for how we understand data collection, and has been voiced the last few years. This is in this study contrasted to metaphors for both data as such (cf Puschmann & Burgess, 2014) as well as notions of surveillance, such as the Foucauldian Panopticon or the more ubiquitous and invisible “Cryptopticon” (Vaidhyanathan, 2015), enabling “pan-analytics” through what has been called “panspectric surveillance” (Palmås, 2011). Evgeny Morozov, for example, points out the concept of “open” itself as troublesome: “the ambiguity of a term like ‘openness’ in part explains the confusion, excitement and disappointment generated by various recent campaigns to promote ‘open government’ and liberate ‘open government data’” (2013, p. 93), and discusses the normative content that follows in terms of “openness and its messiahs.” Similarly, Astra Taylor, in The People’s Platform, describes open as a concept “capacious enough to contain both the communal and capitalistic impulses central to Web 2.0 while being thankfully free of any socialist connotations”, adding that new-media thinkers have “claimed openness as the appropriate utopian ideal for our time, and the concept has caught on” (Taylor, 2014, p. 21). Further, she argues, “in tech circles, open systems – like the Internet itself – are always good, while closed systems – like the classic broadcast model – are bad.” Therefore, open, being an embodied concept, carries with it normativity for both digital architecture and business models. Taylor develops her critique that new media players, now grown into mega corporations, share similar monopolist traits to traditional mass media, but with the rhetorical advantages brought by the “openness” metaphor. We should by no means be tricked, she argues, into thinking that open by necessity means free. Instead, this business model is not built around selling specific products but around measuring us, storing and selling our data to the advertising industry. She argues that this “open model” leads to the distinction between commercial and non-commercial having ’melted away’: “Where there is no distinction between inner and outer, our bonds with family and friends, our private desires and curiosities, all become commodities” (2014, p. 212). One of the common features of metaphors, however, is that just as they highlight some aspects of a phenomenon they also hide other aspects of it. “Open” comes with culturally embedded positive connotations, sometimes in connection with “free”, which may downplay any notion of surveillance that the exact same practices sometimes are understood as in other contexts. 
References.Andrejevic, M. and K. Gates. 2014. Editorial. Big Data Surveillance: Introduction. Surveillance & Society 12(2): 185-196. Larsson, S. (2013) Metaphors, Law and Digital Phenomena: The Swedish Pirate Bay Court Case. International Journal of Law and Information Technology 21(4): 329–353.Larsson, S. (2014) Karl Renner and (Intellectual) Property – How Cognitive Theory Can Enrich a Socio-legal Analysis of Contemporary Copyright. Law & Society Review 48(1): 3–33.Larsson, S. (2017) Conceptions in the Code. How Metaphors Explain Legal Challenges in Digital Times. Oxford Studies in Language and Law: Oxford University Press. Morozov, E. (2013) To Save Everything, Click Here: The Folly of Technological Solutionism. New York: Public Affairs. Palmås, K. (2011) Predicting what you’ll do tomorrow: Panspectric surveillance and the contemporary corporation. Surveillance & Society 8(3): 338–354.Puschmann, C., & Burgess, J (2014) Big Data, Big Questions. Metaphors of Big Data, International Journal of Communication, vol 8.Rubinstein, I. (2013) Big Data: The End of Privacy or a New Beginning?, 3 INT’L DATA PRIVACY L. 74, 77-78.Söderberg, J. (2008) Hacking Capitalism – The Free and Open Source Software Movement. Routledge. Taylor, A. (2014) The People’s Platform. Taking Back Power and Culture in the Digital Age. Metropolitan Books/Henry Holt & Company. Tene, O. & Polonetsky, J. (2012) Privacy in the Age of Big Data: A Time for Big Decisions, 64 Stanford Law Review 63.Vaidhyanathan, S. (2015) The Rise of the Cryptopticon, The Hedgehog Review 17(1).
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keywords
openness, privacy, data, big data, conceptual obscurity, metaphor
conference name
AOIR 2016
language
English
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yes
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aeef19db-9fc1-4788-9377-c2aa92200428
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@misc{aeef19db-9fc1-4788-9377-c2aa92200428,
  abstract     = {<b>Internet Metaphors and Norms. </b>To what extent is digital “openness” also creating a modern “Panopticon”? I.e. to what extent is the conceptual imaginary of relevance for the legitimacy of modern data practices in terms of privacy? This paper argues that conceptual battles around what the Internet is and the digital development means are significant battles. The metaphorical descriptions of the internet and the significance of digitization are not just part of rhetoric or poetic language but are an outcome of how we understand this complex socio-technological phenomenon and how this understanding can be negotiated, over time and cultures, with strong discursive relevance (cf Larsson, 2013; 2014; forthcoming). “The Internet” used to be an “information superhighway”, a “cyberspace”, or a “world wide web” often described as an empowering structure, that now has transformed to be understood in terms of “layers”, a generator of big data for a number of “platform” ventures and preferably consisting of “open” attributes. <br/><b>Open Platforms, Collecting Data. </b>There have been a number of thorough expositions of big data benefits in a digitized world conducted from a multitude of perspectives. However, one of the major concerns put forward regards individual privacy, and to what extent, and how, it needs to be protected from overly aggressive information collectors, often framed in terms of how to balance utility against privacy (Rubinstein, 2013; Tene &amp; Polonotsky, 2012). Predictive analytics and phenomena such as machine learning, artificial intelligence and cognitive computing all depend on massive amounts of human information, which according to critics, leads to a commodification of the private sphere (Taylor, 2014), a lack of insight into where the information travels and what it is used for (Pasquale, 2015), as well as creating a deeply asymmetric power relationship between the individuals and the data collectors, in what has been described as a “regime of compulsory self-disclosure” (Andrejevic &amp; Gates, 2014, p. 7). <br/><b>“Open [fill in blank]”. </b>Metaphorically, it is of interest to see what type of values that may be hidden beneath the “open” concept for what it hides as much as it highlights. The debates on freedom, control, and regulation for a number of digitally related innovative fields are related to or framed in the terminology of the importance of openness. The open source movement is a clear example, pushing for the benefits of being able to co-work in primarily software development, as in a movement of “free and open source” (cf Söderberg, 2007). Open access on the other hand has underscored some of the imbalances of conventional academic publishing, and more, where some of the tax-funded research is “locked” into the proprietary models of the publishers, sometimes with the twist of being sold back to the research community through massive license agreements. Similarly, there has in the last few years been what can be called an open data movement that has taken on international significance, with government agencies around the world committing to releasing data through government and non-government websites. As a means to promote government accountability, civil participation or innovation based on public sector information (PSI). Openness, it seems, comes in many forms. <br/><b>Critique. </b>Some quite substantial critique concerning the appraisal for “openness” in a digital context is also relevant for how we understand data collection, and has been voiced the last few years. This is in this study contrasted to metaphors for both data as such (cf Puschmann &amp; Burgess, 2014) as well as notions of surveillance, such as the Foucauldian Panopticon or the more ubiquitous and invisible “Cryptopticon” (Vaidhyanathan, 2015), enabling “pan-analytics” through what has been called “panspectric surveillance” (Palmås, 2011). Evgeny Morozov, for example, points out the concept of “open” itself as troublesome: “the ambiguity of a term like ‘openness’ in part explains the confusion, excitement and disappointment generated by various recent campaigns to promote ‘open government’ and liberate ‘open government data’” (2013, p. 93), and discusses the normative content that follows in terms of “openness and its messiahs.” Similarly, Astra Taylor, in The People’s Platform, describes open as a concept “capacious enough to contain both the communal and capitalistic impulses central to Web 2.0 while being thankfully free of any socialist connotations”, adding that new-media thinkers have “claimed openness as the appropriate utopian ideal for our time, and the concept has caught on” (Taylor, 2014, p. 21). Further, she argues, “in tech circles, open systems – like the Internet itself – are always good, while closed systems – like the classic broadcast model – are bad.” Therefore, open, being an embodied concept, carries with it normativity for both digital architecture and business models. Taylor develops her critique that new media players, now grown into mega corporations, share similar monopolist traits to traditional mass media, but with the rhetorical advantages brought by the “openness” metaphor. We should by no means be tricked, she argues, into thinking that open by necessity means free. Instead, this business model is not built around selling specific products but around measuring us, storing and selling our data to the advertising industry. She argues that this “open model” leads to the distinction between commercial and non-commercial having ’melted away’: “Where there is no distinction between inner and outer, our bonds with family and friends, our private desires and curiosities, all become commodities” (2014, p. 212).  One of the common features of metaphors, however, is that just as they highlight some aspects of a phenomenon they also hide other aspects of it. “Open” comes with culturally embedded positive connotations, sometimes in connection with “free”, which may downplay any notion of surveillance that the exact same practices sometimes are understood as in other contexts. <br/><b>References.</b>Andrejevic, M. and K. Gates. 2014. Editorial. Big Data Surveillance: Introduction. Surveillance &amp; Society 12(2): 185-196. Larsson, S. (2013) Metaphors, Law and Digital Phenomena: The Swedish Pirate Bay Court Case. International Journal of Law and Information Technology 21(4): 329–353.Larsson, S. (2014) Karl Renner and (Intellectual) Property – How Cognitive Theory Can Enrich a Socio-legal Analysis of Contemporary Copyright. Law &amp; Society Review 48(1): 3–33.Larsson, S. (2017) Conceptions in the Code. How Metaphors Explain Legal Challenges in Digital Times. Oxford Studies in Language and Law: Oxford University Press. Morozov, E. (2013) To Save Everything, Click Here: The Folly of Technological Solutionism. New York: Public Affairs. Palmås, K. (2011) Predicting what you’ll do tomorrow: Panspectric surveillance and the contemporary corporation. Surveillance &amp; Society 8(3): 338–354.Puschmann, C., &amp; Burgess, J (2014) Big Data, Big Questions. Metaphors of Big Data, International Journal of Communication, vol 8.Rubinstein, I. (2013) Big Data: The End of Privacy or a New Beginning?, 3 INT’L DATA PRIVACY L. 74, 77-78.Söderberg, J. (2008) Hacking Capitalism – The Free and Open Source Software Movement. Routledge. Taylor, A. (2014) The People’s Platform. Taking Back Power and Culture in the Digital Age. Metropolitan Books/Henry Holt &amp; Company. Tene, O. &amp; Polonetsky, J. (2012) Privacy in the Age of Big Data: A Time for Big Decisions, 64 Stanford Law Review 63.Vaidhyanathan, S. (2015) The Rise of the Cryptopticon, The Hedgehog Review 17(1).<br/>},
  author       = {Larsson, Stefan},
  keyword      = {openness,privacy,data,big data,conceptual obscurity,metaphor},
  language     = {eng},
  month        = {10},
  title        = {The Image is Openness, the Practice is Data: Notes on Conceptual Obscurity and Some of Its Implications for Privacy},
  year         = {2016},
}