Dataveillance: Difference between revisions
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= Dataveillance = |
= Dataveillance = |
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Dataveillance is the surveillance and collection of online data as well as metadata.<ref name=":2">{{Cite journal|last=van Dijck|first=José|year=2014|title=Datafication, dadaism and dataveillance: Big Data between scientific paradigm and ideology|journal=Surveillance & Society|volume=12|issue=2|issn=1477-7487}}</ref> Dataveillance is concerned with the continuous monitoring of users' communications and actions across various platforms.<ref name=":0">{{Cite journal|last=Clarke|first=Roger A.|year=1988|title=Information Technology and Dataveillance|journal=Communications of the ACM|volume=31|pages=498 - 511}}</ref> For instance, dataveillance refers to the monitoring of data produced by credit card transactions, GPS coordinates, emails, [[Social network|social networks]], etc. Using [[digital media]] often leaves traces of data and creates a [[digital footprint]] of our activity.<ref name=":4">{{Cite journal|last=Selwyn|first=Neil|year=2014|title=Data entry: towards the critical study of digital data and education|url=http://www.tandfonline.com/doi/abs/10.1080/17439884.2014.921628|journal=Learning, Media and Technology|publisher=Routledge|volume=40|issue=1|pages=64-82|doi=10.1080/17439884.2014.921628|via=}}</ref> This type of surveillance is not often known and happens discreetly.<ref>{{Cite journal|last=Clarke|first=Roger|year=1996|title=Privacy and dataveillance, and organizational strategy|journal=Proceedings of the IS Audit & Control Associate Conference|volume=}}</ref> Unlike [[sousveillance]], where individuals willingly surveillance their activity, dataveillance is more discrete and unknown. Dataveillance may involve the surveillance of groups of individuals. There exist three types of dataveillance: ''personal dataveillance, mass dataveillance,'' and ''facilitiative mechanisms''. <ref name=":0" /> |
Dataveillance is the surveillance and collection of online data as well as metadata.<ref name=":2">{{Cite journal|last=van Dijck|first=José|year=2014|title=Datafication, dadaism and dataveillance: Big Data between scientific paradigm and ideology|journal=Surveillance & Society|volume=12|issue=2|issn=1477-7487}}</ref> Dataveillance is concerned with the continuous monitoring of users' communications and actions across various platforms.<ref name=":0">{{Cite journal|last=Clarke|first=Roger A.|year=1988|title=Information Technology and Dataveillance|journal=Communications of the ACM|volume=31|pages=498 - 511}}</ref> For instance, dataveillance refers to the monitoring of data produced by credit card transactions, GPS coordinates, emails, [[Social network|social networks]], etc. Using [[digital media]] often leaves traces of data and creates a [[digital footprint]] of our activity.<ref name=":4">{{Cite journal|last=Selwyn|first=Neil|year=2014|title=Data entry: towards the critical study of digital data and education|url=http://www.tandfonline.com/doi/abs/10.1080/17439884.2014.921628|journal=Learning, Media and Technology|publisher=Routledge|volume=40|issue=1|pages=64-82|doi=10.1080/17439884.2014.921628|via=}}</ref> This type of surveillance is not often known and happens discreetly.<ref>{{Cite journal|last=Clarke|first=Roger|year=1996|title=Privacy and dataveillance, and organizational strategy|journal=Proceedings of the IS Audit & Control Associate Conference|volume=}}</ref> Unlike [[sousveillance]], where individuals willingly surveillance their activity, dataveillance is more discrete and unknown. Dataveillance may involve the surveillance of groups of individuals. There exist three types of dataveillance: ''personal dataveillance, mass dataveillance,'' and ''facilitiative mechanisms''. <ref name=":0" /> |
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One of the major issues with dataveillance is the removal of a human actors who are replaced by computer system that oversee data and construct a representation from it.<ref name=":4" /> The removal of human actors can allow for false representations to be created based on the data collected. This is largely due to the lack of logical reasoning or understanding of the data. Computer systems can only use the data they have, which is not necessarily an accurate depiction of individuals or their situations. Dataveillance is highly automated through computer systems which observe our interactions and activities. High automated systems and technology eliminates human understanding of our activities. |
One of the major issues with dataveillance is the removal of a human actors who are replaced by computer system that oversee data and construct a representation from it.<ref name=":4" /> The removal of human actors can allow for false representations to be created based on the data collected. This is largely due to the lack of logical reasoning or understanding of the data. Computer systems can only use the data they have, which is not necessarily an accurate depiction of individuals or their situations. Dataveillance is highly automated through computer systems which observe our interactions and activities. High automated systems and technology eliminates human understanding of our activities. |
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== Resistance to Dataveillance == |
== Resistance to Dataveillance == |
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Revision as of 01:17, 1 December 2016
Dataveillance
Dataveillance is the surveillance and collection of online data as well as metadata.[1] Dataveillance is concerned with the continuous monitoring of users' communications and actions across various platforms.[2] For instance, dataveillance refers to the monitoring of data produced by credit card transactions, GPS coordinates, emails, social networks, etc. Using digital media often leaves traces of data and creates a digital footprint of our activity.[3] This type of surveillance is not often known and happens discreetly.[4] Unlike sousveillance, where individuals willingly surveillance their activity, dataveillance is more discrete and unknown. Dataveillance may involve the surveillance of groups of individuals. There exist three types of dataveillance: personal dataveillance, mass dataveillance, and facilitiative mechanisms. [2]
Unlike computer and network surveillance, which collects data from computer networks and hard drives, dataveillance collects data (and metadata) online through social networks and various platforms. Dataveillance is not to be confused with electronic surveillance. Electronic surveillance refers to the surveillance of oral and audio systems such as wire tapping.[2] Additionally, electronic surveillance depends on having suspects already presumed before surveillance can occur.[5] On the other hand, dataveillance can use data to identify an individual or several suspect(s).[5] The suspects that being referred to are people who leave data behind with their online activity.
Types of Dataveillance
The types of dataveillance are separated by the way data is collected, as well as the number of being individuals associated with it.
Personal Dataveillance: Personal dataveillance refers to the collection of a person's personal data. Personal dataveillance can occur when an individual's data causes a suspicion or has attracted attention in some way.[2] Personal data can include information such as birth date, address, social security (or social insurance) number, as well as other unique identifiers.
Mass Dataveillance: Refers to the collection of data related to the
Benefits and Concerns
Pros
There are many concerns and benefits associated with dataveillance. Dataveillance can be useful for collecting and verifying data in ways that are beneficial. For instance, personal dataveillance can be utilized by financial institutions to track frantulent purchases on credit card accounts.[2] This has the potential to prevent and regulate fradulent financial claims and resolve the issue.
Dataveillance has also been useful in assessing security threats associated with terrorism. Authorities have utilized dataveillance to help them understand and predict potential terrorist or criminal threats.[6] Dataveillance is very important to the concept of predictive policing. Since predictive policing requires a great deal of data to operate effectively and dataveillance can do just that. Predictive policing allows police to intervene in potential crimes to create safer communities and better understand potential threats.
Businesses also rely on dataveillance to help them understand the online activity for potential clients by tracking their online activity.[7] By tracking their online activity through cookies, as well as various other methods, businesses are able to better understand what sort of advertisements work with their existing and potential clients.[7] While making online transactions users often give away their information freely which is later used by the company for corporate or private interests.[8] For businesses this information can help boost sales and attract attention towards their products to help generate revenue.
Cons
On the other hand, there are many concerns that arise with dataveillance. Dataveillance assumes that our technologies and data are a true reflection of ourselves.[2] This presents itself as a potential concern given that it can be believed that our data is true to our own actions and behaviours .[6] This becomes a critical concern when associated with the surveillance of criminal suspects and terrorist groups. Authorities who monitor these suspects would then assume that the data they have collected reflects their actions.[6] This helps to understand potential or past threats for criminals as well. [6]
There is also the lack of transparency and privacy with companies who collect and share their user's data.[2] This is a critical issue with both the trust and belief of the data and its uses.[1] Many social networks have argued that their user's forfeit part of their privacy in order to provide their service for free.[1] Several of these companies choose not to fully disclose what data is collected and who it is shared with. When data is volunteered to companies it is difficult to know what companies have gain data about you and your online activity.[6] Much of an individual's data is shared with websites and social networks in order to provide a more customized marketing experience. Many of those social networks may share your information with intelligent agencies and authorities without a user's knowledge.[1] Since the recent scandal involving Edward Snowden and National Security Agency it has been revealed that authorities may have access to more data from various devices and platforms.[1] It has become very difficult to know what will happen with your data or what specifically has been collected. It is also important to recognize that while online users are worried about their information many of those same worries are not always applied to their activities or behavoir.[9] With social networks collecting a large amount of personal data such as birth date, legal name, sex, and photos there is an issue of dataveillance compromising confidentiality. Ultimately, dataveillance can comprise online anonymity.
Despite dataveillance compromising anonymity, anonymity itself presents a crucial issue. Online criminals who steal users' data and information may exploit it for their own gain. Tactics used by online users to conceal their identity make it difficult for others to track the criminal behavior and lay claim to those responsible. Having unique identifiers such as IP addresses allows for the identification of users actions, which are often used to track illegal online activity such as piracy.
While dataveillance may help businesses market their products to existing and potential clients there are concerns over how and who has access to customer data. When visiting a business's website often install cookies onto users' devices. Cookies have been a new way for businesses to obtain data on potential customers since it allows them to track their online activities .[7] Companies may also look to sell information they have collected on their clients to third parties.[7] Since clients are not notified about these transactions it becomes difficult to know where your data has been sold. Furthermore, since dataveillance is discrete clients are very unlikely to know the exact nature of the data that has been either collected or sold.[7] Education on tracking tools such as cookies presents a critical issue. If businesses or online services are unwilling to define cookies or educate their users as to why they used many may unwillingly accept them.[10]
The issue stemming from companies and other agencies which collect personal data and information is that they have now engaged in the practices of data brokering. Data brokers, such as Acxiom, collect users; information and are known for often selling that information to third parties. While companies may disclose that they are collecting data or online activity from their users it is usually not comprehensible by everyday users.[8] It is difficult for everyday people to spot this disclosure since it is hidden by jargon and writing most often understood by lawyers.[8] This is now becoming a new source of revenue for companies.
One of the major issues with dataveillance is the removal of a human actors who are replaced by computer system that oversee data and construct a representation from it.[3] The removal of human actors can allow for false representations to be created based on the data collected. This is largely due to the lack of logical reasoning or understanding of the data. Computer systems can only use the data they have, which is not necessarily an accurate depiction of individuals or their situations. Dataveillance is highly automated through computer systems which observe our interactions and activities. High automated systems and technology eliminates human understanding of our activities.
Resistance to Dataveillance
With such an increase in data collection and the various concerns associated with it, many individuals are now attempting to reduce the amount of data collected about them. Privacy Enhancing Technologies, otherwise known as PETS, have been utilized by individuals to reduce data collection and decrease the possibility for dataveillance.[11] PETs, such as adblocker, attempt to prevent other actors from collecting users data. In the case of adblock, the web browser extension is able to prevent the display of advertisements, which disrupts data collection about users online interactions.[11] For businesses that may limit their opportunity to provide online users with tailored advertisements.
Recently, the European Union demanded companies to indicate that their website uses cookies.[10] This law has become basic practice by many online services and companies, however, education on tracking tools with the general public differs and therefor can prevent the effectiveness of this sort of ruling.[10] However, many companies are launching new PETs initiatives within their products. For example, Mozilla's Firefox Focus in pre-enabled with customizable privacy features, which allows for better online privacy.[12] A few of the tools featured in Firefox Focus are also mimicked by other web browsers such as Apple's Safari. Some of the various tools featured with these web browsers are the capabilities to block ads and remove cookie data and history. Private browsing, otherwise known as Incognito for Google Chrome users, allows users to browse the web with having their history or cookies saved. These tools help to curve dataveillance by disrupting the collection and analysis of users' data. While several other web browsers may not pre-enable these PETs within their software users can download the same tools, like adblocker, through their browser's web store such as the Google Chrome Web Store. Many of these extensions help enable better privacy tools.
Social networks, such as Facebook, have introduced new security measures to help users protect their online data. Users are able to block their posts and other information on their account other than their name and profile picture. While this doesn't necessarily prevent data tracking these tools have helped to keep users data more private and less accessible for online criminals to exploit.
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- ^ a b c d e van Dijck, José (2014). "Datafication, dadaism and dataveillance: Big Data between scientific paradigm and ideology". Surveillance & Society. 12 (2). ISSN 1477-7487.
- ^ a b c d e f g Clarke, Roger A. (1988). "Information Technology and Dataveillance". Communications of the ACM. 31: 498–511.
- ^ a b Selwyn, Neil (2014). "Data entry: towards the critical study of digital data and education". Learning, Media and Technology. 40 (1). Routledge: 64–82. doi:10.1080/17439884.2014.921628.
- ^ Clarke, Roger (1996). "Privacy and dataveillance, and organizational strategy". Proceedings of the IS Audit & Control Associate Conference.
- ^ a b Frikken, Keith B.; Atallah, Mikhail J. (2003). "Privacy preserving electronic surveillance". Proceedings of the 2003 ACM workshop on Privacy in the electronic society.
- ^ a b c d e Amoore, Louise; Goede, Marieke De. "Governance, risk and dataveillance in the war on terror". Crime, Law and Social Change. 43 (2–3): 149–173. doi:10.1007/s10611-005-1717-8. ISSN 0925-4994.
- ^ a b c d e Ashworth, Laurence; Free, Clinton (2006-08-26). "Marketing Dataveillance and Digital Privacy: Using Theories of Justice to Understand Consumers' Online Privacy Concerns". Journal of Business Ethics. 67 (2): 107–123. doi:10.1007/s10551-006-9007-7. ISSN 0167-4544.
- ^ a b c Tsesis, Alexander (2014). "The Right to Erasure: Privacy, Data Brokers, and the Indefinite Retention of Data". Scientific American. 49: 433–484 – via HeinOnline.
- ^ Ragnedda, Massimo (2015-01-01). "Electronic surveillance on Social Networking Sites. A critical case study of the usage of SNSs by students in Sassari, Italy". Studies in Communication Sciences. 15 (2): 221–228. doi:10.1016/j.scoms.2015.05.001.
- ^ a b c Gomer, R.C. (2014). The Grey Web: Dataveillance Vision Fulfilled Through the Evolving Web.
- ^ a b Clarke, Roger (2003). "Dataveillance - 15 years on". Privacy Issues Forum. 28.
- ^ Peers, Nick. "Firefox Focus 2.0 - Internet Tools - Downloads". PC Advisor. Retrieved 2016-11-30.