Privacy and Information Technology (Stanford Encyclopedia of Philosophy)
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The challenge with respect to privacy in the twenty-first century is to assure that technology is designed in such a way that it incorporates privacy requirements in the software, architecture, infrastructure, and work processes in a way that makes privacy violations unlikely to occur. Typically, this involves the use of computers and communication networks. The amount of information that can be stored or processed in an information system depends on the technology used.
The capacity of the technology has increased rapidly over the past decades, in accordance with Moore's law. This holds for storage capacity, processing capacity, and communication bandwidth.
We are now capable of storing and processing data on the exabyte level. These developments have fundamentally changed our practices of information provisioning. Even within the academic research field, current practices of writing, submitting, reviewing and publishing texts such as this one would be unthinkable without information technology support.
At the same time, many parties collate information about publications, authors, etc. This enables recommendations on which papers researchers should read, but at the same time builds a detailed profile of each individual researcher.
The rapid changes have increased the need for careful consideration of the desirability of effects. Some even speak of a digital revolution as a technological leap similar to the industrial revolution, or a digital revolution as a revolution in understanding human nature and the world, similar to the revolutions of Copernicus, Darwin and Freud Floridi In both the technical and the epistemic sense, emphasis has been put on connectivity and interaction.
Physical space has become less important, information is ubiquitous, and social relations have adapted as well. As connectivity increases access to information, it also increases the possibility for agents to act based on the new sources of information.
When these sources contain personal information, risks of harm, inequality, discrimination, and loss of autonomy easily emerge. For example, your enemies may have less difficulty finding out where you are, users may be tempted to give up privacy for perceived benefits in online environments, and employers may use online information to avoid hiring certain groups of people. Furthermore, systems rather than users may decide which information is displayed, thus confronting users only with news that matches their profiles.
Although the technology operates on a device level, information technology consists of a complex system of socio-technical practices, and its context of use forms the basis for discussing its role in changing possibilities for accessing information, and thereby impacting privacy. We will discuss some specific developments and their impact in the following sections.
The World Wide Web of today was not foreseen, and neither was the possibility of misuse of the Internet. Social network sites emerged for use within a community of people who knew each other in real life—at first, mostly in academic settings—rather than being developed for a worldwide community of users Ellison It was assumed that sharing with close friends would not cause any harm, and privacy and security only appeared on the agenda when the network grew larger.
This means that privacy concerns often had to be dealt with as add-ons rather than by-design.
Similarly, features of social network sites embedded in other sites e. Previously, whereas information would be available from the web, user data and programs would still be stored locally, preventing program vendors from having access to the data and usage statistics.
In cloud computing, both data and programs are online in the cloudand it is not always clear what the user-generated and system-generated data are used for. Moreover, as data is located elsewhere in the world, it is not even always obvious which law is applicable, and which authorities can demand access to the data.
Data gathered by online services and apps such as search engines and games are of particular concern here. Which data is used and communicated by applications browsing history, contact lists, etc. Some special features of Internet privacy social media and Big Data are discussed in the following sections.
The question is not merely about the moral reasons for limiting access to information, it is also about the moral reasons for limiting the invitations to users to submit all kinds of personal information. Users are tempted to exchange their personal data for the benefits of using services, and provide both this data and their attention as payment for the services.
Merely limiting the access to personal information does not do justice to the issues here, and the more fundamental question lies in steering the users' behavior of sharing.Security, Privacy and Ethical Issues in Information Systems
One way of limiting the temptation of users to share is requiring default privacy settings to be strict. Also, such restrictions limit the value and usability of the social network sites themselves, and may reduce positive effects of such services. A particular example of privacy-friendly defaults is the opt-in as opposed to the opt-out approach.
When the user has to take an explicit action to share data or to subscribe to a service or mailing list, the resulting effects may be more acceptable to the user.
This is not only data explicitly entered by the user, but also numerous statistics on user behavior: Data mining can be employed to extract patterns from such data, which can then be used to make decisions about the user. These may only affect the online experience advertisements shownbut, depending on which parties have access to the information, they may also impact the user in completely different contexts.
In particular, Big Data may be used in profiling the user Hildebrandtcreating patterns of typical combinations of user properties, which can then be used to predict interests and behavior.
These derivations could then in turn lead to inequality or discrimination. When a user can be assigned to a particular group, even only probabilistically, this may influence the actions taken by others.
For example, profiling could lead to refusal of insurance or a credit card, in which case profit is the main reason for discrimination. Profiling could also be used by organizations or possible future governments that have discrimination of particular groups on their political agenda, in order to find their targets and deny them access to services, or worse.
Big Data does not only emerge from Internet transactions.
Privacy and Information Technology
Similarly, data may be collected when shopping, when being recorded by surveillance cameras in public or private spaces, or when using smartcard-based public transport payment systems.
All these data could be used to profile citizens, and base decisions upon such profiles. For example, shopping data could be used to send information about healthy food habits to particular individuals, but again also for decisions on insurance. According to EU data protection law, permission is needed for processing personal data, and they can only be processed for the purpose for which they were obtained.
One particular concern could emerge from genetics data Tavani Like other data, genomics can be used to predict, and in particular could predict risks of diseases. Apart from others having access to detailed user profiles, a fundamental question here is whether the individual should know what is known about her. In general, users could be said to have a right to access any information stored about them, but in this case, there may also be a right not to know, in particular when knowledge of the data e.
With respect to previous examples, one may not want to know the patterns in one's own shopping behavior either. These devices typically contain a range of data-generating sensors, including GPS locationmovement sensors, and cameras, and may transmit the resulting data via the Internet or other networks.
One particular example concerns location data. Many mobile devices have a GPS sensor that registers the user's location, but even without a GPS sensor, approximate locations can be derived, for example by monitoring the available wireless networks. As location data links the online world to the user's physical environment, with the potential of physical harm stalking, burglary during holidays, etc.
Many of these devices also contain cameras which, when applications have access, can be used to take pictures. These can be considered sensors as well, and the data they generate may be particularly private. For sensors like cameras, it is assumed that the user is aware when they are activated, and privacy depends on such knowledge. For webcams, a light typically indicates whether the camera is on, but this light may be manipulated by malicious software. RFID radio frequency identification chips can be read from a limited distance, such that you can hold them in front of a reader rather than inserting them.
Still, such chips could be used to trace a person once it is known that he carries an item containing a chip. In the home, there are smart meters for automatically reading and sending electricity consumption, and thermostats and other devices that can be remotely controlled by the owner. Such devices again generate statistics, and these can be used for mining and profiling.
In the future, more and more household appliances will be connected, each generating its own information. Examples of these changes are biometric passports, online e-government services, voting systems, a variety of online citizen participation tools and platforms or online access to recordings of sessions of parliament and government committee meetings. Consider the case of voting in elections. Information technology may play a role in different phases in the voting process, which may have different impact on voter privacy.
Most countries have a requirement that elections are to be held by secret ballot, to prevent vote buying and coercion. In this case, the voter is supposed to keep her vote private, even if she would want to reveal it.
In polling stations, the authorities see to it that the voter keeps the vote private, but such surveillance is not possible when voting by mail or online, and it cannot even be enforced by technological means, as someone can always watch while the voter votes.
In this case, privacy is not only a right but also a duty, and information technology developments play an important role in the possibilities of the voter to fulfill this duty, as well as the possibilities of the authorities to verify this.
In a broader sense, e-democracy initiatives may change the way privacy is viewed in the political process. How can information technology itself solve privacy concerns? Whereas information technology is typically seen as the cause of privacy problems, there are also several ways in which information technology can help to solve these problems.
There are rules, guidelines or best practices that can be used for designing privacy-preserving systems. Such possibilities range from ethically-informed design methodologies to using encryption to protect personal information from unauthorized use.
It provides a set of rules and guidelines for designing a system with a certain value in mind. The Privacy by Design approach provides high-level guidelines in the form of seven principles for designing privacy-preserving systems.
Privacy by design's main point is that data protection should be central in all phases of product life cycles, from initial design to operational use and disposal. The Privacy Impact Assessment approach proposed by Clarke makes a similar point.
Note that these approaches should not only be seen as auditing approaches, but rather as a means to make privacy awareness and compliance an integral part of the organizational and engineering culture. There are also several industry guidelines that can be used to design privacy preserving IT systems. Systems that are designed with these rules and guidelines in mind should thus—in principle—be in compliance with EU privacy laws and respect the privacy of its users.
The rules and principles described above give high-level guidance for designing privacy-preserving systems, but this does not mean that if these methodologies are followed the resulting IT system will automatically be privacy friendly.
Security, privacy, and confidentiality issues on the Internet
Some design principles are rather vague and abstract. What does it mean to make a transparent design or to design for proportionality?
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- Security, privacy, and confidentiality issues on the Internet
The principles need to be interpreted and placed in a context when designing a specific system. But different people will interpret the principles differently, which will lead to different design choices, some of which will be clearly better than others.
There is also a difference between the design and the implementation of a computer system. During the implementation phase software bugs are introduced, some of which can be exploited to break the system and extract private information. How to implement bug-free computer systems remains an open research question Hoare In addition, implementation is another phase wherein choices and interpretations are made: Some specific solutions to privacy problems aim at increasing the level of awareness and consent of the user.
Communication anonymizing tools allow users to anonymously browse the web with Tor or anonymously share content Freenet. They employ a number of cryptographic techniques and security protocols in order to ensure their goal of anonymous communication.
Both systems use the property that numerous users use the system at the same time which provides k-anonymity Sweeney Depending on the system, the value of k can vary between a few hundred to hundreds of thousands. In Tor, messages are encrypted and routed along numerous different computers, thereby obscuring the original sender of the message and thus providing anonymity. The risks are internal, external, and random, and can result in data damage, falsification, loss, or leakage. It is helpful to imagine your connected system as resembling a data stream right from your keyboard to that of the recipient, and to consider the risks along the way.
Protecting local data Even before you connect, your data is at risk. Clearly you don't want your Internet-linked clinical system or home computer to be burnt, flooded, stolen, hit by lightning, damaged by third party software, or accessed by untrained staff or inappropriate people.
You will need to back it up properly, look after the backups, and periodically reconstitute the system from backups so that you know it will work if you ever need it. Ensure that your terminal or PC is left logged out when you are apart from it for a reasonable length of time. Most systems can be set to log out automatically by default under these circumstances and this makes good sense. Make sure that your screen shows information only to people who are entitled to see it.
If you connect to the Internet at work e. Doing so prevents staff from using e-mail at work to converse with friends--which not only reduces working efficiency, but also provides a means of access for viruses see below and other unwelcome material. Appropriate advice and countermeasures are detailed elsewhere [ ], enabling you to develop robust protocols to preserve the integrity of your local system. Security on a data island is simple: However, when you build bridges by creating a network link this approach on its own is inadequate.
Any potential benefits of connecting must be weighed against the risks to your own data. In a healthcare environment, this data is often of a highly sensitive nature. Even connecting a home computer may expose data, such as banking details, which you would prefer to remain private. In other words, why don't we connect only to trusted computers over trusted network links, thus extending our own trusted computing base?
Intranets are suited to smaller organizations with enforced security policies and strict personnel control--something not always attainable within a large health service. They are by nature restrictive, as security through exclusion conflicts with the potential of a network to enhance medical communications in a connected world.
Intranets may provide a false sense of security: A properly secured intranet therefore demands such things as locked rooms for terminals, physiological checks for terminal access, and armoured, pressurized cables to detect cable tapping.