Human Computer Interaction Privacy Issues - Assignment Example

 Human-Computer Interaction (HCI) Privacy Issues and Human-Computer Interaction (HCI) As a subfield of Computer Science, Human-Computer Interaction (HCI) studies how people interact via computational technologies. Thus, privacy is a key issue of the user experience with computers, new technologies and online systems. It is essential to know what to consider regarding users and their views regarding computer systems, therefore improving privacy mechanisms. This research paper examines what HCI offers to both those composing and the previously mentioned, exploring protection instruments. HCI is a broad research field in its own right. Its roots being in human aspects and the design and evaluation of “man-machine” interfaces for aircrafts together with other complex and possibly dangerous mechanical systems (Alan, Janet, Gregory, & Russell, 2003). HCI’s roots were in cognitive-oriented, single-user interfaces referred to as user interface. Since then, HCI has expanded considering a range of subareas – design methodologies, usability and usability testing, intelligent interfaces and adaptive interfaces among others. In this research, the main focus is Computer-Supported Cooperative Work (CSCW), also known as groupware. CSCW focuses on how groups of people work or interact together by incorporating computational technologies. HCI has developed in general to have in mind factors like organizational, institutional and societal affects on how computer systems are merged and how the users interact with systems. This has increasingly become essential since systems nowadays are no longer single-user, but internet-wide in their use. This research will largely view HCI in its broader context. This is concerning how HCI is not only about client interfaces but also concerning the client interaction of frameworks: how folks recognize and understand explanations and study about, and respond and acclimate to advanced advances. First we require a working definition of privacy, comparing and contrasting privacy concerns with HCI concerns before going deep into HCI research streams (Andrew & Julie, 2007). Privacy and HCI This research revolves around two somewhat amorphous terms, “privacy” and “HCI”. There has already been an introduction of HCI, together with its main concerns of enhancing ease of use and the overall user experience. On the other hand, privacy as a term is broader. Privacy is not like “HCI,” since it’s a term in everyday language, thus its meanings are rooted in broader cultural practices and understandings. For the purposes of this research, we are going to use a simple but useful definition of privacy as “the capability of an individual to have power over the terms under which their personal information is acquired and used.”Thus, privacy regards individuals’ capabilities in a particular social situation to control what they perceive to be personal data. Though seeming to be easy this definition immediately raises a number of important points: Privacy is based on information and the efficiency of individuals in having power over its flow, thus having a natural relationship with the concerns of HCI. Since systems have increasingly involved the processing of personal information, for the most part in the context of financial and governmental transactions, issues of privacy have naturally risen in prominence within the field of HCI. Privacy, concerns risk, its perception, and its management. Problems pertaining privacy often lie in the likely future consequences of the prevailing behavior, which can be regarded as either risky or safe according to the standards of judgment. Thus, privacy goes back to HCI’s origins in ergonomics and the safe operation of intricate machinery. Privacy pertains to control, trust, and its power in social situations implying ethical, political, and legal issues appealing to notions of individual independence and freedom. Important HCI Research Streams HCI comprises of several research streams which are of immediate interest to privacy evaluation and privacy mechanisms design. They include: Fundamental design considerations that is designing for the purpose of overall usability and its evaluation. Computer-Supported Cooperative work which is basically how people interact via the systems. How individuals are different in their abilities and how this aspect influences HCI. HCI role in next-generation structural design Usability Engineering Considerable interest and effort has been put in enhancing computer usability over the past twenty years. Advances of mice and GUI interfaces in the 1980s significantly broadened the market by taking away ease-of-use barriers. The ensuing investment involving HCI community has brought about broad engineering usability and methods of testing. These days it is generally known that advanced software and hardware accept usability. It is the potential users who do not incorporate features which are hard to use, and organizations are not likely to deploy hardware and software which are cumbersome to manage. Talking about these requirements is now an accepted part of most methodologies in development. It has been incorporated into process models such as prototyping, and spiral models in software engineering. In general, these acknowledge the importance to plan, build up, and test against real users so as to come up with usable systems. A good example pertaining this for a privacy mechanism is observed in a research based on implementation of privacy bird by Croner, that going through a total of five development and evaluation iterations. It is only through successive refinement that software engineers can be able to meet all of the users’ expectations. In many respects privacy mechanisms can be treated like any other platform feature which is critical, and talked about with the present usability engineering methods therefore there is no exception on privacy mechanisms (Julie, 2012). Presented below are some of the main differences between privacy and mechanisms of security, which are worth reflecting upon: We would only bringing attention to privacy thus making it an unambiguous task at any point will cause problems and although privacy is valued, it is not the user’s main task. For example, in Cranor’s studies users’ barriers in expressing their privacy preferences is discussed. Therefore the main aim with privacy is not mainly inclined in factors that measure and refine task performance, but more so to refine the invisibility of a task. Since privacy badly increases the stakes of designed features leads, it will not only to the rejection by the user and high development costs, but also to probable injury like bodily injury, in a situation where there is stalking by use of location-tracking technologies. Systems are required to answer to the environments pertaining law and regulation. However this places more demands for an increase of specialized expertise on the composition of usability engineering efforts, surpassing their pre-existing interdisciplinary competencies. Computer-Supported Cooperative Work CSCW is an essential stream of HCI research. As previously stated, HCI started by mainly looking into single-user systems and applications. Since 1980s, CSCW began as an effort to counter so as to have in mind the joint computer use. It abruptly grew to incorporate many varying aspects of harmonization and social organization. Computer-Supported Cooperative Work also grew to bring in many levels of analysis, reaching Internet-scale systems from small groups, and several forms of activity that include entertainment, chat, and work among other activities in communication. HCI privacy is, in fact, the contra positive of this research focus – this is what transpires as a result of many people sharing data, some even without knowing – therefore in its own right it becomes a research interest within CSCW. While the overall HCI began by drawing on literature pertaining cognitive psychology, CSCW’s main focus is in social interaction. Due to this, CSCW roots and assumptions are at a greater extent in micro-sociology, and to a lesser extent in cognitive Anthropology and social psychology. This information is not only essential in comprehending the current CSCW research but also critical in overall comprehension of privacy (Julie & Andrew, 2003). Individual differences Privacy concerns broadly differ in users. We have been informed from the research article which persons do not have uniform view “privacy”. People have varying forms of concerns. In this regard Culnan and Armstrong bring the argument that people’s privacy concerns are of two types. First, they are concerned over unauthorized persons being able to gain access to their personal data due to security breaches or absence of controls which are within. Second, individuals have concerns regarding the risk of secondary use of data. It includes the combination of personal data to come up with a profile It also includes sharing data with persons who were not part of the main transaction. Smith, Milberg, and Burke also came up with two concerns: These are I) People are generally anxious about collection of personal data, and ii) people also have concerns over their inability to fix any errors. These people are grouped as privacy fundamentalists, marginally concerned and there is the pragmatic majority. The estimates of these privacy concern groups’ differ in sizes, and seem to change as time goes by. In a research by Westin, he came up with the population estimates shown in the Table below, (N/B Westin 2003 was carried out after 9/11). Table: population estimates, by privacy cluster Privacy marginally pragmatic Fundamentalists concerned majority Westin 1995- 25% 20% 55% Westin 2000- 25% 12% 63% Westin 2003 - 37% 11% 52% Based on this variance regarding how users perceive privacy, the big question is how can one come up with a design for these differences regarding various aspects of the users? There is a HCI research theme which focuses on individual differences. As literatures, cognitive and experimental psychologies have for the most part ignored differences among subjects, being regarded to be part of the error in the experiment. On the part of commercial computer interface designers differences among users is yet to be a major concern. Nevertheless, HCI's custom pertaining man-machine human factors has led HCI to be glad about how people varied. This was found to be a critical human factor: When building airplane cockpits or even office chairs, variables between individuals are critical for usability, safety and comfort. It is this concern from human factors that led over to user interfaces and research on HCI (Matt & Gary, 2006). Methods to allowing user differences as described in a research by Egan are required to be of considerable interest to those building or researching mechanisms of privacy. The approaches he described still are the main methods in HCI research and preparation for dealing with diversity, and have direct relevance to mechanisms of privacy. These approaches are: -Building better interfaces. As stated by Egan, "This approach is the same as the standard human-interface design; the difference is its shape is based on a concern for the differences among users. (p. 559)." For systems where the users are not expert and where they will stay as "permanent casual users" this design is important particularly for them (Yvonne & Helen, 2011). Clustering users In this approach accommodating user variance by locating user clusters sets then interacting with them via the classifications is advocated. There are many different ways of doing this. Egan largely viewed it as a question of coming up with different interfaces. Also one could have different interaction patterns incorporating different user classes. These varying clusters of users can be treated differently. As stated by Egan, "Similar actions arising from two differing users can be treated very differently given that the user’s prototypes have been differently classified. Recently, the aspect of clustering in privacy preferences was explored by Olson, Grudin, and Horvitz. Though still preliminary, their work proposed that there are main classes of data and recipients. Even though generally people vary, these grouping of data and recipients can remain relatively constant (Yvonne & Helen, 2011). Adaptive systems These systems help users by preventing user errors. Ackerman and Cranor used critics in assisting users with their web privacy issues. For example, this Privacy Critics system notified the user when he/she might be infringing their individual privacy or during problematic times in the sites. Automated "Mastery Learning" There is a large amount of studies pertaining documentation and training based on HCI. Use of training which is automated like tutors, to assist users in gaining the skills which are necessary in order to effectively use the systems was promoted by Egan. There are broad studies which have identified the use of training in order to ease the progress of the changing and expanding the mental representation of the system users' and likely tasks. So far, no such system of tutoring or training has been built for privacy, although it is quite clear that one would be very useful (Yvonne & Helen, 2011). This final approach comes from the previous two approaches: Tailor cable systems Having the users to either tailor or modify the systems in such a way that it fits their needs is another approach. Customizing mostly refers to altering the exterior interfaces of a system and tailoring more often than not refers to deeper alterations to the applications functionality. The designer brings in large amounts of functionality. In this approach, most of these functionalities are those which not any given user will use. Contrary to robust interfaces, which present interfaces which are based on “one size fits all” tailor cable systems have room for users to select and choose their desired functionality. In summary, HCI has considerable experience in handling particularized differences. Through a singular approach which is appropriate to the mechanisms in privacy, it has been known to be important to cluster users, then to existing different interfaces or functionality to those users (Yvonne & Helen, 2011). Another approach is to allow users to tailor the systems according to their individual needs; nevertheless, this will over and over again require users to obtain tailoring help from others. Finally, two intellectual augmentations have been discovered to be of great importance in the HCI literature – mechanisms in helping users avert errors as well as mechanisms to assist in tutoring the users regarding this case of privacy. There is a flip side which is essential to keep in mind regarding the thought of coming up with designs for singular differences. This is the probability of intensifying power imbalances and reducing the level of fairness. A system could decide that a user is highly disturbed and erect barriers to prevent use by classifying the individual as a fundamentalist in privacy. We can also observe that unscrupulous designers can put the users in segment so as to find beginners or those who are marginally concerned, not to give assistance, but for simply taking advantage of. These problems are not confined to privacy; since any system which discriminates among users bears itself to the notion pertaining to the fairness of this discrimination is fair. While it is important to recognize and protect from actual effects or perception, this does not mean we should keep away from an individual differences approach but rather it should only to be used with caution (Yvonne & Helen, 2011). Ubiquitous Computing (Ubicomp) Currently there is a wide interest in both aspects of HCI which is ubiquitous and pervasive HCI computing. It is possible for one to have several sensors and other computational devices spread out either through a room a building, or other environment in these architectures. People would have the option of dressed in them, carrying them, or may even have them embedded. There is an intersect in research pertaining HCI and ubicomp even though they are not similar aspects of computer science. Particular, HCI researchers mainly focus on applications based on augmented reality, sensor-based entertainment like geogames, and interfaces which are user-centered into ubicomp rooms. There are noteworthy privacy concerns regarding ubiquitous computing (ubicomp) environments. It is obvious that location sensors can trace persons across an environment. By use of sensor aggregation one is able to tell a large amount regarding what a person might be doing (Yvonne & Helen, 2011). Big quantities of data which seem personal can be gathered without notice or the permission of the environment's users. Several studies recently have explicitly looked into ubicomp privacy environments. Finally, the system issues have been examined by Hong and Landay. Their Confab system gives a middleware layer upon which ubicomp applications can be built. Confab gives ample room for users to publish and offer services to request data which have strong privacy controls through a combination of boards and dataflow structural design. Users are able to put discretion tags on all the data that have control over the entrée contained by Confab info space and also give hints regarding how the data are to be put to use outside the Confab system. Extension mechanisms are included in Confab, currently on location awareness. Research on Ubicomp is just beginning, and as time goes, we expect this to provide considerable feedback regarding the overall privacy mechanisms (Yvonne & Helen, 2011). Conclusions In this research, a range of HCI studies believed that is of help to those designing privacy mechanisms has been studied. They are usability evaluations and requirements gathering, which includes the large range of HCI methods for integrating users and their view points in the process? There are collaborative views of information and activity, including many systems and applications as well as a range of social analyses which uphold a detailed and situated examination of privacy; handling multiplicity and difference among users, which includes the HCI approaches to this problem; and, recent methods regarding recent computational environments which includes studies and systems for persistent environments (Yvonne & Helen, 2011). In passing we note that HCI could profit by increasing their level of considering privacy. A one-way direction of research should be avoided since cross-cultural studies of privacy are able to inform the emerging interest in HCI in cross-cultural interfaces and coordination. An increased knowledge on the multiplicity and intricacy of user preferences, and possible clustering’s, is offering new impetus for HCI research regarding individual differences. Also we should consider visualizations and intelligent tutoring systems for privacy, in a series of applications and tasks can bring forth new emphases in HCI. I hope that the work on HCI develops to the level of considering these and other privacy needs aspects. For the foreseeable future in digital environments privacy will likely remain a serious issue. This is because it directly engages user control aspects and power, which is pivotal to the concerns of HCI. I wholly expect the above researched areas of interest – HCI and privacy – to continue being closely linked in interest and need (Yvonne & Helen, 2011). References Alan, D., Janet, F., Gregory, A., & Russell, B., 2003. Human–Computer Interaction. London: Prentice Hall. Andrew, S., & Julie, A. J., 2007. Human-Computer Interaction Handbook. London: CRC Press. Julie, A. J., 2012. Human-Computer Interaction Handbook. London: CRC Press. Julie, A. J., & Andrew, S., 2003. Human-Computer Interaction Handbook. Mahwah: Lawrence Erlbaum & Associates. Matt, J., & Gary, M., 2006. Mobile Interaction Design. New York: John Wiley and Sons Ltd. Yvonne, R., & Helen, S., 2011. Interaction Design: Beyond Human–Computer Interaction. New York: John Wiley & Sons Ltd. Read More