Online research in philosophy

: Widespread collection and use of identifiable information can promote social goods while, at the same time, infringing on personal privacy. Information systems are developing within the context of a fundamental transformation in the organization, delivery, and financing of health care. Changes in the health care system include rapid development of employer-sponsored health coverage, managed care organizations, and integrated delivery systems. These complex, multifaceted arrangements for delivering and paying for health care require ever-more-sophisticated information systems that facilitate extensive sharing of personal data. Systemic flows of sensitive health information occur both vertically and horizontally among employers, hospitals, insurers, laboratories, and suppliers. Beyond this complex web of vertical and horizontal sharing are the multiple demands for information management, quality assurance, research, governmental regulation, and public health. Theoretical problems exist with the law and ethics of informational privacy. The traditional method of exercising control over personal health information is through informed consent. Informed consent, however, within a modern health information infrastructure becomes highly complex. In this kind of environment, the doctrine of informed consent is flawed and does not provide sufficient control over personal information to assure adequate protection of privacy.

Identity governance is an emerging concept for fine-grained conditional disclosure of identity information and enforcement of corresponding data handling policies. Although numerous technologies underlying identity management have been developed, people still have difficulty obtaining a clear picture of how their identity information is maintained, used, and propagated. An identity management framework is described for tracking the history of how a person’s identity information is handled after it is transferred across domains of control and for enforcing meta-policies related to managing identity information distributed over the Internet. With this framework, organizations that manage identity information can improve accountability for their data practices and thereby increase their trustworthiness. The framework also enables users to control and optimize the propagation of their identity information in a user-centric manner.

Three of the major issues in information ethics – intellectual property, speech regulation, and privacy – concern the morality of restricting peoples access to certain information. Consequently, policies in these areas have a significant impact on the amount and types of knowledge that people acquire. As a result, epistemic considerations are critical to the ethics of information policy decisions (cf. Mill, 1978 [1859]). The fact that information ethics is a part of the philosophy of information highlights this important connection with epistemology. In this paper, I illustrate how a value-theoretic approach to epistemology can help to clarify these major issues in information ethics. However, I also identify several open questions about epistemic values that need to be answered before we will be able to evaluate the epistemic consequences of many information policies.

One of the basic principles of the general definition of information is its rejection of dataless information, which is reflected in its endorsement of an ontological neutrality. In general, this principles states that “there can be no information without physical implementation” (Floridi (2005)). Though this is standardly considered a commonsensical assumption, many questions arise with regard to its generalised application. In this paper a combined logic for data and information is elaborated, and specifically used to investigate the consequences of restricted and unrestricted data-implementation-principles.

Privacy concerns involving data mining are examined in terms of four questions: (1) What exactly is data mining? (2) How does data mining raise concerns for personal privacy? (3) How do privacy concerns raised by data mining differ from those concerns introduced by traditional information-retrieval techniques in computer databases? (4) How do privacy concerns raised by mining personal data from the Internet differ from those concerns introduced by mining such data from data warehouses? It is argued that the practice of using data-mining techniques, whether on the Internet or in data warehouses, to gain information about persons raises privacy concerns that (a) go beyond concerns introduced in traditional information-retrieval techniques in computer databases and (b) are not covered by present data-protection guidelines and privacy laws.

The proliferation of electronic databases is raising someimportant questions about how the evolving access to new or previously inaccessible information is likely to change the practice of law. This paper discusses TRAC, an interesting electronic source of previously inaccessible information that is currently used by members of the media, public interest groups, lawyers, and the federal government. Summaries, reports, and snapshots of TRAC's data can be accessed through a series of public web sites. TRAC's subscription service allows users access to the data warehouse and data mining tools (see http://tracfed.syr.edu/info.html for more information). Additionally the paper examines how AI can be employed to assist for the legal profession in utilization of TRAC's data. Finally, it speculates about how TRAC and other new electronic data sources may impact the practice of law.

Discusses the public interest in the free flow of information.

James Rachels’ seminal paper “ Why Privacy Is Important ” (1975) remains one of the most influential statements on the topic. It offers a general theory that explains why privacy is important in relation to mundane personal information and situations. According to the theory, privacy is important because it allows us to selectively disclose personal information and to engage in behaviors appropriate to and necessary for creating and maintaining diverse personal relationships. Without this control, it is implied, the diversity of relationships would diminish; relationships would “flatten out”, we might say. The aspect of the paper that addresses information flows (what I refer to as his information privacy theory) has been of particular interest to computer information privacy theorists. Despite its continued importance to computer privacy theorists, however, the information privacy theory appears to be contradicted by recent developments in computing. In particular, since the publication of Rachels’ paper we have seen an extensive amount of personal information collected. Further, recent developments in computing falling under the heading of social computing have brought about a new wave of personal information creation and collection. This paper will reassess and resituate Rachels’ information privacy theory in light of these developments. I will argue that the increasing collection of personal data will not flatten relationships as the information privacy theory predicts because such data lack contextual factors important to Rachels’ general theory. The paper will conclude by pointing to some areas where Rachels’ general theory and where his information privacy theory will continue to be relevant.

There is no consensus yet on the definition of semantic information. This paper contributes to the current debate by criticising and revising the Standard Definition of semantic Information (SDI) as meaningful data, in favour of the Dretske-Grice approach: meaningful and well-formed data constitute semantic information only if they also qualify as contingently truthful. After a brief introduction, SDI is criticised for providing necessary but insufficient conditions for the definition of semantic information. SDI is incorrect because truth-values do not supervene on semantic information, and misinformation (that is, false semantic information) is not a type of semantic information, but pseudo-information, that is not semantic information at all. This is shown by arguing that none of the reasons for interpreting misinformation as a type of semantic information is convincing, whilst there are compelling reasons to treat it as pseudo-information. As a consequence, SDI is revised to include a necessary truth-condition. The last section summarises the main results of the paper and indicates some interesting areas of application of the revised definition.

Computers and new information technologies have greatly increased the power of surveillance by government and large corporate entities. The state is a repository of a growing array of data bases that provide it with information on its citizens. Corporations also now possess increasing power to accumulate information on potential consumers. This power to collect information is significant and can be instrumental in securing loans, insurance, and credit; increases the power of law enforcement agencies; makes possible surveillance of workers and the workplace by managers; and provides information on consumer habits and preferences that can be useful to the marketing and promotion of consumer goods. The intensifying computerization of information raises important questions concerning privacy and individual rights in the current information revolution, such as: who collects what kind of information, what is done with this information, and what rights do individuals have concerning privacy and the circulation of information about them?