Online research in philosophy

Luciano Floridi (2003) offers a theory of information as a strongly semantic notion, according to which information encapsulates truth, thereby making truth a necessary condition for a sentence to qualify as information. While Floridi provides an impressive development of this position, the aspects of his approach of greatest philosophical significance are its foundations rather than its formalization. He rejects the conception of information as meaningful data, which entails at least three theses – that information can be false; that tautologies are information; and, that It is true that ... is non-redundant – appear to be defensible. This inquiry offers various logical, epistemic, and ordinary-language grounds to demonstrate that an account of his kind is too narrow to be true and that its adoption would hopelessly obscure crucial differences between information, misinformation, and disinformation.

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.

Information and representation are thought to be intimately related. Representation, in fact, is commonly considered to be a special kind of information. It must be a _special_ kind, because otherwise all of the myriad instances of informational relationships in the universe would be representational -- some restrictions must be placed on informational relationships in order to refine the vast set into those that are truly representational. I will argue that information in this general sense is important to genuine agents, but that it is a blind alley with regard to the attempt to understand representation. On the other hand, I will also argue that a different, quite non-standard, form of information is central to genuine representation. First I turn to some of the reasons why information as usually considered is the wrong category for understanding representation; second to an alternative model of representation -- one that is naturally emergent in autonomous agents, and that does involve information, but not in any standard form; and third I return to standard notions of informational relationships and show what they are in fact useful for.

This paper investigates the ethical issues surrounding the concept of Internet neutrality focusing specifically on the correlation between neutrality and fairness. Moving from an analysis of the many available definitions of Internet neutrality and the heterogeneity of the Internet infrastructure, the common assumption that a neutral Internet is also a fair Internet is challenged. It is argued that a properly neutral Internet supports undesirable situations in which few users can exhaust the majority of the available resources or in which specific types of applications and services cannot be developed or properly deployed. The solution offered to these shortcomings is based on (1) an environmental approach to the Internet, (2) the four guiding principles of Floridi’s Information Ethics and (3) a principle called ‘Information Diversity’. The paper is divided into six sections. Section 1 briefly presents the debate concerning the concepts of network and Internet neutrality. Section 2 poses a general and unifying definition of Internet neutrality based on the critical assessment of several domain-specific approaches to the problem of neutrality. Section 3 is dedicated to the analysis of the relationship between Internet neutrality and the ethical principle of fairness. Section 4 introduces Floridi’s Information Ethics, the definition of Information Diversity and an analysis of how they can be used to address the limitations of Internet neutrality. Section 5 summarises the ethics of Internet neutrality and Information Diversity defining their relationship. Section 6 reviews the arguments presented in the paper clarifying the foundational role played by Information Diversity and Information Ethics in Internet policy-making activity.

The distinction between the modeling of information and the modeling of data in the creation of automated systems has historically been important because the development tools available to programmers have been wedded to machine oriented data types and processes. However, advances in software engineering, particularly the move toward data abstraction in software design, allow activities reasonably described as information modeling to be performed in the software creation process. An examination of the evolution of programming languages and development of general programming paradigms, including object-oriented design and implementation, suggests that while data modeling will necessarily continue to be a programmer's concern, more and more of the programming process itself is coming to be characterized by information modeling activities.

The theories of information ethics articulated by Luciano Floridi and his collaborators have clear implications for law. Information law, including the law of privacy and of intellectual property, is especially likely to benefit from a coherent and comprehensive theory of information ethics. This article illustrates how information ethics might apply to legal doctrine, by examining legal questions related to the ownership and control of the personal data representations, including photographs, game avatars, and consumer profiles, that have become ubiquitous with the proliferation of information and communication technologies. Recent controversy over the control of player performance statistics in “fantasy” sports leagues provides a limiting case for the analysis. Such data representations will in many instances constitute the kind of personal data that information ethics asserts constitutes an information entity. Legal doctrine in some instances proves sympathetic to such an assertion, but remains largely inchoate as to which data might constitute a given information entity in a given instance. Neither is information ethics, in its current state of development, entirely helpful in answering this critical question. While information ethics holds some promise to bring coherence to this area of the law, further work articulating a richer theory of information ethics will be necessary before it can do so.

This paper addresses the problem of upgrading functional information to knowledge. Functional information is defined as syntactically well-formed, meaningful and collectively opaque data. Its use in the formal epistemology of information theories is crucial to solve the debate on the veridical nature of information, and it represents the companion notion to standard strongly semantic information, defined as well-formed, meaningful and true data. The formal framework, on which the definitions are based, uses a contextual version of the verificationist principle of truth in order to connect functional to semantic information, avoiding Gettierization and decoupling from true informational contents. The upgrade operation from functional information uses the machinery of epistemic modalities in order to add data localization and accessibility as its main properties. We show in this way the conceptual worthiness of this notion for issues in contemporary epistemology debates, such as the explanation of knowledge process acquisition from information retrieval systems, and open data repositories.

Ethical problems are related to computer data bases, containing data on individuals and groups of persons, as well as to computer knowledge bases, containing general rules and elements of expert systems.In the present essay the following conclusions are made regarding computer data bases: privacy, security, and confidentiality of medical computer data bases should be ensured. This duty should rest with physicians in hospitals. The principle of informed consent should be applied to gathering information which is to be stored and processed by computers. Information stored in computer data bases should not be used for purposes for which the subjects (patients as well as personnel) have not given their consent. In order to decrease the possibility of misuses of medical data bases containing information on individuals, these registers should not be linked to other central data bases.

The paper investigates the ethics of information transparency (henceforth transparency). It argues that transparency is not an ethical principle in itself but a pro-ethical condition for enabling or impairing other ethical practices or principles. A new definition of transparency is offered in order to take into account the dynamics of information production and the differences between data and information. It is then argued that the proposed definition provides a better understanding of what sort of information should be disclosed and what sort of information should be used in order to implement and make effective the ethical practices and principles to which an organisation is committed. The concepts of “heterogeneous organisation” and “autonomous computational artefact” are further defined in order to clarify the ethical implications of the technology used in implementing information transparency. It is argued that explicit ethical designs, which describe how ethical principles are embedded into the practice of software design, would represent valuable information that could be disclosed by organisations in order to support their ethical standing.

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.