Timpson’s deflationary view of information is an innovative and well articulated view that had a great impact on the philosophy of physics community. However, recently some of the arguments supporting the deflationist view have been critically reviewed. The aim of this paper is to retain the general idea behind Timpson’s proposal, but replacing the conflictive elements used to support his thesis with new argumentative resources based on the notion of manipulability.

Information is often modelled as a set of relevant possibilities, treated as logically possible worlds. However, this has the unintuitive consequence that the logical consequences of an agent's information cannot be informative for that agent. There are many scenarios in which such consequences are clearly informative for the agent in question. Attempts to weaken the logic underlying each possible world are misguided. Instead, I provide a genuinely psychological notion of epistemic possibility and show how it can be captured in a (...) formal model, which I call a fan. I then show how to use fans to build formal models of being informed, as well as knowledge, belief and information update. (shrink)

In this short paper, we show that a popular view in information science, information-as-thing, fails to account for a common example of information that seems physical. We then demonstrate how the distinction between types and tokens, recently used to analyse Shannon information, can account for this same example by viewing information as abstract, and discuss existing definitions of information that are consistent with this approach. -/- Dans ce court article nous montrons qu'une vision populaire en sciences de l'information, l'information en (...) tant qu’une chose, échoue à rendre compte d'un exemple commun d'information qui semble physique. Nous démontrons ensuite comment la distinction type/token, utilisée récemment pour analyser l'information de Shannon, peut rendre compte de ce même exemple en considérant l'information comme abstraite, et nous discutons des définitions existantes de l’information qui sont compatibles avec cette approche. (shrink)

In this talk I present the main results from Anta (2021), namely, that the theoretical division between Boltzmannian and Gibbsian statistical mechanics should be understood as a separation in the epistemic capabilities of this physical discipline. In particular, while from the Boltzmannian framework one can generate powerful explanations of thermal processes by appealing to their microdynamics, from the Gibbsian framework one can predict observable values in a computationally effective way. Finally, I argue that this statistical mechanical schism contradicts the Hempelian (...) (1958) thesis that the predictive power of a scientific theory is directly proportional to its explanatory potential, and vice versa. (shrink)

One of the open problems in the philosophy of information is whether there is an information logic (IL), different from epistemic (EL) and doxastic logic (DL), which formalises the relation “a is informed that p” (Iap) satisfactorily. In this paper, the problem is solved by arguing that the axiom schemata of the normal modal logic (NML) KTB (also known as B or Br or Brouwer’s system) are well suited to formalise the relation of “being informed”. After having shown that IL (...) can be constructed as an informational reading of KTB, four consequences of a KTB-based IL are explored: information overload; the veridicality thesis (Iap → p); the relation between IL and EL; and the Kp → Bp principle or entailment property, according to which knowledge implies belief. Although these issues are discussed later in the article, they are the motivations behind the development of IL. (shrink)

The topic of this paper may be introduced by fast zooming in and out of the philosophy of information. In recent years, philosophical interest in the nature of information has been increasing steadily. This has led to a focus on semantic information, and then on the logic of being informed, which has attracted analyses concentrating both on the statal sense in which S holds the information that p (this is what I mean by logic of being informed in the rest (...) of this article) and on the actional sense in which S becomes informed that p. One of the consequences of the logic debate has been a renewed epistemological interest in the principle of information closure (henceforth PIC), which finally has motivated a revival of a skeptical objection against its tenability first made popular by Dretske. This is the topic of the paper, in which I seek to defend PIC against the skeptical objection. If I am successful, this means – and we are now zooming out – that the plausibility of PIC is not undermined by the skeptical objection, and therefore that a major epistemological argument against the formalization of the logic of being informed based on the axiom of distribution in modal logic is removed. But since the axiom of distribution discriminates between normal and non-normal modal logics, this means that a potentially good reason to look for a formalization of the logic of being informed among the non-normal modal logics, which reject the axiom, is also removed. And this in turn means that a formalization of the logic of being informed in terms of the normal modal logic B (also known as KTB) is still very plausible, at least insofar as this specific obstacle is concerned. In short, I shall argue that the skeptical objection against PIC fails, so it is not a good reason to abandon the normal modal logic B as a good formalization of the logic of being informed. (shrink)

Philosophers of information, according to Luciano Floridi (The philosophy of information. Oxford University Press, Oxford, 2010, p 32), study how information should be “adequately created, processed, managed, and used.” A small number of epistemologists have employed the concept of information as a cornerstone of their theoretical framework. How this concept can be used to make sense of seemingly intractable epistemological problems, however, has not been widely explored. This paper examines Fred Dretske’s information-based epistemology, in particular his response to radical epistemological (...) skepticism. We discuss the relationship between information, evidence and knowledge in relation to the problem of skepticism and the options available to an information-based epistemology for dealing with it. (shrink)

In this article, I argue that consciousness is a unique way of processing information, in that: it produces information, rather than purely transmitting it; the information it produces is meaningful for us; the meaning it has is always individuated. This uniqueness allows us to process information on the basis of our personal needs and ever-changing interactions with the environment, and consequently to act autonomously. Three main basic cognitive processes contribute to realize this unique way of information processing: the self, attention (...) and working memory. The self, which is primarily expressed via the central and peripheral nervous systems, maps our body, the environment, and our relations with the environment. It is the primary means by which the complexity inherent to our composite structure is reduced into the “single voice” of a unique individual. It provides a reference system that (albeit evolving) is sufficiently stable to define the variations that will be used as the raw material for the construction of conscious information. Attention allows for the selection of those variations in the state of the self that are most relevant in the given situation. Attention originates and is deployed from a single locus inside our body, which represents the center of the self, around which all our conscious experiences are organized. Whatever is focused by attention appears in our consciousness as possessing a spatial quality defined by this center and the direction toward which attention is focused. In addition, attention determines two other features of conscious experience: periodicity and phenomenal quality. Self and attention are necessary but not sufficient for conscious information to be produced. Complex forms of conscious experiences, such as the various modes of givenness of conscious experience and the stream of consciousness, need a working memory mechanism to assemble the basic pieces of information selected by attention. (shrink)

As physical entities that translate symbols into physical actions, computers offer insights into the nature of meaning and agency. • Physical symbol systems, generically known as agents, link abstractions to material actions. The meaning of a symbol is defined as the physical actions an agent takes when the symbol is encountered. • An agent has autonomy when it has the power to select actions based on internal decision processes. Autonomy offers a partial escape from constraints imposed by direct physical influences (...) such as gravity and the transfer of momentum. Swimming upstream is an example. • Symbols are names that can designate other entities. It appears difficult to explain the use of names and symbols in terms of more primitive functionality. The ability to use names and symbols, i.e., symbol grounding, may be a fundamental cognitive building block. • The standard understanding of causality—wiggling X results in Y wiggling—applies to both physical causes (e.g., one billiard ball hitting another) and symbolic causes (e.g., a traffic light changing color). Because symbols are abstract, they cannot produce direct physical effects. For a symbol to be a cause requires that the affected entity determine its own response. This is called autonomous causality. • This analysis of meaning and autonomy offers new perspectives on free will. (shrink)

This doctoral thesis consists of five research papers that address four tangential topics, all of which are relevant for the challenges we are facing in our socio-technical society: information, security, privacy, and anonymity. All topics are approached by similar methods, i.e. with a concern about conceptual and definitional issues. In Paper I—concerning the concept of information and a semantic conception thereof—it is argued that the veridicality thesis is false. In Paper II—concerning information security—it is argued that the current leading definitions (...) suffer from counter-examples, and lack an appropriate conceptual sense. Based on this criticism a new kind of definition is proposed and defended. In Paper III—concerning control definitions of privacy—it is argued that any sensible control-definition of privacy must properly recognize the context as part of the defining criteria. In Paper IV—concerning the concept of privacy—it is argued that privacy is a normative concept and that it is constituted by our social relations. Final, in Paper V—concerning anonymity—it is argued that the threat from deanonymization technology goes beyond harm to anonymity. It is argued that a person who never is deanonymized can still be harmed and what is at stake is an ability to be anonymous. (shrink)

This paper contributes to the current debate on the nature of semantic information by offering a semantic argument in favour of the veridical thesis according to which p counts as information only if p is true. In the course of the analysis, the paper reviews some basic principles and requirements for any theory of semantic information.

A formal introduction to Kolmogorov complexity is given, along with its fundamental theorems. Most importantly the theorem of undecidability of a random string and the information-theoretic reformulation of Gödel’s first theorem of incompleteness, stated by Chaitin. Then, the discussion moves on to inquire about some philosophical implications the concept randomness has in the fields of physics and mathematics. Starting from the notion of “understanding as compression” of information, as it is illuminated by algorithmic information theory, it is investigated (1) what (...) K-randomness has to say about the concept of natural law, (2) what is the role of incompleteness in physics and (3) how K-randomness is related to unpredictability, chance and determinism. Regarding mathematics, the discourse starts with a general exposition of the relationship between proving and programming, to propose then some ideas on the nature of mathematics itself; namely, that it is not as unworldly as it is often regarded: indeed, it should be considered a quasi-empirical science (the terminology is from Lakatos, the metamathematical argument by Chaitin) and, more interestingly, random at its core. Finally, a further proposal about the relationship between physics and mathematics is made: the boundary between the two disciplines is blurred; no conceptual separation is possible. Mathematics can be seen as a computational activity (i.e. a physical process), the structure of such a type of process is analyzed. (shrink)

Semantic Information conveyed by daily language has been researched for many years; yet, we still need a practical formula to measure information of a simple sentence or prediction, such as “There will be heavy rain tomorrow”. For practical purpose, this paper introduces a new formula, Semantic Information Formula (SIF), which is based on L. A. Zadeh’s fuzzy set theory and P. Z. Wang’s random set falling shadow theory. It carries forward C. E. Shannon and K. Popper’s thought. The fuzzy set’s (...) probability defined by Zadeh is treated as the logical probability sought by Popper, and the membership grade is treated as the truth-value of a proposition and also as the posterior logical probability. The classical relative information formula (Information=log(Posterior probability / Prior probability) is revised into SIF by replacing the posterior probability with the membership grade and the prior probability with the fuzzy set’s probability. The SIF can be explained as “Information=Testing severity – Relative square deviation” and hence can be used as Popper's information criterion to test scientific theories or propositions. The information measure defined by the SIF also means the spared codeword length as the classical information measure. This paper introduces the set-Bayes’ formula which establishes the relationship between statistical probability and logical probability, derives Fuzzy Information Criterion (FIC) for the optimization of semantic channel, and discusses applications of SIF and FIC in areas such as linguistic communication, prediction, estimation, test, GPS, translation, and fuzzy reasoning. Particularly, through a detailed example of reasoning, it is proved that we can improve semantic channel with proper fuzziness to increase average semantic information to reach its upper limit: Shannon mutual information. (shrink)