Online research in philosophy

Abstraction and Ideation - The Semantics of chemical and biological fundamental concepts. The methods of abstraction and ideation are indispensable tools to introduce new concepts in a scientific terminology. The latter is paradigmatically introduced within the 'protophysical program' whereas abstraction is commonly applied in logics and mathematics. The application within the reconstruction of chemistry and biology causes several problems. Ideation appears to be inadequate whereas the application of abstraction necessitates a critical and minute examination of the corresponding equivalence relations. These problems are solved by the introduction of the method of materially-synthetic (material-synthetische) abstraction which is exemplified by the introduction of the chemical concept of 'substance' (Stoff) and the biological concept of 'hereditary factor' (Erbanlage).

This article presents an in-depth analysis of past and present publishing practices in academic computer science to suggest the establishment of a more consistent publishing standard. Historical precedent for academic publishing in computer science is established through the study of anecdotes as well as statistics collected from databases of published computer science papers. After examining these facts alongside information about analogous publishing situations and standards in other scientific fields, the article concludes with a list of basic principles that should be adopted in any computer science publishing standard. These principles would contribute to the reliability and scientific nature of academic publications in computer science and would allow for more straightforward discourse in future publications.

Kit Fine develops a Fregean theory of abstraction, and suggests that it may yield a new philosophical foundation for mathematics, one that can account for both our reference to various mathematical objects and our knowledge of various mathematical truths. The Limits of Abstraction breaks new ground both technically and philosophically.

Semantic information is usually supposed to satisfy the veridicality thesis: p qualifies as semantic information only if p is true. However, what it means for semantic information to be true is often left implicit, with correspondentist interpretations representing the most popular, default option. The article develops an alternative approach, namely a correctness theory of truth (CTT) for semantic information. This is meant as a contribution not only to the philosophy of information but also to the philosophical debate on the nature of truth. After the introduction, in Sect. 2, semantic information is shown to be translatable into propositional semantic information (i). In Sect. 3, i is polarised into a query (Q) and a result (R), qualified by a specific context, a level of abstraction and a purpose. This polarization is normalised in Sect. 4, where [Q + R] is transformed into a Boolean question and its relative yes/no answer [Q + A]. This completes the reduction of the truth of i to the correctness of A. In Sects. 5 and 6, it is argued that (1) A is the correct answer to Q if and only if (2) A correctly saturates Q by verifying and validating it (in the computer science’s sense of verification and validation ); that (2) is the case if and only if (3) [Q + A] generates an adequate model (m) of the relevant system (s) identified by Q; that (3) is the case if and only if (4) m is a proxy of s (in the computer science’s sense of proxy ) and (5) proximal access to m commutes with the distal access to s (in the category theory’s sense of commutation ); and that (5) is the case if and only if (6) reading/writing (accessing, in the computer science’s technical sense of the term) m enables one to read/write (access) s. Sect. 7 provides some further clarifications about CTT, in the light of semantic paradoxes. Section 8 draws a general conclusion about the nature of CTT as a theory for systems designers not just systems users. In the course of the article all technical expressions from computer science are explained.

How engineering enabled abstraction—in computer science.

In this paper we introduce three methods to approach philosophical problems informationally: Minimalism, the Method of Abstraction and Constructionism. Minimalism considers the specifications of the starting problems and systems that are tractable for a philosophical analysis. The Method of Abstraction describes the process of making explicit the level of abstraction at which a system is observed and investigated. Constructionism provides a series of principles that the investigation of the problem must fulfil once it has been fully characterised by the previous two methods. For each method, we also provide an application: the problem of visual perception, functionalism, and the Turing Test, respectively.

Floridi and Sanders, seminal work, “On the morality of artificial agents” has catalyzed attention around the moral status of computer systems that perform tasks for humans, effectively acting as “artificial agents.” Floridi and Sanders argue that the class of entities considered moral agents can be expanded to include computers if we adopt the appropriate level of abstraction. In this paper we argue that the move to distinguish levels of abstraction is far from decisive on this issue. We also argue that adopting certain levels of abstraction out of context can be dangerous when the level of abstraction obscures the humans who constitute computer systems. We arrive at this critique of Floridi and Sanders by examining the debate over the moral status of computer systems using the notion of interpretive flexibility. We frame the debate as a struggle over the meaning and significance of computer systems that behave independently, and not as a debate about the ‘true’ status of autonomous systems. Our analysis leads to the conclusion that while levels of abstraction are useful for particular purposes, when it comes to agency and responsibility, computer systems should be conceptualized and identified in ways that keep them tethered to the humans who create and deploy them.

Computer science is an engineering science whose objective is to determine how to best control interactions among computational objects. We argue that it is a fundamental computer science value to design computational objects so that the dependencies required by their interactions do not result in couplings, since coupling inhibits change. The nature of knowledge in any science is revealed by how concepts in that science change through paradigm shifts, so we analyze classic paradigm shifts in both natural and computer science in terms of decoupling. We show that decoupling pervades computer science both at its core and in the wider context of computing at large, and lies at the very heart of computer science’s value system.

This article presents an historical and conceptual overview on different approaches to logical abstraction. Two main trends concerning abstraction in the history of logic are highlighted, starting from the logical notions of concept and function. This analysis strictly relates to the philosophical discussion on the nature of abstract objects. I develop this issue further with respect to the procedure of abstraction involved by (typed) λ-systems, focusing on the crucial change about meaning and predicability. In particular, the analysis of the nature of logical types in the context of Constructive Type Theory allows elucidation of the role of the previously introduced notions. Finally, the connection to the analysis of abstraction in computer science is drawn, and the methodological contribution provided by the notion of information is considered, showing its conceptual and technical relevance. Future research shall focus on the notion of information in distributed systems, analysing the paradigm of information hiding in dependent type theories.

Abstract: Laws of computer science are prescriptive in nature but can have descriptive analogs in the physical sciences. Here, we describe a law of conservation of information in network programming, and various laws of computational motion (invariants) for programming in general, along with their pedagogical utility. Invariants specify constraints on objects in abstract computational worlds, so we describe language and data abstraction employed by software developers and compare them to Floridi's concept of levels of abstraction. We also consider Floridi's structural account of reality and its fit for describing abstract computational worlds. Being abstract, such worlds are products of programmers' creative imaginations, so any "laws" in these worlds are easily broken. The worlds of computational objects need laws in the form of self-prescribed invariants, but the suspension of these laws might be creative acts. Bending the rules of abstract reality facilitates algorithm design, as we demonstrate through the example of search trees.