Computer Science

It is possible to rely on current corporate law to grant legal personhood to Artificially Intelligent (AI) agents. In this paper, after introducing pathways to AI personhood, we analyze consequences of such AI empowerment on human dignity, human safety and AI rights. We emphasize possibility of creating selfish memes and legal system hacking in the context of artificial entities. Finally, we consider some potential solutions for addressing described problems.

The historical development has lead to the decay of Natural Philosophy which until 19th century included all of our knowledge about the physical world into the growing multitude of specialized sciences. The focus on the in-depth enquiry disentangled from its broad context lead to the problem of loss of common world-view and impossibility of communication between specialist research fields because of different languages they developed in isolation. The need for a new unifying framework is becoming increasingly apparent with the information technology enabling and intensifying the communication between different research fields and knowledge communities. This time, not only natural sciences, but also all of human knowledge is being integrated in a global network such as Internet with its diverse knowledge and language communities. Info-computationalism (ICON) as a synthesis of pancomputationalism and paninformationalism presents a unifying framework for understanding of natural phenomena including living beings and their cognition, their ways of processing information and producing knowledge. Within ICON physical universe is understood as a network of computational processes on an informational structure.

This paper aims to introduce an application to Kalman Filtering Theory, which is rather unconventional. Recent experiments have shown that many natural phenomena, especially from ecology or meteorology, could be monitored and predicted more accurately when accounting their evolution over some geographical area. Thus, the signals they provide are gathered together into a collection of distributed time series. Despite the common sense, such time series are more or less correlated each other. Instead of processing each time series independently, their collection can constitute the set of measurable states provided by some open system. Modeling and predicting the system states can take benefit from the family of Kalman filtering algorithms. The article describes an adaptation of basic Kalman filter to the context of distributed signals collections and completes with an application coming from Meteorology.

These reminiscences are about the "dark ages" of algorithmic information theory in the USSR. After a great interest in this topic in 1960s and the beginning of 1970s the number of people working in this area in the USSR decreased significantly. At that time L.A. Levin published a bunch of papers that were seminal for the modern algorithmic information theory. Then he left the USSR, and the new wave of interest was triggered by the talk of A.N. Kolmogorov at a Moscow State (Lomonosov) University Mathematical Department (Logic and Algorithms Division) seminar organized by him; several younger researchers obtained some new results in algorithmic information theory.

In this survey, we explore Andrei Nikolayevich Kolmogorov's seminal work in just one of his many facets: its influence Computer Science especially his viewpoint of what herein we call 'Algorithmic Theory of Informatics.' Can a computer file 'reduce' its 'size' if we add to it new symbols? Do equations of state like second Newton law in Physics exist in Computer Science? Can Leibniz' principle of identification by indistinguishability be formalized? In the computer, there are no coordinates, no distances, and no dimensions; most of traditional mathematical approaches do not work. The computer processes finite binary sequences i.e. the sequences of 0 and 1. A natural question arises: Should we continue today, as we have done for many years, to approach Computer Science problems by using classical mathematical apparatus such as 'mathematical modeling'? The first who drew attention to this question and gave insightful answers to it was Kolmogorov in 1960s. Kolmogorov's empirical postulate about existence of a program that translates 'a natural number into its binary record and the record into the number' formulated in 1958 represents a hint of Kolmogorov's approach to Computer Science. Following his ideas, we interpret Kolmogorov algorithm, Kolmogorov machine, and Kolmogorov complexity in the context of modern information technologies showing that they essentially represent fundamental elements of Algorithmic Theory of Informatics, Kolmogorov Programmable Technology, and new Komputer Mathematics i.e. Mathematics of computers.

Although the history of informatics is recent, this field poses unusual problems with respect to its preservation. These problems are amplified by legal issues, digital law being in itself a subject matter whose history is also worth presenting in a computer science museum. The purpose of this paper is to present a quick overview of the evolution of law regarding digital matters, from an historical perspective as well as with respect to the preservation and presentation of the works.

How to manage knowledge on the Web.

In a recent article, Luciano Floridi explains his view of Turing's legacy in connection to the philosophy of information. I will very briefly survey one of Turing's other contributions to the philosophy of information and computation, including similarities to Shannon's own methodological approach to information through communication, showing how crucial they are and have been as methodological strategies to understanding key aspects of these concepts. While Floridi's concept of Levels of Abstraction is related to the novel methodology of Turing's imitation game for tackling the question of machine intelligence, Turing's other main contribution to the philosophy of information runs contrary to it. Indeed, the seminal concept of computation universality strongly suggests the deletion of fundamental differences among seemingly different levels of description. How might we reconcile these apparently contradictory contributions? I will argue that Turing's contribution should prompt us to plot some directions for a philosophy of information and computation, one that closely parallels the most important developments in computer science, one that understands the profound implications of the works of Turing, Shannon and others.

Incompleteness theorems of Godel, Turing, Chaitin, and Algorithmic Information Theory have profound epistemological implications. Incompleteness limits our ability to ever understand every observable phenomenon in the universe. Incompleteness limits the ability of evolutionary processes from finding optimal solutions. Incompleteness limits the detectability of machine consciousness. This is an effort to convey these thoughts and results in a somewhat entertaining manner.

We propose a soft-output detection scheme for Multiple-Input-Multiple-Output (MIMO) systems. The detector employs Markov Chain Monte Carlo method to compute bit reliabilities from the signals received and is thus suited for coded MIMO systems. It offers a good trade-off between achievable performance and algorithmic complexity.