Online research in philosophy

Efforts to counter software piracy are an increasing focus of software publishers. This study attempts to develop a profile of those who illegally copy software by looking at undergraduate and graduate students and the extent to which they pirate software. The data indicate factors that can be used to profile the software pirater. In particular, males were found to pirate software more frequently than females and older students more than younger students, based on self-reporting.

Although there are various ways to express actions and behaviors in natural languages, it is found in cognitive informatics that human and system behaviors may be classified into three basic categories: to be , to have , and to do . All mathematical means and forms, in general, are an abstract description of these three categories of system behaviors and their common rules. Taking this view, mathematical logic may be perceived as the abstract means for describing to be, set theory for describing 'to have,' and algebras, particularly the process algebra, for describing to do. This is a fundamental view toward the formal description and modeling of human and system behaviors in general, and software behaviors in particular, because a software system can be perceived as a virtual agent of human beings, and it is created to do something repeatable, to extend human capability, reachability, and/or memory capacity. The author found that both human and software behaviors can be described by a three-dimensional representative model comprising action, time, and space. For software system behaviors, the three dimensions are known as mathematical operations, event/process timing, and memory manipulation. This paper introduces the real-time process algebra (RTPA) that serves as an expressive notation system for describing thoughts and notions of dynamic software behaviors. Experimental case studies on applications of RTPA in describing the equivalent software and human behaviors as a series of actions and cognitive processes are demonstrated with real-world examples.

A simple exogenous growth model gives conservative estimates of the economic implications of machine intelligence. Machines complement human labor when they become more productive at the jobs they perform, but machines also substitute for human labor by taking over human jobs. At first, expensive hardware and software does only the few jobs where computers have the strongest advantage over humans. Eventually, computers do most jobs. At first, complementary effects dominate, and human wages rise with computer productivity. But eventually substitution can dominate, making wages fall as fast as computer prices now do. An intelligence population explosion makes per-intelligence consumption fall this fast, while economic growth rates rise by an order of magnitude or more. These results are robust to automating incrementally, and to distinguishing hardware, software, and human capital from other forms of capital.

For the greater part of the last 50 years, it has been common for philosophers of mind and cognitive scientists to invoke the notion of realization in discussing the relationship between the mind and the brain. In traditional philosophy of mind, mental states are said to be realized, instantiated, or implemented in brain states. Artificial intelligence is sometimes described as the attempt either to model or to actually construct systems that realize some of the same psychological abilities that we and other living creatures possess. The claim that specific psychological.

For the greater part of the last 50 years, it has been common for philosophers of mind and cognitive scientists to invoke the notion of realization in discussing the relationship between the mind and the brain. In traditional philosophy of mind, mental states are said to be realized, instantiated, or implemented in brain states. Artificial intelligence is sometimes described as the attempt either to model or to actually construct systems that realize some of the same psychological abilities that we and other living creatures possess. The claim that specific psychological..

Supplementary to matter and energy, information is the third essence for modeling the natural world. An emerging discipline known as cognitive informatics (CI) is developed recently that forms a profound interdisciplinary study of cognitive and information sciences, and tackles the common root problems sharing by informatics, computing, software engineering, artificial intelligence, cognitive science, neuropsychology, philosophy, linguistics, and life science. CI focuses on internal information processing mechanisms and the natural intelligence of the brain. This paper describes the historical development of informatics from the classical information theory and contemporary informatics, to CI. The domain of CI, and its interdisciplinary nature are explored. Foundations of CI, particularly the brain versus the mind, the acquired life functions versus the inherited ones, and generic relationships between information, matter, and energy are investigated. The potential engineering applications of CI and perspectives on future research are discussed. It is expected that the investigation into CI will result in fundamental findings towards the development of next generation IT and software technologies, and new architectures of computing systems.

Supplementary to matter and energy, information is the third essence for modeling the natural world. An emerging discipline known as cognitive informatics (CI) is developed recently that forms a profound interdisciplinary study of cognitive and information sciences, and tackles the common root problems sharing by informatics, computing, software engineering, artificial intelligence, cognitive science, neuropsychology, philosophy, linguistics, and life science. CI focuses on internal information processing mechanisms and the natural intelligence of the brain. This paper describes the historical development of informatics from the classical information theory and contemporary informatics, to CI. The domain of CI, and its interdisciplinary nature are explored. Foundations of CI, particularly the brain versus the mind, the acquired life functions versus the inherited ones, and generic relationships between information, matter, and energy are investigated. The potential engineering applications of CI and perspectives on future research are discussed. It is expected that the investigation into CI will result in fundamental findings towards the development of next generation IT and software technologies, and new architectures of computing systems.

Cognition is best understood by examining a model of a cognitive system. Such a model is presented in the following paper. Most discussions of the mind or brain focus on the "hardware", the neural structure and its biological / electrochemical functioning. But, it is the "software", how the neural components logically interact, that produces the results that we experience in our own minds. The objective is intelligence -- how we see, think, remember, know ourselves, learn, plan create. To describe and explain those sophisticated functions it is necessary to start with simple first steps, building blocks, and gradually erect the total structure. The reader is urged to be patient with the review of fundamentals in the earlier portions of this paper, which review lays the basis for the development. The development begins with universals and mechanisms for recognizing or identifying them. It then proceeds through perception, learning, and the processing of universals to mental concepts, thoughts, thinking and memory. Then purposive behavior and its related goals, motivation and consciousness are developed. Finally the implications for the issue of free will [versus predestination] and the designing of an artificial intelligence are addressed.

Within artificial intelligence and the philosophy of mind,there is considerable disagreement over the relationship between anagent's body and its capacity for intelligent behavior. Some treatthe body as peripheral and tangential to intelligence; others arguethat embodiment and intelligence are inextricably linked. Softwareagents–-computer programs that interact with software environmentssuch as the Internet–-provide an ideal context in which to studythis tension. I develop a computational framework for analyzingembodiment. The framework generalizes the notion of a body beyondmerely having a physical presence. My analysis sheds light oncertain claims made about the relevance of the body to intelligence,as well as on embodiment in software worlds.

Brain-machine interfaces are a growing field of research and application. The increasing possibilities to connect the human brain to electronic devices and computer software can be put to use in medicine, the military, and entertainment. Concrete technologies include cochlear implants, Deep Brain Stimulation, neurofeedback and neuroprosthesis. The expectations for the near and further future are high, though it is difficult to separate hope from hype. The focus in this paper is on the effects that these new technologies may have on our ‘symbolic order’—on the ways in which popular categories and concepts may change or be reinterpreted. First, the blurring distinction between man and machine and the idea of the cyborg are discussed. It is argued that the morally relevant difference is that between persons and non-persons, which does not necessarily coincide with the distinction between man and machine. The concept of the person remains useful. It may, however, become more difficult to assess the limits of the human body. Next, the distinction between body and mind is discussed. The mind is increasingly seen as a function of the brain, and thus understood in bodily and mechanical terms. This raises questions concerning concepts of free will and moral responsibility that may have far reaching consequences in the field of law, where some have argued for a revision of our criminal justice system, from retributivist to consequentialist. Even without such a (unlikely and unwarranted) revision occurring, brain-machine interactions raise many interesting questions regarding distribution and attribution of responsibility.