The publication of scientific papers has become increasingly problematic in the last decades. Even if we agree that a renewed model is needed for peer-reviewed scientific publication, we think the problem does not essentially lie in professional publishing—with economic incentives—but in the publish-or-perish culture that dominates the lives of researchers and academics.

The publication of scientific papers has become increasingly problematic in the last decades. Even if we agree that a renewed model is needed for peer-reviewed scientific publication, we think the problem does not essentially lie in professional publishing—with economic incentives—but in the publish-or-perish culture that dominates the lives of researchers and academics.

This article deals with a modern disease of academic science that consists of an enormous increase in the number of scientific publications without a corresponding advance of knowledge. Findings are sliced as thin as salami and submitted to different journals to produce more papers. If we consider academic papers as a kind of scientific ‘currency’ that is backed by gold bullion in the central bank of ‘true’ science, then we are witnessing an article-inflation phenomenon, a scientometric bubble that is most (...) harmful for science and promotes an unethical and antiscientific culture among researchers. The main problem behind the scenes is that the impact factor is used as a proxy for quality. Therefore, not only for convenience, but also based on ethical principles of scientific research, we adhere to the San Francisco Declaration on Research Assessment when it emphasizes “the need to eliminate the use of journal-based metrics in funding, appointment and promotion considerations; and the need to assess research on its own merits rather on the journal in which the research is published”. Our message is mainly addressed to the funding agencies and universities that award tenures or grants and manage research programmes, especially in developing countries. The message is also addressed to well-established scientists who have the power to change things when they participate in committees for grants and jobs. (shrink)

The digital transfer of the mind to a computer system requires representing the mind as a finite sequence of bits. The classic “stored-program computer” paradigm, in turn, implies the equivalence between program and data, so that the sequence of bits themselves can be interpreted as a program, which will be algorithmically executed in the receiving device. Now, according to a previous proof, on which this paper is based, a computational or algorithmic machine, however complex, cannot be free. Consequently, a finite (...) sequence of bits cannot adequately represent a free mind and, therefore, a free mind cannot be digitally transferred, quod erat demonstrandum. The impossibility of making this transfer, as demonstrated here, should be a concern especially for those who wish to achieve it. Since we intend this to be a rigorous demonstration, we must give precise definitions and conditions of validity. The most important part of the paper is devoted to explaining the meaning and reasonableness of these definitions and conditions. Special attention is paid, also, to the philosophical implications of the demonstration. Finally, this thesis is distinguished from other closely related issues. (shrink)

In this paper we present the authors’ experience of teaching a course in Ethics for Engineers, which has been delivered four times in three different universities in Spain and Chile. We begin by presenting the material context of the course, and especially the intellectual background of the participating students, in terms of their previous understanding of philosophy in general, and of ethics in particular. Next we set out the objectives of the course and the main topics addressed, as well as (...) the methodology and teaching resources employed to have students achieve a genuine philosophical reflection on the ethical aspects of the profession, starting from their own mindset as engineers. Finally we offer some results based on opinion surveys of the students, as well as a more personal assessment by the authors, recapitulating the most significant achievements of the course and indicating its underlying Socratic structure. (shrink)

In this essay we argue that the notion of machine necessarily includes its being designed for a purpose. Therefore, being a mechanical system is not enough for being a machine. Since the experimental scientific method excludes any consideration of finality on methodological grounds, it is then also insufficient to fully understand what machines are. Instead in order to understand a machine it is first required to understand its purpose, along with its structure, in clear parallel with Aristotle’s final and formal (...) causes. Obviously, purpose and structure are not machine components that can physically interact with other components; nonetheless they are essential to understanding their operation. This casts an interesting light on the relationship between mind and body: for just as an artifact’s finality and structure explain its operation, so also consciousness is the explanation—not the efficient cause—of specifically human behavior. What machines and human beings have in common is that, in order to understand them, it is necessary to appeal to the principle of finality. Yet while finality is given and extrinsic in the case of machines, we human beings are characterized by the ability to self-propose our own ends. Since the principle of finality is essential to understanding the production of machines, the traditional view in modern Western philosophy that finality lies beyond the scope of objective/scientific knowledge should be rectified to allow for a genuine science of the artificial. We think a correct understanding of final causality will overcome current resistance to this principle. (shrink)

An engineer who becomes an educator in a school of software engineering has the mission to teach how to design and construct software systems, therein applying his or her knowledge and expertise. However, due to their engineering background, engineers may forget that educating a person is not the same as designing a machine, since a machine has a well-defined goal, whilst a person is capable to self-propose his or her own objectives. The ethical implications are clear: educating a free person (...) must leave space for creativity and self-determination in his or her own discovery of the way towards personal and professional fulfillment, which cannot consist only in achieving goals selected by others. We present here an argument that is applicable to most fields of engineering. However, the dis-analogy between educating students and programming robots may have a particular appeal to software engineers and computer scientists. We think the consideration of three different stages in the educational process may be useful to engineers when they act as educators. We claim that the three stages are essential to engineering education. In particular, education is incomplete if the third stage is not reached. Moreover, mentoring is incompatible with an educational assessment framework that considers the goals of the engineer are always given by others. In our view, then, an integral education is not only beyond programming the behavior of students, but also beyond having them reach those given goals. (shrink)

Is ethics a computable function? Can machines learn ethics like humans do? If teaching consists in no more than programming, training, indoctrinating… and if ethics is merely following a code of conduct, then yes, we can teach ethics to algorithmic machines. But if ethics is not merely about following a code of conduct or about imitating the behavior of others, then an approach based on computing outcomes, and on the reduction of ethics to the compilation and application of a set (...) of rules, either a priori or learned, misses the point. Our intention is not to solve the technical problem of machine ethics, but to learn something about human ethics, and its rationality, by reflecting on the ethics that can and should be implemented in machines. Any machine ethics implementation will have to face a number of fundamental or conceptual problems, which in the end refer to philosophical questions, such as: what is a human being (or more generally, what is a worthy being); what is human intentional acting; and how are intentional actions and their consequences morally evaluated. We are convinced that a proper understanding of ethical issues in AI can teach us something valuable about ourselves, and what it means to lead a free and responsible ethical life, that is, being good people beyond merely “following a moral code”. In the end we believe that rationality must be seen to involve more than just computing, and that value rationality is beyond numbers. Such an understanding is a required step to recovering a renewed rationality of ethics, one that is urgently needed in our highly technified society. (shrink)

Among the various contemporary schools of moral thinking, consequence-based ethics, as opposed to rule-based, seems to have a good acceptance among professionals such as software engineers. But naïve consequentialism is intellectually too weak to serve as a practical guide in the profession. Besides, the complexity of software systems makes it very hard to know in advance the consequences that will derive from professional activities in the production of software. Therefore, following the spirit of well-known codes of ethics such as the (...) ACM/IEEE’s, we advocate for a more solid position in the ethical education of software engineers, which we call ‘moderate deontologism’, that takes into account both rules and consequences to assess the goodness of actions, and at the same time pays an adequate consideration to the absolute values of human dignity. In order to educate responsible professionals, however, this position should be complemented with a pedagogical approach to virtue ethics. (shrink)

This is an analysis of Peirce's theory of the three types of reasoning as explained in his 1877 essay "Deduction, Induction, and Hypothesis", which is representative of his earlier views on this subject. Hypothesis -which l-ter would become his abduction or retroduction- and induction are considered variants of probable syllogisms of the second and third figures. Specific attention is devoted to similarities and differences between induction and hypothesis.

A long tradition, which starts with the metaphor of the wax tablet presented in the Theaetetus of Plato, leads us to think that the relationship between mental representation and the represented reality is in a certain way mechanical or automatic. But the truth is that the conventional aspects of signification make it impossible to understand it as a physical- mechanical process. The computer sciences, contrary to a superficial vision, do not support but rather disprove this mechanistic conception of rationality, confirming (...) that semiosis can only occur in free subjects, that is to say, not completely subject to the laws of matter. (shrink)