It is axiomatic that the fuller and more integrated interpretation of scientific discoveries and data lies within the domain of the philosopher. This statement has all the more force when we come to deal with the problem of Life and its origins. In his book, Dr. Fothergill rightly takes for granted that eventually all life goes back to God for its origin, but his primary concern is the origin of life on the earth. Arguing that before we look for the (...) origin of life we must try to find out what life itself is, he examines the various theories of abiogenesis and points out that they all fail to find a real distinction between the living and the non-living. They all assume that fundamentally a living organism is nothing more than a complex physicochemical system in equilibrium. The proponents of these theories while readily admitting the enormous complexity of the organic molecules that take part in biological reactions, yet with incredible naiveté postulate that these have evolved from simpler peptides which in turn have been synthetised from simple inorganic molecules like carbon dioxide and ammonia in the primaeval oceans. While even fairly complex polypeptides have been built up in vitro, their synthesis from a mixture of inorganic chemicals has never been observed. (shrink)

Because it is fundamental in the training of a chemist, any new work on Thermodynamics is bound to evoke the interest of those who are engaged in teaching chemistry at higher levels. The present book is intended for University students taking Chemistry as a Degree subject. It is written in a straightforward style and the subject is developed clearly and logically. The laws of thermodynamics are treated adequately, the first and second getting fuller attention since they serve as a foundation (...) for the definition and consideration of free energy, entropy and other thermodynamical functions. The criteria of equilibrium are thoroughly examined and a considerable amount of data illustrative of the chief topics is given. Rather unusual but interesting and highly useful features include bond-energies, the Born-Haber Cycle, the velocity of an adiabatically expanded jet of gas, the stretching of rubber, high polymer solutions. (shrink)

This work is a series of studies by various authors, the result of a symposium of the Union Catholique des Scientifiques Français held in October 1956, to discuss man’s peculiar biological place in creation. They comprise chapters on the human brain, neurology, biochemistry and endocrinology. These are intended for specialists in biology and philosophy rather than for the general reader. There are however chapters devoted to the discussion of conclusions drawn from previous studies, and these are both useful and helpful (...) generally. (shrink)

The present volume is a welcome addition to the many monographs which have appeared. Its avowed purpose is two-fold: to show that scientific research properly understood is concerned with the discovery of the plans of God the Almighty Creator and the revealing of their intrinsic beauty and purpose; to guide scientists, and in general, public opinion on matters where science plays a leading part.

This is a translation of part of Fr. Hoenen’s Cosmologia in which the author sets out, so the translator tells us in the preface, to discover the philosophical explanation of non-living or inorganic compounds. One wonders why he decided to equate non-living with inorganic and to omit a number of organic compounds which are also non-living. The book makes heavy reading for the English is prolix, awkward and jejune. One gets the impression too that the translator is not exactly at (...) home in the field of chemistry. When quoting chemical laws it would have been better to employ some standard formula which would have avoided such clumsy statements as the following: ‘Given gases at a constant temperature and pressure, the volumes of the component gases taking part in a reaction are in simple proportion to one another and to the volume of the chemical compound’. Again on p. 36 we find: ‘The Molecular theory, in so far as it is now confirmed, may be stated thus: Gaseous bodies consist of molecules as of parts actually discrete’. (shrink)

What role does the imagination play in scientific progress? After examining several studies in cognitive science, I argue that one thing the imagination does is help to increase scientific understanding, which is itself indispensable for scientific progress. Then, I sketch a transcendental justification of the role of imagination in this process.

We might think that thought experiments are at their most powerful or most interesting when they produce new knowledge. This would be a mistake; thought experiments that seek understanding are just as powerful and interesting, and perhaps even more so. A growing number of epistemologists are emphasizing the importance of understanding for epistemology, arguing that it should supplant knowledge as the central notion. In this chapter, I bring the literature on understanding in epistemology to bear on explicating the different ways (...) that thought experiments increase three important kinds of understanding: explanatory, objectual and practical. (shrink)

I claim that one way thought experiments contribute to scientific progress is by increasing scientific understanding. Understanding does not have a currently accepted characterization in the philosophical literature, but I argue that we already have ways to test for it. For instance, current pedagogical practice often requires that students demonstrate being in either or both of the following two states: 1) Having grasped the meaning of some relevant theory, concept, law or model, 2) Being able to apply that theory, concept, (...) law or model fruitfully to new instances. Three thought experiments are presented which have been important historically in helping us pass these tests, and two others that cause us to fail. Then I use this operationalization of understanding to clarify the relationships between scientific thought experiments, the understanding they produce, and the progress they enable. I conclude that while no specific instance of understanding (thus conceived) is necessary for scientific progress, understanding in general is. (shrink)

The causal premise of the evolutionary debunking argument contends that human moral beliefs are explained by the process of natural selection. While it is universally acknowledged that such a premise is fundamental to the debunker’s case, the vast majority of philosophers focus instead on the epistemic premise that natural selection does not track moral truth and the resulting skeptical conclusion. Recently, however, some have begun to concentrate on the causal premise. So far, the upshot of this small but growing literature (...) has been that the causal premise is likely false due to the seemingly persuasive evidence that our moral beliefs are in fact not the result of natural selection. In this paper, I argue that this view is mistaken. Specifically, I advocate the Innate Biases Model, which contends that there is not only compelling evidence for an evolved cognitive capacity for acquiring norms but also for the existence of an evolutionarily instilled set of cognitive biases that make it either more or less likely that we adopt certain moral beliefs. (shrink)

John D. Norton is responsible for a number of influential views in contemporary philosophy of science. This paper will discuss two of them. The material theory of induction claims that inductive arguments are ultimately justified by their material features, not their formal features. Thus, while a deductive argument can be valid irrespective of the content of the propositions that make up the argument, an inductive argument about, say, apples, will be justified (or not) depending on facts about apples. The argument (...) view of thought experiments claims that thought experiments are arguments, and that they function epistemically however arguments do. These two views have generated a great deal of discussion, although there hasn’t been much written about their combination. I argue that despite some interesting harmonies, there is a serious tension between them. I consider several options for easing this tension, before suggesting a set of changes to the argument view that I take to be consistent with Norton’s fundamental philosophical commitments, and which retain what seems intuitively correct about the argument view. These changes require that we move away from a unitary epistemology of thought experiments and towards a more pluralist position. (shrink)

In his article “Beyond Point-and-Shoot Morality,” Joshua Greene argues that the empirical findings of cognitive neuroscience have implications for ethics. Specifically, he contends that we ought to trust our manual, conscious reasoning system more than our automatic, emotional system when confronting unfamiliar problems; and because cognitive neuroscience has shown that consequentialist judgments are generated by the manual system and deontological judgments are generated by the automatic system, we ought to trust the former more than the latter when facing unfamiliar moral (...) problems. In the present article, I analyze one of the premises of Greene’s argument. In particular, I ask what exactly an unfamiliar problem is and whether moral problems can be classified as unfamiliar. After exploring several different possible interpretations of familiarity and unfamiliarity, I conclude that the concepts are too problematic to be philosophically compelling, and thus should be abandoned. (shrink)

Joshua Greene has argued that the empirical findings of cognitive science have implications for ethics. In particular, he has argued (1) that people’s deontological judgments in response to trolley problems are strongly influenced by at least one morally irrelevant factor, personal force, and are therefore at least somewhat unreliable, and (2) that we ought to trust our consequentialist judgments more than our deontological judgments when making decisions about unfamiliar moral problems. While many cognitive scientists have rejected Greene’s dual-process theory of (...) moral judgment on empirical grounds, philosophers have mostly taken issue with his normative assertions. For the most part, these two discussions have occurred separately. The current analysis aims to remedy this situation by philosophically analyzing the implications of moral dilemma research using the CNI model of moral decision-making – a formalized, mathematical model that decomposes three distinct aspects of moral-dilemma judgments. In particular, we show how research guided by the CNI model reveals significant conceptual, empirical, and theoretical problems with Greene’s dual-process theory, thereby questioning the foundations of his normative conclusions. (shrink)

While philosophers hold that it is patently absurd to blame robots or hold them morally responsible [1], a series of recent empirical studies suggest that people do ascribe blame to AI systems and robots in certain contexts [2]. This is disconcerting: Blame might be shifted from the owners, users or designers of AI systems to the systems themselves, leading to the diminished accountability of the responsible human agents [3]. In this paper, we explore one of the potential underlying reasons for (...) robot blame, namely the folk's willingness to ascribe inculpating mental states or "mens rea" to robots. In a vignette-based experiment (N=513), we presented participants with a situation in which an agent knowingly runs the risk of bringing about substantial harm. We manipulated agent type (human v. group agent v. AI-driven robot) and outcome (neutral v. bad), and measured both moral judgment (wrongness of the action and blameworthiness of the agent) and mental states attributed to the agent (recklessness and the desire to inflict harm). We found that (i) judgments of wrongness and blame were relatively similar across agent types, possibly because (ii) attributions of mental states were, as suspected, similar across agent types. This raised the question - also explored in the experiment - whether people attribute knowledge and desire to robots in a merely metaphorical way (e.g., the robot "knew" rather than really knew). However, (iii), according to our data people were unwilling to downgrade to mens rea in a merely metaphorical sense when given the chance. Finally, (iv), we report a surprising and novel finding, which we call the inverse outcome effect on robot blame: People were less willing to blame artificial agents for bad outcomes than for neutral outcomes. This suggests that they are implicitly aware of the dangers of overattributing blame to robots when harm comes to pass, such as inappropriately letting the responsible human agent off the moral hook. (shrink)

Multiple endogenous and exogenous prenatal influences interact to form a system that induces the development of individual lateralization across a range of perceptual and motor abilities in precocial birds. As these influences are nearly invariant for all species members, they produce a phylogenetic influence that creates high levels of population laterality and social cohesion in the postnatal state.

Traditionally, species have been treated as classes. In fact they may be considered individuals. The logical term “individual” has been confused with a biological synonym for “organism.” If species are individuals, then: 1) their names are proper, 2) there cannot be instances of them, 3) they do not have defining properties, 4) their constituent organisms are parts, not members. “ Species " may be defined as the most extensive units in the natural economy such that reproductive competition occurs among their (...) parts. Species are to evolutionary theory as firms are to economic theory: this analogy resolves many issues, such as the problems of “reality” and the ontological status of nomenclatorial types. (shrink)

_This sweeping discussion of the philosophy of evolutionary biology is based on the revolutionary idea that species are not kinds of organisms but wholes composed of organisms._.

A coherent treatment of the flow of ideas throughout Darwin's works, this volume presents a unified theoretical system that explains Darwin's investigations, evaluating the literature from a historical, scientific, and philosophical perspective.

Recent research shows – somewhat astonishingly – that people are willing to ascribe moral blame to AI-driven systems when they cause harm [1]–[4]. In this paper, we explore the moral- psychological underpinnings of these findings. Our hypothesis was that the reason why people ascribe moral blame to AI systems is that they consider them capable of entertaining inculpating mental states (what is called mens rea in the law). To explore this hypothesis, we created a scenario in which an AI system (...) runs a risk of poisoning people by using a novel type of fertilizer. Manipulating the computational (or quasi-cognitive) abilities of the AI system in a between-subjects design, we tested whether people’s willingness to ascribe knowledge of a substantial risk of harm (i.e., recklessness) and blame to the AI system. Furthermore, we investigated whether the ascription of recklessness and blame to the AI system would influence the perceived blameworthiness of the system’s user (or owner). In an experiment with 347 participants, we found (i) that people are willing to ascribe blame to AI systems in contexts of recklessness, (ii) that blame ascriptions depend strongly on the willingness to attribute recklessness and (iii) that the latter, in turn, depends on the perceived “cognitive” capacities of the system. Furthermore, our results suggest (iv) that the higher the computational sophistication of the AI system, the more blame is shifted from the human user to the AI system. (shrink)

Sometimes we learn through the use of imagination. The epistemology of imagination asks how this is possible. One barrier to progress on this question has been a lack of agreement on how to characterize imagination; for example, is imagination a mental state, ability, character trait, or cognitive process? This paper argues that we should characterize imagination as a cognitive ability, exercises of which are cognitive processes. Following dual process theories of cognition developed in cognitive science, the set of imaginative processes (...) is then divided into two kinds: one that is unconscious, uncontrolled, and effortless, and another that is conscious, controlled, and effortful. This paper outlines the different epistemological strengths and weaknesses of the two kinds of imaginative process, and argues that a dual process model of imagination helpfully resolves or clarifies issues in the epistemology of imagination and the closely related epistemology of thought experiments. (shrink)

Classifying is a fundamental operation in the acquisition of knowledge. Taxonomic theory can help students of cognition, evolutionary psychology, ethology, anatomy, and sociobiology to avoid serious mistakes, both practical and theoretical. More positively, it helps in generating hypotheses useful to a wide range of disciplines. Composite wholes, such as species and societies, are “individuals” in the logical sense, and should not be treated as if they were classes. A group of analogous features is a natural kind, but a group of (...) homologous features is not. Imposing hypotheses justified only on the basis of nominalist, realist, phenomenalist, or conceptualist metaphysics upon the neurophysiology of organisms or upon the causes of behavior exemplifies the “psychologist's fallacy” of William James. Levels should be distinguished from their members and from classes of levels, and the ontological status of entities ranked at levels should be made clear. It is important not to confuse such categories as substance and process with one another. Several genetical terms, such as “gene” and chromosome,” are even more equivocal than has been realized. Discussions about units of selection, behavior, and thinking suffer from the ambiguity of a “unit of” an entity. An important source of misunderstanding about natural selection is the habit of treating it as an “agent”: in an important sense, natural selection does not “act” at all. (shrink)

The structure of the brain and the nature of evolution suggest that, despite its uniqueness, language likely depends on brain systems that also subserve other functions. The declarative / procedural model claims that the mental lexicon of memorized word- specific knowledge depends on the largely temporal-lobe substrates of declarative memory, which underlies the storage and use of knowledge of facts and events. The mental grammar, which subserves the rule-governed combination of lexical items into complex representations, depends on a distinct neural (...) system. This system, which is composed of a network of specific frontal, basal - ganglia, parietal and cerebellar structures, underlies procedural memory, which supports the learning and execution of motor and cognitive skills, especially those involving sequences. The functions of the two brain systems, together with their anatomical, physiological and biochemical substrates, lead to specific claims and predictions regarding their roles in language. These predictions are compared with those of other neurocognitive models of language. Empirical evidence is presented from neuroimaging studies of normal language processing, and from developmental and adult- onset disorders. It is argued that this evidence supports the DP model. It is additionally proposed that “ language ” disorders, such as specific language impairment and non-fluent and fluent aphasia, may be profitably viewed as impairments primarily affecting one or the other brain system. Overall, the data suggest a new neurocognitive framework for the study of lexicon and grammar. (shrink)

Imagination is important for many things in science: solving problems, interpreting data, designing studies, etc. Philosophers of imagination typically account for the productive role played by imagination in science by focusing on how imagination is constrained, e.g., by using self-imposed rules to infer logically, or model events accurately. But the constraints offered by these philosophers either constrain too much, or not enough, and they can never account for uses of imagination that are needed to break today’s constraints in order to (...) make progress tomorrow. Thus, epistemology of imagination needs to make room for an element of epistemological anarchy. (shrink)

Scientists imagine for epistemic reasons, and these imaginings can be better or worse. But what does it mean for an imagining to be epistemically better or worse? There are at least three metaepistemological frameworks that present different answers to this question: epistemological consequentialism, deontic epistemology, and virtue epistemology. This paper presents empirical evidence that scientists adopt each of these different epistemic frameworks with respect to imagination, but argues that the way they do this is best explained if scientists are fundamentally (...) epistemic consequentialists about imagination. (shrink)

This is the introduction to the Routledge Companion to Thought Experiments.