" In Imagination and the Meaningful Brain, psychoanalyst Arnold Modell claims that subjective human experience must be included in any scientific...

Abstract.Since the gene splicing debates of the 1980s, the public has been exposed to an ongoing sequence of genetic and reproductive technologies. Many issue areas have outcomes that lose track of people's inner values or engender opposing religious viewpoints defying final resolution. This essay relocates the discussion of what is an acceptable application from the individual to the societal level, examining technologies that stand to address large numbers of people and thus call for policy resolution, rather than individual fiat, in (...) their application. A major source of guidance is the “Genetic Frontiers” series of professional dialogues and conferences held by the National Conference for Community and Justice from 2002 to 2004. Genetic testing, human gene therapy, genetic engineering of plants and animals, and stem cell technology are examined. While differences in perspective on the beginning of life persist, a stepwise approach to the examination of genetic testing reveals areas of general agreement. Stewardship of life, human co‐creativity with the divine, and social justice help define the bounds of application of genetic engineering and therapy; compassionate care plays a major role in establishing stem cell policy. Active, sustained dialogue is a useful resource for enabling sharing of religious values and crystallization of policies. (shrink)

Aristotle is oftentimes viewed through a strictly philosophical lens as heir to Plato and has having introduced logical rigor where an emphasis on the theory of Forms formerly prevailed. It must be appreciated that Aristotle was the son of a physician, and that his inculcation of the thought of other Greek philosophers addressing health and the natural elements led to an extremely broad set of biologically- and medically-related writings. As this article proposes, Aristotle deepened the fourfold theory of the elements (...) with anatomic and physiologic observations. In books like History of Animals, Parts of Animals, and the lost Anatomai, he actively dissected organisms and recorded his findings. The corpus of medically-related literature Aristotle developed had a direct influence on subsequent Greek thinkers, including Galen, and on Medieval Islamic and modern Western practitioners such as William Harvey. Aristotle's ideas continue to influence modern medical thinkers in Europe and America through both his interpretation by European philosophers gaining the attention of medical humanists, and his writings' enduring impact on medical researchers balancing scientific with more personalistic approaches to medicine. (shrink)

The estrangement between genetic scientists and theologians originating in the 1960s is reflected in novel combinations of human thought (subject) and genes (investigational object), paralleling each other through the universal process known in chaos theory as self-similarity. The clash and recombination of genes and knowledge captures what Philip Hefner refers to as irony, one of four voices he suggests transmit the knowledge and arguments of the religion-and-science debate. When viewed along a tangent connecting irony to leadership, journal dissemination, and the (...) activities of the "public intellectual" and the public at large, the sequence of voices is shown to resemble the passage of genetic information from DNA to mRNA, tRNA, and protein, and from cell nucleus to surrounding environment. In this light, Hefner's inquiry into the voices of Zygon is bound up with the very subject matter Zygon covers. (shrink)

This paper outlines the demographic characteristics of the Baiga tribe, one of the most primitive of the aboriginal tribal groups of Central India. The Baiga population has grown steadily since the first anthropological study of the tribe in the 1930s. Age at menarche, age at marriage, breast-feeding, and time interval between marriage and first conception are natural. There are more females than males. Sub-tribe endogamy is common; consanguineous marriage is favoured (34% of marriages are between first cousins) and marital distance (...) is low (mean 7·1 km). Though the mean menarcheal age is high (15·2 years), mean age at first marriage is low (16·6 years), giving a long reproductive period. (shrink)

Coherence and correspondence are classical contenders as theories of truth. In this paper we examine them instead as interacting factors in the dynamics of belief across epistemic networks. We construct an agent-based model of network contact in which agents are characterized not in terms of single beliefs but in terms of internal belief suites. Individuals update elements of their belief suites on input from other agents in order both to maximize internal belief coherence and to incorporate ‘trickled in’ elements of (...) truth as correspondence. Results, though often intuitive, prove more complex than in simpler models (Hegselmann & Krause 2002, 2006; Grim, Singer, Reade & Fisher 2015). The optimistic finding is that pressures toward internal coherence can exploit and expand on small elements of truth as correspondence is introduced into epistemic networks. Less optimistic results show that pressures for coherence can also work directly against the incorporation of truth, particularly when coherence is established first and new data is introduced later. (shrink)

Models are of central importance in many scientific contexts. The centrality of models such as inflationary models in cosmology, general-circulation models of the global climate, the double-helix model of DNA, evolutionary models in biology, agent-based models in the social sciences, and general-equilibrium models of markets in their respective domains is a case in point (the Other Internet Resources section at the end of this entry contains links to online resources that discuss these models). Scientists spend significant amounts of time building, (...) testing, comparing, and revising models, and much journal space is dedicated to interpreting and discussing the implications of models. In short, models are one of the principal instruments of modern science. (shrink)

The chapter argues that a model‐building methodology like that widespread in contemporary natural and social science already plays a significant role in philosophy. One neglected form of progress in philosophy over the past fifty years has been the development of better and better formal models of significant phenomena. Examples are given from both philosophy of language and epistemology. Philosophy can do still better in the future by applying model‐building methods more systematically and self‐consciously, with consequent readjustments to its methodology. Although (...) it is neither likely nor desirable for model‐building to become the sole or even main philosophical method, its use enhances the power and reliability of philosophical thinking. (shrink)

Biologists, climate scientists, and economists all rely on models to move their work forward. In this book, I explore the use of models in these and other fields to introduce readers to the various philosophical issues that arise in scientific modeling. I show that paying attention to models plays a crucial role in appraising scientific work. -/- After surveying a wide range of models from a number of different scientific disciplines, I demonstrate how focusing on models sheds light on many (...) perennial issues in philosophy of science and in philosophy in general. For example, reviewing the range of views on how models represent their targets introduces readers to the key issues in debates on representation, not only in science but in the arts as well. Also, standard epistemological questions are cast in new and interesting ways when we confront the question, "What makes for a good (or bad) model?". (shrink)

Current work in language models (LMs) helps us speed up or even skip thinking by accelerating and automating cognitive work. But can LMs help us with critical thinking -- thinking in deeper, more reflective ways which challenge assumptions, clarify ideas, and engineer new concepts? We treat philosophy as a case study in critical thinking, and interview 21 professional philosophers about how they engage in critical thinking and on their experiences with LMs. We find that philosophers do not find LMs to (...) be useful because they lack a sense of selfhood (memory, beliefs, consistency) and initiative (curiosity, proactivity). We propose the selfhood-initiative model for critical thinking tools to characterize this gap. Using the model, we formulate three roles LMs could play as critical thinking tools: the Interlocutor, the Monitor, and the Respondent. We hope that our work inspires LM researchers to further develop LMs as critical thinking tools and philosophers and other 'critical thinkers' to imagine intellectually substantive uses of LMs. (shrink)

Science and fiction seem to lie at opposite ends of the cognitive-epistemic spectrum. The former is typically seen as the study of hard, real-world facts in a rigorous manner. The latter is treated as an instrument of play and recreation, dealing in figments of the imagination. Initial appearances notwithstanding, several central features of scientific modeling in fact suggest a close connection with the imagination and recent philosophers have developed detailed accounts of models that treat them, in one way or another, (...) as akin to fictions. This chapter will critically discuss the fictions approach as an epistemology of scientific modeling. (shrink)

Philosophical interest in thought experiments has grown over the last couple of decades. Several positions have emerged, defined largely by their differing responses to a perceived epistemological challenge: how do thought experiments yield justified belief revision, even in science, when they provide no new empirical data? Attitudes towards this supposed explanandum differ. Many philosophers accept that it poses a genuine puzzle and hence seek to provide a substantive explanation. Others reject or deflate the epistemic claims made for thought experiments.In this (...) paper I present a model for many thought experiments in philosophy and science. The model doesn't assume that thought experiments in fact manage to achieve epistemic justifi cation, but it allows us to see how they aspire to do so. It also emphasises both the parallels and the discrepancies between thought experiments and ordinary scientific experiments. (shrink)

Instead of arguing for a specific animal model, Striedter will review the history and philosophy of animal models in biomedical research, examining their various advantages and limitations.

Research on natural and artificial brains is proceeding at a rapid pace. However, the understanding of the essence of consciousness has changed slightly over the millennia, and only the last decade has brought some progress to the area. Scientific ideas emerged that the soul could be a product of the material body and that calculating machines could imitate brain processes. However, the authors of this book reject the previously common dualism—the view that the material and spiritual-psychic processes are separate and (...) require a completely different substance as their foundation. -/- Reductive Model of the Conscious Mind is a forward-thinking book wherein the authors identify processes that are the essence of conscious thinking and place them in the imagined, simplified structure of cells able to memorize and transmit information in the form of impulses, which they call neurons. The purpose of the study is to explain the essence of consciousness to the degree of development of natural sciences, because only the latter can find a way to embed the concept of the conscious mind in material brains. The book is divided into three parts. Part 1 works to convince readers that the emergence of consciousness does not require detailed knowledge of the structure and morphology of the brain, with the exception of some specific properties of the neural network structure that the authors attempt to point out. Part 2 proves that the biological structure of many natural brains fulfills the necessary conditions for consciousness and intelligent thinking. Similarly, Part 3 shows the ways in which artificial creatures imitating natural brains can meet these conditions, which gives great hopes for building artificially intelligent beings endowed with consciousness. Covering topics that include cognitive architecture, the embodied mind, and machine learning, this book is ideal for cognitive scientists, philosophers of mind, neuroscientists, psychologists, researchers, academicians, and advanced-level students. The book can also help to focus the research of linguists, neurologists, and biophysicists on the biophysical basis of postulated information processing into knowledge structures. (shrink)

Safeguarding GenAI models against threats and aligning them with security requirements is imperative yet challenging. This chapter provides an overview of the security landscape for generative models. It begins by elucidating common vulnerabilities and attack vectors, including adversarial attacks, model inversion, backdoors, data extraction, and algorithmic bias. The practical implications of these threats are discussed, spanning domains like finance, healthcare, and content creation. The narrative then shifts to exploring mitigation strategies and innovative security paradigms. Differential privacy, blockchain-based provenance, quantum-resistant algorithms, (...) and human-guided reinforcement learning are analyzed as potential techniques to harden generative models. Broader ethical concerns surrounding transparency, accountability, deepfakes, and model interpretability are also addressed. The chapter aims to establish a conceptual foundation encompassing both the technical and ethical dimensions of security for generative AI. It highlights open challenges and lays the groundwork for developing robust, trustworthy, and human-centric solutions. The multifaceted perspective spanning vulnerabilities, implications, and solutions is intended to further discourse on securing society’s growing reliance on generative models. Frontier model security is discussed using Anthropic proposed approach. (shrink)

This chapter distinguishes two different modeling relations between vehicles and targets: design relation and representation relation. The relations are characterized by their different directions of fit. Three examples of modeling enterprises are discussed: a bioengineering model, called the “lung chip,” an architectural model, called the “weekend cottage,” and an engineering design model, called the “jet engine.” The two modeling relations with different directions of fit are analyzed in the three examples. The lung chip is standing in a representation relation to (...) its corresponding target and the modeling of the cottage involves a design relation to its target. With the help of these examples a basic assumption of philosophy of engineering and philosophy of technology is challenged. These examples show that it is not strictly speaking true that engineering modeling is exclusively about how things should be rather than about how things are. It is shown that a representation relation is prominently involved in the first model of the lung chip. This modeling involves reasoning about how things are rather than about how things should be. So, one modeling enterprise seems to be rather about what is than about what should be. The other two examples may be seen as confirming evidence for the basic assumption. What is common to all three models is that they involve design and representation relations. (shrink)

Models and theories are of central importance in science, and scientists spend substantial amounts of time building, testing, comparing and revising models and theories. It is therefore not surprising that the nature of scientific models and theories has been a widely debated topic within the philosophy of science for many years. The product of two decades of research, in this book Roman Frigg provides an accessible yet critical introduction to the debates about models and theories within analytical philosophy of science (...) since the 1920s. Models and Theories is the first book to address the topic from a philosophical perspective, making it essential reading for advanced undergraduates, researchers, and professional philosophers working in philosophy of science, philosophy of mathematics, and philosophy of technology. It will also be of interest to philosophically minded readers working in physics, computer sciences and STEM fields more broadly. (shrink)

This chapter explains the screening‐off rule in the psychological laboratory. The Markov assumption states that any variable in a set is independent in probability of all its ancestors in the set conditional on its own parents. The screening‐off rule is also critical to allow Bayes nets to make an inference of the state of an unknown variable in a causal structure from the states of other variables in that structure. The chapter examines which causal representations people use to make predictions (...) and whether people conform to the screening‐off rule with respect to a causal model they have in mind. It analyzes what leads them to modify their causal model and whether or not people are causally oriented when making predictions. Making probability judgments is hard and requires careful deliberation. People are capable of such deliberation although they avoid it until they cannot, until the facts require more careful thought. (shrink)

Les modèles basés sur des agents en interactions, constituent des systèmes sociaux complexes, qui peuvent être simulés par informatiques. Ils se répandent dans les sciences économiques et sociales - comme dans la plupart des sciences des systèmes complexes. Des énigmes épistémologiques (ré)apparaissent. On a souvent opposé modèles et investigations empiriques : d’un côté, on considère les sciences empiriques fondées sur une observation méthodique (enquêtes, expériences) tandis que de l’autre, on conçoit les approches théoriques et la modélisation comme s’appuyant sur une (...) approche conceptuelle ou hypothético-déductive. la simulation a de son coté souvent été comparée à une forme d’expérience ou à une méthode intermédiaire entre la théorie et l’expérience. Tesfatsion a parlé de « laboratoire computationnel » comme d’une manière d’étudier « les comportements des systèmes complexes au moyen d’expériences sous contrôle qu’on peut répéter (réplicable)» et Axelrod a proclamé que la simulation serait « une troisième manière de pratiquer la science dans les sciences sociales », entre l’induction et la déduction. Nous introduisons de nouveaux concepts épistémologiques afin de montrer dans quelle mesure les auteurs ont raison lorsqu'ils se concentrent sur une signification empirique, instrumentale ou conceptuelle de leur modèle ou simulation. La première partie du chapitre discute plus particulièrement de l'épistémologie des modèles économiques à partir des travaux d’Hausman, Guala, Mäki, Sugden, Schelling etc. pour expliquer les divergences entre modèles et simulations. En distinguant entre modèles et simulations, comme entre entre types de modèles, types de simulations informatiques et types d'empiricité obtenue par une simulation, la seconde partie donne la possibilité de comprendre plus précisément - et ensuite de justifier - la diversité des positions épistémologiques présentées dans la première partie. En utilisant les notion de sous-symbolisation (due à Smolensky) et, de hiérarchie dénotationnelle (due à Goodman), une attention particulière est accordée à la multiplicité des pouvoirs dénotationnels des symboles en jeu dans les modèles complexes et les simulations informatiques. Selon cette grille d'analyse, on peut déterminer, dans chaque cas particulier son statut épistémique et la crédibilité qui peut y être associée. -/- Ce chapitre est une traduction (par Gilles Campagnolo) réviséee et augmentée par les auteurs de : Agent-Based Models and Simulations in Economics and Social Sciences: From Conceptual Exploration to Distinct Ways of Experimenting, Journal of Artificial Societies and Social Simulation 13 (1) 5 DOI: 10.18564/jasss.1532. (shrink)