This paper is concerned with reasonings that purport to explain why certain organisms have certain traits by showing that their actual design is better than contrasting designs. Biologists call such reasonings 'functional explanations'. To avoid confusion with other uses of that phrase, I call them 'design explanations'. This paper discusses the structure of design explanations and how they contribute to scientific understanding. Design explanations are contrastive and often compare real organisms to hypothetical organisms that cannot possibly (...) exist. They are not causal but appeal to functional dependencies between an organism's different traits. These explanations point out that because an organism has certain traits, it cannot be alive if the trait to be explained were replaced by a specified alternative. They can be understood from a mechanistic point of view as revealing the constraints on what mechanisms can be alive. (shrink)

In this paper we assess the explanatory role of idealizations in ‘design explanations’, a type of functional explanation used in biology. In design explanations, idealizations highlight which factors make a difference to phenomena to be explained: hypothetical, idealized, organisms are invoked to make salient which traits of extant organisms make a difference to organismal fitness. This result negates the view that idealizations serve only pragmatic benefits, and complements the view that idealizations highlight factors that do not make (...) a difference. This analysis in particular strengthens the perspective that idealizations are means to highlight difference making factors, and identifies a novel, more direct role for idealizations in doing so. It thus offers a novel argument why in some explanatory contexts idealizations are in-eliminable. (shrink)

In this paper we assess the explanatory role of idealizations in ‘design explanations’, a type of functional explanation used in biology. In design explanations, idealizations highlight which factors make a difference to phenomena to be explained: hypothetical, idealized, organisms are invoked to make salient which traits of extant organisms make a difference to organismal fitness. This result negates the view that idealizations serve only pragmatic benefits, and complements the view that idealizations highlight factors that do not make (...) a difference. This analysis in particular strengthens the perspective that idealizations are means to highlight difference making factors, and identifies a novel, more direct role for idealizations in doing so. It thus offers a novel argument why in some explanatory contexts idealizations are in-eliminable. (shrink)

In the recent literature on explanation in biology, increasing attention is being paid to the connection between design explanation and mechanistic explanation, viz. the role of design principles and heuristics for mechanism discovery and mechanistic explanation. In this paper we extend the connection between design explanation and mechanism discovery by prizing apart two different types of design explanation and by elaborating novel heuristics that one specific type offers for mechanism discovery (...) across species. We illustrate our claims in terms of two lines of biological research on the biological advantages of organismal traits, one on the eye-size of giant squid, the other on foraging habits of specific bat species. We argue that this research illustrates useful heuristics for mechanism discovery across species, viz. reasoning strategies to infer likely mechanisms for a certain biological role based on assessments of the environmental conditions in which the role is performed efficiently and less or in-efficiently. We bring out the novel features of our analysis in terms of a comparison with mechanistic approaches to mechanism discovery, amongst which graph-theoretical ones, and by comparing the different types of design explanation and the discovery heuristics they support. (shrink)

In the recent literature on explanation in biology, increasing attention is being paid to the connection between design explanation and mechanistic explanation, viz. the role of design principles and heuristics for mechanism discovery and mechanistic explanation. In this paper we extend the connection between design explanation and mechanism discovery by prizing apart two different types of design explanation and by elaborating novel heuristics that one specific type offers for mechanism discovery (...) across species. We illustrate our claims in terms of two lines of biological research on the biological advantages of organismal traits, one on the eye-size of giant squid, the other on foraging habits of specific bat species. We argue that this research illustrates useful heuristics for mechanism discovery across species, viz. reasoning strategies to infer likely mechanisms for a certain biological role based on assessments of the environmental conditions in which the role is performed efficiently and less or in-efficiently. We bring out the novel features of our analysis in terms of a comparison with mechanistic approaches to mechanism discovery, amongst which graph-theoretical ones, and by comparing the different types of design explanation and the discovery heuristics they support. (shrink)

Given the pervasiveness of AI systems and their potential negative effects on people’s lives (especially among already marginalised groups), it becomes imperative to comprehend what goes on when an AI system generates a result, and based on what reasons, it is achieved. There are consistent technical efforts for making systems more “explainable” by reducing their opaqueness and increasing their interpretability and explainability. In this paper, we explore an alternative non-technical approach towards explainability that complement existing ones. Leaving aside technical, statistical, (...) or data-related issues, we focus on the very conceptual underpinnings of the design decisions made by developers and other stakeholders during the lifecycle of a machine learning project. For instance, the design and development of an app to track snoring to detect possible health risks presuppose some picture or another of “health”, which is a key notion that conceptually underpins the project. We take it as a premise that these key concepts are necessarily present during design and development, albeit perhaps tacitly. We argue that by providing “justificatory explanations” about how the team understands the relevant key concepts behind its design decisions, interested parties could gain valuable insights and make better sense of the workings and outcomes of systems. Using the concept of “health”, we illustrate how a particular understanding of it might influence decisions during the design and development stages of a machine learning project, and how making this explicit by incorporating it into ex-post explanations might increase the explanatory and justificatory power of these explanations. We posit that a greater conceptual awareness of the key concepts that underpin design and development decisions may be beneficial to any attempt to develop explainability methods. We recommend that “justificatory explanations” are provided as technical documentation. These are declarative statements that contain at its simplest: (1) a high-level account of the understanding of the relevant key concepts a team possess related to a project’s main domain, (2) how these understandings drive decision-making during the life-cycle stages, and (3) it gives reasons (which could be implicit in the account) that the person or persons doing the explanation consider to have plausible justificatory power for the decisions that were made during the project. (shrink)

In this essay I propose that what design principles in systems biology and systems neuroscience do is to present abstract characterizations of mechanisms, and thereby facilitate mechanistic explanation. To show this, one design principle in systems neuroscience, i.e., the multilayer perceptron, is examined. However, Braillard (2010) contends that design principles provide a sort of non-mechanistic explanation due to two related reasons: they are very general and describe non-causal dependence relationships. In response to this, I argue (...) that, on the one hand, all mechanisms are more or less general (or abstract), and on the other, many (if not all) design principles are causal systems. (shrink)

Design plays an integral role in the functions of modern society. Yet the abstract process by which designers carry out their work is not obvious. The study of design thinking has grown in recent years into a major area of academic research, yet it presently lacks a clear theoretical basis; and as a discipline, its methodologies are disparate. Here, we outline and clarify the framework of the scholarly study of design thinking, introducing the major ideas and concepts (...) upon which the field is based. We then discuss in detail the various methodological issues of the field, and argue that, in its current state, the field of design thinking cannot sustain itself as an independent area of academic research. We suggest that design thinking may best be studied from a sociological or science, technology, and society (STS) studies perspective. (shrink)

In this essay I propose that what design principles in systems biology and systems neuroscience do is to present abstract characterizations of mechanisms, and thereby facilitate mechanistic explanation. To show this, one design principle in systems neuroscience, i.e., the multilayer perceptron, is examined. However, Braillard contends that design principles provide a sort of non-mechanistic explanation due to two related reasons: they are very general and describe non-causal dependence relationships. In response to this, I argue that, (...) on the one hand, all mechanisms are more or less general, and on the other, many design principles are causal systems. (shrink)

My understanding is that proximate explanations concern adaptive mechanism and that ultimate explanations concern adaptive rationale. Viewed in this light, the two kinds of explanation are quite distinct, but they interact in a complementary way to give a full understanding of biological adaptations. In contrast, Laland et al. (2013)—following a literal reading of Mayr (Science 134:1501–1506, 1961)—have characterized ultimate explanations as concerning any and all mechanisms that have operated over the course of an organism’s evolutionary history. This has unfortunate (...) consequences, such as allowing random drift to form the basis for ultimate explanations, and allowing proximate and ultimate explanations to bleed into each other until their distinction is meaningless. Here, I suggest Laland et al’s explanatory framework of “reciprocal causation” is not conducive to successful biological science, and that they have misunderstood key elements of the theory of Darwinian adaptation. (shrink)

This essay argues that, despite the failure of demarcation criteria for separating science from non-science, the mathematics of design and design-theoretic inferences nonetheless satisfy all the criteria of various competing theories of scientific explanation.

We propose a formal framework for interpretable machine learning. Combining elements from statistical learning, causal interventionism, and decision theory, we design an idealised explanation game in which players collaborate to find the best explanation for a given algorithmic prediction. Through an iterative procedure of questions and answers, the players establish a three-dimensional Pareto frontier that describes the optimal trade-offs between explanatory accuracy, simplicity, and relevance. Multiple rounds are played at different levels of abstraction, allowing the players to (...) explore overlapping causal patterns of variable granularity and scope. We characterise the conditions under which such a game is almost surely guaranteed to converge on a optimal explanation surface in polynomial time, and highlight obstacles that will tend to prevent the players from advancing beyond certain explanatory thresholds. The game serves a descriptive and a normative function, establishing a conceptual space in which to analyse and compare existing proposals, as well as design new and improved solutions. (shrink)

This Element analyzes the various forms that design arguments for the existence of God can take, but the main focus is on two such arguments. The first concerns the complex adaptive features that organisms have. Creationists who advance this argument contend that evolution by natural selection cannot be the right explanation. The second design argument - the argument from fine-tuning - begins with the fact that life could not exist in our universe if the constants found in (...) the laws of physics had values that differed more than a little from their actual values. Since probability is the main analytical tool used, the book provides a primer on probability theory. (shrink)

This paper examines the explanatory distinctness of wiring optimization models in neuroscience. Wiring optimization models aim to represent the organizational features of neural and brain systems as optimal (or near-optimal) solutions to wiring optimization problems. My claim is that that wiring optimization models provide design explanations. In particular, they support ideal interventions on the decision variables of the relevant design problem and assess the impact of such interventions on the viability of the target system.

As idealized descriptions of mathematical language, there is a sense in which formal systems specify too little, and there is a sense in which they specify too much. On the one hand, formal languages fail to account for a number of features of informal mathematical language that are essential to the communicative and inferential goals of the subject. On the other hand, many of these features are independent of the choice of a formal foundation, so grounding their analysis on a (...) particular choice of a formal system introduces unnecessary specificity. This chapter begins to map out the design features of mathematical language without descending to the level of formal implementation, drawing on examples from the mathematical literature and insights from the design of computational proof assistants and their libraries. (shrink)

The informational humidity model (IHM) classifies a message into two modes, and describes communication and community in a novel aspect. At first, a flame message, dry information vs. wet information, is introduced. Dry information is the message content itself, whereas wet information is the attributes of the message sender. Second, the characteristics of communities are defined by two factors: the message sender’s personal specifications, and personal identification. These factors affect the humidity of the community, which corresponds to two phases of (...) knowledge creation. In a rather wet community, members easily specify other members. This is effective for managing memberships and changing knowledge from tacit to formal. In a rather dry community, members barely identify with other members at all. This method is suitable for the formal-to-tacit phase of knowledge creation. Finally, it is discussed how social intelligence should be designed and what features are needed to support knowledge-creating communities. (shrink)

Shoot an arrow at a wall, and then paint a target around it so that the arrow sticks squarely in the bull's eye. Alternatively, paint a fixed target on a wall, and then shoot an arrow so that it sticks squarely in the bull's eye. How do these situations differ? In both instances the precise place where the arrow lands is highly improbable. Yet in the one, one can do no better than attribute the arrow's landing to chance, whereas in (...) the other one rightly attributes the arrow's landing to the archer's skill. ;Highly improbable events occur all the time, and by themselves may legitimately be attributed to chance. Yet when an event also conforms to a pattern given independently of that event , one rightly refuses to attribute the event to chance. Patterns given independently of events are called specifications. This dissertation explicates the relation of independence between specification and event, and sets precise bounds on what may count as a probability small enough to eliminate chance. Although this dissertation connects with how statistics eliminates chance, it considerably extends and clarifies the range of application for chance-elimination arguments based on small probabilities. ;The dual notions of specification and small probability together help justify a regulative principle of probability called the Law of Small Probability, which asserts that specified events of small probability do not occur by chance. This principle engenders a form of inference called the design inference, and a mode of explanation called design. To infer design in explaining an event is to eliminate decisively explanations of that event which appeal to law-like regularities or chance. (shrink)

There are two different, and somewhat competing, strategic explanations for why firms certify for ISO 14001. On the one hand, firms may seek to reinforce their present strategies thereby further enhancing their competitive advantage. On the other hand, firms may use ISO 14001 as a mechanism to reorient their strategies, so that a clear signal is sent about the firm's change in strategic positioning. This paper aims to identify the most likely explanation for early adopters of ISO 14001. Using (...) a matched pair design, we test these alternative explanations on a sample of US firms that certified for ISO 14001 in the first two years after its introduction. In particular, we tested whether ISO 14001 was used to reinforce or reorient firm strategies in respect to the natural environment, corporate social responsibility, quality, and internationalization. We found that firms that certified early for ISO 14001 had considerable environmental legitimacy and a strong international presence. We also found that the firm's commitment to corporate social responsibility and quality were not significantly different between certified and non-certified firms. These findings suggest that early adopters of ISO 14001 leaned towards reinforcing rather than reorienting their firm strategy, which calls into question the ultimate reach of ISO 14001. (shrink)

In this essay I suggest that we view design principles in systems biology as minimal models, for a design principle usually exhibits universal behaviors that are common to a whole range of heterogeneous (living and nonliving) systems with different underlying mechanisms. A well-known design principle in systems biology, integral feedback control, is discussed, showing that it satisfies all the conditions for a model to be a minimal model. This approach has significant philosophical implications: it not only accounts (...) for how design principles explain, but also helps clarify one dispute over design principles, e.g., whether design principles provide mechanistic explanations or a distinct kind of explanations called design explanations. (shrink)

We propose a formal framework for interpretable machine learning. Combining elements from statistical learning, causal interventionism, and decision theory, we design an idealised explanation game in which players collaborate to find the best explanation for a given algorithmic prediction. Through an iterative procedure of questions and answers, the players establish a three-dimensional Pareto frontier that describes the optimal trade-offs between explanatory accuracy, simplicity, and relevance. Multiple rounds are played at different levels of abstraction, allowing the players to (...) explore overlapping causal patterns of variable granularity and scope. We characterise the conditions under which such a game is almost surely guaranteed to converge on a optimal explanation surface in polynomial time, and highlight obstacles that will tend to prevent the players from advancing beyond certain explanatory thresholds. The game serves a descriptive and a normative function, establishing a conceptual space in which to analyse and compare existing proposals, as well as design new and improved solutions. (shrink)

This article deals with a type of functional explanation, viability explanation, that has been overlooked in recent philosophy of science. Viability explanations relate traits of organisms and their environments in terms of what an individual needs to survive and reproduce. I show that viability explanations are neither causal nor historical and that, therefore, they should be accounted for as a distinct type of explanation.

This work presents a requirement analysis for collaborative dialogues among medical experts and an inquiry dialogue game based on this analysis for incorporating explainability into multiagent system design. The game allows experts with different knowledge bases to collaboratively make recommendations while generating rich traces of the reasoning process through combining explanation-based illocutionary forces in an inquiry dialogue. The dialogue game was implemented as a prototype web-application and evaluated against the specification through a formative user study. The user study (...) confirms that the dialogue game meets the needs for collaboration among medical experts. It also provides insights on the real-life value of dialogue-based communication tools for the medical community. (shrink)

In Aristotle's teleological view of the world, natural things come to be and are present for the sake of some function or end. Whereas much of recent scholarship has focused on uncovering the physical underpinnings of Aristotle's teleology and its contrasts with his notions of chance and necessity, this book examines Aristotle's use of the theory of natural teleology in producing explanations of natural phenomena. Close analyses of Aristotle's natural treatises and his Posterior Analytics show what methods are used for (...) the discovery of functions or ends that figure in teleological explanations, how these explanations are structured, and how well they work in making sense of phenomena. The book will be valuable for all who are interested in Aristotle's natural science, his philosophy of science, and his biology. (shrink)

The design argument was rebutted by David Hume. He argued that the world and its contents (such as organisms) were not analogous to human artifacts. Hume further suggested that there were equally plausible alternatives to design to explain the organized complexity of the cosmos, such as random processes in multiple universes, or that matter could have inherent properties to self-organize, absent any external crafting. William Paley, writing after Hume, argued that the functional complexity of living beings, however, defied (...) naturalistic explanations. In effect he dared anyone to come up with an alternative to his inference to design, and hence a designer, outside of nature. Charles Darwin explained the apparent design of functional complexity by his theory of natural selection. Asa Gray, however, in essays as well as in correspondence with Darwin argued that natural selection allowed for a type of ' evolutionary teleology' in which design at most could be considered the result of universal principles. F. E. Hicks updated Hume by specifically objecting to the use of design arguments by Paley. Hicks argued that the apparent design seen in nature reflected order at a deep level in nature. The design argument was briefly revived by Lawrence Henderson early in the twentieth century but he ultimately concluded that design and teleology were not necessarily mutually entailing and he retracted his design argument in favor of one that he termed ' natural teleology'. The current claims of ' intelligent design' have the same logical problems that have beset previous design arguments. If design is divorced from teleology and its discontents put behind us, then there is a possibility that the latter can have a place in the development of theories to explain the phenomena of emergent complexity. (shrink)

We propose a formal framework for interpretable machine learning. Combining elements from statistical learning, causal interventionism, and decision theory, we design an idealisedexplanation gamein which players collaborate to find the best explanation(s) for a given algorithmic prediction. Through an iterative procedure of questions and answers, the players establish a three-dimensional Pareto frontier that describes the optimal trade-offs between explanatory accuracy, simplicity, and relevance. Multiple rounds are played at different levels of abstraction, allowing the players to explore overlapping causal (...) patterns of variable granularity and scope. We characterise the conditions under which such a game is almost surely guaranteed to converge on a (conditionally) optimal explanation surface in polynomial time, and highlight obstacles that will tend to prevent the players from advancing beyond certain explanatory thresholds. The game serves a descriptive and a normative function, establishing a conceptual space in which to analyse and compare existing proposals, as well as design new and improved solutions. (shrink)

This chapter explores the epistemic roles played by connectionist models of cognition, and offers a formal analysis of how connectionist models explain. It looks at how other types of computational models explain. Classical artificial intelligence (AI) programs explain using abductive reasoning, or inference to the best explanation; they begin with the phenomena to be explained, and devise rules that can produce the right outcome. The chapter also looks at several examples of connectionist models of cognition, observing what sorts of (...) constraints are used in their design, and how their results are evaluated. It argues that the point of implementing networks roughly analogous to neural structures is to discover and explores the generic mechanisms at work in the brain, not to deduce the precise activities of specific structures. The chapter explores a formal analysis of the explanations offered, which interprets connectionist models and the cognitive theories they represent as sharing membership in a type of mechanism. (shrink)

Providing meaningful and actionable explanations for end-users is a situated problem requiring the intersection of multiple disciplines to address social, operational, and technical challenges. However, the explainable artificial intelligence community has not commonly adopted or created tangible design tools that allow interdisciplinary work to develop reliable AI-powered solutions. This paper proposes a formative architecture that defines the explanation space from a user-inspired perspective. The architecture comprises five intertwined components to outline explanation requirements for a task: (1) the (...) end-users’ mental models, (2) the end-users’ cognitive process, (3) the user interface, (4) the Human-Explainer Agent, and (5) the agent process. We first define each component of the architecture. Then, we present the Abstracted Explanation Space, a modeling tool that aggregates the architecture’s components to support designers in systematically aligning explanations with end-users’ work practices, needs, and goals. It guides the specifications of what needs to be explained (content: end-users’ mental model), why this explanation is necessary (context: end-users’ cognitive process), to delimit how to explain it (format: Human-Explainer Agent and user interface), and when the explanations should be given. We then exemplify the tool’s use in an ongoing case study in the aircraft maintenance domain. Finally, we discuss possible contributions of the tool, known limitations or areas for improvement, and future work to be done. (shrink)

This paper examines the explanatory distinctness of wiring optimization models in neuroscience. Wiring optimization models aim to represent the organizational features of neural and brain systems as optimal (or near-optimal) solutions to wiring optimization problems. My claim is that that wiring optimization models provide design explanations. In particular, they support ideal interventions on the decision variables of the relevant design problem and assess the impact of such interventions on the viability of the target system.

It is argued that once biological systems reach a certain level of complexity, mechanistic explanations provide an inadequate account of many relevant phenomena. In this article, I evaluate such claims with respect to a representative programme in systems biological research: the study of regulatory networks within single-celled organisms. I argue that these networks are amenable to mechanistic philosophy without need to appeal to some alternate form of explanation. In particular, I claim that we can understand the mathematical modelling techniques (...) of systems biologists as part of a broader practice of constructing and evaluating mechanism schemas. This argument is elaborated by considering the case of bacterial chemotactic networks, where some research has been interpreted as explaining phenomena by means of abstract design principles. (shrink)

The article discusses an idea of how to extend the notion of rigidity to predicates, namely the idea that predicates stand in a certain systematic semantic relation to properties, such that this relation may hold rigidly or nonrigidly. The relation (which I call signification) can be characterised by recourse to canonical property designators which are derived from predicates (or general terms) by means of nominalization: a predicate signifies that property which the derived property designator designates. Whether signification divides into rigid (...) and non-rigid cases will then depend uponwhether canonical property designators divide into rigid and non-rigid ones. But, I shall argue, they do not, and so the only notion of rigidity gained this way is trivial. To show this, I first focus on the kind of canonical property designators which could be thought to be nonrigid, canonical designators such as having the colour of ripe tomatoes which themselves contain non-rigid property designators. An argument to the effect that such complex canonical designators are non-rigid is rebutted, five arguments to the effect that they are rigid are formulated, and finally an explanation of their rigidity based on the general nature of canonical property designators is presented. (shrink)

The "New Atheists" are pulling no punches. If the world of nature needs a designer, they ask, then why wouldn't the designer itself need a designer, too? Or if it can exist without any designer behind it, then why can't we just say the same for the universe and wash our hands of a designer altogether? Interweaving its pursuit of the First Cause with personal stories and humor, this ground-breaking book takes a fresh approach to ultimate questions. While attentive to (...) empirical science, it builds its case not on authoritative pronouncements of experts that readers must take on faith, but instead on a nuanced understanding of universal principles implicit in everyone's experience. Here is essential reading for all people who care about contemplating God, not exclusively as a best-explanation for the findings of science, but also as the surprising-yet-inevitable implication of our commonsense contact with reality. Augros harnesses such intellects as Plato, Aristotle, and Aquinas, ushering into the light a wealth of powerful inferences that have hitherto received little or no public exposure. The result is an easygoing yet extraordinary journey, beginning from the world as we all encounter it and ending in the divine mind" --Cover, p. 4. (shrink)

In this paper we attempt to identify which peer collaboration characteristics may be accountable for conceptual change through interaction. We focus on different socio‐cognitive aspects of the peer dialog and relate these with learning gains on the dyadic as well as the individual level. The scientific topic that was used for this study concerns natural selection, a topic for which students’ intuitive conceptions have been shown to be particularly robust. Learning tasks were designed according to the socio‐cognitive conflict instructional paradigm. (...) After receiving a short instructional intervention on natural selection, paired students were asked to collaboratively construct explanations for certain evolutionary phenomena while engaging in dialectical argumentation. Two quantitative coding schemes were developed, each with a different granularity. The first assessed discrete dialog moves that pertained to dialectical argumentation and to consensual explanation development. The second scheme characterized the dialog as a whole on a number of socio‐cognitive dimensions. Results from analyses on the dyadic as well as the individual level revealed that the engagement in dialectical argumentation predicted conceptual learning gains, whereas consensual explanation development did not. These findings open up new venues for research on the mechanisms of learning in and from peer collaboration. (shrink)

Emotions can be explained as specialized states, shaped by natural selection, that increase fitness in specific situations. The physiological, psychological, and behavioral characteristics of a specific emotion can be analyzed as possible design features that increase the ability to cope with the threats and opportunities present in the corresponding situation. This approach to understanding the evolutionary functions of emotions is illustrated by the correspondence between (a) the subtypes of fear and the different kinds of threat; (b) the attributes of (...) happiness and sadness and the changes that would be advantageous in propitious and unpropitious situations; and (c) the social emotions and the adaptive challenges of reciprocity relationships. In addition to addressing a core theoretical problem shared by evolutionary and cognitive psychology, explicit formulations of the evolutionary functions of specific emotions are of practical importance for understanding and treating emotional disorders. (shrink)

This paper explores the implications of conceptualising phenomenology as explanatory for the ongoing dialogue between the phenomenological tradition and cognitive science, especially enactive approaches to cognition. The first half of the paper offers three interlinked arguments: Firstly, that differentiating between phenomenology and the natural sciences by designating one as descriptive and the other as explanatory undermines opportunities for the kind of productive friction that is required for genuine ‘mutual enlightenment’. Secondly, that conceiving of phenomenology as descriptive rather than explanatory risks (...) committing us to what Zahavi (2019) identifies as the error of equating the phenomenological with the phenomenal. Finally, that the erroneous reduction to the descriptive occludes the rich resources that the phenomenological tradition can contribute to investigations of non-human cognition. The second half of the paper then turns to focus specifically on the promising relationship between phenomenology and enactive approaches to cognition. It will suggest that phenomenology must be seen as having explanatory capacities if it is to shed light on the structures of “mind in life” (Thompson, 2007), before drawing on the model of explanation put forward by Louis Sass to explore what this might look like. (shrink)

Consider an infinite series whose items are each explained by their immediate successor. Does such an infinite explanation explain the whole series or does it leave something to be explained? Hume arguably claimed that it does fully explain the whole series. Leibniz, however, designed a very telling objection against this claim, an objection involving an infinite series of book copies. In this paper, I argue that the Humean claim can, in certain cases, be saved from the Leibnizian “infinite book (...) copies” objection, and that this provides an interesting way to defuse some cosmological arguments for the existence of God and to give a non-theistic but complete explanation of the Universe. In the course of my argumentation, I also show that circular explanations can be “self-explanatory” as well: explaining two items by each other can explain the couple of items tout court. (shrink)

Mechanistic models in molecular systems biology are generally mathematical models of the action of networks of biochemical reactions, involving metabolism, signal transduction, and/or gene expression. They can be either simulated numerically or analyzed analytically. Systems biology integrates quantitative molecular data acquisition with mathematical models to design new experiments, discriminate between alternative mechanisms and explain the molecular basis of cellular properties. At the heart of this approach are mechanistic models of molecular networks. We focus on the articulation and development of (...) mechanistic models, identifying five constraints which guide the articulation of models in molecular systems biology. These constraints are not independent of one another, with the result that modeling becomes an iterative process. We illustrate the use of these constraints in the modeling of the mechanism for bistability in the lac operon. (shrink)

The design argument was rebutted by David Hume. He argued that the world and its contents (such as organisms) were not analogous to human artifacts. Hume further suggested that there were equally plausible alternatives to design to explain the organized complexity of the cosmos, such as random processes in multiple universes, or that matter could have inherent properties to self-organize, absent any external crafting. William Paley, writing after Hume, argued that the functional complexity of living beings, however, defied (...) naturalistic explanations. In effect he dared anyone to come up with an alternative to his inference to design, and hence a designer, outside of nature. Charles Darwin explained the apparent design of functional complexity by his theory of natural selection. Asa Gray, however, in essays as well as in correspondence with Darwin argued that natural selection allowed for a type of ‘evolutionary teleology’ in which design at most could be considered the result of universal principles. F.E. Hicks updated Hume by specifically objecting to the use of design arguments by Paley. Hicks argued that the apparent design seen in nature reflected order at a deep level in nature. The design argument was briefly revived by Lawrence Henderson early in the twentieth century but he ultimately concluded that design and teleology were not necessarily mutually entailing and he retracted his design argument in favor of one that he termed ‘natural teleology’. The current claims of ‘intelligent design’ have the same logical problems that have beset previous design arguments. If design is divorced from teleology and its discontents put behind us, then there is a possibility that the latter can have a place in the development of theories to explain the phenomena of emergent complexity. (shrink)

This paper critiques the new mechanistic explanatory program on grounds that, even when applied to the kinds of examples that it was originally designed to treat, it does not distinguish correct explanations from those that blunder. First, I offer a systematization of the explanatory account, one according to which explanations are mechanistic models that satisfy three desiderata: they must 1) represent causal relations, 2) describe the proper parts, and 3) depict the system at the right ‘level.’ Second, I argue that (...) even the most developed attempts to fulfill these desiderata fall short by failing to appropriately constrain explanatorily apt mechanistic models. -/- *This paper used to be called "The Emperor's New Mechanisms". (shrink)

In his recent anthology, Intelligent Design Creationism and Its Critics, Robert Pennock continues his attack on what he considers to be the pseudoscience of Intelligent Design Theory. In this critical review, I discuss the main issues in the debate. Although the rhetoric is often heavy and the articles are intentionally stacked against Intelligent Design, there are many interesting topics in the philosophy of science to be found. I conclude that, contra Pennock, there is nothing intrinsically unscientific about (...) Intelligent Design. At this stage, however, it remains more of a provocative idea than a research program. Whether design theorists can bridge this gap is still very much in question. In any case, the debate serves as a modern case study for such classic problems as the nature of scientific explanations, theory change, the demarcation problem, and the role of metaphysical assumptions in the development of science. (shrink)

This contribution to design methodology reflects upon the barriers to effectiveness imposed by our tendency to gravitate towards the over-formal in human affairs. We see a correspondingly cleaned-up description of the process of design, a failure to consider its jagged elements and to take proper account of the non-formal in knowledge (e.g. tacit knowledge) and communication. Discipline in methodology is accordingly wrongly equated with formality. The failure of design to be effective is more likely for innovative (...) class='Hi'>design rather than routine design.It is suggested by way of explanation that design methodology especially in the field of information technology is infused with the ghost of positivism, manifest in an unconditional belief in the value of rationality and an implied naive realist conviction about the fixed, singular and transparent nature of the environment for which design is undertaken.We need to be able to work with uncertainty rather than try for its entire elimination. A breadth of approach in carrying out the activity of design is threatened by lack of attention to the variety of forms which knowledge and corresponding forms of discourse can take.We undertake the disciplined reduction from the messy real work to metaphors tidy enough to work with, or models as they are usually misnamed.The notion of “language of struggle” is invoked as a suitable metaphor for the non-formal discourse particularly relevant to innovative design. A complementary exploration is offered of socio-linguistic space which is the common context for design.In view of the concern with social space necessary to effective design, it may be enlightening to consider the designer as applied anthropologist. (shrink)

Like many, though of course not all, philosophers, I believe in propositions. I take propositions to be structured, sentence-like entities whose structures are identical to the syntactic structures of the sentences that express them; and I have defended a particular version of such a view of propositions elsewhere. In the present work, I shall assume that the structures of propositions are at least very similar to the structures of the sentences that express them. Further, I shall assume that ordinary names (...) are devices of direct reference and contribute only their bearers to propositions, that n-place predicates contribute n-place properties or relations to propositions, and that verbs of propositional attitude contribute to propositions two-place relations between individuals and propositions. The broad outline of a framework that includes these assumptions is one that I think many, though again not all, philosophers of language find congenial. I am concerned here to investigate and explain, from the standpoint of this framework, a puzzling phenomenon. The explanation I give of the phenomenon could be adapted to fit with frameworks somewhat different from the one adopted here. I adopt the present framework in part simply for definiteness. (shrink)

The cosmological and teleological argument both start with some contingent feature of the actual world and argue that the best or only explanation of that feature is that it was produced by an intelligent and powerful supernatural being. The cosmological argument starts with a general feature, such as the existence of contingent being or the presence of motion and uses some version of the Principle of Sufficient Reason to conclude that this feature must have an explanation. The debate (...) then focuses on two points: first, whether the PSR in question is true, and second, whether the explanation must involve God or at least some God-like being. The teleological argument begins with a general feature of the cosmos judged to have value, such as the existence of intelligent life or the presence of order in the universe, and argues, usually inductively but sometimes deductively, that this feature is to be explained by the agency of a powerful supernatural being. Here, the debate tends to focus on whether there are alternate naturalistic explanations, such as Darwinian evolution. (shrink)