This paper discusses modeling from the artifactual perspective. The artifactual approach conceives models as erotetic devices. They are purpose-built systems of dependencies that are constrained in view of answering a pending scientific question, motivated by theoretical or empirical considerations. In treating models as artifacts, the artifactual approach is able to address the various languages of sciences that are overlooked by the traditional accounts that concentrate on the relationship of representation in an abstract and general manner. In contrast, (...) the artifactual approach focuses on epistemic affordances of different kinds of external representational and other tools employed in model construction. In doing so, the artifactual account gives a unified treatment of different model types as it circumvents the tendency of the fictional and other representational approaches to separate model systems from their “model descriptions”. (shrink)

How do artifacts get their functions? It is typically thought that an artifact’s function depends on its maker’s intentions. This chapter argues that this common understanding is fatally flawed. Nor can artifact function be understood in terms of current uses or capacities. Instead, it proposes that we understand artifact function on the etiological model that Ruth Millikan and others have proposed for the biological realm. This model offers a robustly normative conception of function, but it does so naturalistically by (...) employing our best scientific theories, in particular natural selection. To help make this case, it proposes “living artifacts” (organisms designed for human purposes through artificial selection) as a bridge between the artifactual and the biological realms. (shrink)

This paper presents an artifactual approach to models that also addresses their fictional features. It discusses first the imaginary accounts of models and fiction that set model descriptions apart from imagined-objects, concentrating on the latter :251–268, 2010; Frigg and Nguyen in The Monist 99:225–242, 2016; Godfrey-Smith in Biol Philos 21:725–740, 2006; Philos Stud 143:101–116, 2009). While the imaginary approaches accommodate surrogative reasoning as an important characteristic of scientific modeling, they simultaneously raise difficult questions concerning how the imagined entities (...) are related to actual representational tools, and coordinated among different scientists, and with real-world phenomena. The artifactual account focuses, in contrast, on the culturally established external representational tools that enable, embody, and extend scientific imagination and reasoning. While there are commonalities between models and fictions, it is argued that the focus should be on the fictional uses of models rather than considering models as fictions. (shrink)

The epistemic value of models has traditionally been approached from a representational perspective. This paper argues that the artifactual approach evades the problem of accounting for representation and better accommodates the modal dimension of modeling. From an artifactual perspective, models are viewed as erotetic vehicles constrained by their construction and available representational tools. The modal dimension of modeling is approached through two case studies. The first portrays mathematical modeling in economics, while the other discusses the modeling practice of (...) synthetic biology, which exploits and combines models in various modes and media. Neither model intends to represent any actual target system. Rather, they are constructed to study possible mechanisms through the construction of a model system with built-in dependencies. (shrink)

Scientific models share one central characteristic with fiction: their relation to the physical world is ambiguous. It is often unclear whether an element in a model represents something in the world or presents an artifact of model building. Fiction, too, can resemble our world to varying degrees. However, we assign a different epistemic function to scientific representations. As artifacts of human activity, how are scientific representations allowing us to make inferences about real phenomena? In reply to this concern, (...) philosophers of science have started analyzing scientific representations in terms of fictionalization strategies. Many arguments center on a dyadic relation between the model and its target system, focusing on structural resemblances and “as if” scenarios. This chapter provides a different approach. It looks more closely at model building to analyze the interpretative strategies dealing with the representational limits of models. How do we interpret ambiguous elements in models? Moreover, how do we determine the validity of model-based inferences to information that is not an explicit part of a representational structure? I argue that the problem of ambiguous inference emerges from two features of representations, namely their hybridity and incompleteness. To distinguish between fictional and non-fictional elements in scientific models my suggestion is to look at the integrative strategies that link a particular model to other methods in an ongoing research context. To exemplify this idea, I examine protein modeling through X-ray crystallography as a pivotal method in biochemistry. (shrink)

Scientific research is constrained by limited resources, so it is imperative that it be conducted efficiently. This paper introduces the notion of epistemic expression, a kind of representation that expedites the solution of research problems. Epistemic expressions are representations that (i) contain information in a way that enables more reliable information to place the most stringent constraints on possible solutions and (ii) make new information readily extractible by biasing the search through that space. I illustrate these conditions using historical and (...) contemporary examples of biomolecular structure determination. Then, I argue that the notion of epistemic expression parts ways with pragmatic accounts of scientific representation and an understanding of models as artifacts, neither of which require models to accurately represent. Explicating epistemic expression thus fills a gap in our understanding of scientific practice, extending Morrison and Morgan's (1999) conception of models as investigative instruments. (shrink)

Methodological problems often arise when a special case is confused with the general principle. So you will find affordances only for ‚artifacts’ if you restrict the analysis to ‚artifacts’. The general principle, however, is an ‚invitation character’, which triggers an action. Consequently, an action-theoretical approach known as ‚pragmatic turn’ in cognitive science is recommended. According to this approach, the human being is not a passive-receptive being but actively produces those action effects that open up the world to us. (...) This ‚ideomotor approach’ focuses on the so-called ‚epistemic actions’, which guide our perception as conscious and unconscious cognitions. Due to ‚embodied cognition’ the own body is assigned an indispensable role. The action theoretical approach of ‚enactive cognition’ enables that every form can be consistently processualized. Thus, each ‚Gestalt’ is understood as the process result of interlocking cognitions of ‚forward modelling’ and ‚inverse modelling’. As can be shown, these cognitions are fed by previous experiences of real interaction, which later changes into a mental trial treatment, which is highly automated and can therefore take place unconsciously. It is now central that every object may have such affordances that call for instrumental or epistemic action. In the simplest case, it is the body and the facial expressions of our counterpart that can be understood as a question and provoke an answer/reaction. Thus, emotion is not only to be understood as expression/output according to the scheme ‚input-processing-output’, but acts itself as a provocative act/input. Consequently, artifacts are neither necessary nor sufficient conditions for affordances. Rather, they exist in all areas of cognition—from Enactive Cognition to Social Cognition. (shrink)

This paper analyses the phenomenology and epistemology of chatbots such as ChatGPT and Bard. The computational architecture underpinning these chatbots are large language models (LLMs), which are generative artificial intelligence (AI) systems trained on a massive dataset of text extracted from the Web. We conceptualise these LLMs as multifunctional computational cognitive artifacts, used for various cognitive tasks such as translating, summarizing, answering questions, information-seeking, and much more. Phenomenologically, LLMs can be experienced as a “quasi-other”; when that happens, users (...) anthropomorphise them. For most users, current LLMs are black boxes, i.e., for the most part, they lack data transparency and algorithmic transparency. They can, however, be phenomenologically and informationally transparent, in which case there is an interactional flow. Anthropomorphising and interactional flow can, in some users, create an attitude of (unwarranted) trust towards the output LLMs generate. We conclude this paper by drawing on the epistemology of trust and testimony to examine the epistemic implications of these dimensions. Whilst LLMs generally generate accurate responses, we observe two epistemic pitfalls. Ideally, users should be able to match the level of trust that they place in LLMs to the degree that LLMs are trustworthy. However, both their data and algorithmic opacity and their phenomenological and informational transparency can make it difficult for users to calibrate their trust correctly. The effects of these limitations are twofold: users may adopt unwarranted attitudes of trust towards the outputs of LLMs (which is particularly problematic when LLMs hallucinate), and the trustworthiness of LLMs may be undermined. (shrink)

Models as Make-Believe offers a new approach to scientific modelling by looking to an unlikely source of inspiration: the dolls and toy trucks of children's games of make-believe.

This article critically evaluates Itzhak Gilboa, Andrew Postlewaite, Larry Samuelson, and David Schmeidler’s account of economic models. First, it gives a selective overview of their argument, highlighting its emphasis on similarity and their oversight of the role of idealizations in economics. Second, it proposes a sketch of an account of models as arguments and argumentative devices. This account not only sheds light on Gilboa et al.’s approach, including its shortcomings, but also identifies key challenges in model-based inference, suggesting (...) a fresh perspective on the uses of models in economics for diverse objectives. (shrink)

In this paper I propose an account of representation for scientific models based on Kendall Walton’s ‘make-believe’ theory of representation in art. I first set out the problem of scientific representation and respond to a recent argument due to Craig Callender and Jonathan Cohen, which aims to show that the problem may be easily dismissed. I then introduce my account of models as props in games of make-believe and show how it offers a solution to the problem. Finally, (...) I demonstrate an important advantage my account has over other theories of scientific representation. All existing theories analyse scientific representation in terms of relations, such as similarity or denotation. By contrast, my account does not take representation in modelling to be essentially relational. For this reason, it can accommodate a group of models often ignored in discussions of scientific representation, namely models which are representational but which represent no actual object. (shrink)

ABSTRACT Is there something specific about modelling that distinguishes it from many other theoretical endeavours? We consider Michael Weisberg’s thesis that modelling is a form of indirect representation through a close examination of the historical roots of the Lotka–Volterra model. While Weisberg discusses only Volterra’s work, we also study Lotka’s very different design of the Lotka–Volterra model. We will argue that while there are elements of indirect representation in both Volterra’s and Lotka’s modelling approaches, they are largely due to two (...) other features of contemporary model construction processes that Weisberg does not explicitly consider: the methods-drivenness and outcome-orientedness of modelling. 1Introduction 2Modelling as Indirect Representation 3The Design of the Lotka–Volterra Model by Volterra 3.1Volterra’s method of hypothesis 3.2The construction of the Lotka–Volterra model by Volterra 4The Design of the Lotka–Volterra Model by Lotka 4.1Physical biology according to Lotka 4.2Lotka’s systems approach and the Lotka–Volterra model 5Philosophical Discussion: Strategies and Tools of Modelling 5.1Volterra’s path from the method of isolation to the method of hypothesis 5.2The template-based approach of Lotka 5.3Modelling: methods-driven and outcome-oriented 6Conclusion. (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)

In recent decades, philosophers of science have devoted considerable efforts to understand what models represent. One popular position is that models represent fictional situations. Another position states that, though models often involve fictional elements, they represent real objects or scenarios. Though these two positions may seem to be incompatible, I believe it is possible to reconcile them. Using a threefold distinction between different signs proposed by Peirce, I develop an argument based on a proposal recently made by (...) Kralemann and Lattman (in Synthese 190:3397–3420, 2013) that shows that the two aforementioned positions can be reconciled by distinguishing different ways in which a model representation can be used. In particular, on the basis of Peirce’s distinction between icons, indices and symbols, I argue that models can sometimes function as icons, sometimes as indexes and sometimes as symbols, depending on the context in which they are considered and the use that they are developed for because they all have iconic, indexical and symbolic features. In addition, I show that conceiving models as signs enables us to develop an account of scientific representation that meets the main desiderata that Shech (in Synthese 192:3463–3485, 2015) presents. (shrink)

This article shows how the MISS account of models—as isolations and surrogate systems—accommodates and elaborates Sugden’s account of models as credible worlds and Hausman’s account of models as explorations. Theoretical models typically isolate by means of idealization, and they are representatives of some target system, which prompts issues of resemblance between the two to arise. Models as representations are constrained both ontologically (by their targets) and pragmatically (by the purposes and audiences of the modeller), and (...) these relations are coordinated by a model commentary. Surrogate models are often about single mechanisms. They are distinguishable from substitute models, which are examined without any concern about their connections with the target. Models as credible worlds are surrogate models that are believed to provide access to their targets on account of their credibility (of which a few senses are distinguished). (shrink)

Both the irreducible complexity of biological phenomena and the aim of a universalized biology (life-as-it-could-be) have lead to a deep methodological shift in the study of life; represented by the appearance of ALife, with its claim that computational modelling is the main tool for studying the general principles of biological phenomenology. However this methodological shift implies important questions concerning the aesthetic, engineering and specially the epistemological status of computational models in scientific research: halfway between the well established categories of (...) theory and experiment. ALife models become powerful epistemic artefacts allowing the simulation of emergent phenomena, the interaction between different levels of organization and the integration of different causal factors in the very same manipulable object. The use of computational models in ALife can be classified in four main categories depending on their position between theoretical and empirical practices: generic, conceptual, functional and mechanistic. For each of these categories we analyse their epistemic value and select paradigmatic examples that illustrate how ALife models can be fruitfully inserted in the study of life. (shrink)

Most philosophical accounts of scientific models assume that models represent some aspect, or some theory, of reality. They also assume that interpretation plays only a supporting role. This paper challenges both assumptions. It proposes that models can be used in science to interpret reality. (a) I distinguish these interpretative models from representational ones. They find new meanings in a target system’s behaviour, rather than fit its parts together. They are built through idealisation, abstraction and recontextualisation. (b) (...) To show how interpretative models work, I offer a case study on the scientific controversy over foetal pain. It highlights how pain scientists use conflicting models to interpret the human foetus and its behaviour, and thereby to support opposing claims about whether the foetus can feel pain. (c) I raise a sceptical worry and a methodological challenge for interpretative models. To address the latter, I use my case study to compare how interpretative and representational models ought to be evaluated. (shrink)

In this article, I argue that the use of scientific models that attribute intentional content to complex systems bears a striking similarity to the way in which statistical descriptions are used. To demonstrate this, I compare and contrast an intentional model with a statistical model, and argue that key similarities between the two give us compelling reasons to consider both as a type of phenomenological model. I then demonstrate how intentional descriptions play an important role in scientific methodology as (...) a type of phenomenal model, and argue that this makes them as essential as any other model of this type. (shrink)

Various data from communication that does not occur face-to-face are taken to be problematic for Kaplan’s account of indexical expressions, as is the case with the so-called answering machine paradox. One fix, developed by Sidelle (1991) and Briciu (2018), is the remote utterance view: recording artifacts are means by which speakers perform utterances at a distance, just as by means of other artifacts agents performs other types of actions at a distance. This view has faced an important objection, (...) namely that remote utterances lead to Moorean paradoxes. In this paper, I defend the remote utterance view against this objection and further develop the view. I argue that worries about Moorean paradoxes can easily be dispelled if we take into consideration the artifactual nature of recording devices, their materiality, and the communicative affordances they bring about. In the first section, we’ll present the answering machine paradox and give a brief overview of the remote utterance view. The second section presents the objection against the view, while the third gives a detailed rejoinder to the objection. Answering this objection is important also because it allows us to explore some underdeveloped aspects of the remote utterance view. First, I will discuss how the theorist calibrates her model with the data she seeks to explain and predict. Secondly, I will argue that speech acts performed via recording devices have different felicity conditions than their oral counterparts. I conclude with a short discussion of some semantic and pragmatic consequences of the view. (shrink)

Agent-based models (ABMs) are one type of simulation model used in the context of the COVID-19 pandemic. In contrast to equation-based models, ABMs are algorithms that use individual agents and attribute changing characteristics to each one, multiple times during multiple iterations over time. This paper focuses on three philosophical aspects of ABMs as models of causal mechanisms, as generators of emergent phenomena, and as providers of explanation. Based on my discussion, I conclude that while ABMs cannot help (...) much with causal inference, they can be viewed as etio-prognostic explanations of illness occurrence and outcome. (shrink)

In Economics Rules, Dani Rodrik (2015) argues that what makes economics powerful despite the limitations of each and every model is its diversity of models. Rodrik suggests that the diversity of models in economics improves its explanatory capacities, but he does not fully explain how. I offer a clearer picture of how models relate to explanations of particular economic facts or events, and suggest that the diversity of models is a means to better economic explanations.

We live in a world of crowds and corporations, artworks and artifacts, legislatures and languages, money and markets. These are all social objects — they are made, at least in part, by people and by communities. But what exactly are these things? How are they made, and what is the role of people in making them? In The Ant Trap, Brian Epstein rewrites our understanding of the nature of the social world and the foundations of the social sciences. Epstein (...) explains and challenges the three prevailing traditions about how the social world is made. One tradition takes the social world to be built out of people, much as traffic is built out of cars. A second tradition also takes people to be the building blocks of the social world, but focuses on thoughts and attitudes we have toward one another. And a third tradition takes the social world to be a collective projection onto the physical world. Epstein shows that these share critical flaws. Most fundamentally, all three traditions overestimate the role of people in building the social world: they are overly anthropocentric. Epstein starts from scratch, bringing the resources of contemporary metaphysics to bear. In the place of traditional theories, he introduces a model based on a new distinction between the grounds and the anchors of social facts. Epstein illustrates the model with a study of the nature of law, and shows how to interpret the prevailing traditions about the social world. Then he turns to social groups, and to what it means for a group to take an action or have an intention. Contrary to the overwhelming consensus, these often depend on more than the actions and intentions of group members. (shrink)

Ecological-enactive approaches to cognition aim to explain cognition in terms of the dynamic coupling between agent and environment. Accordingly, cognition of one’s immediate environment (which is sometimes labeled “basic” cognition) depends on enaction and the picking up of affordances. However, ecological-enactive views supposedly fail to account for what is sometimes called “higher” cognition, i.e., cognition about potentially absent targets, which therefore can only be explained by postulating representational content. This challenge levelled against ecological-enactive approaches highlights a putative explanatory gap between (...) basic and higher cognition. In this paper, we examine scientific cognition—a paradigmatic case of higher cognition—and argue that it shares fundamental features with basic cognition, for enaction and affordance selection are central to the scientific enterprise. Our argument focuses on modeling, and on how models promote scientific understanding. We base our argument on a non-representational account of scientific understanding and on the material engagement theory, for models are hereby conceived as material objects designed for scientific engagements. Having done so, we conclude that the explanatory gap is significantly less threatening to the ecological-enactive approach than it might appear. (shrink)

Teleology has a complicated history in the biological sciences. Some have argued that Darwin’s theory has allowed biology to purge itself of teleological explanations. Others have been content to retain teleology and to treat it as metaphorical, or have sought to replace it with less problematic notions like teleonomy. And still others have tried to naturalize it in a way that distances it from the vitalism of the nineteenth century, focusing on the role that function plays in teleological explanation. No (...) consensus has seemed possible in this debate. This paper takes a different approach. It argues that teleology is a perfectly acceptable scientific notion, but that the debate took an unfortunate misstep some 2300 years ago, one that has confused things ever since. The misstep comes in the beginning of Aristotle’s Physics when a distinction is made between two types of teleological explanation. One type pertains to artifacts while the other pertains to entities in nature. For Aristotle, artifacts are guided by something external to themselves, human intentions, while natural entities are guided by an internal nature. We aim to show that there is, in fact, only one type of legitimate teleological explanation, what Aristotle would have considered a variant of an artifact model, where entities are guided by external fields. We begin with an analysis of the differences between the two types of explanation. We then examine some evidence in Aristotle’s biological works suggesting that on account of his natural-artifactual distinction, he encountered difficulties in trying to provide teleological accounts of spontaneous generation. And we show that it is possible to resolve these difficulties with a more robust version of an artifact model of teleology, in other words, with an externalist teleology. This is McShea’s model, in which goal-directed entities are guided by a nested series of upper-level fields. To explain teleological behavior, this account invokes only external physical forces rather than mysterious internal natures. We then consider how field theory differs from other efforts to naturalize teleology in biology. And finally, we show how the account enables us to grapple with certain difficult cases – genes and intentions – where, even in biology today, the temptation to posit internal natures remains strong. (shrink)

This work aims to present an overview of the top-level ontology BFO - Basic Formal Ontology - and its applicability for Satellite Systems. As an upper level ontology, the BFO was designed to be extended, providing the basis for the specification of detailed representational artifacts about scientific information domains. These aspects and the challenges of satellite systems complexity and large size compose a suitable scenario for the creation of a specialized dialect to improve efficiency and accuracy when modeling such (...) systems. By analyzing BFO based ontologies in other disciplines and existing satellite models it is possible to describe an application for satellite systems, which can provide a foundation for the creation of a concrete ontology to be applied on satellite modeling. (shrink)

Conversational Artificial Intelligence (CAI) systems (also known as AI “chatbots”) are among the most promising examples of the use of technology in mental health care. With already millions of users worldwide, CAI is likely to change the landscape of psychological help. Most researchers agree that existing CAIs are not “digital therapists” and using them is not a substitute for psychotherapy delivered by a human. But if they are not therapists, what are they, and what role can they play in mental (...) health care? To answer these questions, we appeal to two well-established and widely discussed concepts: cognitive and affective artifacts. Cognitive artifacts are artificial devices contributing functionally to the performance of a cognitive task. Affective artifacts are objects which have the capacity to alter subjects’ affective state. We argue that therapeutic CAIs are a kind of cognitive-affective artifacts which contribute to positive therapeutic change by (i) simulating a (quasi-)therapeutic interaction, (ii) supporting the performance of cognitive tasks, and (iii) altering the affective condition of their users. This sheds new light on why virtually all existing mental health CAIs implement principles and techniques of Cognitive Behavioral Therapy — a therapeutic orientation according to which affective change and, ultimately, positive therapeutic change is mediated by cognitive change. Simultaneously, it allows us to conceptualize better the potential and limitations of applying these technologies in therapy. (shrink)

We introduce a novel point of view on the “models as mediators” framework in order to emphasize certain important epistemological questions about models in science which have so far been little investigated. To illustrate how this perspective can help answer these kinds of questions, we explore the use of simplified models in high energy physics research beyond the Standard Model. We show in detail how the construction of simplified models is grounded in the need to mitigate (...) pressing epistemic problems concerning the uncertainty inherent in the present theoretical and experimental contexts. (shrink)

To naturalize the concept of teleological causality in biology it is not enough to avoid assuming backward causation or positing the existence of an inscrutable te- leological essence like the élan vital. We must also specify how the causality of or- ganisms is distinct from the causality of designed artifacts like thermostats or asym- metrically oriented processes like the ubiquitous increase of entropy. Historically, the concept of teleological causality in biology has been based on an analogy to the familiar (...) experience of purposeful action. This is experienced by us as a disposition to achieve a general type of end that is represented in advance, and which regulates the selection of efficient means to achieve it. Inspired by this analogy, to bridge the gap between biology and human agency we describe a simple molecular pro- cess called autogenesis that shows how two linked complementary self-organizing processes can give rise to higher-order relations that resemble purposeful disposi- tions, though expressed in terms of constraints on molecular processes. Because the autogenic model is described in sufficient detail to be empirically realizable, it provides a proof of principle demonstrating a simple form of teleological causality. (shrink)

I compare Frith and colleagues’ influential comparator account of how the sense of agency is elicited to the multifactorial weighting model advocated by Synofzik and colleagues. I defend the comparator model from the common objection that the actual sensory consequences of action are not needed to elicit the sense of agency. I examine the comparator model’s ability to explain the performance of healthy subjects and those suffering from delusions of alien control on various self-attribution tasks. It transpires that the comparator (...) model needs case-by-case adjustment to deal with problematic data. In response to this, the multifactorial weighting model of Synofzik and colleagues is introduced. Although this model is incomplete, it is more naturally constrained by the cases that are problematic for the comparator model. However, this model may be untestable. I conclude that currently the comparator model approach has stronger support than the multifactorial weighting model approach. (shrink)

We propose a typology of representational artifacts for health care and life sciences domains and associate this typology with different kinds of formal ontology and logic, drawing conclusions as to the strengths and limitations for ontology in a description logics framework. The four types of domain representation we consider are: (i) lexico-semantic representation, (ii) representation of types of entities, (iii) representations of background knowledge, and (iv) representation of individuals. We advocate a clear distinction of the four kinds of representation (...) in order to provide a more rational basis for using ontologies and related artifacts to advance integration of data and enhance interoperability of associated reasoning systems. We highlight the fact that only a minor portion of scientifically relevant facts in a domain such as biomedicine can be adequately represented by formal ontologies as long as the latter are conceived as representations of entity types. In particular, the attempt to encode default or probabilistic knowledge using ontologies so conceived is prone to produce unintended, erroneous models. (shrink)

The descriptions and theoretical laws scientists write down when they model a system are often false of any real system. And yet we commonly talk as if there were objects that satisfy the scientists’ assumptions and as if we may learn about their properties. Many attempt to make sense of this by taking the scientists’ descriptions and theoretical laws to define abstract or fictional entities. In this paper, I propose an alternative account of theoretical modelling that draws upon Kendall Walton’s (...) ‘make-believe’ theory of representation in art. I argue that this account allows us to understand theoretical modelling without positing any object of which scientists’ modelling assumptions are true. (shrink)

There have been several calls from LIS researchers for practical or applied research not to ignore the epistemological assumptions underlying the systems and artifacts they design lest they showcase only the dominant theory at a given time. Others have also deplored the "epistemological promiscuity" or "eclecticism" of the field, its incessant borrowing of theories and models from elsewhere and the fact that the field has largely neglected the contributions that philosophy and epistemology could have made in its research. (...) This problem raises that of the boundaries of LIS and is all the more troublesome because boundaries between epistemological theories are fuzzy. Indeed, some epistemological theories share the same basic assumptions or are historically derived from one another. Gathering a wide array of acknowledged theorists in philosophy of science and epistemology, this panel aims to examine how research work in the LIS field can clearly articulate the epistemological assumptions underlying that research and under what constraints this can be achieved. The topic is of prime importance to Information studies as a whole and to ASIST as the scientific flag bearer of information scientists worldwide. (shrink)

This paper is a tentative step towards a historical cognitive science, in the domain of memory and personal identity. I treat theoretical models of memory in history as specimens of the way cultural norms and artifacts can permeate ('proto')scientific views of inner processes. I apply this analysis to the topic of psychological control over one's own body, brain, and mind. Some metaphors and models for memory and mental representation signal the projection inside of external aids. Overtly at (...) least, medieval and Renaissance theorists agreed that such models had to allow for, or even guarantee, some conception of cognitive order and discipline. Individual memory traces had to be independent, not mixed up or interfering with others. The long tradition of improving or bypassing 'natural memory' by deliberately internalizing artefactual models was part of an arduous process of self-fashioning. Moral panic about confusion and mixture features centrally in the imposition of cognitive discipline in local memory traditions. (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)

Modern humans are probably a product of social and anatomical preadaptations on the part of our Miocene australopithecine ancestors combined with the increasingly high amplitude, high frequency climate variation of the Pleistocene. The genus Homo first appeared in the early Pleistocene as ice age climates began to grip the earth. We hypothesize that this co-occurrence is causal. The human ability to adapt by cultural means is, in theory, an adaptation to highly variable environments because cultural evolution can better track rapidly (...) changing environments than can genes. High resolution ice and sediment cores published in the early 1990s showed the last ice age was characterized by high amplitude millennial and submillenial scale variation, exactly the sort of variation mathematical models suggest should favor a costly capacity for culture. More recent cores suggest that over the last several 100 thousand year glacial cycles the amount of millennial scale variation has increased rather dramatically in parallel with increases in hominin brain size and sophistication of the artifacts they made. (shrink)

As the title of this essay suggests, my concern is with the issue of what are economic models. However, the goal of the paper is not to offer an in-depth study on multiple approaches to modelling in economics, but rather to overcome the dichotomical divide between conceptualizing models as isolations and constructions. This is done by introducing the idea of economic models as believable worlds, precisely descriptions of mechanisms that refer to the essentials of the modelled targets. (...) In doing so I make use of the Woodward’s (2002) conceptualization of mechanisms. It is shown that such models do not offer the perfectly true descriptions of the actual world but justified beliefs about the modelled, precisely they aim at maximizing truth and minimizing falsity in a large body of belief about the real world. The analysis throughout the paper is supported by in-depth examination of the Varian’s (1980) model of sales that is here treated as a representative way of reasoning in neoclassical economics. (shrink)

Is it sensical to ascribe psychological predicates to AI systems like chatbots based on large language models (LLMs)? People have intuitively started ascribing emotions or consciousness to social AI (‘affective artificial agents’), with consequences that range from love to suicide. The philosophical question of whether such ascriptions are warranted is thus very relevant. This paper advances the argument that LLMs instantiate language users in Ludwig Wittgenstein’s sense but that ascribing psychological predicates to these systems remains a functionalist temptation. Social (...) AIs are not full-blown language users, but rather more like Italo Calvino’s literature machines. The ideas of LLMs as Wittgensteinian language users and Calvino’s literature-producing writing machine are combined. This sheds light on the misguided functionalist temptation inherent in moving from equating the two to the ascription of psychological predicates to social AI. Finally, the framework of mortal computation is used to show that social AIs lack the basic autopoiesis needed for narrative façons de parler and their role in the sensemaking of human (inter)action. Such psychological predicate ascriptions could make sense: the transition ‘from quantity to quality’ can take place, but its route lies somewhere between life and death, not between affective artifacts and emotion approximation by literature machines. (shrink)

AI-based technologies are increasingly pervasive in a number of contexts. Our affective and emotional life makes no exception. In this article, we analyze one way in which AI-based technologies can affect them. In particular, our investigation will focus on affective artificial agents, namely AI-powered software or robotic agents designed to interact with us in affectively salient ways. We build upon the existing literature on affective artifacts with the aim of providing an original analysis of affective artificial agents and their (...) distinctive features. We argue that, unlike comparatively low-tech affective artifacts, affective artificial agents display a specific form of agency, which prevents them from being perceived by their users as extensions of their selves. In addition to this, we claim that their functioning crucially depends on the simulation of human-like emotion-driven behavior and requires a distinctive form of transparency—we call it emotional transparency—that might give rise to ethical and normative tensions. (shrink)

Over the last thirty years, once staunchly film history scholars such as Thomas Elsaesser, Jane Gaines, Siegfried Zielinski, André Gaudreault and Benoît Turquety (to name just a few) have abandoned history for historiography and film studies for media archaeology. Considering the heightened attention given to kulturtechnik (Siegert), the database as a dominant symbolic metaphor,1 and the decentered networked tenants of the postmodern global present, cinema is taking on the characteristics of new media, existing in increasingly intertextual space. Thus, the term (...) “post-cinema” has been co-opted as a viable intermediary that accounts for new media conditions, as cinema is no longer emblematic of our cultural climate. It was once presaged in 1992 that “[t]he end of the cinema truly sounds the death knell of the ultimate metaphysical adventure of Dasein. In the twilight of post-cinema, of which we are seeing the beginning, human quasi-existence, now stripped of any metaphysical hypostasis and deprived of any theological model, will have to seek its proper generic consistency elsewhere.” Accordingly, we are no longer “moviegoing animals” who seek images of ourselves among a collective in the dark but, rather, users interfacing within a network of moving images. By locating post-cinema within the semblance of social media, we are allocated a newfound series of theoretical interventions, the most marked of which is that of media archeology vis-à-vis dialectical materialism. This is a lens through which Brian Winston has recently deftly decried Virtual Reality’s “empathy machine” utopic illusionism, bolstered by Chris Milk and a slew of neurohumanities researchers, steadily maintaining that the fundamental myth of “technologies of seeing” is in disguising “their artifice, their cultural formation and their ideological import.” However, this approach, which illuminates the bifurcation between Max Horkheimer/Theodor Adorno and Walter Benjamin, neglects what Benjamin identified as occurring to the work of art in the age of its technological reproducibility—a shift from a technology’s “cult value,” associated with the unique work, to its “exhibition value,” associated with the social act of viewing as part of a mass. Speaking to this divarication, Benjamin Barber, in Strong Democracy, foresaw new media’s two-fold potential—as they are organized and networked, new media and communications technologies possess the possibility to both energize citizen information and political participation but, simultaneously, to supplement the deterioration of public debate. As evinced by Mark Adrejevic’s concept of Infoglut, this two-pronged possibility has only been exacerbated by the interlocking relationship between the advent of a “glut” of information, post-truth politics, the demise of symbolic efficiency, and a renewed focus on the role of affect and emotion as “alternative modalities for thinking about the role of communication in a post-referential era.” Manuel Castells qualifies Barber’s pessimism, noting that the Internet can “be an appropriate platform for informed, interactive politics, stimulating political participation.. […] beyond the closed doors of political institutions,” but that the Internet, like any technology, “is shaped by its uses and users.” Thus, if there exists a positive correlation between exposure to post-cinema media artifacts and political participation, then I seek to explore the revelatory political possibilities of “exhibition value” by way of a particular “post-cinema” case study: the Marxist-Leninist Turkish hacktivist group Redhack’s YouTube-circulated documentary RED! (2013), a project that demanded—by way of the moving-image—to galvanize cyberprotest and democratize a “hacktivist commons. (shrink)

Scholarly processes play a pivotal role in discovering, challenging, improving, advancing, synthesizing, codifying, and disseminating knowledge. Since the 17th Century, both the quality and quantity of knowledge that scholarship has produced has increased tremendously, granting academic research a pivotal role in ensuring material and social progress. Artificial Intelligence (AI) is poised to enable a new leap in the creation of scholarly content. New forms of engagement with AI systems, such as collaborations with large language models like GPT-3, offer affordances (...) that will change the nature of both the scholarly process and the artifacts it produces. (shrink)

I propose a distinct type of robustness, which I suggest can support a confirmatory role in scientific reasoning, contrary to the usual philosophical claims. In model robustness, repeated production of the empirically successful model prediction or retrodiction against a background of independentlysupported and varying model constructions, within a group of models containing a shared causal factor, may suggest how confident we can be in the causal factor and predictions/retrodictions, especially once supported by a variety of evidence framework. I present (...) climate models of greenhouse gas global warming of the 20th Century as an example, and emphasize climate scientists’ discussions of robust models and causal aspects. The account is intended as applicable to a broad array of sciences that use complex modeling techniques. (shrink)

Using as case studies two early diagrams that represent mechanisms of the cell division cycle, we aim to extend prior philosophical analyses of the roles of diagrams in scientific reasoning, and specifically their role in biological reasoning. The diagrams we discuss are, in practice, integral and indispensible elements of reasoning from experimental data about the cell division cycle to mathematical models of the cycle’s molecular mechanisms. In accordance with prior analyses, the diagrams provide functional explanations of the cell cycle (...) and facilitate the construction of mathematical models of the cell cycle. But, extending beyond those analyses, we show how diagrams facilitate the construction of mathematical models, and we argue that the diagrams permit nomological explanations of the cell cycle. We further argue that what makes diagrams integral and indispensible for explanation and model construction is their nature as locality aids: they group together information that is to be used together in a way that sentential representations do not. (shrink)

Th ere is much controversy surrounding the nature of the relation between fictional individuals and possible individuals. Some have argued that no fictional individual is a possible individual; others have argued that (some) fictional individuals just are (merely) possible individuals. In this paper, I off er further grounds for believing the theory of fictional individuals defended by Amie Thomasson,viz., Artifactualism, by arguing that her view best allows one to make sense of this puzzling relation. More specifically, when we realize that (...) the view allows for an identification of merely possible individuals with fictional individuals, we seethat the utility, and hence the level of credence lent to Artifactualism, is increased. After arguing for this thesis, I respond to three of the most pressing worries. (shrink)

Fiat objects may come into existence by intentional explicit defnition and convention or they can be the result of some spontaneous and unintentional activity resulting in tracing fat spatial boundaries. Artifacts and fiat objects seem intuitively to be correlated: both artifacts and fiat objects depend for their existence on agents and their intentions. Is it possible to consider fiat objects as artifacts and to what extent? Or else can we conceive at least some artifacts as fiat (...) objects? In order to draw a map of the possible answers to these two questions we will take into account various defnitions of artifacts stemming from the two classical approaches: the intentional and the functional one. (shrink)

I have spent over 50 years of dedicated research on this theme. These are my overall conclusions. I think that science-as-it-is has come to too-limited conclusions, largely because, by in large, they are using an outmoded, "Newtonian" model of reality, (echoing Penrose, D'Espagnat, Maturana). Twentieth century physics has changed that, and it is time to apply its results to the rest of our world picture. I contend that the "materialists", as exemplified by Dennett, are archeological artifacts! There still remains (...) room for the human mind and the human soul -and my book shows how! This book proposes an entirely new perspective and an actual solution to the problem based on modern biology,(Maturana), modern physics, (Bohr, D'Espagnat, Einstein), modern logic, (Quine) and modern philosophy, (Cassirer), but it is still firmly grounded in Realism. It's conclusion is that the existence of "mind" is a necessary consequence of realism. (shrink)

Given the robust reputation of Nigeria in Africa, as a continental giant, and the need to harness the potentials of the nation to strategically reposition her economy on the global map in the 21st century, the nation is in dire need of speedy development. With a population of over 160 million, the country is blessed with both human and natural resources. Like other African countries, Nigeria has had her fair share of colonial experience which ended on October 1st, 1960 when (...) the nation was granted independence by the British government. Nigeria’s independence is undoubtedly a political phenomenon as the nation still largely depends economically and socially on foreign nations especially developed countries like Britain, America and China. (shrink)

In recent years, with the advances in machine learning and neuroscience, the abundances of sensors and emotion data, computer engineers have started to endow machines with ability to detect, classify, and interact with human emotions. Emotional artificial intelligence (AI), also known as a more technical term in affective computing, is increasingly more prevalent in our daily life as it is embedded in many applications in our mobile devices as well as in physical spaces. Critically, emotional AI systems have not only (...) the ability to not passively read and classify emotions, but most also have an ability to predict and ‘nudge’ users to certain desired emotional states. Drawing from Piredda (2020)’s account, we've examined various emerging emotion-sensing technologies such as recommender algorithms, personal AI assistants, work-related emotion trackers, and emotional AI toys and robots through the lens of affective artifacts. We show how these technologies fulfill the criteria of being affective artifacts: they can influence the affective states of the users (e.g., help regulate emotions of ourselves and others), some emotion-sensing algorithms and importantly, our manipulation of these algorithms, can intersect with the maintenance and construction of our sense of self and identity. (shrink)

I defend the intention-dependence of artifacts, which says that something is an artifact of kind K only if it is the successful product of an intention to make an artifact of kind K. I consider objections from two directions. First, that artifacts are often mind- and intention-dependent, but that this isn’t necessary, as shown by swamp cases. I offer various error theories for why someone would have artifact intuitions in such cases. Second, that while artifacts are necessarily (...) mind-dependent, they aren’t necessarily intention-dependent. I consider and reject three kinds of cases which purport to show this: accidental creation, automated production, and mass production. I argue that intentions are present in all of these cases, but not where we would normally expect. (shrink)

In this paper I take it for granted that legal institutions are artifacts. In general, this can very well be considered a trivial thesis in legal philosophy. As trivial as this thesis may be, however, to my knowledge no legal philosopher has attempted an analysis of the peculiar reality of legal phenomena in terms of the reality of artifacts, and this is particularly striking because there has been much discussion about artifacts in general philosophy (specifically analytic metaphysics) (...) over the last twenty years. In particular, the concepts of intention, function, plan of action, and history are in competition to explain the ontology of artifacts, and a similar competition can be found at the core of legal theory. Such a striking parallelism between the domain of artifacts and that of legal institutions is a clue for legal ontology that deserves further attention: I will offer my own interpretation of this parallelism in the first part of this paper (Sections 2 and 3). In providing a theory of legal institutions as artifacts, one could be led to the conclusion that law is essentially an artificial phenomenon, something which does not bear any significant relationship to the natural domain. However, I think that such a conclusion would be mistaken. In fact, this is the second thesis I want to explore in this paper: not only that legal institutions are artifacts, but also that they can be artifacts which in some sense "mirror," or imitate, some descriptions of the natural, pre-social reality we live in. What I would like to show is not that legal institutions are "natural" in the sense that they have some feature which is not human-dependent, as some natural law theorists would say, but rather that their conceptual content can depend on our conceptualization of the natural domain despite being entirely artifactual. This is what I will call the "institutional mimesis" behind several important instances of legal artifacts, and I will deal with it in the second part of this paper (Sections 4 and 5). (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)