Generative Emergence provides insight into the non-linear dynamics that lead to organizational emergence through the use of complexity sciences. The book explores how the model of Generative Emergence could be applied to enact emergence within and across organizations.

It has been proposed that intentional actions are supplied by a generative system of the sort described by Chomsky for language. In this paper I aim to provide a closer analysis of this claim for the sake of conceptual clarification. To this end, I will first clarify what is involved in the thesis of a structural analogy between language and action, and then I will consider what kind of evidence there seems to be in favour of the thesis of a (...) neurobiological identity. On this basis, I will subsequently focus on two definitional issues. The first is whether, as the claim of a generative system for intentional action suggests, humans may perform an infinite number of possible actions. The second is whether, as the claim of a generative system for intentional action suggests, what is at issue is conscious planning of action and therefore controlled processing. (shrink)

The generative entrenchment of an entity is a measure of how much of the generated structure or activity of a complex system depends upon the presence or activity of that entity. It is argued that entities with higher degrees of generative entrenchment are more conservative in evolutionary changes of such systems. A variety of models of complex structures incorporating the effects of generative entrenchment are presented and we demonstrate their relevance in analyzing and explaining a variety of developmental and evolutionary (...) phenomena, both on a macroscopic developmental and evolutionary scale, and using models and strategies pioneered by Kauffman, on the more microscopic scale appropriate to the analysis of the structure and behavior of gene control networks. The resulting picture suggests that generative entrenchment acts as a powerful and constructive developmental constraint on the course of evolutionary processes. Since virtually any system exhibits varying degrees of generative entrenchment among its parts and activities, these studies and results have in addition broad potential application for the analysis of generative structures in other areas. (shrink)

This paper explores the implications of the psychology of constructive memory for philosophical theories of the metaphysics of memory and for a central question in the epistemology of memory. I first develop a general interpretation of the psychology of constructive memory. I then argue, on the basis of this interpretation, for an updated version of Martin and Deutscher's influential causal theory of memory. I conclude by sketching the implications of this updated theory for the question of memory 's status as (...) a generative epistemic source. (shrink)

Generative AI technologies have the potential to be socially and politically transformative. In this paper, we focus on exploring the potential impacts that Generative AI could have on the functioning of our democracies and the nature of citizenship. We do so by drawing on accounts of deliberative democracy and the deliberative virtues associated with it, as well as the reciprocal impacts that social media and Generative AI will have on each other and the broader information landscape. Drawing on this background (...) theory, we outline some of the key positive and negative impacts that Generative AI is likely to have on democratic citizenship. The political significance of these impacts suggests the need for further regulation. (shrink)

The behavior of an organism, according to Merleau-Ponty, lays out a milieu through which significant phenomena of varying degrees of optimality elicit adjustment. This leads to the dialectical co-emergence of milieu and aptitude that is both the product and the condition of life. What is present as a norm soliciting optimization is species-specific, but it also depends on the needs of the organism and its prior experience. Although a rich entry point into biological phenomenology, Merleau-Ponty’s work does not adequately describe (...) milieu–aptitude development in interactions between organisms, but it can be assisted through employing Husserl’s three levels of analysis identified by Steinbock, extending all three modes into the biological world. In particular, generative analyses can address inter-organismal behavioral structures slighted in Merleau-Ponty’s work. Generative phenomenology is concerned with the cultural, historical, and intersubjective constitution of human experience and is generally thought to be solely of value in examining the structure of human phenomenality. However, the possibility of human generativity presupposes structures produced widely in the biological world. Ecological, embryogenic, and evolutionary development already depend on protocultural and historical processes creating and created through intercorporeal interaction. After developing the concept of biological generativity through a consideration of plant ecology, mammalian embryology, and insect mimicry, I conclude with implications for humans, who can participate in biological generativity not merely phenomenally, but phenomenologically. (shrink)

Although Hurricane Katrina precipitated considerable reflection across various media, a practice crucial to our capacities to apprehend and interpret the disaster has not yet been analyzed as such. I call this practice generative assembly. I don’t mean the events of emergency and political gathering that took place in response to the massive storm and fatal, preventable levee failures—although I will propose connections between different forms of assembly. Instead I mean a kind of documentary practice. That practice, which can be undertaken (...) individually or in collaboration, and sometimes at anonymous remove, involves the work of assembling records and signifiers related to the disaster into particular kinds of media artifacts. Those artifacts— which take shape in formats as varied as comics, photobooks, paintings, films, exhibitions, and multithousand-item online archives—characteristically maintain the active appearance and interactive potential of selection and arrangement. In exhibiting such qualities, or so I will argue, these assembly-based artifacts support various articulable and often highly effective kinds of generativity. And thus, I will further suggest, these artifacts can constitute especially powerful means of intervening in prevailing conditions of representation and remembrance around events of environmental and social violence. Crucially, those material legacies of generative assembly can also fall short, fail, and deceive, and this is especially true of those assemblies that take digital forms. It is my contention, however, that we would be misguided if we thus entirely dismissed such assemblies or if we refused their potential for dissident reuse or generative reassembly. (shrink)

This article seeks to disclose the sense(s) of translation by attending to it in the phenomenological key with Edmund Husserl’s The Origin of Geometry. I suggest that the text could be approached through the prism of generative phenomenology, and I investigate it from two different perspectives: xenological and Derridean. Both perspectives are employed toward the same objective: to demonstrate the theoretical relevance of Husserl’s text to the understanding of a complex social phenomenon such as translation. The emphasis on sociality, historicity, (...) and tradition, as these themes transpire in The Origin, brings about a new understanding of translation as a phenomenon of the liminal in-between, with its basic structure defined as the encounter with the alien. Derrida gives this emphasis much attention in his commentary on The Origin. In this commentary, he focuses on the constitution of a communal history, which is not possible without the iteration of the origin, the basic means of which is communication on the general level, while on the level of different socio-cultural worlds translation comes up as the most optimal mode for the encounter with the alien. The encounter takes place in the liminal in-between which points to repeatability as the original sense of translation inscribed in the acts of binding and approximation. (shrink)

In recent decades, scientists and philosophers have developed several naturalistic theories of consciousness, in which they try to work out some theoretical foundations for a satisfactory solution to the problem of voluntary acts, in particular the genesis of voluntary bodily movements. From the author’s point of view, depending on which concept of consciousness scientists rely on in their empirical studies of voluntary movements, volition can be understood either as a generative act or as a perceptual act. The first part of (...) the article shows that nowadays there are two competing philosophical and scientific models of volition: the generative model (dualistic and casualistic types) and the perceptual model (strong and weak types). The second part of the article deals with some experimental data from cognitive psychology and neuroscience related to the study of voluntary movements and concludes that they are in favor of the perceptive model of volition. (shrink)

Generative AI programs can produce high-quality written and visual content that may be used for good or ill. We argue that a credit–blame asymmetry arises for assigning responsibility for these outputs and discuss urgent ethical and policy implications focused on large-scale language models.

This Perspective traces the evolution of certain central notions in the theory of Generative Grammar (GG). The founding documents of the field suggested a relation between the grammar, construed as recursively enumerating an infinite set of sentences, and the idealized native speaker that was essentially equivalent to the relation between a formal language (a set of well-formed formulas) and an automaton that recognizes strings as belonging to the language or not. But this early view was later abandoned, when the focus (...) of the field shifted to the grammar's strong generative capacity as recursive generation of hierarchically structured objects as opposed to strings. The grammar is now no longer seen as specifying a set of well-formed expressions and in fact necessarily constructs expressions of any degree of intuitive “acceptability.” The field of GG, however, has not sufficiently acknowledged the significance of this shift in perspective, as evidenced by the fact that (informal and experimentally-controlled) observations about string acceptability continue to be treated as bona fide data and generalizations for the theory of GG. The focus on strong generative capacity, it is argued, requires a new discussion of what constitutes valid empirical evidence for GG beyond observations pertaining to weak generation. (shrink)

Social scientists associate agent-based simulation (ABS) models with three ideas about explanation: they provide generative explanations, they are models of mechanisms, and they implement methodological individualism. In light of a philosophical account of explanation, we show that these ideas are not necessarily related and offer an account of the explanatory import of ABS models. We also argue that their bottom-up research strategy should be distinguished from methodological individualism.

Mitte der fünfziger Jahre entsteht mit den Arbeiten der amerikanischen Linguisten Zellig S. Harris und Noam Chomsky die Theorie der generativen (Transformations-)Grammatiken a) Chomskys Grammatikmodell in den "Aspects" ... b) Entwicklung der Theorie ... nach 1965 ...

This paper will analyze how and to what extent terrorists and violent extremistshave interacted with generative artificial intelligence so far and identify potentialways in which they could misuse generative AI in the future. It is therefore necessaryto question assumptions that terrorist and violent extremist actors will quickly adoptgenerative AI solely based on an assessment of the capabilities it may offer. Althoughresearch has shown that technological capability and availability are key drivers of terroristinnovation, terrorist and violent extremist actors also assess any (...) new technologyon its compatibility (with both their modus operandi and ideology), relative complexity,cost, and the context in which they are operating. Understanding these factors, both inisolation and in relation to one another, will be a key aspect in monitoring the extent towhich terrorists and violent extremists adopt generative AI tools. In doing so, the paperwill seek to identify a likely trajectory for the abuse of this technology by terrorist actorsas well as conclude with some initial recommendations for policymakers. (shrink)

OpenAI’s Chat Generative Pre-training Transformer (ChatGPT), Google’s Bard and other generative artificial intelligence (GenAI) technologies can greatly enhance the capability of healthcare profess...

Social scientists associate agent-based simulation (ABS) models with three ideas about explanation: they provide generative explanations, they are models of mechanisms, and they implement methodological individualism. In light of a philosophical account of explanation, we show that these ideas are not necessarily related and offer an account of the explanatory import of ABS models. We also argue that their bottom-up research strategy should be distinguished from methodological individualism.

When cognitive scientists are looking for the neural basis of consciousness or the computational processes underlying vision, what are they looking to find? I argue for a new account of this explanatory project in cognitive science (and the special sciences more generally) on which it is best understood on close analogy with causal explanation in the special sciences. Causal explanations cite causal difference-makers: they explain how certain events causally depend on other events. Generative explanations cite generative difference-makers: they explain how (...) certain events obtain in virtue of (and so are generated by) other events. I show how that this generative difference-making account (GDM) extends well regarded developments in philosophical work on causal explanation, helps to usefully clarify and expands the hypothesis space of a key project in cognitive science – that of understanding how underlying nonmental processes give rise to the mental, including consciousness. In section 2, I develop GDM by close analogy with causal explanation, and locate both of them as species of a more general project in the special sciences: that of discovering what makes a difference to what. In section 3, I motivate GDM by contrasting it with other rival accounts, including correlationist, identity, and grounding accounts, as well as Carl Craver’s constitutive relevance account. In section 4, I tie all of the strands of the preceding discussion together to show how GDM provides a new and compelling response to the so-called hard problem of consciousness. (shrink)

Peter Ludlow presents the first book on the philosophy of generative linguistics, including both Chomsky's government and binding theory and his minimalist ...

This paper has two motivations. First, I want to delineate structurally the dimensions of phenomenological method: not merely the static and genetic methods, but along with them I want to introduce the new ideas of generativity and generative method (Section 2). Second, because these dimensions cannot merely be treated structurally, I want to examine their dynamic interrelation, that is, the system of motivations obtaining between them. I will do this by elaborating the phenomenological concept of "leading clue" (Section 3). Finally, (...) I will conclude by addressing the relation of phenomenology to generativity (Section 4). (shrink)

Generative AI appears to threaten argument creativity. Because of its capacity to generate coherent texts, individuals are likely to integrate its ideas, and not their own, into arguments, thereby reducing their creative contribution. This article argues that this view is mistaken—it rests on a misunderstanding of the nature of creativity. Within arguments, creative and critical thinking cannot be separated. Because creativity is enmeshed with skills such as analysis and evaluation, the use of generative AI in the construction of arguments, especially (...) in the role as universal audience, has the potential to heighten, not diminish argument creativity. (shrink)

Classical categorial grammars are the grammars introduced by Ajdukiewicz [1] and formalized by Bar-Hillel [2], Bar-Hillel et al. [3]. In [3] there is proved the weak equivalence of CCG’s and context-free grammars [6]. In this note we characterize the strong generative capacity of finite and rigid CCG’s, i.e. their capacity of structure generation. These results are more completely discussed in [4], [5].

This paper presents a version of neurophenomenology based on generative modelling techniques developed in computational neuroscience and biology. Our approach can be described as _computational phenomenology_ because it applies methods originally developed in computational modelling to provide a formal model of the descriptions of lived experience in the phenomenological tradition of philosophy (e.g., the work of Edmund Husserl, Maurice Merleau-Ponty, etc.). The first section presents a brief review of the overall project to naturalize phenomenology. The second section presents and evaluates (...) philosophical objections to that project and situates our version of computational phenomenology with respect to these projects. The third section reviews the generative modelling framework. The final section presents our approach in detail. We conclude by discussing how our approach differs from previous attempts to use generative modelling to help understand consciousness. In summary, we describe a version of computational phenomenology which uses generative modelling to construct a computational model of the inferential or interpretive processes that best explain this or that kind of lived experience. (shrink)

The Bayesian brain hypothesis, predictive processing, and variational free energy minimisation are typically used to describe perceptual processes based on accurate generative models of the world. However, generative models need not be veridical representations of the environment. We suggest that they can be used to describe sensorimotor relationships relevant for behaviour rather than precise accounts of the world.

Discourses on Responsible Innovation and Responsible Research and Innovation, in short RI, have revolved around but not elaborated on the notion of critique. In this article, generative critique is introduced to RI as a practice that sits in-between adversarial armchair critique and co-opted, uncritical service. How to position oneself and be positioned on this spectrum has puzzled humanities scholars and social scientists who engage in interdisciplinary collaborations with scientists, engineers, and other professionals. Recently, generative critique has been presented as a (...) solution to the puzzle in interdisciplinary collaborations on neuroscientific experiments. Generative critique seeks to create connections across disciplines that help remake seemingly stable objects in moments when taken-for-granted ways of seeing and approaching objects are unsettled. In order to translate generative critique from the neurosciences to RI, socio-technical integration research is proposed as a practice of generative critique in interdisciplinary RI collaborations. These collaborations aim to account for societal aspects in research and technology development. For this purpose, a variety of approaches have been developed, including STIR and video-reflexive ethnography. STIR and VRE resemble each other but diverge on affective, collaborative, and temporal dimensions. Their juxtaposition serves to develop suggestions for how STIR could be modified on these dimensions to better enact generative critique in interdisciplinary RI collaborations. In this way, the article contributes to ongoing discussions in RI and in the engaged programme in science and technology studies more broadly on the dynamics of positioning in collaborative work. (shrink)

Written by two of the leading figures in the field, this is a lucid and systematic introduction to semantics as applied to transformational grammars of the ...

Generative models have been proposed as a new type of non-representational scientific models recently. A generative model is characterized with the capacity of producing new models on the basis of the existing one. The current accounts do not explain sufficiently the mechanism of the generative capacity of a generative model. I attempt to accomplish this task in this paper. I outline two antecedent accounts of generative models. I point out that both types of generative models function to generate new homogenous (...) models in the sense that the latter is a straightforward derivative of the former, both of which share many similar features. Unfortunately, both accounts are implicit about the generative capacity of generative models. Using a case study, I articulate that a two-staged process of abstraction and idealization in modeling may contribute to the generative capacity of a scientific model. I also demonstrate that this two-staged process may go beyond the capacity of generating new homogenous models to generating new heterogeneous models. (shrink)

The new wave of ‘foundation models’—general-purpose generative AI models, for production of text (e.g., ChatGPT) or images (e.g., MidJourney)—represent a dramatic advance in the state of the art for AI. But their use also introduces a range of new risks, which has prompted an ongoing conversation about possible regulatory mechanisms. Here we propose a specific principle that should be incorporated into legislation: that any organization developing a foundation model intended for public use must demonstrate a reliable detection mechanism for the (...) content it generates, as a condition of its public release. The detection mechanism should be made publicly available in a tool that allows users to query, for an arbitrary item of content, whether the item was generated (wholly or partly) by the model. In this paper, we argue that this requirement is technically feasible and would play an important role in reducing certain risks from new AI models in many domains. We also outline a number of options for the tool’s design, and summarize a number of points where further input from policymakers and researchers would be required. (shrink)

There is a history of thinking that photographs provide a special kind of access to the objects depicted in them, beyond the access that would be provided by a painting or drawing. What is included in the photograph does not depend on the photographer’s beliefs about what is in front of the camera. This feature leads Kendall Walton to argue that photographs literally allow us to see the objects which appear in them. Current generative algorithms produce images in response to (...) users’ text prompts. Depending on the parameters, the output can resemble specific people or things which are named in the prompt. This resemblance does not depend on the user’s beliefs, so generated images are in this sense like photographs. Given this parallel, how should we think about AI-generated images? (shrink)

Zero-shot learning is dedicated to solving the classification problem of unseen categories, while generalized zero-shot learning aims to classify the samples selected from both seen classes and unseen classes, in which “seen” and “unseen” classes indicate whether they can be used in the training process, and if so, they indicate seen classes, and vice versa. Nowadays, with the promotion of deep learning technology, the performance of zero-shot learning has been greatly improved. Generalized zero-shot learning is a challenging topic that has (...) promising prospects in many realistic scenarios. Although the zero-shot learning task has made gratifying progress, there is still a strong deviation between seen classes and unseen classes in the existing methods. Recent methods focus on learning a unified semantic-aligned visual representation to transfer knowledge between two domains, while ignoring the intrinsic characteristics of visual features which are discriminative enough to be classified by itself. To solve the above problems, we propose a novel model that uses the discriminative information of visual features to optimize the generative module, in which the generative module is a dual generation network framework composed of conditional VAE and improved WGAN. Specifically, the model uses the discrimination information of visual features, according to the relevant semantic embedding, synthesizes the visual features of unseen categories by using the learned generator, and then trains the final softmax classifier by using the generated visual features, thus realizing the recognition of unseen categories. In addition, this paper also analyzes the effect of the additional classifiers with different structures on the transmission of discriminative information. We have conducted a lot of experiments on six commonly used benchmark datasets. The experimental results show that our model outperforms several state-of-the-art methods for both traditional as well as generalized zero-shot learning. (shrink)

Harmonic Grammar (HG) and Optimality Theory (OT) are closely related formal frameworks for the study of language. In both, the structure of a given language is determined by the relative strengths of a set of constraints. They differ in how these strengths are represented: as numerical weights (HG) or as ranks (OT). Weighted constraints have advantages for the construction of accounts of language learning and other cognitive processes, partly because they allow for the adaptation of connectionist and statistical models. HG (...) has been little studied in generative linguistics, however, largely due to influential claims that weighted constraints make incorrect predictions about the typology of natural languages, predictions that are not shared by the more popular OT. This paper makes the case that HG is in fact a promising framework for typological research, and reviews and extends the existing arguments for weighted over ranked constraints. (shrink)

A probabilistic Chomsky–Schützenberger hierarchy of grammars is introduced and studied, with the aim of understanding the expressive power of generative models. We offer characterizations of the distributions definable at each level of the hierarchy, including probabilistic regular, context-free, (linear) indexed, context-sensitive, and unrestricted grammars, each corresponding to familiar probabilistic machine classes. Special attention is given to distributions on (unary notations for) positive integers. Unlike in the classical case where the "semi-linear" languages all collapse into the regular languages, using analytic tools (...) adapted from the classical setting we show there is no collapse in the probabilistic hierarchy: more distributions become definable at each level. We also address related issues such as closure under probabilistic conditioning. (shrink)

Generative artificial intelligence (GenAI) promises to revolutionize data-driven fields (Milmo 2023). Building on decades of large language modeling (LLM) (Toner 2023), GenAI can collect, harmonize...

Previous research shows that manipulations (e.g. levels-of-processing) that facilitate true memory often increase susceptibility to false memory. An exception is the generation effect. Using the Deese/Roediger–McDermott (DRM) paradigm, Soraci et al. found that generating rather than reading list items led to an increase in true but not false memories. They argued that generation led to enhanced item-distinctiveness that drove down false memory production. In the current study, we investigated the effects of generative processing on valenced stimuli and after a delayed (...) retention interval to examine factors that may lead to a generation effect that increases false memories. At the immediate test, false recognition rates for both negative and neutral valanced critical lures were similar across read and generate conditions. However, after a one-week delay, we saw a valence differentiation, with a generation effect for false recognition but only for negative stimuli. The roles of item-specific and relational processing during encoding and their interaction with long-term retention are discussed. (shrink)

The advent of generative artificial intelligence and the widespread adoption of it in society engendered intensive debates about its ethical implications and risks. These risks often differ from those associated with traditional discriminative machine learning. To synthesize the recent discourse and map its normative concepts, we conducted a scoping review on the ethics of generative artificial intelligence, including especially large language models and text-to-image models. Our analysis provides a taxonomy of 378 normative issues in 19 topic areas and ranks them (...) according to their prevalence in the literature. The study offers a comprehensive overview for scholars, practitioners, or policymakers, condensing the ethical debates surrounding fairness, safety, harmful content, hallucinations, privacy, interaction risks, security, alignment, societal impacts, and others. We discuss the results, evaluate imbalances in the literature, and explore unsubstantiated risk scenarios. (shrink)

Philosophers interested in the theoretical consequences of predictive processing often assume that predictive processing is an inferentialist and representationalist theory of cognition. More specifically, they assume that predictive processing revolves around approximated Bayesian inferences drawn by inverting a generative model. Generative models, in turn, are said to be structural representations: representational vehicles that represent their targets by being structurally similar to them. Here, I challenge this assumption, claiming that, at present, it lacks an adequate justification. I examine the only argument (...) offered to establish that generative models are structural representations, and argue that it does not substantiate the desired conclusion. Having so done, I consider a number of alternative arguments aimed at showing that the relevant structural similarity obtains, and argue that all these arguments are unconvincing for a variety of reasons. I then conclude the paper by briefly highlighting three themes that might be relevant for further investigation on the matter. (shrink)

Generative AI has captured the public imagination as a tool that promises access to expertise beyond the technical jargon and expense that traditionally characterize such infospheres as those of medicine and law. Largely absent from the current literature, however, are interrogations of generative AI’s abilities to deal in culturally responsive communication, or the expertise interwoven with culturally aware, socially responsible, and personally sensitive communication best practices. To interrogate the possibilities of cultural responsiveness in generative AI, we examine the patterns of (...) response that characterize ChatGPT-3.5’s advice for coming out. Specifically, we submitted 100 prompts soliciting coming out advice to GPT-3.5, variegating each of those prompts slightly to account for intersectional identities. From the analysis, we find that, while the responses are largely in-line with best practices, there are also instances that might represent problematics concerning the interpellation of the user or the persons to whom one is coming out. (shrink)