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)

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)

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.

The ever increasing use of generative artificial intelligence raises significant questions about authorship and related issues such as credit and accountability. In this paper, I consider whether works produced by means of users inputting natural language prompts into Generative Adversarial Networks are works of authorship. I argue that they are not. This is not due to concerns about randomness or machine-assistance compromising human labor or intellectual vision, but instead due to the syntactical and compositional limitations of existing AI systems in (...) handling natural language prompts. This, I argue, gives rise to ‘authorship gaps’. (shrink)

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 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)

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)

We present a generative distributional model for the unsupervised induction of natural language syntax which explicitly models constituent yields and contexts. Parameter search with EM produces higher quality analyses than previously exhibited by unsupervised systems, giving the best published unsupervised parsing results on the ATIS corpus. Experiments on Penn treebank sentences of comparable length show an even higher F1 of 71% on nontrivial brackets. We compare distributionally induced and actual part-of-speech tags as input data, and examine extensions to the basic (...) model. We discuss errors made by the system, compare the system to previous models, and discuss upper bounds, lower bounds, and stability for this task. (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.

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 proliferation of Generative Artificial Intelligence (Generative AI) has led to an increased reliance on AI‐generated content for designing and deploying digital health interventions. While generative AI has the potential to facilitate and automate healthcare, there are concerns that AI‐generated content and AI‐generated health advice could trigger, perpetuate, or exacerbate prior traumatic experiences among vulnerable populations. In this discussion article, I examined how generative‐AI‐powered digital health interventions could trigger, perpetuate, or exacerbate emotional trauma among vulnerable populations who rely on digital (...) health interventions as complementary or alternative sources of seeking health services or information. I then proposed actionable strategies for mitigating AI‐generated trauma in the context of digital health interventions. The arguments raised in this article are expected to shift the focus of AI practitioners against prioritizing dominant narratives in AI algorithms into seriously considering the needs of vulnerable minority groups who are at the greatest risk for trauma but are often invisible in AI data sets, AI algorithms, and their resultant technologies. (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 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)

Background:Policemen all over the world are tasked with the heavy work of maintaining social security. With the imbalance in mentality brought about by high population density and social transformation, the work of the Chinese police is particularly hard. As the window of demographic dividend is closing and the number of newborns is insufficient, China has started to adjust its established fertility policy to encourage a family to have two children. However, the results have not met the expectations of the policy (...) adjustment. It is generally believed that factors such as high work pressure, high parenting costs, and low levels of happiness may be the main reasons for low fertility intentions. Studying this typical population of police officers may explore the relationship between work stress, happiness, and reproductive concerns, and provide evidence of Chinese sample.Objectives:To explore the relations between job burnout, subjective well-being, and generativity concern in Chinese police officers.Methods:The study used a cross-sectional survey to collect data from 494 police officers from H city in China. The participants completed the Maslach Burnout Inventory (MBI), the Family Adaptability and Cohesion Scale (FACESII), the Loyola Generativity Scale (LGS), and the Satisfaction with life scale (SWLS). Moderated mediation effect models assessed the association between job burnout, subjective well-being, and generativity concern.Results:Job burnout had a significant negative predictive effect on both subjective well-being and generativity concern, and subjective well-being played a mediating role between job burnout and generativity concern. In addition, family intimacy and adaptability had a significant negative moderating effect between subjective well-being and generativity concern. In a conclusion, there is a moderated mediating effect between job burnout and generativity concern.Conclusion:Subjective well-being played a mediating role between job burnout and generativity concern. (shrink)

ABSTRACTThis article deals with the recent interest shown by critical realists in the study of generative mechanisms in sociology and proposes stronger integration of hermeneutics into this theoretical approach. There are important differences between realism and hermeneutics. While realism strives to overcome the extremes of empiricism and interpretivism with a new version of naturalism, hermeneutics bases its explanations of society on research into meanings. The question is whether underlining these differences is useful for social theory. On the one hand, underestimating (...) hermeneutics makes it difficult for realists to recognize fully the role that processes of understanding play in generating social change. On the other hand, hermeneutical arguments in sociology idealistically identify being with interpreted being. The concept of generative hermeneutics is designed to help to build an alliance between realism and hermeneutics, since one-sided overemphasis on mechanistic logic devaluates the study of social interaction pursued by interpretative sociology. (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)

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.

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...

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].

In search of general generative principles I start from the postulate of a reality which comprises both materialistic and psychic aspects. This overall reality, described by others as the world of archetypes, is not directly accessible to sensory perception. Yet, by studying archetypical manifestations, it is possible to distinguish different structures or generative principles in it. Comparison of three models, which depict developmental processes in different disciplines, shows that they have the same basic structure. The effects of the archetypes involved (...) can be described as four general generative principles: 1st the principle of wholeness (connection and integration of conflicting opposites), 2nd the principle of complementation and compensation (periodic change of opposite influences); 3rd the enstructuring principle (relative stability or spatial aspect of a manifest structure), and 4th the principle of gesture (change or temporal aspect of that structure). (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 article examines the transformative role of Generative Artificial Intelligence (GAI) in education, exploring diverse disciplines such as engineering, medicine, programming, and information systems. GAI emerges as a revolutionary force, promising to fundamentally change educational practices. The PRISMA 2020 methodology (Page et al., 2021) was used to evaluate the relevant scientific literature. The systematic review identified research that applied specific criteria in the analysis of IAG in education. The selected papers covered a variety of disciplines, providing a comprehensive view of (...) the impact of IAG in education. The results show a diversity of approaches and institutional responses to IAG in education. From significant changes in teaching practices to the identification of specific opportunities in disciplines such as computer science and engineering, GAI stands out as a catalyst for transformation. The adaptation of tertiary education, the need for specific skills to work with GAI, and ethical responses emerge as key themes. It focuses on the need for a deeper and more consensual understanding of the role of GAI in education. Concrete research-supported opportunities are highlighted, but ethical limitations and concerns are also underscored. Collaboration, reflection, and adaptation to open educational practices are proposed as approaches to address the challenges and fully exploit the benefits of IAG in education. This comprehensive analysis contributes to understanding the current and future landscape of GAI in education, providing valuable guidelines for educators, institutions, and educational technology developers. (shrink)

Mesoudi et al.'s new synthesis for cultural evolution closely parallels the evolutionary synthesis of Neo-Darwinism. It too draws inspiration from population genetics, recruits other fields, and, unfortunately, also ignores development. Enculturation involves many serially acquired skills and dependencies that allow us to build a rich cumulative culture. The newer synthesis, evolutionary developmental biology, provides a key tool, generative entrenchment, to analyze them. (Published Online November 9 2006).

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)

This paper describes a generative theory of bugs. It claims that all bugs of a procedural skill can be derived by a highly constrained form of problem solving acting on incomplete procedures. These procedures are characterized by formal deletion operations that model incomplete learning and forgetting. The problem solver and the deletion operator have been constrained to make it impossible to derive “star‐bugs”—algorithms that are so absurd that expert diagnosticians agree that the alogorithm will never be observed as a bug. (...) Hence, the theory not only generates the observed bugs, it fails to generate star‐bugs.The theory has been tested on an extensive data base of bugs for multidigit subtraction that was collected with the aid of the diagnostic systems buggy and debuggy. In addition to predicting bug occurrence, by adoption of additional hypotheses, the theory also makes predictions about the frequency and stability of bugs, as well as the occurrence of certain latencies in processing time during testing. Arguments are given that the theory can be applied to domains other than subtraction and that it can be extended to provide a theory of procedural learning that accounts for bug acquisition. Lastly, particular care has been taken to make the theory principled so that it can not be tailored to fit any possible data. (shrink)

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

Since their public launch, a little over a year ago, large language models (LLMs) have inspired a flurry of analysis about what their implications might be for medical ethics, and for society more broadly. 1 Much of the recent debate has moved beyond categorical evaluations of the permissibility or impermissibility of LLM use in different general contexts (eg, at work or school), to more fine-grained discussions of the criteria that should govern their appropriate use in specific domains or towards certain (...) ends. 2 With each passing week, it seems more and more inevitable that LLMs will be a pervasive feature of many, if not most, of our lives. It would not be possible—and would not be desirable—to prohibit them across the board. We need to learn how to live with LLMs; to identify and mitigate the risks they pose to us, to our fellow creatures, and the... (shrink)

Im Zentrum des Beitrags stehen Konzeption und Analyse generativer Verantwortung. Dazu werden erstens Herausforderungen der Verantwortung für die Folgegeneration und ihre Blockaden beschrieben. Zweitens wird Generativität als Sorge und Verantwortung für die Nachkommen psychoanalytisch-sozialpsychologisch bestimmt. Drittens geht es um Aufklärungspotenziale psychoanalytischer Perspektiven. Normative Orientierungen der von vielen Seiten geforderten neuen Aufklärung im Anthropozän erlangen potenzielle Wirkmächtigkeit – so eine zentrale These – erst durch die systematische Analyse der Widerstände gegen generative Verantwortung. Die Möglichkeit der Aufklärung ergibt sich dabei nicht allein (...) aus individueller psychischer Arbeit, sondern auch aus entsprechender Selbstaufklärung der Gesellschaft über ihre Ausblendungen. (shrink)

Humanistic management and mindfulness practices can potentiate one another to foster an inclusive society. By moving beyond a limited instrumental understanding of mindfulness practice to a generative mindfulness that incorporates a recognition of the rich nature of the human mind, awareness of cultural practices, and deeply rooted ethical foundations, managers can create organizational cultures that honor the sacred in every human being. A set of interviews with noted consultants and researchers on mindfulness and leadership suggests convergence on this perspective, as (...) does the experience of a university administrator in developing an anti-racist agenda for a large U.S. university. This article is based on both the personal experience and scholarly research of its authors and suggests ways that humanistic management education can contribute to creating inclusive workplaces through incorporating generative mindfulness in executive development as well as undergraduate programs. (shrink)

With people’s concerns about the environment growing, the demand for organic food has increased. However, few studies have focused on organic dining intention. Therefore, this study examined generativity, which is defined as the direction and care for the growth of future generations through self-expanding forms, and its influence on attitude toward organic food, environment concern and dining intention. The moderating effect of age was also examined. A total of 418 responses were collected through a face-to-face survey from Shanghai respondents. PLS-SEM (...) was utilized to verify the model and test the relationships among the constructs. The results show that generativity directly influences environmental concerns, attitudes toward organic food and dining intentions. Furthermore, environmental concerns and attitudes toward organic food are mediating variables for generativity to affect dining intentions. The older the age group, the more likely it is for generativity to have a positive influence on attitude toward organic food and environmental concerns. Theoretical and practical implications are also discussed in this study. (shrink)

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)

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 ...

The objective of this article is to assess the impact of generative artificial intelligence (AGI) as a learning tool in clinical practice, as perceived by clinical students of human medicine. To this end, six learning activities were devised and executed, employing diverse pedagogical approaches and AGI tools, with the objective of addressing various facets of clinical practice. These included the creation of explanatory material, literature analysis, the selection of clinical cases for publication, the development of self-assessment questions, the production of (...) explanatory videos, and the creation of scientific posters. These activities were conducted during the clinical internships of the fifth year of the medical curriculum and were evaluated using both quantitative and qualitative methods. The findings indicated that the incorporation of GAI as a pedagogical instrument in the clinical training of medical students yielded a favorable influence on their motivation, self-assurance, satisfaction, competencies, and knowledge. The students identified GAI as a novel, applicable, useful, and transferable tool and expressed interest in continuing to use it in the future. However, the results also indicated that students encountered certain challenges and difficulties in utilizing GAI as a learning tool, including overconfidence, resistance, and a lack of understanding. In conclusion, this study provides empirical evidence on the use of GAI as a learning tool for undergraduate medical students' clinical practices, and contributes to the knowledge base regarding the possibilities and challenges of GAI application in higher education. (shrink)

Traditional scholarship seems not to pay sufficient attention to the fact that Daxue 《大學》 has established a system of ethical and political philosophy on the basis of the idea of xin 心 (heart-mind) whereas the Zhongyong 《中庸》 has argued for the participation of the human person in the creativities of heaven and earth based on the onto-generative nature (xing 性) of the human person. How to explain this fact and interrelate and integrate these two systems become both a historical challenge (...) and a theoretical issue in the understanding of the Confucian philosophy of humanity as we find in the Lunyu 《論語》. (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...

This paper presents the treatment of anaphora in generative grammar. After a broad review of of the different theories covered under the term, it provides an overview of the history of the treatment of anaphora in generative grammar. It then discusses Ariel’s theory of accessibility and shows how it can account for the choice of some of the anaphoric expressions provided in the text. In a final section, the paper presents the author’s recent work on the choice between verbal anaphors. (...) It is shown that accessibility can account for some aspects of the choice but is not sufficient. Further constraints on the choice are proposed in terms of the notion of Question Under Discussion, for which experimental evidence is adduced. (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.

Artists and designers working in the fields of generative and bio art frequently focus on designing speculative visions of how nature can be reimagined with the use of computational media and synthetic biology. Centered on the unique artistic strategies of reimagining life forms, this paper analyzes and compares a selection of generative software-based projects, in which artists are mimicking different natural phenomena and have the tendency to beautify nature and life, with bio art projects, where ethical considerations are prioritized over (...) other aspects of the work. Experimenting with software and producing code-based generative art can be a relatively accessible creative endeavor while working with synthetic biology requires more demanding and controlled workplace conditions and specialized equipment. Despite the differences in accessibility and usability, both fields of generative and bio art challenge the boundaries of contemporary artistic practice and research by mapping, provoking and contemplating the dramatic changes of life forms, in the era when living matter can be re-engineered into a new material capable of computing. (shrink)