The generation of synthetic data is becoming a fundamental task in the daily life of any organization due to the new protection data laws that are emerging. Because of the rise in the use of Artificial Intelligence, one of the most recent proposals to address this problem is the use of Generative Adversarial Networks. These types of networks have demonstrated a great capacity to create synthetic data with very good performance. The goal of (...) class='Hi'>synthetic data generation is to create data that will perform similarly to the original dataset for many analysis tasks, such as classification. The problem of GANs is that in a classification problem, GANs do not take class labels into account when generating new data, it is treated as any other attribute. This research work has focused on the creation of new synthetic data from datasets with different characteristics with a Conditional Generative Adversarial Network. CGANs are an extension of GANs where the class label is taken into account when the new data is generated. The performance of our results has been measured in two different ways: firstly, by comparing the results obtained with classification algorithms, both in the original datasets and in the data generated; secondly, by checking that the correlation between the original data and those generated is minimal. (shrink)

One of the most active areas of research in semi-supervised learning has been to study methods for constructing good ensembles of classifiers. Ensemble systems are techniques that create multiple models and then combine them to produce improved results. These systems usually produce more accurate solutions than a single model would. Specially, multi-view ensemble systems improve the accuracy of text classification because they optimize the functions to exploit different views of the same input data. However, despite being more promising than (...) the single-view approaches, document datasets often have no natural multiple views available. This study proposes an algorithm to generate a synthetic view from a standard text dataset. The model generates a new view from the standard bag-of-words approach using an algorithm based on hidden Markov models. To show the effectiveness of the proposed HMM-based synthetic view generation method, it has been integrated in a co-training ensemble system and tested with four text corpora: Reuters, 20 Newsgroup, TREC Genomics and OHSUMED. The results obtained are promising, showing a significant increase in the efficiency of the ensemble system compared to a single-view approach. (shrink)

What is the relationship between ideas of sameness and difference for machine learning and AI? Algorithms are often understood to participate in the continual displacement of the different and heterogeneous in society in favour of sameness, of that which is socio-politically similar and proximate. In contrast to this prevalent emphasis on sameness, however, this paper argues that there is a nascent heterophilic logic underpinning the intersection of synthetic data and machine learning, a move towards actively generating differences and (...) heterogeneous data attributes to train, fine-tune, and optimize algorithms. Yet, these synthetic attribute data are nonetheless always machine compatible, devoid of their socio-cultural dynamics and tensions. As such, through a critical examination of three core dimensions of this emergent politics of difference of synthetic data – disentanglement, compositionality, and normativity – the paper argues that this has the potential to ultimately undercut a politics of intervention that seeks to foreground the systemic unfairness and violence of machine learning. (shrink)

Researchers and practitioners are increasingly using machine‐generated synthetic data as a tool for advancing health science and practice, by expanding access to health data while—potentially—mitigating privacy and related ethical concerns around data sharing. While using synthetic data in this way holds promise, we argue that it also raises significant ethical, legal, and policy concerns, including persistent privacy and security problems, accuracy and reliability issues, worries about fairness and bias, and new regulatory challenges. The virtue (...) of synthetic data is often understood to be its detachment from the data subjects whose measurement data is used to generate it. However, we argue that addressing the ethical issues synthetic data raises might require bringing data subjects back into the picture, finding ways that researchers and data subjects can be more meaningfully engaged in the construction and evaluation of datasets and in the creation of institutional safeguards that promote responsible use. (shrink)

Researchers and practitioners are increasingly using machine-generated synthetic data as a tool for advancing health science and practice, by expanding access to health data while—potentially—mitigating privacy and related ethical concerns around data sharing. While using synthetic data in this way holds promise, we argue that it also raises significant ethical, legal, and policy concerns, including persistent privacy and security problems, accuracy and reliability issues, worries about fairness and bias, and new regulatory challenges. The virtue (...) of synthetic data is often understood to be its detachment from the data subjects whose measurement data is used to generate it. However, we argue that addressing the ethical issues synthetic data raises might require bringing data subjects back into the picture, finding ways that researchers and data subjects can be more meaningfully engaged in the construction and evaluation of datasets and in the creation of institutional safeguards that promote responsible use. (shrink)

In this paper we propose an non-machine learning artificial intelligence (AI) based approach for telecom data analysis, with a special focus on clique detection. Clique detection can be used to identify households, which is a major challenge in telecom data analysis and predictive analytics. Our approach does not use any form of machine learning, but another type of algorithm: satisfiability for propositional logic. This is a neglected approach in modern AI, and we aim to demonstrate that for certain (...) tasks, it may be a good alternative to machine learning-based approaches. We have used a simple DPLL satisfiability solver over an artificially generated telecom dataset (due to GDPR regulations), but our approach can be implemented on any telecom data by following the SAT encoding we have developed, and the DPLL solver can be substituted by a more advanced alternative such as CDCL. This paper extends the method presented in [1] for banking logs to data containing caller information, and proposes a more efficient encoding. -/- . (shrink)

The emergence of new techniques in both microbial biotechnology and artificial intelligence (AI) is opening up a completely new field for monitoring and sometimes even controlling the evolution of pathogens. However, the now famous generative AI extracts and reorganizes prior knowledge from large datasets, making it poorly suited to making predictions in an unreliable future. In contrast, an unfamiliar perspective can help us identify key issues related to the emergence of new technologies, such as those arising from synthetic biology, (...) whilst revisiting old views of AI or including generative AI as a generator of abduction as a resource. This could enable us to identify dangerous situations that are bound to emerge in the not-too-distant future, and prepare ourselves to anticipate when and where they will occur. Here, we emphasize the fact that amongst the many causes of pathogen outbreaks, often driven by the explosion of the human population, laboratory accidents are a major cause of epidemics. This review, limited to animal pathogens, concludes with a discussion of potential epidemic origins based on unusual organisms or associations of organisms that have rarely been highlighted or studied. (shrink)

Archival data processing consists of cleaning and formatting data between the moment a dataset is deposited and its publication on the archive’s website. In this article, I approach data processing by combining scholarship on invisible labor in knowledge infrastructures with a Marxian framework and show the relevance of considering data processing as factory labor. Using this perspective to analyze ethnographic data collected during a six-month participatory observation at a U.S. data archive, I generate a (...) taxonomy of the forms of alienation that data processing generates, but also the types of resistance that processors develop, across four categories: routine, speed, skill, and meaning. This synthetic approach demonstrates, first, that data processing reproduces typical forms of factory worker’s alienation: processors are asked to work along a strict standardized pipeline, at a fast pace, without acquiring substantive skills or having a meaningful involvement in their work. It reveals, second, how data processors resist the alienating nature of this workflow by developing multiple tactics along the same four categories. Seen through this dual lens, data processors are therefore not only invisible workers, but also factory workers who follow and subvert a workflow organized as an assembly line. I conclude by proposing a four-step framework to better value the social contribution of data workers beyond the archive. (shrink)

We describe a new approach for developing and validating cognitive process models. We develop graphical models (specifically, hidden Markov models) both from human empirical data on a task, as well as from synthetic data traces generated by a cognitive process model of human behavior on the task. We show that considering differences between the two graphical models can unveil substantive and nuanced imperfections of cognitive process models that can then be addressed to increase their fidelity to empirical (...) data. (shrink)

. Many large companies transact from multiple branches. It results in generating multiple databases, since local transactions are stored locally. The number of multi-branch companies as well as the number of branches of a multi-branch company is increasing over time. Thus, it is important to study data mining on multiple databases. Global exceptional patterns describe interesting individuality of few branches. Therefore, it is interesting to identify such patterns. In this paper, we propose type I and type II global exceptional (...) frequent itemsets in multiple databases by extending the notion of global exceptional frequent itemset. Also, we propose the notion of exceptional sources for a type II global exceptional frequent itemset. We propose type I and type II global exceptional association rules in multiple databases by extending the notion of global exceptional association rule. We propose an algorithm for synthesizing type II global exceptional frequent itemsets. Experimental results are presented on both real and synthetic databases. We compare the proposed algorithm with the existing algorithm theoretically as well as experimentally. The experimental results show that the proposed algorithm is effective and promising. (shrink)

Training artificial intelligence (AI) systems requires vast quantities of data, and AI developers face a variety of barriers to accessing the information they need. Synthetic data has captured researchers’ and industry’s imagination as a potential solution to this problem. While some of the enthusiasm for synthetic data may be warranted, in this short paper we offer critical counterweight to simplistic narratives that position synthetic data as a cost-free solution to every data-access challenge—provocations (...) highlighting ethical, political, and governance issues the use of synthetic data can create. We question the idea that synthetic data, by its nature, is exempt from privacy and related ethical concerns. We caution that framing synthetic data in binary opposition to “real” measurement data could subtly shift the normative standards to which data collectors and processors are held. And we argue that by promising to divorce data from its constituents—the people it represents and impacts—synthetic data could create new obstacles to democratic data governance. (shrink)

Diffusions in Architecture: Artificial Intelligence and Image Generators delves into the impact of Diffusion AI algorithms and generative image models on architecture design and aesthetics. The book presents an in-depth analysis of how these new technologies are revolutionizing the field of architecture. The architects presented in the book focus on the application of specific AI techniques and tools used in generative design, such as Diffusion models, Dall-E2, Stable Diffusion, and MidJourney. It discusses how these techniques can generate synthetic images (...) that are both realistic and imaginative, creating new possibilities for architectural design and aesthetics. This comprehensive overview of the impact of Diffusion AI algorithms and generative image models on the field of architecture shows how they are changing the way architects approach their work. With a foreword by Lev Manovich—artist, writer and one of the world's most influential digital culture theorists. Sharing the work and insights of a team of designers and theorists from a range of backgrounds, offering disciplinary depth, and covering the full impact of these tools and models on architecture, Diffusions in Architecture includes information on: Fresh perspectives on design and aesthetics, with designs, images, and commentary from 22 leading architects, theorists, and designersThe potential of prompt engineering and text-to-image models applicable to a broad interdisciplinary audienceWhether image generators, or AI in general, will be an aid for human design, or potentially displace humans from the market fundamentals of a larger debate in the architectural discourse (and practice) on the use of image generatorsCollecting the different ideas that have emerged in the field, Diffusions in Architecture provides architects, designers, concept artists, and theorists with an overview of this cornucopia of architectural imaginations produced in a common effort between humans and artificial intelligence. (shrink)

It is commonplace to encounter nonstationary or heterogeneous data, of which the underlying generating process changes over time or across data sets. Such a distribution shift feature presents both challenges and opportunities for causal discovery. In this paper we develop a principled framework for causal discovery from such data, called Constraint-based causal Discovery from Nonstationary/heterogeneous Data, which addresses two important questions. First, we propose an enhanced constraint-based procedure to detect variables whose local mechanisms change and recover (...) the skeleton of the causal structure over observed variables. Second, we present a way to determine causal orientations by making use of independence changes in the data distribution implied by the underlying causal model, benefiting from information carried by changing distributions. Experimental results on various synthetic and real-world data sets are presented to demonstrate the efficacy of our methods. (shrink)

Virtual screening is the most critical process in drug discovery, and it relies on machine learning to facilitate the screening process. It enables the discovery of molecules that bind to a specific protein to form a drug. Despite its benefits, virtual screening generates enormous data and suffers from drawbacks such as high dimensions and imbalance. This paper tackles data imbalance and aims to improve virtual screening accuracy, especially for a minority dataset. For a dataset identified without considering the (...) data’s imbalanced nature, most classification methods tend to have high predictive accuracy for the majority category. However, the accuracy was significantly poor for the minority category. The paper proposes a K-mean algorithm coupled with Synthetic Minority Oversampling Technique to overcome the problem of imbalanced datasets. The proposed algorithm is named as KSMOTE. Using KSMOTE, minority data can be identified at high accuracy and can be detected at high precision. A large set of experiments were implemented on Apache Spark using numeric PaDEL and fingerprint descriptors. The proposed solution was compared to both no-sampling method and SMOTE on the same datasets. Experimental results showed that the proposed solution outperformed other methods. (shrink)

Cho and Martinez-Martin (2023) provide a compelling critique of the profound influence that data sourcing for artificial intelligence (AI) has on the healthcare sector. They emphasize the need for...

. Software testing is a very important phase in the development of software. Testing includes the generation of test cases which, if done manually, is time consuming. To automate this process and generate optimal test cases, several meta-heuristic techniques have been developed. These approaches include genetic algorithm, cuckoo search, tabu search, intelligent water drop, etc. This paper presents an effective approach for test data generation using the cuckoo search and tabu search algorithms. It combines the cuckoo algorithm's (...) strength of converging to the solution in minimal time along with the tabu mechanism of backtracking from local optima by Lévy flight. The experimental results show that the algorithm is effective in generating test cases optimally and its performance is better than various earlier proposed approaches. (shrink)

What if gravity satisfied the Klein-Gordon equation? Both particle physics from the 1920s-30s and the 1890s Neumann-Seeliger modification of Newtonian gravity with exponential decay suggest considering a "graviton mass term" for gravity, which is _algebraic_ in the potential. Unlike Nordström's "massless" theory, massive scalar gravity is strictly special relativistic in the sense of being invariant under the Poincaré group but not the 15-parameter Bateman-Cunningham conformal group. It therefore exhibits the whole of Minkowski space-time structure, albeit only indirectly concerning volumes. Massive (...) scalar gravity is plausible in terms of relativistic field theory, while violating most interesting versions of Einstein's principles of general covariance, general relativity, equivalence, and Mach. Geometry is a poor guide to understanding massive scalar gravity: matter sees a conformally flat metric due to universal coupling, but gravity also sees the rest of the flat metric in the mass term. What is the 'true' geometry, one might wonder, in line with Poincaré's modal conventionality argument? Infinitely many theories exhibit this bimetric 'geometry,' all with the total stress-energy's trace as source; thus geometry does not explain the field equations. The irrelevance of the Ehlers-Pirani-Schild construction to a critique of conventionalism becomes evident when multi-geometry theories are contemplated. Much as Seeliger envisaged, the smooth massless limit indicates underdetermination of theories by data between massless and massive scalar gravities---indeed an unconceived alternative. At least one version easily could have been developed before General Relativity; it then would have motivated thinking of Einstein's equations along the lines of Einstein's newly re-appreciated "physical strategy" and particle physics and would have suggested a rivalry from massive spin 2 variants of General Relativity. The Putnam-Grünbaum debate on conventionality is revisited with an emphasis on the broad modal scope of conventionalist views. Massive scalar gravity thus contributes to a historically plausible rational reconstruction of much of 20th-21st century space-time philosophy in the light of particle physics. An appendix reconsiders the Malament-Weatherall-Manchak conformal restriction of conventionality and constructs the 'universal force' influencing the causal structure. Subsequent works will discuss how massive gravity could have provided a template for a more Kant-friendly space-time theory that would have blocked Moritz Schlick's supposed refutation of synthetic _a priori_ knowledge, and how Einstein's false analogy between the Neumann-Seeliger-Einstein modification of Newtonian gravity and the cosmological constant \Lambda generated lasting confusion that obscured massive gravity as a conceptual possibility. (shrink)

De Vries' mutation theory has not stood the test of time. The supposed mutations of Oenothera were in reality complex recombination phenomena, ultimately explicable in Mendelian terms, while instances of large-scale mutations were found wanting in other species. By 1915 the mutation theory had begun to lose its grip on the biological community; by de Vries' death in 1935 it was almost completely abandoned. Yet, as we have seen, during the first decade of the present century it achieved an enormous (...) popularity. As this paper has tried to suggest, one of the principal reasons for this was that de Vries' theory served as a banner around which a whole crowd of disaffected Darwinians or anti-Darwinians could rally. However, not all of those who favored de Vries did so for quite the same reasons. Underlying the multitude of views ran several common threads: a dissatisfaction with current Darwinian theory born out of misunderstanding natural selection, a general misunderstanding of the nature of species, and a prejudice against speculative, nontestable theories in biology.Supporters of de Vries were not the only opponents of Darwinism, nor was the mutation theory the only alternative to natural selection. In the early twentieth century a number of theories had been proposed to explain away the problems which Darwin had left unsolved. There was the idea of orthogenesis, championed by the American paleontologists Cope, Osborn and others; organic selection (or orthoplasy) was championed by M. M. Baldwin and C. Lloyd Morgan; there were the concepts of convergent evolution proposed by Hermann Friedmann, the theory of physiological selection by John George Romanes, and the concepts of reproductive divergence by H. M. Vernon. Virtually none of these men either accepted or were strong supporters of the de Vriesian theory, for each had his own particular ‘ism” to advocate as the major factor in evolution. The existence of a large number of such theories, each purporting to be the explanation, was characteristic of evolutionary theory at the turn of the century. It is to a large extent the emphasis on such fragmentary concepts that retarded development of the comprehensive theory of evolution which emerged in the 1920's and 1930's. For the historian, however, a study of these alternative theories is instructive in trying to understand the inherent difficulties which Dawwinian theory posed to biologists at the time. De Vries' mutation theory serves historically as a mirror to reflect the critical mood of a generation hostile to the theory of natural selection.It has often been claimed that it was impossible to understand the mechanism of natural selection until it could be placed in genetic and mathematical terms. It is certainly true that great strides have been made in population genetics and the treatment of evolutionary concepts with mathematical tools in the last forty years. But the very people who developed the genetical and mathematical approach to evolution were already convinced of the essential correctness of Darwinian theory before they started. Advances in an understanding of Mendelian heredity aided greatly in solving one important issue for evolutionists: the origin of variations. And the rigor with which selection acted could best be studied by observing changes in gene frequencies (calculated mathematically) over a number of generations. But as this paper has shown, two of the basic problems which biologists faced in evaluating Darwinian theory at the turn of the century-the nature of species, and the criteria of what constituted an acceptable explanation in biological science-could not be answered directly by mathematics. What mathematical and genetical theory did do was to help convince the skeptics of the validity of the Darwinian proposition.The change in explanatory criteria which many hailed as de Vries' most important contribution to evolutionary theory seems to have been part of a general emergence of twentieth-century biology from the domination of theorizers in the nineteenth. It also marked the emergence of America from the domination of biological, and particularly evolutionary, influence of Europeans. The change occurred in three areas: in the kinds of questions asked: testable versus non-testable; in the kind of data sought: quantitative versus qualitative; and in the kinds of theories proposed: analytical and reductive—the attempt to see complex processes in terms of simpler components-as opposed to synthetic and speculative. Although ultimately wrong in his idea, de Vries and his theories rode high on the wave of “experimentalism” which was the harbinger of a new era in evolutionary theory. (shrink)

Critics of the erotetic model of explanation question its ability to discriminate significant from spurious explanations. One response to these criticisms has been to impose contextual restrictions on a case-by-case basis. In this article, the author argues that these approaches have overestimated the role of interests at the expense of other contextual aspects characteristic of social-scientific explanation. For this reason, he shows how procedures of measuring occupational status and social mobility affected different aspects of one explanation that Peter Blau and (...) Otis Dudley Duncan offered in their sociological classic, The American Occupational Structure. He uses the findings from this case study to meet objections to the erotetic model. Key Words: explanation • social science • erotetic • why-question • context. (shrink)

Depending on different positions in the debate on scientific realism, there are various accounts of the phenomena of physics. For scientific realists like Bogen and Woodward, phenomena are matters of fact in nature, i.e., the effects explained and predicted by physical theories. For empiricists like van Fraassen, the phenomena of physics are the appearances observed or perceived by sensory experience. Constructivists, however, regard the phenomena of physics as artificial structures generated by experimental and mathematical methods. My paper investigates the historical (...) background of these different meanings of phenomenon in the traditions of physics and philosophy. In particular, I discuss Newton’s account of the phenomena and Bohr’s view of quantum phenomena, their relation to the philosophical discussion, and to data and evidence in current particle physics and quantum optics. (shrink)

In this paper we wish to bring together two seemingly independent areas of research: synaesthesia and sensory substitution. Synaesthesia refers to a rare condition where a sensory stimulus elicits not only the sensation that stimulus evokes in its own modality, but an additional one; a synaesthete may thus hear the word “Monday”, and, in addition to hearing it, have a concurrent visual experience of a red color. Sensory substitution, in contrast, attempts to substitute a sensory modality that a person has (...) lost by transforming the information it provided so that it can be accessed through another, intact sensory modality. To make visual information accessible to a blind person, for example, data taken by a camera would be transformed into tactile or auditory information. What do synaesthesia and sensory substitution have in common? Research in both of these areas contributes to our understanding both of cross-modal cooperation and of sensory sensations or qualia, asking under what circumstances these can arise in a modality that is not stimulated. Synaesthesia reveals that this “sensory cross-activation” is possible, and sensory substitution research hopes to induce it. In this article, we will review briefly the literature on synaesthesia, and discuss the issue of qualia for this domain of research. We will then address the evidence for synaesthesia and visual qualia in the blind, and the research on sensory substitution, to finally ask whether sensory substitution may induce a ‘synthetic’ form of synaesthesia by taking advantage of the nervous system’s capacity for generating visual images in the absence of retinal input. (shrink)

This paper introduces moral argument analytics, a technology that provides insights into the use of moral arguments in discourse. We analyse five socio-political corpora of argument annotated data from offline and online discussions, totalling 240k words with 9k arguments, with an average annotation accuracy of 78%. Using a lexicon-based method, we automatically annotate these arguments with moral foundations, achieving an estimated accuracy of 83%. Quantitative analysis allows us to observe statistical patterns and trends in the use of moral arguments, (...) whereas qualitative analysis enables us to understand and explain the communication strategies in the use of moral arguments in different settings. For instance, supporting arguments often rely on Loyalty and Authority, while attacking arguments use Care. We find that online discussions exhibit a greater diversity of moral foundations and a higher negative valence of moral arguments. Online arguers often rely more on Harm rather than Care, Degradation rather than Sanctity. These insights have significant implications for AI applications, particularly in understanding and predicting human and machine moral behaviours. This work contributes to the construction of more convincing messages and the detection of harmful or biased AI-generated synthetic content. (shrink)

This article examines the social acceptability and governance of emotional artificial intelligence in children’s toys and other child-oriented devices. To explore this, it conducts interviews with stakeholders with a professional interest in emotional AI, toys, children and policy to consider implications of the usage of emotional AI in children’s toys and services. It also conducts a demographically representative UK national survey to ascertain parental perspectives on networked toys that utilise data about emotions. The article highlights disquiet about the evolution (...) of generational unfairness, that encompasses injustices regarding the datafication of childhood, manipulation, parental vulnerability, synthetic personalities, child and parental media literacy, and need for improved governance. It concludes with practical recommendations for regulators and the toy industry. (shrink)

Neural organization: Structure, function, and dynamics shows how theory and experiment can supplement each other in an integrated, evolving account of the brain's structure, function, and dynamics. (1) Structure: Studies of brain function and dynamics build on and contribute to an understanding of many brain regions, the neural circuits that constitute them, and their spatial relations. We emphasize Szentágothai's modular architectonics principle, but also stress the importance of the microcomplexes of cerebellar circuitry and the lamellae of hippocampus. (2) Function: Control (...) of eye movements, reaching and grasping, cognitive maps, and the roles of vision receive a functional decomposition in terms of schemas. Hypotheses as to how each schema is implemented through the interaction of specific brain regions provide the basis for modeling the overall function by neural networks constrained by neural data. Synthetic PET integrates modeling of primate circuitry with data from human brain imaging. (3) Dynamics: Dynamic system theory analyzes spatiotemporal neural phenomena, such as oscillatory and chaotic activity in both single neurons and (often synchronized) neural networks, the self-organizing development and plasticity of ordered neural structures, and learning and memory phenomena associated with synaptic modification. Rhythm generation involves multiple levels of analysis, from intrinsic cellular processes to loops involving multiple brain regions. A variety of rhythms are related to memory functions. The Précis presents a multifaceted case study of the hippocampus. We conclude with the claim that language and other cognitive processes can be fruitfully studied within the framework of neural organization that the authors have charted with John Szentágothai. Key Words: cognitive maps; computational neuroscience; dynamics; hippocampus; memory; modular architectonics; neural modeling; neural organization; neural plasticity; rhythmogenesis; Szentágothai. (shrink)

The essay broadens the understanding of Ortega's thought by elaborating his historiosophy, which is crucial to fully comprehend his popular work, 'The Revolt of the Masses'. The author argues that Ortega's famous sociological framework (based on the interplay between the elites and the masses) is very often trivialized due to the lack of knowledge about his anthropological assumptions, upon which the model of the evolution of culture is constructed. Utilizing the already existing literature (inter alia a synthetic work by (...) K. Polit), the essay reconstructs three philosophical crises in European thought that can be ultimately depicted as a suggestive sinusoid of social attitudes operating throughout the history of Western Civilization between the two boundary lines of the primary 'belief'. The belief is in fact a trust in the first data people have to adopt before they start to think philosophically: the priority of the object or the subject (historically: fides or ratio). The sinusoid shows the cyclical change of the first data people tended to accept and reveals a certain cultural mechanism: every culture is first developed by the inspired generation of individuals who structure reality in some way and then fight for the dissemination of their framework. After they prevail and the culture is accepted on a mass level, a process of degradation starts - this is because the culture gradually looses its link with the vivid circumstances that once constituted the stimulus for the founding generation. As a result, the culture becomes gradually more formal and distant from 'real life' - the elites do not innovate anymore, perceiving their world view as well-established and the masses are able only to renovate what is inherited. In the long run this leads to 'vital disorientation', which must force the next great generation of individuals to structure reality anew. 'The Revolt...' perceived in this way receives another layer of understanding. The popular interpretation of the book is that mass men, knowing their inherent rights (thanks to democracy) and having leisure time (technological advance) enter the public stage and want to be ruled by somebody of their sort. The author highlights that, apart from these two, a third factor is present: the long-term socialization of the culture of 'pure rationalism'. The mass man already feels that it does not correspond fully to his daily experience and becomes disoriented as a result. In consequence, the time of mass movements has come (that will be organized in accordance with the radicalized principle of either rationalism or irrationalism), until the elites harness the revolted masses again. The final part of the essay suggests the possible Eastern European dimension of Ortega's predictions about postmodern Europe and indicates that his intuitions were sufficiently accurate to foresee the emergence of some main currents in the contemporary humanities and sciences. (shrink)

It is becoming increasingly clear that repetitive DNA is of biological significance as well as experimental importance. Here we review the information available about one type of repetitive DNA, the trinucleotide repeat (CAC)n, and briefly compare it with other trinucleotide repeats. Although much work has been done in analysing DNA fingerprinting patterns produced using the synthetic oligonucleotide (CAC)5 as a probe, there is relatively little information about individual (CAC)n‐containing sequences and their abundance, organisation and distribution in mammalian DNA. From (...) the data that is available, it is clear that there are at least two areas that should repay further study: (1) the organisation and generation of long sequences that contain (CAC)n motifs as part of a larger repeating unit (minisatellites) and (2) the distribution of small (CAC)n sequences (microsatellites), in particular their relationship to genes. (shrink)

The guiding thread of the paper is the diagnosis that the advanced division of cognitive labor (that is, intellectual specialization) engenders a set of perennial, political and epistemic challenges (Millgram 2015) that, simultaneously, also generate opportunities for philosophy. In this paper, I re-characterize the nature of synthetic philosophy as a means to advance and institutionalize philosophy. For my definition of synthetic philosophy see section 2. In section 1, I treat Plato’s Republic as offering two models to represent philosophy's (...) relationship to the other sciences within the advanced division of labor. I highlight that for Plato intellectual specialization is central not just to economic, but also to political life. And, yet, that the very dispersion of scientific expertise, and its esoteric nature, also generates non-trivial challenges to the recognition and political utilization of knowledge. From Plato we can infer that in imperfect circumstances, philosophy’s self-constitution is, in part, a response to these challenges in political epistemology. However, how philosophy is institutionalized differs through time. In section 2, I re-introduce my conceptualization of synthetic philosophy and restate it. This makes visible that synthetic philosophy is already widely practiced in the profession as philosophy of the special sciences, PPE, formal modelling, public philosophy, etc. I use recent work by Dorst (2023) to illustrate synthetic philosophy and to identify some of the processes that give rise to the need for it. In sections 2-3, I contrast my account with the evolving ways that Philip Kitcher has conceptualized synthetic philosophy in order to make more precise the version promoted here. I do so not just because Kitcher and I use the same term, ‘synthetic philosophy,’ but because the temptations inherent in Kitcher’s approach should be resisted. -/- . (shrink)

Synthetic biologists aim to generate biological organisms according to rational design principles. Their work may have many beneficial applications, but it also raises potentially serious ethical concerns. In this article, we consider what attention the discipline demands from bioethicists. We argue that the most important issue for ethicists to examine is the risk that knowledge from synthetic biology will be misused, for example, in biological terrorism or warfare. To adequately address this concern, bioethics will need to broaden its (...) scope, contemplating not just the means by which scientific knowledge is produced, but also what kinds of knowledge should be sought and disseminated. (shrink)

Mammalian synthetic biology holds the promise of providing novel therapeutic strategies, and the first success stories are beginning to be reported. Here we focus on the latest generation of mammalian transgene control devices, highlight state‐of‐the‐art synthetic gene network design, and cover prototype therapeutic circuits. These will have an impact on future gene‐ and cell‐based therapies and help bring drug discovery into a new era. The inventory of biological parts that are essential for life on this planet is (...) becoming increasingly complete. The postgenomic era has provided encyclopedic information on gene‐function correlations and systems biology is now delivering comprehensive details on the dynamics of biochemical reaction networks in living organisms. The time has come to reassemble these catalogued items and design new biological devices and systems with novel and useful functionality in a rational and systematic manner. This is the premise of synthetic biology, a constructive systems biology discipline likely to become the life science revolution of the 21st century. (shrink)

Synthetic biology, as an engineering approach to biological systems, has the potential to disruptively innovate the development of vaccines, therapeutics, and diagnostics. Data accessibility and differences in data-usage capabilities are important factors in shaping this innovation landscape. In this paper, the data that underpin synthetic biology responses to the COVID-19 pandemic are analyzed as positional information goods—goods whose value depends on exclusivity. The positionality of biological data impacts the ability to guide innovations toward societally (...) preferred goals. From both an ethical and economic point of view, positionality can lead to suboptimal as well as beneficial situations. When aiming for responsible innovation (i.e. embedding societal deliberation in the innovation process), it is important to consider hurdles and facilitators in data access and use. Central governance and knowledge commons provide routes to mitigate the negative effects of data positionality. (shrink)

This article considers an apparent Achilles heel for Kant’s transcendental idealism, concerning his account of how synthetic a priori knowledge is possible. The problem is that while Kant’s distinctive attempt to explain synthetic a priori knowledge lies at the heart of his transcendental idealism, this explanation appears to face a dilemma: either the explanation generates a problematic regress, or the explanation it offers gives us no reason to favour transcendental idealism over transcendental realism. In the article, I consider (...) G. E. Moore’s version of the problem, which I argue has not yet received an adequate response. Instead, I offer a way out of this dilemma by focusing on the normativity rather than the metaphysics of the mind. (shrink)

Synthetic biology is a field of research that concentrates on the design, construction, and modification of new biomolecular parts and metabolic pathways using engineering techniques and computational models. By employing knowledge of operational pathways from engineering and mathematics such as circuits, oscillators, and digital logic gates, it uses these to understand, model, rewire, and reprogram biological networks and modules. Standard biological parts with known functions are catalogued in a number of registries (e.g. Massachusetts Institute of Technology Registry of Standard (...) Biological Parts). Biological parts can then be selected from the catalogue and assembled in a variety of combinations to construct a system or pathway in a microbe. Through the innovative re-engineering of biological circuits and the optimization of certain metabolic pathways, biological modules can be designed to reprogram organisms to produce products or behaviors. Synthetic biology is what is known as a “platform technology”. That is, it generates highly transferrable theoretical models, engineering principles, and know-how that can be applied to create potential products in a wide variety of industries. Proponents suggest that applications of synthetic biology may be able to provide scientific and engineered solutions to a multitude of worldwide problems from health to energy. Synthetic biology research has already been successful in constructing microbial products which promise to offer cheaper pharmaceuticals such as the antimalarial synthetic drug artemisinin, engineered microbes capable of cleaning up oil spills, and the engineering of biosensors that can detect the presence of high concentrations of arsenic in drinking water. One of the potential benefits of synthetic biology research is in its application to biofuel production. It is this application which is the focus of this entry. The term “biofuel” has referred generally to all liquid fuels that are sourced from plant or plant byproducts and are used for energy necessary for transportation vehicles (Thompson 2012). Biofuels that are produced using synthetic biological techniques re-engineer microbes into biofuel factories are a subset of these. (shrink)

Synthetic biology emerged around 2000 as a new biological discipline. It shares with systems biology the same modular vision of organisms, but is more concerned with applications than with a better understanding of the functioning of organisms. A herald of this new discipline is Craig Venter who aims to create an artificial microorganism with the minimal genome compatible with life and to implement into it different 'functional modules' to generate new micro-organisms adapted to specific tasks. Synthetic biology is (...) based on the possibilities raised by genetic engineering, but it aims to engineer organisms, and not simply to modify them, mimicking the practice of computer engineers. Three points will be discussed: In what regard does synthetic biology represent a new epistemology of the life sciences? What are the relations between synthetic biology and evolutionary biology? What is the raison d'être of synthetic biology as a discipline independent of nanotechnologies? (shrink)

Artificially generated content threatens to seriously disrupt the public sphere. Generative AI massively facilitates the production of convincing portrayals of fabricated events. We have already begun to witness the spread of synthetic misinformation, political propaganda, and non-consensual intimate deepfakes. Malicious uses of the new technologies can only be expected to proliferate over time. In the face of this threat, social media platforms must surely act. But how? While it is tempting to think they need new sui generis policies targeting (...) synthetic content, we argue that the challenge posed by generative AI should be met through the enforcement of general platform rules. We demonstrate that the threat posed to individuals and society by AI-generated content is no different in kind from that of ordinary harmful content—a threat which is already well recognised. Generative AI massively increases the problem but, ultimately, it requires the same approach. Therefore, platforms do best to double down on improving and enforcing their existing rules, regardless of whether the content they are dealing with was produced by humans or machines. (shrink)

The guiding thread of the paper is the diagnosis that the advanced division of cognitive labour (that is, intellectual specialization) engenders a set of perennial, political and epistemic challenges (Millgram 2015) that, simultaneously, also generate opportunities for philosophy. In this paper, I re-characterize the nature of synthetic philosophy as a means to advance and institutionalize philosophy. In §i, I treat Plato’s Republic as offering two models to represent philosophy’s relationship to the other sciences within the advanced division of labour. (...) I highlight that for Plato intellectual specialization is central not just to economic but also to political life; and yet, that the very dispersion of scientific expertise, and its esoteric nature, also generates non-trivial challenges to the recognition and political utilization of knowledge. From Plato we can infer that in imperfect circumstances, philosophy’s self-constitution is, in part, a response to these challenges in political epistemology. However, how philosophy is institutionalized differs through time. In §ii, I re-introduce my conceptualization of synthetic philosophy and restate it. I use recent work by Dorst (2023) to illustrate synthetic philosophy and to identify some of the processes that give rise to the need for it. In §§ii–iii, I contrast my account with the evolving ways that Philip Kitcher has conceptualized synthetic philosophy, in order to make more precise the version promoted here. I do so not just because Kitcher and I use the same term, ‘synthetic philosophy’, but because the temptations inherent in Kitcher’s approach should be resisted. (shrink)

This editorial introduces a special issue of Bioethics focusing on the ethical implications of synthetic biology for human health. It highlights the proactive approach of synthetic biology researchers in engaging with ethical considerations early on, hoping to avoid public backlash similar to that experienced with genetically modified foods. The editorial outlines the key ethical questions raised by synthetic biology, including its implications for the moral status of life, conceptualization of risks and benefits, and potential impacts on future (...) generations. The editorial summarizes the contributions of various authors who explore different ethical perspectives on synthetic biology. These perspectives range from examining issues of social justice and biodiversity to philosophical debates about the creation of life and the nature of health and disease. The editors aim to provide a multifaceted analysis of synthetic biology's potential benefits and concerns, ultimately hoping to inform future policy-making and public discourse about this emerging technology. (shrink)

The aim of synthetic biology is to rationally design devices, systems, and organisms with desired innovative and useful functions (Slusarczyk, Lin, and Weiss 2012). To achieve this aim, synthetic biology uses a concept similar to engineering sciences: well-characterized and standardized modular biological building blocks are reassembled in a systematic and rational manner to generate complex devices and systems with a predicted function. In the past, molecular biological research in combination with intense work in new research areas like systems (...) biology and functional genomics revealed a large inventory of multifaceted modular biological parts that are now in the toolboxes of synthetic biologists. Due to .. (shrink)

Not all research in machine consciousness aims to instantiate phenomenal states in artefacts. For example, one can use artefacts that do not themselves have phenomenal states, merely to simulate or model organisms that do. Nevertheless, one might refer to all of these pursuits -- instantiating, simulating or modelling phenomenal states in an artefact -- as 'synthetic phenomenality'. But there is another way in which artificial agents (be they simulated or real) may play a crucial role in understanding or creating (...) consciousness: 'synthetic phenomenology'. Explanations involving specific experiential events require a means of specifying the contents of experience; not all of them can be specified linguistically. One alternative, at least for the case of visual experience, is to use depictions that either evoke or refer to the content of the experience. Practical considerations concerning the generation and integration of such depictions argue in favour of a synthetic approach: the generation of depictions through the use of an embodied, perceiving and acting agent, either virtual or real. Synthetic phenomenology, then, is the attempt to use the states, interactions and capacities of an artificial agent for the purpose of specifying the contents of conscious experience. This paper takes the first steps toward seeing how one might use a robot to specify the non- conceptual content of the visual experience of an (hypothetical) organism that the robot models. (shrink)

In this paper, we discuss the ethical concerns that may arise from the synthesis of human DNA. To date, only small stretches of DNA have been constructed, but the prospect of generating human genomes is becoming feasible. At the same time, the significance of genes for identity, health and reproduction is coming under increased scrutiny. We examine the implications of DNA synthesis and its impact on debates over the relationship with our DNA and the ownership of our genes, its potential (...) to disrupt common understandings of reproduction and privacy, and the way in which synthetic DNA challenges traditional associations between genes and identity. We explore the degree to which synthetic DNA may further undermine overgeneticised accounts of identity, health, reproduction, parenthood and privacy that are prevalent in the public domain and in some areas of policy-making. While avoiding making normative claims of our own, we conclude that there is a need for reflection on the ethical implications of these developing technologies before they are on us. (shrink)

The artificial creation of life arises both strong fascination by scientists and strong concerns, if not abhorrence, by critics of science. What appears to be the crowning achievement of synthetic biology is at the same time considered a major evil. That conflict, which perhaps epitomizes many of the cultural conflicts about science in Western societies, calls for a deeper analysis. Standard ethical analyses, which would try to relate such conflicts to a difference in fundamental values, are difficult to apply (...) here, because it is unclear what the underlying values of such emotions as fascination and abhorrence are. These emotions or affects, rather than just referring to what is morally right or wrong, seem to be rooted in our cultural heritage of desires and taboos of transgression. My analysis in this paper is primarily of historical nature. By investigating ideas about the creation of life from the earliest times to the present, I aim to clarify the cultural origins of those emotions. I argue that both the fascination and the abhorrence regarding the creation of life have a common religious basis. Moreover, unlike many commentators of 19th-century mad-scientist classics, from Mary Shelley to H.G. Wells, I argue that this basis has no ancient model in religious or mythological traditions but emerged only in the 19th century from an exchange between science and religion. As long as these emotions dominate public debates, ethical deliberations about synthetic biology are likely to be neglected. (shrink)

With the recent renewed interest in AI, the field has made substantial advancements, particularly in generative systems. Increased computational power and the availability of very large datasets has enabled systems such as ChatGPT to effectively replicate aspects of human social interactions, such as verbal communication, thus bringing about profound changes in society. In this paper, we explain that the arrival of generative AI systems marks a shift from ‘interacting through’ to ‘interacting with’ technologies and calls for a reconceptualization of socio-technical (...) systems as we currently understand them. We dub this new generation of socio-technical systems synthetic to signal the increased interactions between human and artificial agents, and, in the footsteps of philosophers of information, we cash out agency in terms of ‘poiêsis’. We close the paper with a discussion of the potential policy implications of synthetic socio-technical system. -/- . (shrink)

Given an issue and related propositions for or against it, a major challenge to make these propositions accessible to readers is to produce a synthesis that is readable, synthetic enough, and relevant for various types of needs and points of view. Based on the Generative Lexicon (GL) Qualia Structure, which is a kind of lexical and knowledge repository, that we have enhanced in different manners and associated with inferences and language patterns, we show, via a number of preliminary experiments, (...) how to construct a synthesis that outlines the typical elements found in propositions for or against a controversial issue. We propose a two-level approach: a synthesis of the propositions that have been mined, and navigation facilities that allow users to access arguments, structured in clusters, in order to get more details. This approach contributes to characterize why and how propositions support or attack an issue or some facets of that issue. (shrink)

The structures of protein and DNA were discovered primarily by means of synthesizing component-level information about bond types, lengths, and angles, rather than analyzing X-ray diffraction photographs of these molecules. In this paper, I consider the synthetic and analytic approaches to exemplify alternative heuristics for approaching mid-twentieth-century macromolecular structure determination. I argue that the former was, all else being equal, likeliest to generate the correct structure in the shortest period of time. I begin by characterizing problem solving in these (...) cases as proceeding via the elimination of candidate structures through the successive application of component-level information and interpretations of X-ray diffraction photographs, each of which serves as a kind of constraint on structure. Then, I argue that although each kind of constraint enables the elimination of a considerable proportion of candidate structures, component-level constraints are significantly more likely to do so correctly. Thus, considering them before X-ray diffraction photographs is a better heuristic than one that reverses this order. Because the synthetic approach that resulted in the determination of the protein and DNA structures exemplifies such a heuristic, its use can help account for these discoveries. (shrink)

What are the ethics of using voices generated by artificial intelligence or “deepfake” technology in documentary film? This case study explores the controversy surrounding the use of AI to reconstruct Anthony Bourdain’s voice in the biographical film, Roadrunner.

Within French epistemology the question is central whether the present can be a reference point for the history of science or whether scientific practices should be understood within their own historical context. Both positions are linked with problems: either it results in a ‘whig history’ written from the perspective of the victors or it leads to the accusation of relativism and to resistance from the scientists themselves. Isabelle Stengers claims that this resistance by scientists must be considered as an essential (...) element in the historiography of the sciences. She is part of a more recent generation of French philosophers of science, who build on the work of the earlier generation but with significant differences. Stengers interprets the scientist’s work as ‘in the service of history’: everyone must be forced to recognize their work not as the product of personal construction but as a necessary discovery in the history of science. The work of the historian of science is in conflict with the aims of the scientists themselves, who want to be seen as the norm of the present by which one should read the history of science. This service of history is not some external ideological factor, but an internal part of the scientific practice itself. The construction of the difference between the discovery of a pre-given fact and the construction of a fiction is for Stengers the core of the scientific practices. This use of history will be illustrated by the case of synthetic biology, as described by Bernadette Bensaude-Vincent. Synthetic biologists are invoking specific past or future scenario’s, such as that of synthetic chemistry or computer engineering, to legitimatize their current research projects and ambitions. From this perspective, the problematic tension between the past and the present is so hard to cope with because it is not merely a struggle among historians and philosophers of science, but also among the scientists themselves. (shrink)

What happens when there is not enough data to train machine learning algorithms? In recent years, so-called ‘synthetic data’ have been increasingly used to add to or supplement the training regimes of various machine learning algorithms. Seeking to read the notion of supplementarity differently through an engagement with the work of Jacques Derrida, I propose that the nascent emergence of synthetic data embodies what I call the logic of the synthetic supplement in algorithmic societies. (...) I argue, on the one hand, that the synthetic supplement promises and claims to resolve the ethico-political tensions, frictions, and intractabilities of machine learning. On the other hand, it always falls short of these promises because it necessarily intervenes in that which it claims to merely augment. Ultimately, this means that the gaps and frictions of machine learning cannot be completely filled, supplemented, or resolved. (shrink)