Designing Women: Essentializing Femininity in AI Linguistics

Since the eighties, feminists have considered technology a force capable of subverting sexism because of technology’s ability to produce unbiased logic. Most famously, Donna Haraway’s “A Cyborg Manifesto” posits that the cyborg has the inherent capability to transcend gender because of its removal from social construct and lack of loyalty to the natural world. But while humanoids and artificial intelligence have been imagined as inherently subversive to gender, current artificial intelligence perpetuates gender divides in labor and language as their programmers imbue them with traits considered “feminine.” A majority of 21st century AI and humanoids are programmed to fit female stereotypes as they fulfill emotional labor and perform pink-collar tasks, whether through roles as therapists, query-fillers, or companions. This paper examines four specific chat-based AI --ELIZA, XiaoIce, Sophia, and Erica-- and examines how their feminine linguistic patterns are used to maintain the illusion of emotional understanding in regards to the tasks that they perform. Overall, chat-based AI fails to subvert gender roles, as feminine AI are relegated to the realm of emotional intelligence and labor

Coordination and Concurrency in Multi-Engine Prolog

Abstract. We discuss the impact of the separation of logic engines (independent logic processing units) and multi-threading on the design of coordination mechanisms for a Prolog based agent infrastructure. We advocate a combination of coroutining constructs with focus on expressiveness and a simplified, multi-threading API that ensures optimal use available parallelism. In this context, native multi-threading is made available to the application programmer as a set of high-level primitives with a declarative flavor while cooperative constructs provide efficient and predictable coordination mechanisms. As illustrations of our techniques, a parallel fold operation as well as cooperative implementations of Linda blackboards and publish/subscribe are described

Organizational Darwinism and research methodology

I argue that research methodologies in organizational studies provide an example of cultural evolution but that the resulting dominant logic impedes understanding by militating against realistic inductive research. I examine major 'schools' in organizational Darwinism / cultural evolution and identify overlap between those who use evolutionary dynamics as a relativist lens, the more classically positivist thinking derived from Evolutionary Economics and Darwin's original (1871) conceptual or constructive cultural evolution I then take Darwin's inductive assembly of facts and test existing research that has used an evolutionary perspective against the various strands of his "one long argument

Customer Strategy In Services Industries

Services industries are diverse, and range from the full service-only dimension through to services that support a product. In almost all cases the service involves capturing, or engaging with, the customer. A Service Value Networks (SVNs) approach offers a new way to engage with the customer. This approach moves the existing business models into the near-real-time customer tracking environment. This paper discusses complex doorways (elucidated by a SVNs approach) through which competitive new business approaches may be better understood, and developed, in line with customer drift, and/or customer changes in sentiment. The customer decision-making process to engage in a transaction process with the business, and the specific business-customer encounter pathways that ensue, contribute to the final customer engagement decision. The „bricks‟ (off-line physical) business and to „clicks‟ (on-line virtual) business both fit within the SVNs approach. This approach may be applied to tertiary institutions and student monitoring

Darwinian Evolutionary Ideas in Business Economics and Organization Studies

This thesis is a study of the use of Darwinian evolutionary ideas in business economics and organization studies. Mindful of the explosion of evolutionary rhetoric in the socio-economic domain over the last three decades and informed by the modern generalized Darwinian perspective, the research has been focused on the evaluation of the precise nature and extent of use of Darwinian ideas in three of the most influential evolutionary accounts in these disciplines. Notably, Nelson and Winter’s Evolutionary Theory of Economic Change (1982), Hannan and Freeman’s Organizational Ecology (1989), and Howard Aldrich’s Organizations Evolving (1999). It is a work of comparative theory. Also since 1980, theoretical and conceptual advances in evolutionary theory confirmed the generic nature of Darwinian theory and provided generalized terms for its articulation. Whilst some major criticisms of Darwinism are easily dismissed, significantly scholars have shown that Lamarckian acquired character inheritance must be accommodated within the meta-theoretical framework of Darwinism. This study shows that whilst the damaging rhetoric of ‘Social Darwinism’ continues to discourage widespread active engagement with Darwinian theory, the pervasive implicit or ‘covert’ adoption of Darwinian ideas by social scientists nevertheless clearly endorses its general nature, confirms a Darwinian social ontology and underlines the inevitability of Darwinism in the socio-cultural domain. Following a detailed exposition of general Darwinism, this study presents a forensic comparative evaluation of the evolutionary theories under study, highlighting theoretical gaps and inconsistencies, and demonstrating their resolution within the Darwinian framework. Through the systematic application and dissection of these disparate theories, one of which is labelled ‘Lamarckian’, the analysis shows the deep extent to which they all are Darwinian. And furthermore, underlining the promise of the Darwinian system for yielding further results, the study clearly illustrates the importance of the explicit adoption of modern Darwinian concepts for helping scholars to understand the complex evolutionary processes they seek to explai

Expressive Copying Behavior for Social Agents: A Perceptual Analysis

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snoDB: An interconnected online database of human snoRNA

L’ARN est bien plus qu’une molécule transitoire entre l’ADN et les protéines. Au-delà des ARN encodant des protéines, on trouve un vaste éventail d’ARN non-codants qui demeurent encore sous-étudiés. Ces ARN ont été découverts dans les années 1960, mais ce n’est qu’au tournant du siècle que leur incroyable prévalence en cellule a pu être confirmée avec la venue de méthodes de séquençage d’ARN à haut débit. Les expériences à haut débit ont également augmenté de façon exponentielle la quantité de données sur l’ARN créant un besoin pour des outils bio-informatiques permettant leur analyse et leur stockage. Un des premiers, et des plus abondant, type d’ARN non-codant à être découvert sont les petit ARN nucléolaires (snoRNA). Canoniquement caractérisés comme guides de modifications spécifiques dans l’ARN ribosomal, ces petits ARN hautement conservés ont maintenant une liste variée de fonctions non-canoniques, notamment au niveau de l’expression génique, ainsi qu’un nombre croissant d’associations à une panoplie de maladies et de cancer. Considérant la littérature grandissante sur les snoRNA chez l’humain, ainsi que leur connexion maintenant apparente à plusieurs domaines de recherche variés, un regroupement accessible de ce large spectre d’information est maintenant indispensable. Malheureusement, les bases de données en ligne de snoRNA humain, snoRNABase, snOPY, et snoRNA Atlas, ne sont plus à jour ou sont trop pointues au niveau de leurs données. De plus, elles figurent peu ou pas de données d’interactions non-canonique et/ou d’expression. Nous avons donc créé snoDB : une base de données interactive de snoRNA humain qui contient des données sur leurs fonctions non-canoniques, trouvées à travers la littérature, des données d’expression dans une panoplie de tissus, et bien plus. Contrairement à ces prédécesseurs, snoDB offre une visualisions sélectives de son plus large éventail de données, au sein d’une table interactive aux options de recherche abondantes. Les données d’expression peuvent également être visualisées dans la même page, sous forme de carte de chaleur, grâce à l’application sœur de snoDB : snoTHAW. snoDB se démarque aussi par sa connectivité à plus d’une douzaine de ressources incluant le consortium RNAcentral, la plus grande base de données d’ARN non-codant, dont snoDB fais maintenant parti. Les données de ces ressources ont été acquises puis jointe ensemble dans une base de données relationnel postgreSQL. De plus, elles sont toutes en lien dans la table de snoDB afin de facilement pouvoir corroborer l’information visible, ainsi qu’accéder aux fonctionnalités des autres sites. Enfin, snoDB a été construit pour être facile à mettre à jour afin d’assurer ces contributions à la recherche pour de nombreuses années.Abstract: RNA is more than just a transitory molecule between DNA and proteins. Beyond the scope of protein-coding RNAs lies a vast underexplored landscape of non-coding RNAs (ncRNA). These RNAs have been slowly uncovered since the 1960s but it took until the turn of the century, and the advent of high-throughput RNA-Sequencing methodologies, for us to finally see how dominated by ncRNAs the transcriptome really is. High-throughput experiments also exponentially expanded the amount of data on RNA and created a need for bioinformatics tools for their analysis and storage. One of the first, and most abundant, ncRNA types to be discovered was small nucleolar RNAs (snoRNAs). Canonically pegged as guides for the modification of pre-ribosomal RNAs, these highly conserved RNAs now boast a diverse list of crucial non-canonical roles, notably in gene expression, as well as being associated to a myriad of diseases and cancers. Considering the growing body of literature surrounding snoRNAs in humans, and their increasing connections to a broad range of fields of study, having an accessible and comprehensive assessment of these data has become essential. Unfortunately, existing online human snoRNA databases, snoRNABase, snOPY, and snoRNA Atlas, are either outdated or too narrow in scope, focusing almost exclusively on canonical snoRNA interactions and lacking expression data. As such, we have created snoDB: a modern, interactive database of human snoRNAs with curated data on non-canonical snoRNA interactions, expression data in a growing range of tissues and cell lines, and more. Unlike the old snoRNA databases, snoDB features extensive visualisation and filtering capabilities, allowing for its larger array of data to be selectively viewed in an interactive and customizable table. Expression data can be further visualised in interactive heatmaps thanks to snoDB’s sister tool: snoTHAW. snoDB also innovates by being much more interconnected with other resources. Data was gathered, and joined together in a relational postgreSQL database, from over a dozen resources, including the RNAcentral database consortium, the largest database of ncRNA sequences, of which snoDB is now a part of. In addition, all resources are linked to in-table, where data they provided appears, to help corroborate the data shown for transparency, as well as to grant access to interesting features housed on remote sites. Finally, snoDB is built to be easily maintainable, updatable and extensible to keep up with ongoing developments and insure that the information it contains will contribute to snoRNA research for years to come