Over the past two decades, researchers have made great advances in the area of computational methods for extracting meaning from text. This research has to a large extent been spurred by the development of latent semantic analysis (LSA), a method for extracting and representing the meaning of words using statistical computations applied to large corpora of text. Since the advent of LSA, researchers have developed and tested alternative statistical methods designed to detect and analyze meaning in text (...) corpora. This research exemplifies how statistical models of semantics play an important role in our understanding of cognition and contribute to the field of cognitive science. Importantly, these models afford large-scale representations of human knowledge and allow researchers to explore various questions regarding knowledge, discourse processing, text comprehension, and language. This topic includes the latest progress by the leading researchers in the endeavor to go beyond LSA. (shrink)

Understanding arithmetic word problems involves a complex interaction of text comprehension and mathematical processes. This article presents a computer simulation designed to capture the working memory demands required in “bottomup” comprehension of arithmetic word problems. The simulation's sentence‐level parser and text integration component reflect the importance of processing the problem from its original natural language presentation. Children's probability of solution was analyzed in exploratory regression analyses as a function of the simulation's sentence‐level and text integration (...) processes. Working memory variables measuring the combined effects of concepts to remember and text integration inferences account for a significant proportion of variance in children's solution probabilities across the first four grade levels (K‐3). Consistent with previous results from others, which highlighted the significance of small changes in problem wording, the simulation offers a process‐oriented perspective as to why natural language presentation constrains the comprehension of mathematical relationships. (shrink)

This project continues our interdisciplinary research into computational and cognitive aspects of narrative comprehension. Our ultimate goal is the development of a computational theory of how humans understand narrative texts. The theory will be informed by joint research from the viewpoints of linguistics, cognitive psychology, the study of language acquisition, literary theory, geography, philosophy, and artificial intelligence. The linguists, literary theorists, and geographers in our group are developing theories of narrative language and spatial understanding that are being tested by the (...) cognitive psychologists and language researchers in our group, and a computational model of a reader of narrative text is being developed by the AI researchers, based in part on these theories and results and in part on research on knowledge representation and reasoning. This proposal describes the knowledge-representation and natural-language-processing issues involved in the computational implementation of the theory; discusses a contrast between communicative and narrative uses of language and of the relation of the narrative text to the story world it describes; investigates linguistic, literary, and hermeneutic dimensions of our research; presents a computational investigation of subjective sentences and reference in narrative; studies children’s acquisition of the ability to take third-person perspective in their own storytelling; describes the psychological validation of various linguistic devices; and examines how readers develop an understanding of the geographical space of a story. This report is a longer version of a project description submitted to NSF. This document, produced in May 2007, is a L ATEX version of Technical Report 89-07 (Buffalo: SUNY Buffalo Department of Computer Science, August 1989), with slightly.. (shrink)

COVID-19 is a disease that affects the quality of life in all aspects. However, the government policy applied in 2020 impacted the lifestyle of the whole world. In this sense, the study of sentiments of people in different countries is a very important task to face future challenges related to lockdown caused by a virus. To contribute to this objective, we have proposed a natural language processing model with the aim to detect positive and negative feelings in open-text (...) answers obtained from a survey in pandemic times. We have proposed a distilBERT transformer model to carry out this task. We have used three approaches to perform a comparison, obtaining for our best model the following average metrics: Accuracy: 0.823, Precision: 0.826, Recall: 0.793 and F1 Score: 0.803. (shrink)

The size and variation in both meaning-making and populations that characterize much contemporary text data demand research processes that support both discovery, interpretation and measurement. We assess one dominant strategy within the social sciences that takes a computer-led approach to text analysis. The approach is coined computational grounded theory. This strategy, we argue, relies on a set of unwarranted assumptions, namely, that unsupervised models return natural clusters of meaning, that the researcher can understand text with limited (...) immersion and that indirect validation is sufficient for ensuring unbiased and precise measurement. In response to this criticism, we develop a framework that is computer assisted. We argue that our reformulation of computational grounded theory better aligns with the principles within grounded theory, anthropological theory generation and ethnography. (shrink)

As an answer to the humanistic, socially oriented critique of the information-processing paradigms used as a conceptual frame for library information science, this article formulates a broader and less objective concept of communication than that of the information-processing paradigm. Knowledge can be seen as the mental phenomenon that documents (combining signs into text, depending on the state of knowledge of the recipient) can cause through interpretation. The examination of these “correct circumstances” is an important part of (...) information science. This article represents the following developments in the concept of information: Information is understood as potential until somebody interprets it. The objective carriers of potential knowledge are signs. Signs need interpretation to release knowledge in the form of interpretants. Interpretation is based on the total semantic network, horizons, worldviews, and experience of the person, including the emotional and social aspects. The realm of meaning is rooted in social-historical as well as embodied evolutionary processes that go beyond computational algorithmically logic. The semantic network derives a decisive aspect of signification from a person’s embodied cultural worldview, which, in turn, derives from, develops, and has its roots in undefined tacit knowledge. To theoretically encompass both the computational and the semantic aspects of document classification and retrieval, we need to combine the cybernetic functionalistic approach with the semiotic pragmatic understanding of meaning as social and embodied. For such a marriage, it is necessary to go into the constructivistic secondorder cybernetics and autopoiesis theory of von Foerster, Maturana, and Luhmann, on the one hand, and the pragmatic triadic semiotics of Peirce in the form of the embodied Biosemiotics, on the other hand. This combination is what I call Cybersemiotics. (shrink)

The proposed multilevel framework of discourse comprehension includes the surface code, the textbase, the situation model, the genre and rhetorical structure, and the pragmatic communication level. We describe these five levels when comprehension succeeds and also when there are communication misalignments and comprehension breakdowns. A computer tool has been developed, called Coh-Metrix, that scales discourse (oral or print) on dozens of measures associated with the first four discourse levels. The measurement of these levels with an automated tool helps researchers (...) track and better understand multilevel discourse comprehension. Two sets of analyses illustrate the utility of Coh-Metrix in discourse theory and educational practice. First, Coh-Metrix was used to measure the cohesion of the text base and situation model, as well as potential extraneous variables, in a sample of published studies that manipulated text cohesion. This analysis helped us better understand what was precisely manipulated in these studies and the implications for discourse comprehension mechanisms. Second, Coh-Metrix analyses are reported for samples of narrative and science texts in order to advance the argument that traditional text difficulty measures are limited because they fail to accommodate most of the levels of the multilevel discourse comprehension framework. (shrink)

Cognitive science was established as an interdisciplinary domain of research in the 1970s. Since then, the domain has flourished, despite disputes concerning its interdisciplinarity. Multiple methods exist for the assessment of interdisciplinary research. The present study proposes a methodology for quantifying interdisciplinary aspects of research in cognitive science. We propose models for text similarity analysis that provide helpful information about the relationship between publications and their specific research fields, showing potential as a robust measure of interdisciplinarity. We (...) designed and developed models utilizing the Doc2Vec method for analyzing cognitive science and related fields. Our findings reveal that cognitive science collaborates closely with most constituent disciplines. For instance, we found a balanced engagement between several constituent fields—including psychology, philosophy, linguistics, and computer science—that contribute significantly to cognitive science. On the other hand, anthropology and neuroscience have made limited contributions. In our analysis, we find that the scholarly domain of cognitive science has been exhibiting overt interdisciplinary for the past several decades. (shrink)

Words are not just labels for conceptual categories. Words construct conceptual categories, frame situations and influence behavior. Where do they get their meaning? This book describes how words acquire their meaning. The author argues that mechanisms based on associations, pattern detection, and feature matching processes explain how words acquire their meaning from experience and from language alike. Such mechanisms are summarized by the distributional hypothesis, a computational theory of meaning originally applied to word occurrences only, and hereby extended to extra-linguistic (...) contexts. By arguing in favor of the cognitive foundations of the distributional hypothesis, which suggests that words that appear in similar contexts have similar meaning, this book offers a theoretical account for word meaning construction and extension in first and second language that bridges empirical findings from cognitive and computer sciences. Plain language and illustrations accompany the text, making this book accessible to a multidisciplinary academic audience. (shrink)

What is the relation between material hermeneutics, bodies, perception and materials? In this article, I shall argue cultural learning processes tie them together. Three aspects of learning can be identified in cultural learning processes. First, all learning is tied to cultural practices. Second, all learning in cultural practice entangle humans’ ability to recognize a material world conceptually, and finally the boundaries of objects, the object we perceive, are set by shifting material-conceptual entanglements. All these aspects are important for material hermeneutics (...) in a technoculture. Postphenomenology has expanded the connection between hermeneutics and phenomenology by focusing on studies of how perception, bodies, materials, the sensual realm and hermeneutics are entwined when we perceive the world through technologies. Following Don Ihde, hermeneutics expands beyond interpretation of texts in the humanities. We can interpret materials as for instance animal bones to make new sense of the Bible. New technologies have expanded material hermeneutics, when we can ‘look’ into bodies and ‘perceive’ below surfaces. Interpretation via such tools in a technoculture, both limit and extend our hermeneutic horizons in the humanities as well as in the natural sciences. Furthermore, from the perspective of cultural learning processes, material hermeneutics in the human and natural sciences depend on more than mediating instruments. Material hermeneutics also involve the material cultural environments of scientific apparatuses and the scientists’ processes of learning in cultural practice. This changes the focus from relations in postphenomenology to processes of relations. (shrink)

Digital spaces are saturated with metaphor: we have pages, sites, mice, and windows. Yet, in the world of digital textuality, these metaphors no longer function as we might expect. Martin Paul Eve calls attention to the digital-textual metaphors that condition our experience of digital space, and traces their history as they interact with physical cultures. Eve posits that digital-textual metaphors move through three life phases. Initially they are descriptive. Then they encounter a moment of fracture or rupture. Finally, they go (...) on to have a prescriptive life of their own that conditions future possibilities for our text environments - even when the metaphors have become untethered from their original intent. Why is "whitespace" white? Was the digital page always a foregone conclusion? Over a series of theses, Eve addresses these and other questions in order to understand the moments when digital-textual metaphors break and to show us how it is that our textual softwares become locked into paradigms that no longer make sense. Contributing to book history, literary studies, new media studies, and material textual studies, Theses on the Metaphors of Digital-Textual History provides generative insights into the metaphors that define our digital worlds. (shrink)

Cognitive Science is a single-source undergraduate text that broadly surveys the theories and empirical results of cognitive science within a consistent computational perspective. In addition to covering the individual contributions of psychology, philosophy, linguistics, and artificial intelligence to cognitive science, the book has been revised to introduce the connectionist approach as well as the classical symbolic approach and adds a new chapter on cognitively related advances in neuroscience. Cognitive science is a rapidly evolving field that (...) is characterized by considerable contention among different views and approaches. Cognitive Science presents these in a relatively neutral manner. It covers many new orientations theories and findings, embedding them in an integrated computational perspective and establishing a sense of continuity and contrast with more traditional work in cognitive science. The text assumes no prerequisite knowledge, introducing all topics in a uniform, accessible style. Many topics, such as natural language processing and vision, however, are developed in considerable depth, which allows the book to be used with more advanced undergraduates or even in beginning graduate settings. A Bradford Book. (shrink)

This paper discusses a version of the hermeneutic philosophy of science. Special focus is placed on the ways of reading theoretical objects in scientific inquiry. In implementing readable technologies, this reading succeeds in contextually visualizing the theoretical objects by means of various sorts of signs. A configuration of readable technology accomplishes a further step. The configuration textualizes the contextually produced signs. Textualizing the reading of theoretical objects interlaces the meaningful articulation and objectification of scientific domains. The horizon of possibilities (...) for textualizing is constantly shifting in the process of normal-scientific inquiry, and the shifting horizon plays the role of a hermeneutic fore-structuring of the outcomes of textualizing. The paper explores the importance of “material hermeneutics” for the contextual reading of theoretical objects. The conclusion is drawn that the hermeneutic study of the entanglement of technological artifacts with the outcomes from reading-as-textualizing requires the introduction of ontic-ontological difference. (shrink)

Interpretation is the process whereby a hearer reasons to an interpretation of a speaker's discourse. The hearer normally adopts a credulous attitude to the discourse, at least for the purposes of interpreting it. That is to say the hearer tries to accommodate the truth of all the speaker's utterances in deriving an intended model. We present a nonmonotonic logical model of this process which defines unique minimal preferred models and efficiently simulates a kind of closed‐world reasoning of particular interest for (...) human cognition. Byrne's “suppression” data (Byrne, 1989) are used to illustrate how variants on this logic can capture and motivate subtly different interpretative stances which different subjects adopt, thus indicating where more fine‐grained empirical data are required to understand what subjects are doing in this task. We then show that this logical competence model can be implemented in spreading activation network models. A one pass process interprets the textual input by constructing a network which then computes minimal preferred models for (3‐valued) valuations of the set of propositions of the text. The neural implementation distinguishes easy forward reasoning from more complex backward reasoning in a way that may be useful in explaining directionality in human reasoning. (shrink)

Part I: The Life of Cognitive Science:. William Bechtel, Adele Abrahamsen, and George Graham. Part II: Areas of Study in Cognitive Science:. 1. Analogy: Dedre Gentner. 2. Animal Cognition: Herbert L. Roitblat. 3. Attention: A.H.C. Van Der Heijden. 4. Brain Mapping: Jennifer Mundale. 5. Cognitive Anthropology: Charles W. Nuckolls. 6. Cognitive and Linguistic Development: Adele Abrahamsen. 7. Conceptual Change: Nancy J. Nersessian. 8. Conceptual Organization: Douglas Medin and Sandra R. Waxman. 9. Consciousness: Owen Flanagan. 10. Decision Making: J. (...) Frank Yates and Paul A. Estin. 11. Emotions: Paul E. Griffiths. 12. Imagery and Spatial Representation: Rita E. Anderson. 13. Language Evolution and Neuromechanisms: Terrence W. Deacon. 14. Language Processing: Kathryn Bock and Susan M. Garnsey. 15. Linguistics Theory: D. Terence Langendoen. 16. Machine Learning: Paul Thagard. 17. Memory: Henry L. Roediger III and Lyn M. Goff. 18. Perception: Cees Van Leeuwen. 19. Perception: Color: Austen Clark. 20. Problem Solving: Kevin Dunbar. 21. Reasoning: Lance J. Rips. 22. Social Cognition: Alan J. Lambert and Alison L. Chasteen. 23. Unconscious Intelligence: Rhianon Allen and Arthur S. Reber. 24. Understanding Texts: Art Graesser and Pam Tipping. 25. Word Meaning: Barbara C. Malt. Part III: Methodologies of Cognitive Science:. 26. Artificial Intelligence: Ron Sun. 27. Behavioral Experimentation: Alexander Pollatsek and Keith Rayner. 28. Cognitive Ethology: Marc Bekoff. 29. Deficits and Pathologies: Christopher D. Frith. 30. Ethnomethodology: Barry Saferstein. 31. Functional Analysis: Brian Macwhinney. 32. Neuroimaging: Randy L. Buckner and Steven E. Petersen. 33. Protocal Analysis: K. Anders Ericsson. 34. Single Neuron Electrophysiology: B. E. Stein, M.T. Wallace, and T.R. Stanford. 35. Structural Analysis: Robert Frank. Part IV: Stances in Cognitive Science:. 36. Case-based Reasoning: David B. Leake. 37. Cognitive Linguistics: Michael Tomasello. 38. Connectionism, Artificial Life, and Dynamical Systems: Jeffrey L. Elman. 39. Embodied, Situated, and Distributed Cognition: Andy Clark. 40. Mediated Action: James V. Wertsch. 41. Neurobiological Modeling: P. Read Montague and Peter Dayan. 42. Production Systems: Christian D. Schunn and David Klahr. Part V: Controversies in Cognitive Science:. 43. The Binding Problem: Valerie Gray Hardcastle. 44. Heuristics and Satisficing: Robert C. Richardson. 45. Innate Knowledge: Barbara Landau. 46. Innateness and Emergentism: Elizabeth Bates, Jeffrey L. Elman, Mark H. Johnson, Annette Karmiloff-Smith, Domenico Parisi, and Kim Plunkett. 47. Intentionality: Gilbert Harman. 48. Levels of Explanation and Cognition Architectures: Robert N. McCauley. 49. Modularity: Irene Appelbaum. 50. Representation and Computation: Robert S. Stufflebeam. 51. Representations: Dorrit Billman. 52. Rules: Terence Horgan and John Tienson. 53. Stage Theories Refuted: Donald G. Mackay. Part VI: Cognitive Science in the Real World:. 54. Education: John T. Bruer. 55. Ethics: Mark L. Johnson. 56. Everyday Life Environments: Alex Kirlik. 57. Institutions and Economics: Douglass C. North. 58. Legal Reasoning: Edwina L. Rissland. 59. Mental Retardation: Norman W. Bray, Kevin D. Reilly, Lisa F. Huffman, Lisa A. Grupe, Mark F. Villa, Kathryn L. Fletcher, and Vivek Anumolu. 60. Science: William F. Brewer and Punyashloke Mishra. Selective Biographies of Major Contributors to Cognitive Science: William Bechtel and Tadeusz Zawidzki. (shrink)

Interpretation is the process whereby a hearer reasons to an interpretation of a speaker's discourse. The hearer normally adopts a credulous attitude to the discourse, at least for the purposes of interpreting it. That is to say the hearer tries to accommodate the truth of all the speaker's utterances in deriving an intended model. We present a nonmonotonic logical model of this process which defines unique minimal preferred models and efficiently simulates a kind of closed-world reasoning of particular interest for (...) human cognition. Byrne's “suppression” data (Byrne, 1989) are used to illustrate how variants on this logic can capture and motivate subtly different interpretative stances which different subjects adopt, thus indicating where more fine-grained empirical data are required to understand what subjects are doing in this task. We then show that this logical competence model can be implemented in spreading activation network models. A one pass process interprets the textual input by constructing a network which then computes minimal preferred models for (3-valued) valuations of the set of propositions of the text. The neural implementation distinguishes easy forward reasoning from more complex backward reasoning in a way that may be useful in explaining directionality in human reasoning. (shrink)

BackgroundSelf-report multiple choice questionnaires have been widely utilized to quantitatively measure one’s personality and psychological constructs. Despite several strengths, self-report multiple choice questionnaires have considerable limitations in nature. With the rise of machine learning and Natural language processing, researchers in the field of psychology are widely adopting NLP to assess psychological construct to predict human behaviors. However, there is a lack of connections between the work being performed in computer science and that of psychology due to small (...) data sets and unvalidated modeling practices.AimsThe current article introduces the study method and procedure of phase II which includes the interview questions for the five-factor model of personality developed in phase I. This study aims to develop the interview and open-ended questions for the FFM-based personality assessments, specifically designed with experts in the field of clinical and personality psychology, and to collect the personality-related text data using the interview questions and self-report measures on personality and psychological distress. The purpose of the study includes examining the relationship between natural language data obtained from the interview questions, measuring the FFM personality constructs, and psychological distress to demonstrate the validity of the natural language-based personality prediction.MethodsPhase I study was conducted to fifty-nine native Korean adults to acquire the personality-related text data from the interview and open-ended questions based on the FFM of personality. The interview questions were revised and finalized with the feedback from the external expert committee, consisting of personality and clinical psychologists. Based on the established interview questions, a total of 300 Korean adults will be recruited using a convenience sampling method via online survey. The text data collected from interviews will be analyzed using the natural language processing. The results of the online survey including demographic data, depression, anxiety, and personality inventories will be analyzed together in the model to predict individuals’ FFM of personality and the level of psychological distress. (shrink)

Algorithmic biases, or algorithmic unfairness, have been a topic of public and scientific scrutiny for the past years, as increasing evidence suggests the pervasive assimilation of human cognitive biases and stereotypes in such systems. This research is specifically concerned with analyzing the presence of discursive biases in the text generated by GPT-3, an NLPM which has been praised in recent years for resembling human language so closely that it is becoming difficult to differentiate between the human and the algorithm. (...) The pertinence of this research object is substantiated by the identification of race, gender and religious biases in the model’s completions in recent research, suggesting that the model is indeed heavily influenced by human cognitive biases. To this end, this research inquires: How does the Natural Language Processing Model GPT-3 replicate existing social biases?. This question is addressed through the scrutiny of GPT-3’s completions using Critical Discourse Analysis (CDA), a method which has been deemed as amply valuable for this research as it is aimed at uncovering power asymmetries in language. As such, the analysis is specifically centered around the analysis of gender and race biases in the model’s generated text. Research findings suggest that GPT-3’s language generation model significantly exacerbates existing social biases while replicating dangerous ideologies akin to white supremacy and hegemonic masculinity as factual knowledge. (shrink)

We present interpretation‐based processing—a theory of sentence processing that builds a syntactic and a semantic representation for a sentence and assigns an interpretation to the sentence as soon as possible. That interpretation can further participate in comprehension and in lexical processing and is vital for relating the sentence to the prior discourse. Our theory offers a unified account of the processing of literal sentences, metaphoric sentences, and sentences containing semantic illusions. It also explains how text (...) can prime lexical access. We show that word literality is a matter of degree and that the speed and quality of comprehension depend both on how similar words are to their antecedents in the preceding text and how salient the sentence is with respect to the preceding text. Interpretation‐based processing also reconciles superficially contradictory findings about the difference in processing times for metaphors and literals. The theory has been implemented in ACT‐R [Anderson and Lebiere, The Atomic Components of Thought, Lawrence Erlbaum Associates Publishers, Mahwah, NJ, 1998]. (shrink)

Corpus-based word frequencies are one of the most important predictors in language processing tasks. Frequencies based on conversational corpora are shown to better capture the variance in lexical decision tasks compared to traditional corpora. In this study, we show that frequencies computed from social media are currently the best frequency-based estimators of lexical decision reaction times. The results are robust and are still substantial when we control for corpus size.

The rapid development of computer vision technologies and applications has brought forth a range of social and ethical challenges. Due to the unique characteristics of visual technology in terms of data modalities and application scenarios, computer vision poses specific ethical issues. However, the majority of existing literature either addresses artificial intelligence as a whole or pays particular attention to natural language processing, leaving a gap in specialized research on ethical issues and systematic solutions in the field of (...) computer vision. This paper utilizes bibliometrics and text-mining techniques to quantitatively analyze papers from prominent academic conferences in computer vision over the past decade. It first reveals the developing trends and specific distribution of attention regarding trustworthy aspects in the computer vision field, as well as the inherent connections between ethical dimensions and different stages of visual model development. A life-cycle framework regarding trustworthy computer vision is then presented by making the relevant trustworthy issues, the operation pipeline of AI models, and viable technical solutions interconnected, providing researchers and policymakers with references and guidance for achieving trustworthy CV. Finally, it discusses particular motivations for conducting trustworthy practices and underscores the consistency and ambivalence among various trustworthy principles and technical attributes. (shrink)

BackgroundDescriptive studies examining publication rates and citation counts demonstrate a geographic skew toward high-income countries (HIC), and research from low- or middle-income countries (LMICs) is generally underrepresented. This has been suggested to be due in part to reviewers’ and editors’ preference toward HIC sources; however, in the absence of controlled studies, it is impossible to assert whether there is bias or whether variations in the quality or relevance of the articles being reviewed explains the geographic divide. This study synthesizes the (...) evidence from randomized and controlled studies that explore geographic bias in the peer review process.MethodsA systematic review was conducted to identify research studies that explicitly explore the role of geographic bias in the assessment of the quality of research articles. Only randomized and controlled studies were included in the review. Five databases were searched to locate relevant articles. A narrative synthesis of included articles was performed to identify common findings.ResultsThe systematic literature search yielded 3501 titles from which 12 full texts were reviewed, and a further eight were identified through searching reference lists of the full texts. Of these articles, only three were randomized and controlled studies that examined variants of geographic bias. One study found that abstracts attributed to HIC sources elicited a higher review score regarding relevance of the research and likelihood to recommend the research to a colleague, than did abstracts attributed to LIC sources. Another study found that the predicted odds of acceptance for a submission to a computer science conference were statistically significantly higher for submissions from a “Top University.” Two of the studies showed the presence of geographic bias between articles from “high” or “low” prestige institutions.ConclusionsTwo of the three included studies identified that geographic bias in some form was impacting on peer review; however, further robust, experimental evidence is needed to adequately inform practice surrounding this topic. Reviewers and researchers should nonetheless be aware of whether author and institutional characteristics are interfering in their judgement of research. (shrink)

Speech recognition is an interdisciplinary subfield of natural language processing (NLP) that facilitates the recognition and translation of spoken language into text by machine. Speech recognition plays an important role in digital transformation. It is widely used in different areas such as education, industry, and healthcare and has recently been used in many Internet of Things and Machine Learning applications. The process of speech recognition is one of the most difficult processes in computer science. Despite numerous (...) searches in this domain, an optimal method for speech recognition has not yet been found. This is due to the fact that there are many attributes that characterize natural languages and every language has its particular highlights. The aim of this research is to provide a comprehensive understanding of the various techniques within the domain of Speech Recognition through a systematic literature review of the existing work. We will introduce the most significant and relevant techniques that may provide some directions in the future research. (shrink)

This book explores the universe and its subsystems from the three lenses of evolutionary (diversifying), developmental (converging), and complex (adaptive) processes at all scales. It draws from prolific experts within the academic disciplines of complexity science, physical science, information and computer science, theoretical and evo-devo biology, cosmology, astrobiology, evolutionary theory, developmental theory, and philosophy. The chapters come from a Satellite Meeting, "Evolution, Development and Complexity" (EDC) hosted at the Conference on Complex Systems, in Cancun, 2017. The (...) contributions will be peer-reviewed and contributors from outside the conference will be invited to submit chapters to ensure full coverage of the topics. This book explores many issues within the field of EDC such as the interaction of evolutionary stochasticity and developmental determinism in biological systems and what they might teach us about these twin processes in other complex systems. This text will appeal to students and researchers within the complex systems and EDC fields.. (shrink)

Academic misconduct in all its various forms is a challenge for degree-granting institutions. Whilst text-based plagiarism can be detected using tools such as Turnitin™, Plagscan™ and Urkund™, contract cheating and collusion can be more difficult to detect, and even harder to prove, often falling to no more than a ‘balance of probabilities’ rather than fact. To further complicate the matter, some students will make deliberate attempts to obfuscate cheating behaviours by submitting work in Portable Document Format, in image form, (...) or by inserting hidden glyphs or using alternative character sets which text matching software does not always accurately detect.Educators do not tend to think of academic misconduct in terms of criminality per se, but the tools and techniques used by digital forensics experts in law enforcement can teach us much about how to investigate allegations of academic misconduct. The National Institute of Standards and Technology’s Glossary describes digital forensics as ‘the application of computer science and investigative procedures involving the examination of digital evidence - following proper search authority, chain of custody, validation with mathematics, use of validated tools, repeatability, reporting, and possibly expert testimony.’. These techniques are used in criminal investigations as a means to identify the perpetrator of, or accomplices to, a crime and their associated actions. They are sometimes used in cases relating to intellectual property to establish the legitimate ownership of a variety of objects, both written and graphical, as well as in fraud and forgery. Whilst there have been some research articles and case studies that demonstrate the use of digital forensics techniques to detect academic misconduct as proof of concept, there is no evidence of their actual deployment in an academic setting.This paper will examine some of the tools and techniques that are used in law enforcement and the digital forensics field with a view to determining whether they could be repurposed for use in an academic setting. These include methods widely used to determine if a file has been tampered with that could be repurposed to identify if an image is plagiarised; file extraction techniques for examining meta data, used in criminal cases to determine authorship of documents, and tools such as FTK™ and Autopsy™ which are used to forensically examine single files as well as entire hard drives. The paper will also present a prototype of a bespoke software tool that attempts to repurpose some of these techniques into an automated process for detecting plagiarism and / or contract cheating in Word documents.Finally, this article will discuss whether these tools have a place in an academic setting and whether their use in determining if a student’s work is truly their own is ethical. (shrink)

Every project in digital and computational history of science starts with the collection of data. Depending on the research project, the subject of study, and other factors, data can comprise a variety of different types, including full texts, images, audio, video, and bibliographic metadata. Publications and project reports generally describe their results and the methods and algorithms employed, but few discuss the challenges of the initial data collection process or how it fits into the overall research data life cycle. (...) This essay discusses a concrete research data life cycle and takes a look at the difficulties it involves. It also explores the strategies and challenges of data collection and the question of the comparability of datasets. (shrink)

The study, design and development of a low-cost digital braille printer is boarded with a transdisciplinary approach. The main challenge was focused on reducing significantly the high cost of this type of printers and their printing services. This context is aggravated with the low commercialization of these products in the country, a factor that makes the access of these tools -that are essential to much of the low and middle sectors of the Argentine social structure- even more difficult. An interdisciplinary (...) group of teachers, graduates and students of the careers of industrial design and informatics degree from the National University of La Plata, developed the design and prototype of a braille printer. The work was carried out according to the principles of Gandhian Engineering, based on the reuse of ink-jet printers. The project consists of the design, development and generation of a low-cost Braille printer, produced locally, which prioritizes the use of nationally manufactured components for assembly. To achieve this, an electronic and electromechanical system was designed and manufactured to adapt any Inkjet printer to the objectives of the project, enabling the recycling of obsolete printers. This means, it is proposed to resolve through the use of text printers, applying technical knowledge of computer science and industrial design, to adapt the technological components to the Braille lexicon printer. They also developed, on the one hand, software that controls the printer and allows its use in a simple and accessible way. On the other hand, the hardware and external components were adapted with 3D printing technology and thermoforming, producing a housing that contains the entire printer. Finally, a systematization of the assembly process of the printer prototype was carried out, making it possible to replicate it. Using methodologies of Gandhian Design, a prototype and two alternative proposals of carcasses were obtained. The main objective, which guided this work, was that blind people can access low-cost braille printers promoting by this a favorable impact on the cultural development of their daily lives. (shrink)

Mathematical logic is a branch of mathematics that takes axiom systems and mathematical proofs as its objects of study. This book shows how it can also provide a foundation for the development of information science and technology. The first five chapters systematically present the core topics of classical mathematical logic, including the syntax and models of first-order languages, formal inference systems, computability and representability, and Gödel’s theorems. The last five chapters present extensions and developments of classical mathematical logic, particularly (...) the concepts of version sequences of formal theories and their limits, the system of revision calculus, proschemes (formal descriptions of proof methods and strategies) and their properties, and the theory of inductive inference. All of these themes contribute to a formal theory of axiomatization and its application to the process of developing information technology and scientific theories. The book also describes the paradigm of three kinds of language environments for theories and it presents the basic properties required of a meta-language environment. Finally, the book brings these themes together by describing a workflow for scientific research in the information era in which formal methods, interactive software and human invention are all used to their advantage. The second edition of the book includes major revisions on the proof of the completeness theorem of the Gentzen system and new contents on the logic of scientific discovery, R-calculus without cut, and the operational semantics of program debugging. This book represents a valuable reference for graduate and undergraduate students and researchers in mathematics, information science and technology, and other relevant areas of natural sciences. Its first five chapters serve as an undergraduate text in mathematical logic and the last five chapters are addressed to graduate students in relevant disciplines. (shrink)

Readers of Philosophical Psychology may be most familiar with Ron Sun by way of an article recently appearing in this journal on creative composition expressed within his own hybrid computational intelligence model, CLARION (Sun, 2013). That article represents nearly two decades’ work in situated agency stressing the importance of psychologically realistic architectures and processes in the articulation of both functional, and reflectively informative, AI and agent- level social-cultural simulations. Readers may be less familiar with Sun’s 2001 “prolegomena” to related multi-agent (...) (proto-social) research also from this journal. That article argues that “a proper balance between “objective” social reality and individual cognitive processes” is necessary in order to understand “how individual belief systems... and the social/cultural belief system ... interact” (Sun, 2001, pages 10 and 23). This issue remains central in Sun’s 2012 edited volume, Grounding Social Sciences in the Cognitive Sciences, here addressed from within the expanding field of pioneering researchers bent on orchestrating that proper balance, the “cognitive social sciences.” Its fifteen chapters are sectioned according to culture, politics, religion, and economics, and closes with an especially rewarding pair of contributions from Gintis, and McCubbins and Turner, under the heading of “unifying perspectives.” Most entries – but for Sun’s own - are serviceably summarized in the introductory overview. So, rather than follow suit, this review will focus on setting out Sun’s vision, noting how this text helps us to realize it more clearly, with a positive focus on a few entries in particular. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Empirical Questions Deserve Empirical AnswersColin MartindaleWhat is wrong with the current state of humanistic literary studies? On the theoretical level, we find various types of postmodernism, none of which makes much sense. On the other hand, there are approaches such as Marxism, Feminism, and the New Historicism. One can at least understand the contentions of such theorists, but these contentions are generally quite implausible. If poetry were an effective (...) means of maintaining the status quo or of oppressing anyone, one wonders why this was never noticed by politicians or generals. Now that the fact has been “discovered,” one wonders why it is not put to use by the power elite. What has led literary theory to stray onto such strange grounds? I believe that the faulty methods used by many literary theorists offer us at least part of an answer.Humanistic critics have no reasonable way of deciding among alternative answers if theorists happen to ask a question that is answerable—i.e., if they propose an empirical investigation. Their only method is one of producing examples and trying to persuade the reader. 1 Can a scientific approach provide something better? Certainly it can. First, the scientist does not pose unanswerable questions. Second, science provides methods for resolving disputes, for answering questions that are answerable. These methods are the scientific apparatus of counting, measuring, experimenting, and so on. Humanistic inquiry is simply not as effective as scientific inquiry. If a question is meaningful, it is by definition an empirical question. Science is the only method to us available for answering such questions. Humanism has no decision-making methods, no objective methods of choosing amongst competing hypotheses. [End Page 347]To paraphrase Plato, literary critics hypothesize many fine things but know nothing of how to test them. Science already has the methods. We merely need to apply them. To give an example from my own research, Raymond and a number of other literary scholars tried to say that across the course of the nineteenth century, the content of French poetry became more primary process (Freud), dedifferentiated (Werner), associative (Wundt), or mythic (Cassirer) in its content. 2 Unless one can translate Raymond’s comments into these theoretical terms, it is difficult to understand what in the world he is talking about, let alone to test his contention. Because literary critics usually make up their psychology as they go along, it is difficult to understand what they say. Because they have only a proof-by-example method, it is difficult to believe what they say. If we do make the translation and develop a metric to measure the degree to which poetic content is primary process, we can test Raymond’s hypothesis and find out if it is correct. 3 We can not only find out if it is correct. We can fit curves to the data, compute rates of change, relate rates of change to other variables, and so on. One cannot fit curves to what Lotman aptly called “literary chit-chat.” 4 Without such an objective measure of primary process content, one would no doubt assert that twentieth-century poetry is even more mythic in its content, because the poets themselves have said so. 5 In fact, the metric confirms Plato’s warning that poets lie.Some literary theorists, of course, do things that are at least close to science. Numbers would be of great help to such theorists if only as mnemonic devices. Given that people cannot hold more than about seven things in mind at once, the task of sorting out and comparing hundreds of texts is very difficult unless some counting is done. 6 Humanists can count, but they seem not to realize the value of this ability. Lévi-Strauss and the structuralists were doing what might be called zero-degree science. 7 It is reasonable to segment texts and look for regularities. It is not reasonable to look for regularities before one has determined the reliability of the segmentations: that is, before one has determined whether people agree as to how to segment texts. To compute a reliability coefficient, one has to use numbers, and one has to know the formula. Humanists don’t... (shrink)

It is well established by now that computer science has a number of concerns in common with natural language understanding. Common themes show up in particular with algorithmic aspects of text processing. This chapter gives an overview of border crossings from NLP to CS and back. Starting out from syntactic analysis, we trace our route via a philosophical puzzle about meaning, Hoare correctness rules for dynamic semantics, error state analysis of presupposition, equational reasoning about state change, (...) programming with frameworks originally devised for natural language semantics, and the logic of incremental processing. In many cases methods and perspectives developed on one side of the border proved quite useful on the other side, although usually it becomes clear after a while that tools have to be redesigned to fit. The chapter ends with a sketch of the emerging contours of a ‘proper treatment of context in natural language’ that is more than just an application of a logic designed for program analysis. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:"Your Cell Will Teach You Everything":Old Wisdom, Modern Science, and the Art of AttentionNoreen HerzfeldA brother came to Scetis to visit Abba Moses and asked him "Father, give me a word." The old man said to him "Go, sit in your cell, and your cell will teach you everything." 1 Among the Desert Fathers, Christian monks of the fourth and fifth centuries, it was customary for a novice (...) to go to an elder and ask for "a word," a word of advice, of counsel, a word to take home and reflect on. What does this word of advice say to us today?A Multitasking World"Your cell will teach you everything." To my students, this seems like very strange advice indeed. "Your cell?" When I quoted Abba Moses to a colleague he instinctively reached for his phone. But a monk's cell? Isn't a monk's cell empty, isolated? What can that cell possibly have to teach? And how? The lives of the young men and women I teach are the very antithesis of sitting in a cell. Their attention is fragmented, divided by an array of modern technologies. I watch them walk by my office window, iPod plugged into the ears, cell phone or Blackberry in hand as they check e-mail or send a text message. Time in their rooms is characterized by one eye on the television and another on the computer, on which are open their theology paper, an instant messaging box or two connecting them to friends, their Facebook page, in case one of their friends should post a status update, and perhaps a Twitter feed or their favorite blog. They assure me that they have grown up multitasking. Young Americans spend an average of six hours a day using nonprint media, and at least a quarter of that time they are using more than one screen, device, or channel.2 They are connected, linked in, logged on.It is not just the student who multitasks while doing homework. The average office worker is interrupted roughly every three minutes during the workday, interruptions that the worker herself often initiates.3 These include the phone, e-mail, [End Page 83] checking websites. As more jobs move to the knowledge and service sectors, more of us find the temptation to multitask at work irresistible.But what effect does all this multitasking have on the person? We're not getting more done, for one thing. Several recent studies have shown that, contrary to self-perception, people really can't multitask. The brain cannot concentrate on several things simultaneously. Instead it switches focus from task to task the same way a computer does. This means that all tasks are slowed down somewhat by the switching process, and the attempt to coordinate too many tasks can lead to more time being devoted to the switching than to the tasks at hand, a phenomenon computer scientists have long been aware of, known as "thrashing." Earl Miller, a neuroscientist at MIT, notes: "Think about writing an e-mail and talking on the phone at the same time. You cannot focus on one while doing the other. That's because of interference between the two tasks."4 Miller notes that in an MRI you can actually see the brain struggling as it shifts rapidly from one to the other.One can see that this might have a deleterious effect on one's work life. Research shows that, once interrupted by an e-mail or a phone call, the average worker can take up to half an hour to return to full concentration on the task at hand.5 But why does this matter for the spiritual life? Over time, multitasking erodes our ability to pay focused, close attention, and this eventually eats away at traits such as patience, tenacity, judgment, and problem solving. This is most evident in the latter. In a test of fifteen-year-olds, the United States ranks twenty-fourth out of the twenty-nine developed countries in the Organization for Economic Co-operation and Development on problem solving skills, with nearly 60 percent of them scoring below the most basic level of using a single... (shrink)

Fake news has become an important topic of research in a variety of disciplines including linguistics and computer science. In this paper, we explain how the problem is approached from the perspective of natural language processing, with the goal of building a system to automatically detect misinformation in news. The main challenge in this line of research is collecting quality data, i.e., instances of fake and real news articles on a balanced distribution of topics. We review available (...) datasets and introduce the MisInfoText repository as a contribution of our lab to the community. We make available the full text of the news articles, together with veracity labels previously assigned based on manual assessment of the articles’ truth content. We also perform a topic modelling experiment to elaborate on the gaps and sources of imbalance in currently available datasets to guide future efforts. We appeal to the community to collect more data and to make it available for research purposes. (shrink)

A comprehensive introduction to optimization with a focus on practical algorithms for the design of engineering systems. This book offers a comprehensive introduction to optimization with a focus on practical algorithms. The book approaches optimization from an engineering perspective, where the objective is to design a system that optimizes a set of metrics subject to constraints. Readers will learn about computational approaches for a range of challenges, including searching high-dimensional spaces, handling problems where there are multiple competing objectives, and accommodating (...) uncertainty in the metrics. Figures, examples, and exercises convey the intuition behind the mathematical approaches. The text provides concrete implementations in the Julia programming language. Topics covered include derivatives and their generalization to multiple dimensions; local descent and first- and second-order methods that inform local descent; stochastic methods, which introduce randomness into the optimization process; linear constrained optimization, when both the objective function and the constraints are linear; surrogate models, probabilistic surrogate models, and using probabilistic surrogate models to guide optimization; optimization under uncertainty; uncertainty propagation; expression optimization; and multidisciplinary design optimization. Appendixes offer an introduction to the Julia language, test functions for evaluating algorithm performance, and mathematical concepts used in the derivation and analysis of the optimization methods discussed in the text. The book can be used by advanced undergraduates and graduate students in mathematics, statistics, computer science, any engineering field, (including electrical engineering and aerospace engineering), and operations research, and as a reference for professionals. (shrink)

Classical natural language processing endeavored to understand the language of native speakers. When this proved to lie beyond the horizon, a scaled-down version settled for text analysis and processing but retained the old name and acronym. But text ≠ language. Any combination of signs and symbols qualifies as text. Language presupposes meaning, which is what connects it to real life. Failing to distinguish between the two results in confusing humanoids (machines thinking like humans) with machinoids (...) (humans thinking like machines). As scientific English (SciEng) became the lingua franca of science, it has acquired all the traits of a machine language: reduced vocabulary, where fewer and fewer words have taken on more and more meanings; prescribed use of pronouns; depersonalized rigid syntactic forms and rules of composition. Compliance with SciEng standards can be automatically verified, which means that Sci Eng can be automatically imitated, what is referred to as AI writing (ChatGPT). The article discusses an attempt to automatically correct deviations from the rules by what is touted as AI editing. (shrink)

Large language models (LLMs) produce sequences learned as statistical patterns from large corpora. Their emergent status as representatives of the advances in artificial intelligence (AI) have led to an increased attention to the possibilities of regulating the automated production of linguistic utterances and interactions with human users in a process that computer scientists refer to as ‘alignment’—a series of technological and political mechanisms to impose a normative model of morality on algorithms and networks behind the model. Alignment, which can (...) be viewed as the superimposition of normative structure onto a statistical model, however, reveals a conflicted and complex history of the conceptualisation of an interrelationship between language, mind and technology. This relationship is shaped by and, in turn, influences theories of language, linguistic practice and subjectivity, which are especially relevant to the current sophistication in artificially produced text. In this paper, we propose a critical evaluation of the concept of alignment, arguing that the theories and practice behind LLMs reveal a more complex social and technological dynamic of output coordination. We examine this dynamic as a two-way interaction between users and models by analysing how ChatGPT4 redacts perceived ‘anomalous’ language in fragments of Joyce’s Ulysses. We then situate this alignment problem historically, revisiting earlier postwar linguistic debates which counterposed two views of meaning: as discrete structures, and as continuous probability distributions. We discuss the largely occluded work of the Moscow Linguistic School, which sought to reconcile this opposition. Our attention to the Moscow School and later related arguments by Searle and Kristeva casts the problem of alignment in a new light: as one involving attention to the social regulation of linguistic practice, including rectification of anomalies that, like the Joycean text, exist in defiance of expressive conventions. The “problem of alignment” that we address here is, therefore, twofold: on one hand, it points to its narrow and normative definition in current technological development and critical research and, on the other hand, to the reality of complex and contradictory relations between subjectivity, technology and language that alignment problems reveal. (shrink)

This textbook presents a concise, accessible and engaging first introduction to deep learning, offering a wide range of connectionist models which represent the current state-of-the-art. The text explores the most popular algorithms and architectures in a simple and intuitive style, explaining the mathematical derivations in a step-by-step manner. The content coverage includes convolutional networks, LSTMs, Word2vec, RBMs, DBNs, neural Turing machines, memory networks and autoencoders. Numerous examples in working Python code are provided throughout the book, and the code is (...) also supplied separately at an accompanying website. Topics and features: introduces the fundamentals of machine learning, and the mathematical and computational prerequisites for deep learning; discusses feed-forward neural networks, and explores the modifications to these which can be applied to any neural network; examines convolutional neural networks, and the recurrent connections to a feed-forward neural network; describes the notion of distributed representations, the concept of the autoencoder, and the ideas behind language processing with deep learning; presents a brief history of artificial intelligence and neural networks, and reviews interesting open research problems in deep learning and connectionism. This clearly written and lively primer on deep learning is essential reading for graduate and advanced undergraduate students of computer science, cognitive science and mathematics, as well as fields such as linguistics, logic, philosophy, and psychology. (shrink)

In this series of papers I attempt to provide an answer to the question how the Babylonian scholars arrived at their mathematical theory of planetary motion. Papers I and II were devoted to system A theory of the outer planets and of the planet Venus. In this third and last paper I will study system A theory of the planet Mercury. Our knowledge of the Babylonian theory of Mercury is at present based on twelveEphemeridesand sevenProcedure Texts. Three computational systems of (...) Mercury are known, all of system A. System A1is represented by nineEphemeridescovering the years 190 BC to 100 BC and system A2by twoEphemeridescovering the years 310 to 290 BC. System A3is known from aProcedure Textand from Text M, anEphemerisof the last evening visibility of Mercury for the years 424 to 403 BC. From an analysis of the Babylonian observations of Mercury preserved in theAstronomical DiariesandPlanetary Textswe find: (1) that dates on which Mercury reaches its stationary points are not recorded, (2) that Normal Star observations on or near dates of first and last appearance of Mercury are rare (about once every twenty observations), and (3) that about one out of every seven pairs of first and last appearances is recorded as “omitted” when Mercury remains invisible due to a combination of the low inclination of its orbit to the horizon and the attenuation by atmospheric extinction. To be able to study the way in which the Babylonian scholars constructed their system A models of Mercury from the available observational material I have created a database of synthetic observations by computing the dates and zodiacal longitudes of all first and last appearances and of all stationary points of Mercury in Babylon between 450 and 50 BC. Of the data required for the construction of an ephemeris synodic time intervals Δt can be directly derived from observed dates but zodiacal longitudes and synodic arcs Δλ must be determined in some other way. Because for Mercury positions with respect to Normal Stars can only rarely be determined at its first or last appearance I propose that the Babylonian scholars used the relation Δλ = Δt −3;39,40, which follows from the period relations, to compute synodic arcs of Mercury from the observed synodic time intervals. An additional difficulty in the construction of System A step functions is that most amplitudes are larger than the associated zone lengths so that in the computation of the longitudes of the synodic phases of Mercury quite often two zone boundaries are crossed. This complication makes it difficult to understand how the Babylonian scholars managed to construct System A models for Mercury that fitted the observations so well because it requires an excessive amount of computational effort to find the best possible step function in a complicated trial and error fitting process with four or five free parameters. To circumvent this difficulty I propose that the Babylonian scholars used an alternative more direct method to fit System A-type models to the observational data of Mercury. This alternative method is based on the fact that after three synodic intervals Mercury returns to a position in the sky which is on average only 17.4° less in longitude. Using reduced amplitudes of about 14°–25° but keeping the same zone boundaries, the computation of what I will call 3-synarc system A models of Mercury is significantly simplified. A full ephemeris of a synodic phase of Mercury can then be composed by combining three columns of longitudes computed with 3-synarc step functions, each column starting with a longitude of Mercury one synodic event apart. Confirmation that this method was indeed used by the Babylonian astronomers comes from Text M (BM 36551+), a very early ephemeris of the last appearances in the evening of Mercury from 424 to 403 BC, computed in three columns according to System A3. Based on an analysis of Text M I suggest that around 400 BC the initial approach in system A modelling of Mercury may have been directed towards choosing “nice” sexagesimal numbers for the amplitudes of the system A step functions while in the later final models, dating from around 300 BC onwards, more emphasis was put on selecting numerical values for the amplitudes such that they were related by simple ratios. The fact that different ephemeris periods were used for each of the four synodic phases of Mercury in the later models may be related to the selection of a best fitting set of System A step function amplitudes for each synodic phase. (shrink)

Across the world, artificial intelligence (AI) technologies are being more widely employed in public sector decision-making and processes as a supposedly neutral and an efficient method for optimizing delivery of services. However, the deployment of these technologies has also prompted investigation into the potentially unanticipated consequences of their introduction, to both positive and negative ends. This paper chooses to focus specifically on the relationship between gender bias and AI, exploring claims of the neutrality of such technologies and how its understanding (...) of bias could influence policy and outcomes. Building on a rich seam of literature from both technological and sociological fields, this article constructs an original framework through which to analyse both the perpetuation and mitigation of gender biases, choosing to categorize AI technologies based on whether their input is text or images. Through the close analysis and pairing of four case studies, the paper thus unites two often disparate approaches to the investigation of bias in technology, revealing the large and varied potential for AI to echo and even amplify existing human bias, while acknowledging the important role AI itself can play in reducing or reversing these effects. The conclusion calls for further collaboration between scholars from the worlds of technology, gender studies and public policy in fully exploring algorithmic accountability as well as in accurately and transparently exploring the potential consequences of the introduction of AI technologies. (shrink)

With the accelerated evolution of the internet in the form of web-sites, social networks, microblogs, and online portals, a large number of reviews, opinions, recommendations, ratings, and feedback are generated by writers or users. This user-generated sentiment content can be about books, people, hotels, products, research, events, etc. These sentiments become very beneficial for businesses, governments, and individuals. While this content is meant to be useful, a bulk of this writer-generated content requires using text mining techniques and sentiment analysis. (...) However, there are several challenges facing the sentiment analysis and evaluation process. These challenges become obstacles in analyzing the accurate meaning of sentiments and detecting suitable sentiment polarity specifically in the Bangla language. Sentiment analysis is the practice of applying natural language processing and text analysis techniques to identify and extract subjective information from text. This paper presents how the attention mechanism could be incorporated effectively and efficiently in analyzing the Bangla sentiment or opinion. (shrink)

A proof of ‘correctness’ for a mathematical algorithm cannot be relevant to executions of a program based on that algorithm because both the algorithm and the proof are based on assumptions that do not hold for computations carried out by real-world computers. Thus, proving the ‘correctness’ of an algorithm cannot establish the trustworthiness of programs based on that algorithm. Despite the (deceptive) sameness of the notations used to represent them, the transformation of an algorithm into an executable program is a (...) wrenching metamorphosis that changes a mathematical abstraction into a prescription for concrete actions to be taken by real computers. Therefore, it is verification of program executions (processes) that is needed, not of program texts that are merely the scripts for those processes. In this view, verification is the empirical investigation of: (a) the behavior that programs invoke in a computer system and (b) the larger context in which that behavior occurs. Here, deduction can play no more, and no less, a role than it does in the empirical sciences. (shrink)

This text analyses how generative AI systems are being employed in current artistic practice to question certain historical visual narratives, creating representations that challenge some conventional perceptions of the past and thus opening up new perspectives on the experience of temporality. In this regard, special emphasis will be placed on some artistic projects based on generative historical photography practices. These are works that develop new ways around ‘archival aesthetics’ (Sekula in October 39:3–64 1986; Buchloh in Deep storage. collecting, storing (...) and archiving in art [Exhibition catalog]. P.S.1, Nueva York, 1999; Guasch in Arte y archivo, 1920-2010. Genealogías, tipologías y discontinuidades. Akal, Madrid, 2015, etc.) by producing visual archives that do not exist or are alternatives to others. We will therefore analyse works that critically examine how these generative systems can contribute to a revision and re-evaluation of the past, as well as to the problematisation of the ways in which photography has been used for the historical record. These poetics invite subtle reflections on the role of the visual archive in the processes of shaping subjectivity and personal and communal identity. In the final part of the text, we will deal with the study of some artists who, through appropriationist strategies and remakes assisted by generative AI models, revise artistic works from the past, specifically from the photoconceptualism of the 1970s. In these strategies, the thematisation of the relations between photographic register and temporality also plays a leading role. (shrink)

Narrative generation is growing in importance for data utilization, particularly in the context of co-creation with artificial intelligence (AI) agents. Narratives can, for example, bridge theoretical objects with social understanding and promote human actions. Furthermore, clarifying the narrative generation mechanism is essential for constructing effective relationships between humans and AI agents. However, the narrative generation mechanism in data utilization processes has not been fully elucidated. In this study, we developed a framework called the hierarchical narrative representation (HieNaR) to systematize the (...) structure of narrative generation in data utilization processes. HieNaR comprises twelve levels, ranging from the set of texts down to the particle level (e.g., text, sentence, word, character, and stroke), allowing for a comprehensive analysis of narrative structures. We evaluated the usefulness of HieNaR through case studies, examining both individual user experiences and collaborative work between humans and an AI agent. The results demonstrated that the data utilization process interprets data by inquiring whether it satisfies higher-level expectations. In collaboration, AI agents can be understood as co-creative partners in data utilization, possessing their own worldviews. Through these findings, this study not only elucidates the mechanism of narrative generation in data utilization processes but also provides a foundation for improving human–AI collaboration. (shrink)

In this text, our question is what is the current regulatory trend in countries that are not considered central in the development of artificial intelligence, such as Brazil: a preventive approach, or an experimental approach? We will analyze the bills (PL) that are being processed in legislative houses at the state level, and at the federal level, highlighting some elements, such as: Delimitation of the object (conceptualization), fundamental principles, ethical guidelines, relationship with human work, human supervision, and guidelines for (...) public authorities. Based on these elements, we identified how the issues that drive the contemporary debate on AI have been addressed in these legislative initiatives. The results indicate that the strongest national regulation proposal mentions risks, rights, governance, economic agents; these mentions dialogue with the concerns discussed by researchers around the world, regarding the mitigation and prevention of risks, regarding the preservation of individual and collective rights, the role of the State as a regulator and supervisor, and, as was to be expected, the maintenance of economic policies that possibly tend to protect the market; proposes that the foundations of the development, implementation and use of AI have values consistent with ‘human centered AI’ (Bingley et al. 2023), but also points to the neoliberal matrix; introduces human supervision as an effective element in the AI systems cycle; the trend that we can observe in Brazil is the configuration of a regulation that harmonizes articles that favor the preventive approach, with the presence of articles that favor the experimentation approach. (shrink)

As we write this research paper, we notice an explosion in popularity of machine learning in numerous fields (ranging from governance, education, and management to criminal justice, fraud detection, and internet of things). In this contribution, rather than focusing on any of those fields, which have been well-reviewed already, we decided to concentrate on a series of more recent applications of deep learning models and technologies that have only recently gained significant track in the relevant literature. These applications are concerned (...) with artistic production (Sect. 2.1), the writing process (Sect. 2.2), music production (Sect. 2.3), text recognition and attribution (Sect. 2.4). After reviewing and analyzing the positive contributions as well as some of the major limitations of these technologies in each of those fields, we critically reflect (Sect. 3) on how their widespread implementation may affect humans and their creativity. In Sect. 4, we notice that deep learning models are here to stay; so, rather than embracing a negative or pessimistic stance with respect to their future applications in creative domains, we suggest a balanced approach for their assessment and beneficial usage. Finally (Sect. 5), we conclude by summarising what we have achieved and by pointing out possible future research directions. (shrink)

The growing capabilities of artificial intelligence (AI) word processing models have demonstrated exceptional potential to impact language related tasks and functions. Their fast pace of adoption and probable effect has also given rise to controversy within certain fields. Models, such as GPT-3, are a particular concern for professionals engaged in writing, particularly as their engagement with these technologies is limited due to lack of ability to control their output. Most efforts to maximize and control output rely on a process (...) known as prompt engineering, the construction and modification of the inputted prompt with expectation for certain outputted or desired text. Consequently, prompt engineering has emerged as an important consideration for research and practice. Previous conceptions of prompt engineering have largely focused on technical and logistic modifications to the back-end processing, remaining inaccessible and, still, limited for most users. In this paper, we look to the technical communication field and its methods of text generation—the rhetorical situation—to conceptualize prompt engineering in a more comprehensible way for its users by considering the context and rhetoric. We introduce a framework, consisting of a formula, to prompt engineering, which demands all components of the rhetorical situation be present in the inputted prompt. We present discussions on the future of AI writing models and their use in both professional and educational settings. Ultimately, this discussion and its findings aim to provide a means of integrating agency and writer-centric methods to AI writing tools to advance a more human-in-the-loop approach. As the use of generative AI and especially NLP-based technologies become common across societal functions, the use of prompt engineering will play a crucial role not just in adoption of the technology, but also its productive and responsible use. (shrink)

Book Description (Blurb): Cognitive Design for Artificial Minds explains the crucial role that human cognition research plays in the design and realization of artificial intelligence systems, illustrating the steps necessary for the design of artificial models of cognition. It bridges the gap between the theoretical, experimental and technological issues addressed in the context of AI of cognitive inspiration and computational cognitive science. -/- Beginning with an overview of the historical, methodological and technical issues in the field of Cognitively-Inspired Artificial (...) Intelligence, Lieto illustrates how the cognitive design approach has an important role to play in the development of intelligent AI technologies and plausible computational models of cognition. Introducing a unique perspective that draws upon Cybernetics and early AI principles, Lieto emphasizes the need for an equivalence between cognitive processes and implemented AI procedures, in order to realise biologically and cognitively inspired artificial minds. He also introduces the Minimal Cognitive Grid, a pragmatic method to rank the different degrees of biologically and cognitive accuracy of artificial systems in order project and predict their explanatory power with respect to the natural systems taken as source of inspiration. -/- Providing a comprehensive overview of cognitive design principles in constructing artificial minds, this text will be essential reading for students and researchers of artificial intelligence and cognitive science. (shrink)

Against Nature – Chapter Abstracts Chapter 1. A Transdisciplinary Approach. In this short book you will find philosophy – metaphysical and political - economics, critical theory, complexity theory, ecology, sociology, journalism, and much else besides, along with the signposts and reference texts of the Information Systems field. Such transdisciplinarity is a challenge for both author and reader. Such books are often problematic: sections that are just old hat to one audience are by contrast completely new and difficult to another. My (...) hope is that in the interconnections, arguments and thrust of this polemic, readers will discover both interest and insight, alongside a range of new avenues to explore. This introductory chapter sets the scene – today’s digital world of Tech Giants and Fake News, its roots in the philosophical arguments of the 1920s, and the book’s key claims: (i) that the early 20th century philosophical grounding of today’s digital revolution is culpable in digital’s (growing) contribution to the ecological catastrophe unfolding in the 21st century; (ii) that process philosophy offers a new way to rethink that philosophical grounding, and reshape the digital revolution to support strategies to counter that catastrophe. Chapter 2. The Problem with Digital. This chapter begins with a brief overview of the research approaches in information systems as an academic field, before turning to the deeper roots of its malaise, in individualism, and its looming consequences. The three branches of Information Systems research, in academia, prove to be a useful lens through which to understand the field: Positivism, Interpretivism, and the Critical stance taken by this book. The ‘scientism’ at the root of positivism is examined, and the positivism in Information Systems critiqued as a historically contingent response to the ascendancy of a new brand of economics in Business Schools after the Second World War. But the computational market-fundamentalist form of economics sponsored in the 1950s (and applied by governments since the 1970s) centred around notions of the individual rational actor as an information processor. The philosophical underpinning of methodological and possessive individualism in this approach is exposed, and its influence upon the development – long before computing – of the science of ecology, and our notion of ecosystems, introduced. Chapter 3. The Future Does Not Exist. The philosophical core of the book, this chapter introduces process philosophy. Through an examination of the irreversible reality of subjectivity, Bergson’s famous notion of the durée reélle, and Whitehead’s critique of the bifurcation of subject and object, are introduced. The causally closed ‘time’ of positive science determines existence from the beginning to the end of the universe, be it three seconds or three trillion years. But the reality, of course, is that the future does not exist: our choices are real, and only one of myriad potential futures comes into being at each moment. As Bergson insists, durational succession exists, I am conscious of it; it is a fact. Bergson’s star – once the brightest of any living philosopher in the world – faded almost as quickly as it rose, under the onslaught from the logical positivists whose verificationism insisted that any proposition has no factual meaning if no evidence of observation can count for or against it: all ethics, aesthetics, romance, and metaphysics – and the very subjectivity with which duration is experienced - were thus closed down and dismissed. In this chapter it is reintroduced, to a new audience. Chapter 4. The World in a New Light. Many fundamental problems in the world can be seen as resulting from the false philosophy of bifurcation, fixity, and the reification of abstractions critiqued by process philosophy. Being – with all the isolation and focus upon the individual that it entails – must, if we are to address these problems, be seen as secondary to Becoming, with all the connection, interrelatedness, and complex collectivity that it implies. Choices become clearer, between positivism and interpretivism, between accents upon individualism or collectivism, between reductionist and complex adaptive systems approaches. The systemic individualism in Anglo-American societies can be regarded as actually harmful: the Tech Giants severing ties and bonds rather than connecting us; algebraic ecological models actually breaking the co-dependencies and co-requisites upon which real – complex - ecological health depends. Positivism, built as it is upon methodological individualism, seen in the light of process philosophy, becomes a danger to personal psychological balance – cutting us off from one another; a danger to the social fabric – undermining and impoverishing our civic life; and a danger to the ecological health of the planet – ignoring the immense (eco)systemic impact of our activities over the last centuries upon everything around us in the natural world. Chapter 5. A Theoretical Manifesto for Green IT. We are not islands, and in a process-relational social organisation much must be held in common. We are individuals, but we cannot survive alone. Four different perspectives on individualism show it to be little more than greed. An ecological economics reintegrating the household, the social, the supportive State, and – crucially – the life-giving earth into our polities is introduced and promoted. I introduce the concept of ‘Infomateriality’ – a non-bifurcated digital world where the physical bodies of people - fingers touching keyboards and eyes scanning screens - are as much ‘hardware’ as cabling, circuitboards and haptic interfaces, and the social practices, power relations, and embedded politics within IT artefacts define all such techné as fundamentally social. Abstract divisions are false, and whole, socially embedded systems should be the focus of IS, and from a philosophically and sociologically much deeper perspective. ‘Tech for Good’ is held up as movement in the right direction. My hope is that this book will help promote action, in the field of information systems, toward a better world, where Green Tech for Good is deployed for Nature, rather than against it. (shrink)