Common Sense Research Articles

The Advancement оf Modern Chatbots аnd Their Applications

Artificial Intelligence (AI) is on the rise, with applications which use it developing very rapidly in recent years. This is very much characteristic of one of its subclasses, Generative Artificial Intelligence, which underpins many of today’s most popular AI applications. Challenges in developing Large language models (LLMs) are discussed, which include difficulties such as language ambiguity, common sense, and understanding complex language constructs and queries. The key innovations that led to the development of LLMs are described, namely the creation of transformers, self-supervised learning and large datasets. Next, the most popular applications of LLM today, chatbots, are discussed. The capabilities, advantages, and disadvantages of some of the most popular chatbots, such as ChatGPT, Copilot, Bard, YouChat, HuggingChat, and Jasper, are shown, and an example of wrong answers from them is given. The advantages of chatbots – answering questions asked in natural language, generating creative content, solving problems – are summarized, and a number of their applications in business and economic fields are shown. Disadvantages are pointed out, including the provision of sometimes inaccurate or misleading information. Finally, expectations for the future development of LLMs and chatbots and the dangers they may bring to people are presented.

Common sense, uncommon sense: Tejumola Olaniyan in the theorization of African postcolonial Drama

This paper engages Tejumola Olaniyan’s “Femi Osofisan: The Form of Uncommon Sense.” The essay in question undertakes a reading of a representative selection from the corpus of Femi Osofisan’s plays, employing the theory of uncommon sense which Olaniyan himself formulated. Olaniyan projects uncommon sense as a reflection on Antonio Gramsci’s theory of common sense put forward in his Selections from Prison Notes. He presents it as a new dimension of contemplation which explores new possibilities and unsettles old conclusions. To prove his position that Osofisan’s plays represent the form of uncommon sense, Olaniyan rifles through the playwright’s oeuvre and produces detailed readings of some of the works using the theory. I undertake three main tasks in this paper. First, I evaluate the accuracy of the positions taken by Olaniyan on some of the plays of Osofisan that he investigates using the theory of uncommon sense. Second, while affirming that uncommon sense as formulated by Olaniyan is seminal, I try to see whether it is not possible to re-constitute this principle around the notion of cultural hegemony that Gramsci is best known for. Finally, I attempt an application of the reconfigured theory in the analysis of Ama Ata Aidoo’s Anowa

The Place of Naïve Realism in Russell’s Changing Accounts of Perception

In this paper I describe the place of naive realism in Russell’s changing accounts of perception. I argue ‎for the following conclusions: (1) The early period, 1898-1910: I am inclined to think that the naïve ‎realism that Russell embraced so enthusiastically early on may not have been intended as a naïve ‎realism about perception, but as a metaphysical or semantical thesis. (2) The Problems of Philosophy ‎‎(1912): Russell abandons naïve realism (if, in fact, he ever held it) and presents a sense-datum version ‎of representative realism. (3) “On Matter” (1912): here we see Russell’s best attempt to defend ‎something very close to the standard doctrine of naïve realism. The objects of perception—the ‎‎“everyday material objects such as caterpillars and Cadillacs”—have, of course, undergone severe ‎reconstruction. But the resulting picture does capture the spirit of the doctrine. (4) The period from ‎‎1914 to 1927: though Russell’s thinking about perception underwent some significant changes during ‎this period—the sense datum theory is replaced by neutral monism—I try to show that the ‎distinction between the matter of physics and the thing of common sense is a constant feature of ‎Russell’s changing views. And I suggest that our perceptual relation the thing of common ‎sense (as logically reconstructed by Russell) can usefully be viewed as a limited sort of naïve realism. ‎‎(5) The period after 1927: the thing of common sense no longer features in Russell’s account of our ‎perceptual access to the world. The things we perceive are percepts, located in our private spaces. The ‎only material objects of which these percepts are parts are our brains. All other material objects are ‎beyond our perceptual reach and are accessible only via inference. This is the end of anything ‎resembling the traditional view of naïve realism in Russell’s account of perception. ‎

Contesting the common sense around NGOs

Contesting the common sense around NGOs

The “Global” Deception: Flat-Earth Conspiracy Theory between Science and Religion

The article focuses on flat earthism, one of the most well-known contemporary conspiracy theories in popular culture. According to proponents of this theory, which has found a growing international following in recent years, political institutions such as the U.S. government and scientific institutions such as NASA would operate to deceive humanity about the real shape of our planet and the universe in which we live. In countering the data acquired by modern science and common sense knowledge, flat earthism stands as a heterodox theory and a radical critique of the authority of socially legitimized epistemic institutions. This article consists of two parts. The first part will offer a genealogical reconstruction of the flat-earth conspiracy, tracing its history from the 19th century to the exponents of the current movement. The second part will delve into the discourse of the proponents of flat earthism with specific reference to the Italian context, through documentary analysis of recent publications and online material available on YouTube and Telegram, which constitute some of the main channels for the discussion and dissemination of flat earthism in Italy today. On the basis of the data collected and analyzed, it will be shown how flat earthism represents a paradigmatic case of superconspiracy, that is, of a far-reaching theory capable of linking and including within itself a set of other, more circumscribed theories. To this end, flat earthism elaborates on a discourse that ambivalently combines two registers, scientific and religious language, proposing itself as a dissident narrative that if on the one hand rejects the knowledge of institutionalized and organized science and religion, on the other hand accredits an alternative and anti-intellectualist path of knowledge, accessible to the “common man” that aims to create a space of autonomy and opposition to the processes of secularization and globalization in which the flat earthers see the project of building a dystopian New World Order.

What is the Far-Right in Aotearoa New Zealand

Matthew Cunningham, Paul Spoonley, and Marinus La Rooij (eds.)Histories of Hate: The Radical Right in Aotearoa New ZealandDunedin: Otago University Press, 2023, 444pp
 In 1988, Stuart Hall published The Hard Road to Renewal, a collection of essays written over the previous decade that attempted to grapple with the nature and significance of ‘Thatcherism’ in Britain. The Thatcherist neoliberal project, Hall argued, attempted to reconfigure the common sense of the people. The aim of the neoliberal project was to dismantle social democracy and the post-war welfare state and construct a new modernity characterised by free-market enterprise, imbued with conservative values of tradition,family, and nation.

CORECODE: A Common Sense Annotated Dialogue Dataset with Benchmark Tasks for Chinese Large Language Models

As an indispensable ingredient of intelligence, commonsense reasoning is crucial for large language models (LLMs) in real-world scenarios. In this paper, we propose CORECODE, a dataset that contains abundant commonsense knowledge manually annotated on dyadic dialogues, to evaluate the commonsense reasoning and commonsense conflict detection capabilities of Chinese LLMs. We categorize commonsense knowledge in everyday conversations into three dimensions: entity, event, and social interaction. For easy and consistent annotation, we standardize the form of commonsense knowledge annotation in open-domain dialogues as "domain: slot = value". A total of 9 domains and 37 slots are defined to capture diverse commonsense knowledge. With these pre-defined domains and slots, we collect 76,787 commonsense knowledge annotations from 19,700 dialogues through crowdsourcing. To evaluate and enhance the commonsense reasoning capability for LLMs on the curated dataset, we establish a series of dialogue-level reasoning and detection tasks, including commonsense knowledge filling, commonsense knowledge generation, commonsense conflict phrase detection, domain identification, slot identification, and event causal inference. A wide variety of existing open-source Chinese LLMs are evaluated with these tasks on our dataset. Experimental results demonstrate that these models are not competent to predict CORECODE's plentiful reasoning content, and even ChatGPT could only achieve 0.275 and 0.084 accuracy on the domain identification and slot identification tasks under the zero-shot setting. We release the data and codes of CORECODE at https://github.com/danshi777/CORECODE to promote commonsense reasoning evaluation and study of LLMs in the context of daily conversations.

TETRIS: Towards Exploring the Robustness of Interactive Segmentation

Interactive segmentation methods rely on user inputs to iteratively update the selection mask. A click specifying the object of interest is arguably the most simple and intuitive interaction type, and thereby the most common choice for interactive segmentation. However, user clicking patterns in the interactive segmentation context remain unexplored. Accordingly, interactive segmentation evaluation strategies rely more on intuition and common sense rather than empirical studies (e.g., assuming that users tend to click in the center of the area with the largest error). In this work, we conduct a real-user study to investigate real user clicking patterns. This study reveals that the intuitive assumption made in the common evaluation strategy may not hold. As a result, interactive segmentation models may show high scores in the standard benchmarks, but it does not imply that they would perform well in a real world scenario. To assess the applicability of interactive segmentation methods, we propose a novel evaluation strategy providing a more comprehensive analysis of a model's performance. To this end, we propose a methodology for finding extreme user inputs by a direct optimization in a white-box adversarial attack on the interactive segmentation model. Based on the performance with such adversarial user inputs, we assess the robustness of interactive segmentation models w.r.t click positions. Besides, we introduce a novel benchmark for measuring the robustness of interactive segmentation, and report the results of an extensive evaluation of dozens of models.

The role of rationales for and criticisms of ethical decisions in the development of meta-moral cognitive skills

ABSTRACT Meta-moral cognitive skills consist of identifying reasons behind ethical decisions, potential criticisms for such reasons, and constructing counterarguments for these criticisms. We assessed the relationship among these three elements of ethical judgment justification using ethical dilemmas. A mixed-methods research design was used to investigate university students from India and Japan. Critical thinking skills, knowledge of professional ethics, discipline, perspective-taking, common sense, and culture influenced the respondents’ meta-moral cognitive skills. There was a correlation between the number/strength of reasons and criticisms and between criticisms and counterarguments. The respondents had difficulty connecting the reasons for their decisions and their counterarguments. The results imply that incorporating personal and professional cases as part of the ethics curriculum can improve meta-moral cognitive skills.

Collaborative Synthesis of Patient Records through Multi-Visit Health State Inference

Electronic health records (EHRs) have become the foundation of machine learning applications in healthcare, while the utility of real patient records is often limited by privacy and security concerns. Synthetic EHR generation provides an additional perspective to compensate for this limitation. Most existing methods synthesize new records based on real EHR data, without consideration of different types of events in EHR data, which cannot control the event combinations in line with medical common sense. In this paper, we propose MSIC, a Multi-visit health Status Inference model for Collaborative EHR synthesis to address these limitations. First, we formulate the synthetic EHR generation process as a probabilistic graphical model and tightly connect different types of events by modeling the latent health states. Then, we derive a health state inference method tailored for the multi-visit scenario to effectively utilize previous records to synthesize current and future records. Furthermore, we propose to generate medical reports to add textual descriptions for each medical event, providing broader applications for synthesized EHR data. For generating different paragraphs in each visit, we incorporate a multi-generator deliberation framework to collaborate the message passing of multiple generators and employ a two-phase decoding strategy to generate high-quality reports. Our extensive experiments on the widely used benchmarks, MIMIC-III and MIMIC-IV, demonstrate that MSIC advances state-of-the-art results on the quality of synthetic data while maintaining low privacy risks.

Large Language Models Are Neurosymbolic Reasoners

A wide range of real-world applications is characterized by their symbolic nature, necessitating a strong capability for symbolic reasoning. This paper investigates the potential application of Large Language Models (LLMs) as symbolic reasoners. We focus on text-based games, significant benchmarks for agents with natural language capabilities, particularly in symbolic tasks like math, map reading, sorting, and applying common sense in text-based worlds. To facilitate these agents, we propose an LLM agent designed to tackle symbolic challenges and achieve in-game objectives. We begin by initializing the LLM agent and informing it of its role. The agent then receives observations and a set of valid actions from the text-based games, along with a specific symbolic module. With these inputs, the LLM agent chooses an action and interacts with the game environments. Our experimental results demonstrate that our method significantly enhances the capability of LLMs as automated agents for symbolic reasoning, and our LLM agent is effective in text-based games involving symbolic tasks, achieving an average performance of 88% across all tasks.

The enhancement effects of multiple hydrogen bonds between bi-terminal groups and penta-alanine assemblies on creep resistance and mechanical strength of polyisoprene rubbers

Along with the continuously advanced requirements for high performance rubbers such as in aircraft tires, natural rubbers show limitations in achieving high temperature creep resistance and high mechanical strength simultaneously. Meanwhile, the bi-terminal interactions of natural rubber (NR) exhibit unique reinforcement effects, which are difficult to realize in synthetic rubbers. In this article, four different types of bi-terminal polyisoprenes with distinct groups were synthesized, and they were assembled with penta-alanine molecule (5 A) to obtain high-performance rubbers by terminal hydrogen bonding reinforcement. Infrared tests indicate that the strong hydrogen bonds can be formed between two terminals and turn stronger after adding 5 A. Thus, the network of rubbers remains stable under different strains and temperatures and the activation energy of networks is elevated. As a result, this biomimetic design endows polyisoprene with high tensile strength compared with Malaysian NR and greater creep resistance. Further Mooney fitting and DMA test suggests that these confined hydrogen bonds not only increased the number of crosslinking points and entanglements of network, but also are beneficial for the segmental chain motion. In contrast to our common sense on hydrogen bonds which present large relaxation and hysteresis, this study proposes a facile method for preparing high-temperature creep-resistant rubbers by introducing confined hydrogen bonds, which represents a great advance in the structural biomimicry of NR.

Spasmolytic Effect of Flopropione Does Not Involve Catechol-O- methyltransferase (COMT) Inhibition.

Flopropione (Flo) has been used for gallstone and urolithiasis as a spasmolytic agent almost exclusively in Japan. According to the package insert, its main mechanism is catechol-O-methyltransferase (COMT) inhibition and anti-serotonergic effect. This is obviously contrary to pharmacological common sense, but it is described that way in pharmacology textbooks and occurs in questions in the National Examination for Pharmacists in Japan. As this is a serious problem in education, we re-examined the action of Flo. The guinea pig ureter was hardly contracted by serotonin, but noradrenaline (NA) elicited repetitive twitch contraction, which was inhibited by Flo. The sphincter of Oddi (SO) exhibited a spontaneous repetitive twitch contraction, which was inhibited by NA and Flo. The inhibitory effect of NA was reversed by α- and β-blockers, whereas that of Flo was not. Entacapone, a representative COMT inhibitor, did not affect the movement of the ureter and the SO. Nifedipine suppressed carbachol-induced contraction of the taenia coli, spontaneous movement of the SO, and NA-induced contraction of the ureter to almost the same extent, whereas Flo did not inhibit the taenia coli, but inhibited the contraction of the SO and the ureter. The inhibitory pattern of Flo resembled that of the ryanodine receptor agonist 4-chloro-m-cresol and the inositol 1,4,5-trisphosphate (IP3) receptor antagonist 2-aminoethoxydiphenyl borate. It is concluded that COMT inhibition or serotonin inhibition is not involved in the spasmolytic action of Flo. Flo might act on ryanodine receptors and/or IP3 receptors, which are responsible for periodic Ca release from Ca stores, to disrupt coordinated Ca dynamics.

‘Tick boxes are just tick boxes’: Problematising evidence-based teaching and exploring the space of the possible through a complexity lens

This article seeks to provide a new paradigm for questioning how quality and excellence in teaching practices are understood and evaluated. By combining ideas from complexity theory and Michel Foucault’s conception of polymorphous correlations, I argue that a shift away from the forms of thought that engender reductionist evaluations can become a starting point to redefine the efficacy of teaching practices. By examining teaching practices through data obtained from interviews and classroom observations at a further education college, this article justifies disrupting our current common sense by which quality is defined in the landscape of educational policies and research. It is necessary, first, to try to unsettle the so-called discourse of evidence-based teaching, resulting in the production and dissemination of universalised pedagogical forms. By exploring how ecological factors affect institutional hierarchies and influence teaching practices, I challenge the notion that power relations in education are solely one-directional and oppressive. Insights from theory and teaching practices suggest that there are new forms of power at play, drawing attention to the concept I refer to as ‘transphenomenal awareness', and offering a more profound understanding of the significance of transcending the confines of pedagogical determinism that presently guides educational policymaking.

The Antibusiness Basis of Leftist “Breakthrough” Presidencies in Neoliberal Latin America

Why did so many of Latin America’s leftist presidential hopefuls win at the turn of the twenty-first century? Why were they successful at breaking with their neoliberal political establishments when other leaders were not? For five of these leftists, antibusiness sentiment—not just frustration with political failures—boosted support. It catalyzed a backlash against the economic conditions and U.S. architects of neoliberalism to tip the electorate in favor of leftist candidates. It did so even as antibusiness sentiment did little for the parties of seven leftist presidential contenders who lost in that same period. These results align with Gramsci’s assessment that left electoral success hinges on breaking through the “common sense” narratives that otherwise occlude the capitalist interests undergirding establishments and thereby preserve class hegemony.

PERAN PEMANGKU ADAT TERHADAP PENGAMBILAN KEPUTUSAN KELOMPOK (FENEMENOLOGI PADA MASYARAKAT DI DESA SUNGAI BATANG, KABUPATEN AGAM, SUMATERA BARAT)

This study examines the role of traditional stakeholders in group decision making, with a phenomenological study of the community in Sungai Batang Village, Agam Regency, West Sumatra. The formulation of the problem in this study is, how is the role of traditional stakeholders in group decision making (phenomenology of the community in Sungai Batang Village, Agam Regency, West Sumatra). The purpose of this study was to determine the role of traditional stakeholders in group decision making (phenomenology in the community in Sungai Batang Village, Agam Regency, West Sumatra. The method in this study was qualitative phenomenology, the object of research was the community in Sungai Batang Village, Tanjung Raya District, Religious District. , West Sumatra. The validity of the data used triangulation of sources and researchers, by comparing and rechecking the results of interviews that researchers conducted with sources.Research results in this study include: (1) Decision making in the community in Sungai Batang has a series of alternatives that are decided rationally or with common sense by customary stakeholders; (2) In the process of making customary decisions in Sungai Batang, this process goes through stages that are not immediately decided, but require a series of communication with customary stakeholders.

Can Robots Be Smarter than Human Beings?

The rapid advancements in artificial intelligence (AI) and robotics have fuelled speculation about the possibility of machines surpassing human intelligence. This abstract explores the question of whether robots can become smarter than human beings. By analyzing the capabilities of contemporary AI technologies and understanding the fundamental characteristics of human intelligence, we assess the potential for machines to outpace human cognitive abilities. To address this question, we examine the current state of AI development, including machine learning, deep learning, and neural networks. We discuss how these technologies enable robots to process vast amounts of data, learn from it, and make autonomous decisions. Additionally, we explore the concept of "general intelligence" and its significance in comparing human intelligence to AI. While machines excel in narrow domains and specific tasks, achieving true human-like general intelligence remains an ongoing challenge. Furthermore, the abstract delves into the unique aspects of human intelligence that set it apart from current AI capabilities. Human cognition encompasses various complex abilities such as creativity, emotional intelligence, moral reasoning, and common sense understanding, which have proven difficult to replicate in machines. We examine the limitations and challenges faced by AI in these areas and explore the philosophical and ethical implications of creating machines that surpass human cognitive capacities. Ultimately, the abstract concludes that while robots have shown remarkable progress in specific domains, surpassing human intelligence in its entirety is a complex and elusive goal. Human intelligence encompasses a multitude of intricacies that extend beyond pure computational power. However, the abstract acknowledges the potential for future advancements in AI and robotics to challenge the boundaries of human cognitive abilities, warranting continued research and thoughtful consideration of their societal impact.

TrafficGPT: Viewing, processing and interacting with traffic foundation models

With the promotion of ChatGPT to the public, Large language models indeed showcase remarkable common sense, reasoning, and planning skills, frequently providing insightful guidance. These capabilities hold significant promise for their application in urban traffic management and control. However, large language models (LLMs) struggle with addressing traffic issues, especially processing numerical data and interacting with simulations, limiting their potential in solving traffic-related challenges. In parallel, specialized traffic foundation models exist but are typically designed for specific tasks with limited input-output interactions. Combining these models with LLMs presents an opportunity to enhance their capacity for tackling complex traffic-related problems and providing insightful suggestions. To bridge this gap, we present TrafficGPT—a fusion of multiple LLMs and traffic foundation models. This integration yields the following key enhancements: 1) empowering LLMs with the capacity to view, analyze, process traffic data, and provide insightful decision support for urban transportation system management; 2) facilitating the intelligent deconstruction of broad and complex tasks and sequential utilization of traffic foundation models for their gradual completion; 3) aiding human decision-making in traffic control through natural language dialogues; and 4) enabling interactive feedback and solicitation of revised outcomes. By seamlessly intertwining large language model and traffic expertise, TrafficGPT not only advances traffic management but also offers a novel approach to leveraging AI capabilities in this domain. The TrafficGPT demo can be found in https://github.com/lijlansg/TrafficGPT.git.

Deflation by Expenditure Components: A Harmless Adjustment?

AbstractWe investigate the effect that seemingly minor features of the implementation of cost‐of‐living adjustments have on the distribution of household expenditures, by developing an analytical framework that is consistent with standard consumer theory, and mindful of data limitations faced by practitioners. The main result is at odds with common sense: even when multiple price indices are available (e.g., a food Consumer Price Index and a non‐food one), it turns out that using a single price index (e.g., the total Consumer Price Index), to adjust the consumption aggregate is recommended. The practice of adjusting subcomponents of consumption separately (food with a food index and nonfood with a nonfood index) can lead to a systematic bias in the welfare measure, and consequently in poverty and inequality measures. Using Iran's 2019 Household Expenditures and Income Survey, we find that the bias manifests as a systematic underestimation of urban poverty and overestimation of rural poverty.

Perceptions from Member-Consumers of a University Community for Sustainable and Healthy Eating: Evidence from Greece

Healthy eating is a vital component of a sustainable daily life, especially after the COVID-19 pandemic. In this study, we investigated the perceptions and attitudes of the members of a Greek university community, especially the young members, on: (i) health itself, (ii) healthy eating, and (iii) healthy eating campaigns today. The research was conducted electronically in the last three months of 2023 via a questionnaire survey and 1046 member-consumers participated. Statistical analysis, including descriptive and cluster analysis to group respondents into homogenous segments, was performed by employing a one-way ANOVA. The highlights of the results indicate that consumers perceive physical and mental health and energy efficiency as health preconditions, while they perceive a balanced and sustainable diet as the main parameter of healthy eating. They are influenced mostly by doctors and health providers and use information mostly based on common sense and their upbringing for their healthy eating choices. The cluster analysis revealed two distinctive groups of consumers categorized by this study as the “approachables” (54.5%), affected by today’s sustainable knowledge and concepts on healthy eating, and the “conservatives” (45.5%), who are reluctant to accepted these as such.