Human Intelligence Research Articles

THE ROLE OF AI AND WEB 2.0 TOOLS IN DEVELOPING PRAGMATIC COMPETENCE OF L2 ENGLISH LEARNERS

Artificial Intelligence (AI) and web 2.0 tools has transformed various sectors, like healthcare and finance, by imitating human intelligence and decision-making. However, AI still struggles with understanding and effectively participating in human communication, which is a crucial challenge. Pragmalinguistics, a branch of linguistics focused on the relationship between language and context, addresses this issue. It examines pragmatic aspects such as speaker intention, context, and shared knowledge to grasp the intended meaning behind communication. By integrating pragmalinguistics into AI systems, researchers and developers aim to narrow the gap between machines and human communication. This article explores how AI and web 2.0tools are helpful in pragmalinguistics collaborate to improve AI capabilities.

Inovasi Perencanaan Keuangan menggunakan Artificial Intelligence (AI) Click Up pada UMKM Chibi-chibi Mochi

This community service aims to innovate Artificial Intelligence (AI) financial planning using the ClickUp application to improve the quality of project management, especially budgeting, thereby increasing efficiency, productivity, and better decision-making so that these MSMEs can be highly competitive in the fintech era. Artificial intelligence is a system in a machine that imitates the way humans think and act (human intelligence). One of a computer science related to the development that can imitate human expertise in carrying out certain tasks is Artificial Intelligence (AI) (Nurcholis, 2023). The program carried out is training and mentoring so that financial planning is more innovative, economical, practical, easily accessible, and has minimal errors. The problem faced by business actors is financial planning that has not been implemented properly so business targets and income targets are often not achieved. This has an impact on the sustainability of the Chibi-Chibi Mochi MSME business in the era of competition. The solution to the problem is that the community service team will provide training and mentoring on financial planning innovation using Artificial Intelligence (AI) ClickUp. The output targets to be achieved are in the form of journal publications and increasing the understanding and skills of business actors.

Beyond the Courts: Artificial Intelligence as a Catalyst for Change in Justice Administration

In the context of technological advances, the concept of digital justice is emerging, an extra-judicial sphere that uses technologies such as artificial intelligence to address controversial situations through physical assistants or even robots, if the litigant so wishes. Thus, while AI is effective in resolving simple disputes without human intervention, even UNESCO warns against its exclusivity in more complicated cases. From this perspective, through a qualitative approach and literature review, this research focused on examining the benefits and limitations of AI in the administration of justice. The review of the academic literature reveals that this technology facilitates the functions performed by judges and lawyers in controversial situations. The studies, however, point to the importance of using human intelligence in law making and more general judicial processes. In conclusion, AI improves the efficiency of the administration of justice; however, its place in judicial operations and process should only be complementary to the use of human intervention. This action maintains fairness and considers the ethical point at stake, reaffirms the existence of some irreplaceable human capabilities in the judicial process.

‘Shakespeare Never Said That’: The Internet’s Thousand Hamlets

ABSTRACT This article synthesises the history of rhetorical commonplacing with the modern digital humanities classroom by examining how university students use references to William Shakespeare to access their identities as individual writers. As students take to the web, combing through online compilations of notable literary quotations, discussion forums, and social media pages – appropriating the language they deem useful to their writing – search engine algorithms do the work of narrowing down and amplifying authority. The result is a hybrid authorship between the individual, subjective identity of each student and the aggregation of all those human and nonhuman intelligences circulating the web. This article orients its discussion around a frequently misattributed quotation about William Shakespeare’s Hamlet that circulates via the Chinese search engine Baidu. This discussion ultimately leads to an argument about the dangers of misinformation, and how the logic of search engine algorithms reveals what is most empowering but also obscuring about a New Media Shakespeare – that is, a Shakespeare whose limits are tested and redefined by sheer masses of users on the web.

Adapting to Diversity: Leveraging AI for ESL Learning Enhancement

Recent years have seen tremendous advancements in artificial intelligence, which is now pervasive in many aspects of society. Its ability to emulate human intelligence sets it apart. Artificial Intelligence is being explored more and more in the field of education as a possible aid to enhance language acquisition, particularly in the development of students' communication skills. Artificial Intelligence possesses the capability to deliver dynamic, adaptable, and personalized learning experiences that are suited to individual student needs and interests. The purpose of this research is to identify each student's preferred method of learning and adapt the language-learning process to meet their needs. This suggests that each student can focus on the areas in which they require the most assistance and work at their own pace while studying. The important part that social interactions, group projects, and cognitive development play. According to this viewpoint, less skilled students participate in cooperative learning activities with more skilled people, such as teachers or, in modern environments, computer programs. In addition, the enormous volumes of data that AI can analyse and draw conclusions from can be utilized to address the varied language and cultural backgrounds of students. It also shows how important it is to adapt lessons to meet the different needs of English language learners. Overall, these results show how important it is to change the way we teach to fit the needs of different groups of people and to use new technologies like AI to make learning more specific and help students do better in ESL classes.

Human natural and artificial intelligence collaboration in urban design: a case study of Indonesia’s new capital city

Human natural and artificial intelligence collaboration in urban design: a case study of Indonesia’s new capital city

THEORETICAL STUDY OF INDIVIDUAL PSYCHOLOGICAL ASPECTS OF INTERNET ADDICTED PERSONS

People's interest in information technology and its activities directly affect the behavioral structures, emotional sphere and nervous system of a person in connection with his time standards. In the studies of scientists of the world, the influence of the internet and the problems of emotional intelligence on the emotional sphere of a person in a virtual environment from various scientific and theoretical points of view have been considered, and the empirical parts of the above studies have been covered. in our work. People now spend more of their free time watching videos, playing games, shopping on the internet and providing various services on the internet than interacting with people, which leads to the fact that interpersonal communication goes into the virtual environment. As a result, the ability to control time and behavior in the virtual world decreases. During stay in the online environment, the emotional sphere of a person is stimulated, and the attitude towards the environment changes. Human emotional intelligence decreases. In the real world, the ability to understand people's feelings, reduce the ability to control their expressions, cyber addiction, acceptance of the culture of the virtual environment acquire negative sides, as a result, their emotional intelligence decreases. This article examines the problem of internet addiction, its significance today and the psychological aspects of its impact on internet users, and also analyzes the socio-psychological factors that contribute to the formation of internet addiction in the context of research by scientists. A theoretical analysis of the individual psychological aspects of people with internet addiction was also conducted. Research object: 206 teenagers, 1st-4th year students studying at the Jizzakh branch of the National University of Uzbekistan. Average age: 20.7 years. Results: A group of teenagers prone to internet addiction are less aware of the place and place of using speech in interpersonal communication, which is an activity learned earlier in ontogenesis, and the opposite is observed in those prone to Internet addiction. Such people often make mistakes in interpreting the words of the interlocutor. The emotional intelligence of a teenager addicted to the Internet is significantly lower than the emotional intelligence of a teenager who uses the Internet less.

Impact of Artificial Intelligence in Endodontics: Precision, Predictions, and Prospects.

Artificial intelligence (AI) has become increasingly prevalent and significant across many industries, including the dental field. AI has shown accuracy and precision in detecting, evaluating, and predicting diseases. It can imitate human intelligence to carry out sophisticated predictions and decision-making in the health-care industry, especially in endodontics. AI models have demonstrated a wide range of applications in the field of endodontics. These include examining the anatomy of the root canal system, predicting the survival of dental pulp stem cells, gauging working lengths, identifying per apical lesions and root fractures, and predicting the outcome of retreatment treatments. Future uses of this technology were discussed in terms of robotic endodontic surgery, drug-drug interactions, patient care, scheduling, and prognostic diagnosis.

Fairness in AI for healthcare

Artificial intelligence (AI) is a technology that enables computers to simulate human intelligence and has the potential to improve healthcare in a multitude of ways. However, there are also possibilities that it may continue, or exacerbate, current disparities. We discuss the problem of bias in healthcare and AI, and go on to highlight some of the ongoing and future solutions that are being researched in the area.

Cognitive evaluation based on regression and eye-tracking for layout on human–computer multi-interface

ABSTRACT The human–computer cooperation process guided by natural interaction, intelligent interaction, and human–computer integration is gradually becoming a new trend in human–computer interaction. Cooperative scenarios of human–computer interaction systems often contain multi-interface and multi-device results in edges often interrupt the cognitive ergonomics of interface layout. This research takes typical areas as an example to establish a stepwise regression model to predict reaction time at an arbitrary position on the left interface. It uses a foveal region to position the starting point of attention and a parafoveal region to calculate the radius of each objective area, and design 10 similar tasks to analyze eye-tracking indexes through physiological assessment. Unlike fixed thinking such as spatial proximity on multi-interfaces, this research summarises cognitive features of layout based on the positive and negative effects of edge impact through eye-tracking analysis. It analyzes cognition including input, process, and output in human–computer cooperation from human intelligence and artificial intelligence respectively, and visualises the mapping relationship between these indexes and specific stages of cognition. Besides, the quantitative evaluation of the regression equation and qualitative analysis of the eye-tracking indexes provide a reference for other interfaces around the front interface.

Complex Pythagorean neutrosophic normal interval-valued set with an aggregation operators using score values

The complex Pythagorean neutrosophic normal interval-valued set approach solves the multiple-attribute decision-making problem. We introduce the new concepts such as complex Pythagorean neutrosophic normal interval-valued weighted averaging, complex Pythagorean neutrosophic normal interval-valued weighted geometric, complex generalized Pythagorean neutrosophic normal interval-valued weighted averaging and complex generalized Pythagorean neutrosophic normal interval-valued weighted geometric operator. We demonstrate that complex Pythagorean neutrosophic normal interval-valued set satisfy algebraic structures such as associative, idempotent, bounded, commutative and monotonic properties. Additionally, we develop algorithm and flowchart that solve problems using these operators. Examples of using enhanced score values and accuracy values in real-world environments are provided in this paper. Artificial intelligence refers to the simulation or approximation of human intelligence in machines. Its goals include computer enhanced learning, reasoning and perception. Artificial intelligence is being used today across different industries, from finance to healthcare. Agricultural robots have been described as being highly dependent on computer and machine tool technology. Four factors can be used to evaluate the quality of a robotics system: the controller’s sophistication, the software efficiency, the maximum moment of inertia, and the manufacturer’s reliability. The best alternative can be determined by comparing expert opinions to the criteria. Therefore, the parameter ∇ has a very significant impact on the results of the model. This comparison aims to prove that the models under consideration are valid and valuable by comparing them with the available and proposed models. In conclusion, the value of ∇ significantly impacts the model performance. Based on the comparison and sensitivity analysis, we conclude that the proposed aggregation operation is superior and more reliable than the existing one. The criteria were compared to the most appropriate options based on expert assessments.

Evidence of interrelated cognitive-like capabilities in large language models: Indications of artificial general intelligence or achievement?

Large language models (LLMs) are advanced artificial intelligence (AI) systems that can perform a variety of tasks commonly found in human intelligence tests, such as defining words, performing calculations, and engaging in verbal reasoning. There are also substantial individual differences in LLM capacities. Given the consistent observation of a positive manifold and general intelligence factor in human samples, along with group-level factors (e.g., crystallised intelligence), we hypothesized that LLM test scores may also exhibit positive inter-correlations, which could potentially give rise to an artificial general ability (AGA) factor and one or more group-level factors. Based on a sample of 591 LLMs and scores from 12 tests aligned with fluid reasoning (Gf), domain-specific knowledge (Gkn), reading/writing (Grw), and quantitative knowledge (Gq), we found strong empirical evidence for a positive manifold and a general factor of ability. Additionally, we identified a combined Gkn/Grw group-level factor. Finally, the number of LLM parameters correlated positively with both general factor of ability and Gkn/Grw factor scores, although the effects showed diminishing returns. We interpreted our results to suggest that LLMs, like human cognitive abilities, may share a common underlying efficiency in processing information and solving problems, though whether LLMs manifest primarily achievement/expertise rather than intelligence remains to be determined. Finally, while models with greater numbers of parameters exhibit greater general cognitive-like abilities, akin to the connection between greater neuronal density and human general intelligence, other characteristics must also be involved.

Human–artificial intellectual capital…beyond a fragmented perspective

PurposeHuman and artificial intelligence has often been examined through competitive and oppositional lenses, which may no longer suffice in modern digital and knowledge-based societies. This paper advocates for a holistic perspective by integrating human and artificial intelligence within the conceptual framework of intellectual capital (IC).Design/methodology/approachEmploying a deductive approach rooted in systems theory, this study reinterprets established dimensions of IC for the era of artificial intelligence.FindingsDrawing inspiration from the Information Variety Model and the 4C Curve Model, both developed within the research framework of the Viable Systems Approach, a conceptual framework is proposed to transcend fragmented perspectives. It aims to provide researchers and practitioners with a comprehensive understanding of human–artificial intelligence relations within the realm of IC.Originality/valueThis paper contributes to the ongoing discourse on the potential evolution of IC in the era of artificial intelligence by presenting a multidisciplinary framework that challenges reductionist perspectives. It underscores the importance of systems thinking in reframing, analyzing and discussing key dimensions of IC in the context of the artificial intelligence era.

From Optimism to Concern: Unveiling Sentiments and Perceptions Surrounding ChatGPT on Twitter

Artificial intelligence (AI) technologies, as a product of processes aimed at imitating human intelligence through computers and software, affect our daily lives in various aspects, including cultural, technological, and economic. The advent of ChatGPT, developed by OpenAI, signifies a pivotal AI advancement in human language comprehension and generation, heralding profound implications across societal, economic, and cultural dimensions. However, a notable gap exists in scholarly literature concerning the examination of perceptions and discussions surrounding ChatGPT. This study aims to address this gap by analyzing Twitter conversations, comprising 1.1 million tweets containing “ChatGPT” or “#ChatGPT” between December 1 2022 and June 1 2023, with geolocation data. Employing a text as data approach encompassing text, sentiment, and semantic network analyses, sentiment polarity and lexical patterns were explained, while semantic network analysis revealed central expressions and prominent themes in Twitter discussions. The study highlights the social effects of AI technologies from the perspective of Twitter users and reveals the sentimental tendency and themes in tweets with geographical and economic dimensions. The findings reflect the prevalence of positive sentiment and hype toward ChatGPT while there are also concerns regarding privacy, cybersecurity, and misuse of AI tools. More importantly, content generation, technical aspects, business applications, educational use, and competitors are among the main themes of ChatGPT-related discussions on Twitter.

Nature as Event: A Study on John Dewey’s Naturalism

John Dewey’s naturalism requires viewing nature and experience from the perspective of holism, emphasising the continuity between these two. To Dewey, nature is not a fixed entity, but an event in an ongoing process of unfolding. The temporality of an event can meet Dewey’s requirement of constructing a philosophical notion about change and development. The event has a relatively stable structure. The continuity between living things and non-living things becomes possible because of the characteristic transactions of events, and experience thus becomes something emergent in nature and actively intervenes in its unfolding. The emergence of human intelligence and the application of language has lifted nature to a controllable and operable plane, making experience a crucial guide for the unfolding of nature.

Through tensions to identity-based motivations: Exploring teacher professional identity in Artificial Intelligence-enhanced teacher training

This mixed-methods case study explores teacher professional identity (TPI) tensions and motivations for Artificial Intelligence (AI) integration in teaching within a Chinese university-level AI-enhanced teacher training programme. Surveys were completed by 216 attendees, followed by in-depth qualitative analysis of 15 selected teachers. The study reveals TPI groupness-individuality, humanity-technology, and continuity-openness tensions. Three conceptual models are introduced: Human Intelligence and AI as Navigator, Collaborator, and Inventor. It underscores the critical role of tailored AI-enhanced teacher training in harmonising educators’ diverse identities and motivations with technological advancements, signalling a strategic approach for effective AI integration in global teacher education.

AGENDA: Predicting Trip Purposes with A New Graph Embedding Network and Active Domain Adaptation

Trip purpose is a meaningful aspect of travel behaviour for the understanding of urban mobility. However, it is non-trivial to automatically obtain trip purposes. On one hand, trip purposes are naturally diverse and complicated, but the available predictive data sources are limited in real-world scenarios. On the other hand, since trip purpose labeling is costly and the development levels of cities are unbalanced, it is infeasible to access large-scale labeled data in less developed cities to train advanced prediction models. To narrow the gaps, this article presents A new Graph Embedding Network and active Domain Adaptation based framework (AGENDA) that only requires open data sources and is capable of predicting in both label-rich cities and label-scarce cities. Specifically, in label-rich source cities, we first use the vehicle’s GPS trajectory and open POI check-ins to augment trip contexts. Then we establish a supervised graph embedding network with two attention mechanisms to extract the passenger’s latent activity semantics and a classifier to predict trip purpose. To enable the prediction in label-scarce target cities, we further devise an active domain adaptation framework, in which adversarial domain adaptation is used to transfer the source-learned knowledge, and active learning is used to integrate human intelligence in the model training. A group of experiments are conducted with real-world datasets in Beijing and Shanghai. Evaluation results demonstrate that the proposed framework significantly outperforms existing trip purpose prediction algorithms, and could make accurate trip purpose prediction in label-scarce cities with much fewer labeling efforts.

Brain-consistent architecture for imagination.

Imagination represents a pivotal capability of human intelligence. To develop human-like artificial intelligence, uncovering the computational architecture pertinent to imaginative capabilities through reverse engineering the brain's computational functions is essential. The existing Structure-Constrained Interface Decomposition (SCID) method, leverages the anatomical structure of the brain to extract computational architecture. However, its efficacy is limited to narrow brain regions, making it unsuitable for realizing the function of imagination, which involves diverse brain areas such as the neocortex, basal ganglia, thalamus, and hippocampus. In this study, we proposed the Function-Oriented SCID method, an advancement over the existing SCID method, comprising four steps designed for reverse engineering broader brain areas. This method was applied to the brain's imaginative capabilities to design a hypothetical computational architecture. The implementation began with defining the human imaginative ability that we aspire to simulate. Subsequently, six critical requirements necessary for actualizing the defined imagination were identified. Constraints were established considering the unique representational capacity and the singularity of the neocortex's modes, a distributed memory structure responsible for executing imaginative functions. In line with these constraints, we developed five distinct functions to fulfill the requirements. We allocated specific components for each function, followed by an architectural proposal aligning each component with a corresponding brain organ. In the proposed architecture, the distributed memory component, associated with the neocortex, realizes the representation and execution function; the imaginary zone maker component, associated with the claustrum, accomplishes the dynamic-zone partitioning function; the routing conductor component, linked with the complex of thalamus and basal ganglia, performs the manipulation function; the mode memory component, related to the specific agranular neocortical area executes the mode maintenance function; and the recorder component, affiliated with the hippocampal formation, handles the history management function. Thus, we have provided a fundamental cognitive architecture of the brain that comprehensively covers the brain's imaginative capacities.

The Uses of Artificial Intelligence in Rheumatology

Artificial intelligence refers to computers performing tasks typically linked to human intelligence, such as recognizing speech, understanding language, identifying objects, and translating between languages. These tasks often involve learning, allowing algorithms to adjust to the data they receive. The integration of AI in medicine, particularly, clinical practice such as rheumatology has revolutionized medical practice in terms of precision in diagnosis, and accuracy in treatment. The main objective of this study was to review the updates of the literature regarding the use of AI in rheumatology. The researcher reviewed the main research engines to collect cited literature. The results of this study confirmed the importance of the integration of AI into medicine to offer precision in diagnosis, cost-effectiveness, and therapeutic accuracy.

Information Professionals’ Metaphorical Perceptions of Artificial Intelligence Concept

This study examines the metaphors used by 66 information professionals in Türkiye to conceptualize artificial intelligence (AI). Through qualitative metaphor analysis, rich insights emerged on perceptions of AI’s nature, functioning, relationships with humans, roles, and societal impacts. Some of the metaphors used are child, human, artist, human intelligence, robot, assistant, doctor, weapon, terminator, something scary, closed box, black hole, Pandora’s box, etc. Multiple, often contradictory metaphors like “child” and “uncontrollable power” indicate AI is viewed in a multidimensional way, evoking both promise and concern. Key findings suggest information professionals appreciate AI’s transformative potential in enhancing services but also harbor anxieties related to human relevance, technocracy, and social issues like privacy. Understanding these complex cognitive and emotional orientations can facilitate responsible AI adoption to augment information services. Gesturing at AI’s multifaceted connotations also foregrounds communication challenges complicating public debate and policymaking on emerging technologies. The value of this study lies in surfacing the nuanced perspectives of a stakeholder group positioned to mediate public understanding and direct integration of AI in information services. Mapping information professionals’ rich construals of AI also highlights the need for public communication attuned to metaphorical reasoning around new technologies.