General Intelligence Research Articles

Configured quantum reservoir computing for multi-task machine learning

Amidst the rapid advancements in experimental technology, noise-intermediate-scale quantum (NISQ) devices have become increasingly programmable, offering versatile opportunities to leverage quantum computational advantage. Here we explore the intricate dynamics of programmable NISQ devices for quantum reservoir computing. Using a genetic algorithm to configure the quantum reservoir dynamics, we systematically enhance the learning performance. Remarkably, a single configured quantum reservoir can simultaneously learn multiple tasks, including a synthetic oscillatory network of transcriptional regulators, chaotic motifs in gene regulatory networks, and the fractional-order Chua’s circuit. Our configured quantum reservoir computing yields highly precise predictions for these learning tasks, outperforming classical reservoir computing. We also test the configured quantum reservoir computing in foreign exchange (FX) market applications and demonstrate its capability to capture the stochastic evolution of the exchange rates with significantly greater accuracy than classical reservoir computing approaches. Through comparison with classical reservoir computing, we highlight the unique role of quantum coherence in the quantum reservoir, which underpins its exceptional learning performance. Our findings suggest the exciting potential of configured quantum reservoir computing for exploiting the quantum computation power of NISQ devices in developing artificial general intelligence.

A Bibliometric Review of Research on Intelligence in Leadership Studies

Intelligence has always been a key factor in people’s assessments of leaders and has featured on most profiles of leadership traits and competences. However, the disparate nature of research on intelligence in leadership studies means that it is time to take stock and to consider what has been learned. We do this by reporting a bibliometric analysis of published scholarly work on intelligence as it relates to leadership. The article begins with a short narrative review of intelligence in leadership studies before 1991, which demonstrates the long history of intelligence being conceptualized as IQ, general intelligence, wisdom, and intellect. This is followed with a bibliometric analysis of the topic from 1991 to 2022, which demonstrates how emotional intelligence has become the primary focus of leadership intelligence scholars. The implications of this shift of scholarly attention are discussed at the end of the article. In addition, we discuss the implications for implicit leadership theory (ILT) and demonstrate that the intelligence attribute in ILT frameworks is underdeveloped.

Rise of artificial general intelligence: risks and opportunities.

Artificial intelligence is making extraordinary progress with an unprecedented rate, reaching and surpassing human capabilities in many tasks previously considered unattainable by machines, as language translation, music composition, object detection, medical diagnoses, software programming, and many others. Some people are excited about these results, while others are raising serious concerns for possible negative impacts in our society. This article addresses several questions that are often raised about intelligent machines: Will machines ever surpass human intellectual capacities? What will happen next? What will be the impact in our society? What are the jobs that artificial intelligence puts at risk? Reasoning about these questions is of fundamental importance to predict possible future scenarios and prepare ourselves to face the consequences.

An Intelligent Robotic System Capable of Sensing and Describing Objects Based on Bimodal, Self‐Powered Flexible Sensors

AbstractThis study presents an intelligent soft robotic system capable of perceiving, describing, and sorting objects based on their physical properties. This work introduces a bimodal self‐powered flexible sensor (BSFS) based on the triboelectric nanogenerator and giant magnetoelastic effect. The BSFS features a simplified structure comprising a magnetoelastic conductive film and a packaged liquid metal coil. The BSFS can precisely detect and distinguish touchless and tactile models, with a response time of 10 ms. By seamlessly integrating the BSFSs into the soft fingers, this study realizes an anthropomorphic soft robotic hand with remarkable multimodal perception capabilities. The touchless signals provide valuable insights into object shape and material composition, while the tactile signals offer precise information regarding surface roughness. Utilizing a convolutional neural network (CNN), this study integrates all sensing information, resulting in an intelligent soft robotic system that accurately describes objects based on their physical properties, including materials, surface roughness, and shapes, with an accuracy rate of up to 97%. This study may lay a robotic foundation for the hardware of the general artificial intelligence with capacities to interpret and interact with the physical world, which also serves as an interface between artificial intelligence and soft robots.

From Machine Learning to Artificial General Intelligence: A Roadmap and Implications

The prospect of developing artificial general intelligence (AGI) with the same comprehensive capabilities as the human mind presents humanity both tremendous opportunities and dire risks. This paper explores the potential applications and implications of AGI across diverse domains including science, healthcare, education, security, and the economy. However, realizing AGI's benefits requires proactive alignment of its goals and values with those of humanity through responsible governance. As AGI approaches and possibly surpasses human-level intellectual abilities, we must grapple with complex ethical issues surrounding autonomy, consciousness, and disruptive societal impacts. The exact timeline for achieving AGI remains uncertain, but its emergence will likely stem from the convergence of advanced technologies like big data, neural networks, and quantum computing. Ultimately, the creation of AGI represents humanity's greatest opportunity to profoundly enhance flourishing, as well as our greatest challenge to steer its development toward benevolence rather than catastrophe. With sage preparation and foresight, AGI could usher in an unparalleled era of insight and invention for the betterment of all people. But without adequate safeguards and alignment, its disruptive potential could prove catastrophically destabilizing. This paper argues prudently governing the transition to AGI is essential for harnessing its transformative power to elevate rather than endanger our collective future.

Using ChatGPT in Education: Human Reflection on ChatGPT’s Self-Reflection

ChatGPT is a fascinating AI text generator tool. It is a language model developed by OpenAI, a research and deployment company with the mission, according to OpenAI’s website: “to ensure that artificial general intelligence benefits all of humanity”. ChatGPT is able to generate human-like texts. But how does it work? What about the quality of the texts it provides? And is it capable of being self-reflective? Information sources must be efficient, effective and reliable in education, in order to enhance students’ learning process. For this reason, we started a dialogue with ChatGPT-3 while using, among others, a SWOT analysis it generated about its own functioning in an educational setting. This enabled us, as human authors, to analyze the extent to which this AI system is able to practice self-reflection. Finally, the paper sketches implications for education and future research.

Cognitive modeling, ecological psychology, and musical improvisation.

Understanding novelty and improvisation in music requires gathering insight from a variety of disciplines. One fruitful path for synthesizing these insights is via modeling. As such, my aim in this paper is to start building a bridge between traditional cognitive models and contemporary embodied and ecological approaches to cognitive science. To achieve this task, I offer a perspective on a model that would combine elements of ecological psychology (especially affordances) and the Learning Intelligent Decision Agent (LIDA) cognitive architecture. Jeff Pressing's cognitive model of musical improvisation will also be a central link between these elements. While some overlap between these three areas already exists, there are several points of tension between them, notably concerning the nature of perception and the function of artificial general intelligence modeling. I thus aim to alleviate the most worrisome concerns here, introduce several future research questions, and conclude with several points on how my account is part of a general theory, rather than merely a redescription of existent work.

Neurocognitive Profiles in Adolescents With Postural Tachycardia Syndrome and Perceived Brain Fog: A Preliminary Report

BackgroundPostural tachycardia syndrome (POTS) is associated with complaints of cognitive and emotional difficulties that may contribute to severe functional disability. For high-achieving adolescents, these symptoms can result in decreased participation in school and extracurricular activities. There are very limited data comparing subjective symptom reports to neurocognitive profiles in adolescents presenting with POTS, “brain fog,” and cognitive difficulties. MethodsA review of medical records and neuropsychological data was conducted for six adolescents diagnosed with POTS at a pediatric neurology clinic. All patients had frequent symptoms of orthostatic intolerance for more than three months. There was heart rate increase of ≥40 beats per minute (bpm) within 10 minutes of active standing or head-up tilt test in five patients and 36 bpm in one patient, who was diagnosed with probable POTS. All were referred for neuropsychological evaluations due to reported debilitating cognitive problems and an inability to function in a regular academic setting. Patients underwent a six-hour neuropsychological evaluation utilizing standardized measures of cognitive and emotional functioning. Clinically reported symptoms included fatigue, poor concentration, and memory impairment as well as “brain fog.” ResultsSubjective complaints differed from patients’ performance on standardized neuropsychological measures. Patients performed in the average to superior range across measures of general intelligence, verbal and working memory, processing speed, and sustained attention. ConclusionsFurther research is needed to elucidate the basis for perceived “brain fog” and cognitive impairment in POTS, such as better understanding of patient and parental perceptions of initial medical symptoms and diagnosis as well as symptom amplification due to biopsychosocial processes.

Are intelligent people more likely to get vaccinated? The association between COVID-19 vaccine adherence and cognitive profiles

IntroductionSince vaccination adherence is crucial in reducing morbidity and mortality during a pandemic, we characterized the association between demographic, intelligence, and personal attributes and COVID-19 vaccination adherence among young adults. MethodsCohort study including vaccination data of 185,061 personnel, collected during 13 months of COVID-19 vaccination campaign, while a wide array of vaccination incentives were offered. The effect of demographic data (age, gender and socioeconomic status), military medical fitness – fit for combat service, administrative service, or unfit (volunteering), general intelligence score (GIS) and military social score (MSS) assessing social abilities, on vaccine adherence (allocating by IMOH guidelines) was examined. ResultsAdherent (vs. nonadherent) personnel presented higher GIS (mean 5.68 ± 1.84 vs. 4.72 ± 1.91) and MSS (median 26 (IQR 23–29) vs. 24 (IQR 19–26)), p < 0.001 for both. Higher intelligence was the strongest predictor for vaccine adherence (OR = 5.38, 95 %CI 5.11–5.67, p < 0.001). The probability for vaccine adherence increased in association with escalating GIS scores, with highest GIS females more likely to adhere to vaccination than same-level males (OR = 5.66, 95 %CI 5.09–6.28 vs. OR = 3.69, 95 %CI 3.45–3.94, respectively, p < 0.001 for both). Medically fit service-members were approximately three times as likely to be adherent than volunteering personnel (OR = 2.90 (95 %CI 2.65–3.17) for administrative and OR = 2.94 (95 %CI 2.70–3.21) for combative fitness, p < 0.001 for both). ConclusionsDuring a COVID-19 vaccination campaign, addressing vaccine hesitancy contributing factors and providing wide vaccine availability, GIS and physical fitness had the strongest association with vaccination adherence among young adults. When planning future vaccination campaigns, implementing these insights should be considered to improve adherence.

How does AI fit into the Management of Human Resources?

&#x0D; &#x0D; &#x0D; Objective: This study aims to comprehend the current state of integration between artificial intelligence (AI) and the human resources (HR) sector. Specifically, it investigates the implementation of AI in HR, explores the challenges associated with this integration, and examines potential hazards related to data usage, AI's perceived gimmickry, and algorithmic governance.&#x0D; Method: Employing a descriptive research design, this study relies on secondary data as no primary research was conducted. Information was collected from research papers, books, websites, blogs on human resources, and survey reports released by various research groups.&#x0D; Results: The analysis reveals that AI's adoption in the HR sector is still in its early stages despite significant advancements made by start-ups. Challenges stem from various factors, including data complexities, the risk of AI being seen as a mere gimmick, and concerns about algorithmic governance. The multifaceted nature of AI introduces diverse approaches and applications, from algorithms to deep learning and natural language processing. The study also differentiates between strong AI (general intelligence) and weak AI (problem-specific intelligence).&#x0D; The study emphasizes that HR is a pivotal element of any business, directly impacting employee well-being, communication, and productivity. The integration of AI has brought notable improvements by automating low-value HR tasks, freeing resources for strategic work. AI's capacity to analyze vast data volumes rapidly promises enhanced employee experiences across talent management and recruitment.&#x0D; Conclusions: In conclusion, AI's integration into the HR sector is still evolving, with both promise and challenges. The study underscores the need for addressing the complexities of data utilization, avoiding AI's reduction to mere gimmickry, and establishing responsible algorithmic governance. By understanding the nuances of AI integration in HR, organizations can leverage its potential to enhance productivity, communication, and employee experiences.&#x0D; &#x0D; &#x0D;

General intelligence, personality traits, and motivation as predictors of performance, potential, and rate of advancement of Royal Navy senior officers

ABSTRACT This paper assesses the impact of general intelligence, as well as specific personality traits, and aspects of motivation, on performance, potential, and advancement of senior leaders. A questionnaire survey was conducted on the full population of 381 senior officers in the Royal Navy with an 80% response rate. Performance, potential, and rate of advancement were established direct from the organization’s appraisal system; intelligence, personality traits and motivation were assessed, at the time of the study, using the Verify G+ Test, Occupational Personality Questionnaire, and Motivation Questionnaire. Findings suggest differences in motivation are more important than differences in general intelligence, or personality traits, in predicting assessed performance, potential within, and actual rate of advancement to, senior leadership positions. This is a rare example of a study into very senior leaders, validated against both formal appraisal data and actual rates of advancement. As a consequence of this study the Royal Navy has started to use psychometric-based assessments as part of the selection and development of its most Senior Officers.

PERSONAL POTENTIAL AS A PSYCHOLOGICAL AND PEDAGOGICAL PROBLEM

The article highlights the interpretations of the multifaceted concept of “personal potential” available in the modern scientific and pedagogical discourse. It is noted that the concept of “personal potential” primarily characterizes the internal physical and spiritual energy of a person, its active nature, focus on creative self-expression and self-realization. It is asserted that the basis of key approaches to determining personal potential lies in the understanding of the problem of personality, the development of which, starting from the last century, is being conducted until now in both Ukrainian and foreign scientific circles. The broad interpretation of the key word “potential” in the concept of “personal potential” is based on its consideration as a source and measure of a person’s capabilities and resources exploited to achieve a certain goal. Personal potential is made up of aptitudes, inclinations, interests, the desire to create something new, the manifestation of general intelligence, perseverance, purposefulness, determination, hard work, and the ability to develop personal strategies. It is emphasized that the potential should be considered in relation to the activity and interpreted not as a state of temporarily unused resources, but as an ever-increasing readiness to solve increasingly complex tasks that may arise before the individual. Personal potential is always a plane of personal growth with opportunities for self-actualization and self-improvement of the individual. The fenimenon under study is a dynamic, integrative quality of a person that characterizes the extent of his capabilities and resources for effective life activities, determines his readiness and ability for self-realization and self-improvement. Such types of human potential are outlined, such as: epistemological, axiological, creative, communicative, professional, spiritual potentials.

The Tong Test: Evaluating Artificial General Intelligence Through Dynamic Embodied Physical and Social Interactions

The release of the generative pre-trained transformer (GPT) series has brought artificial general intelligence (AGI) to the forefront of the artificial intelligence (AI) field once again. However, the questions of how to define and evaluate AGI remain unclear. This perspective article proposes that the evaluation of AGI should be rooted in dynamic embodied physical and social interactions (DEPSI). More specifically, we propose five critical characteristics to be considered as AGI benchmarks and suggest the Tong test as an AGI evaluation system. The Tong test describes a value- and ability-oriented testing system that delineates five levels of AGI milestones through a virtual environment with DEPSI, allowing for infinite task generation. We contrast the Tong test with classical AI testing systems in terms of various aspects and propose a systematic evaluation system to promote standardized, quantitative, and objective benchmarks and evaluation of AGI.

Inductive reasoning in humans and large language models

The impressive recent performance of large language models has led many to wonder to what extent they can serve as models of general intelligence or are similar to human cognition. We address this issue by applying GPT-3.5 and GPT-4 to a classic problem in human inductive reasoning known as property induction. Over two experiments, we elicit human judgments on a range of property induction tasks spanning multiple domains. Although GPT-3.5 struggles to capture many aspects of human behavior, GPT-4 is much more successful: for the most part, its performance qualitatively matches that of humans, and the only notable exception is its failure to capture the phenomenon of premise non-monotonicity. Our work demonstrates that property induction allows for interesting comparisons between human and machine intelligence and provides two large datasets that can serve as benchmarks for future work in this vein.

The association between intelligence and financial literacy: A conceptual and meta-analytic review

Financial literacy is positively associated with intelligence, with typically moderate to large effect sizes across studies. The magnitude of the effect, however, has not yet been estimated meta-analytically. Such results suggest financial literacy may be conceptualised as a possible cognitive ability within the Cattel-Horn-Carroll (CHC) model of cognitive abilities. Consequently, we present a psychometric meta-analysis that estimated the true score correlation between cognitive ability and financial literacy. We identified a large, positive correlation with general intelligence (r’ = .62; k = 64, N = 62,194). We also found that financial literacy shared a substantial amount of variance with quantitative knowledge (Gq; via numeracy; r’ = .69; k = 42, N = 35,611), comprehension knowledge (crystallised intelligence; Gc; r’ = .48; k = 14, N = 10,835), and fluid reasoning (fluid intelligence; Gf; r’ = .48; k =20, N = 15,101). Furthermore, meta-analytic structural equation modelling revealed Gq partially mediated the association between cognitive ability (excluding Gq) and financial literacy. Additionally, both Gc and Gq had significant direct effects on financial literacy, whereas the total effect of Gf on financial literacy was fully mediated by a combination of Gc and Gq. While the meta-analyses provide preliminary support for the potential inclusion of financial literacy as primarily a Gc or Gq ability within the CHC taxonomy (rather than Gf), the review revealed that very few studies employed comprehensive cognitive ability measures and/or psychometrically robust financial literacy tests. Consequently, the review highlighted the need for future factor analytic research to evaluate financial literacy as a candidate for inclusion in the CHC taxonomy.

Will AI avoid exploitation? Artificial general intelligence and expected utility theory

AbstractA simple argument suggests that we can fruitfully model advanced AI systems using expected utility theory. According to this argument, an agent will need to act as if maximising expected utility if they’re to avoid exploitation. Insofar as we should expect advanced AI to avoid exploitation, it follows that we should expected advanced AI to act as if maximising expected utility. I spell out this argument more carefully and demonstrate that it fails, but show that the manner of its failure is instructive: in exploring the argument, we gain insight into how to model advanced AI systems.

The Application of Text Mining Technology in Business Management—Take Hotel Management as an Example

In recent years, the development of the information industry has led to the rapid rise of data mining, and in the face of the trend of data mining development, the field of data mining has become a focal point of concern for various industries. As a very customer-focused service industry, the hospitality industry is imperative to popularize and intelligently integrate text mining into management in the context of rising human resource costs and the general intelligence of all industries. In this paper, the application of text mining technology in business management is explored, using hotel management as an example. The Porter's Five Forces model, the SWOT model are used to analyze the importance of unstructured data such as customer reviews and the great role of text analytics in the internal and external management of hotels. The recommendations for the integration of text mining and hotel management are proposed, suggesting that text mining should be commonly used in hotel management and recommending that managers adopt A small amount of manpower and a large amount of text mining to overcome the drawbacks of text mining and improve hotel operations.

Многостороннее исследование социального интеллекта и сопутствующих личностных характеристик студента поколения Z

The study of the phenomenon of "social intelligence" in foreign and domestic psychology was discovered unexpectedly. In a generalized view, the concept under study is considered as a complex structural formation, including a set of abilities aimed at establishing interpersonal relationships; as a personal formation, regardless of general intelligence and associated with a specific activity. Recently, there has been an opinion about social intelligence as a clear and compatible group of mental abilities associated with the processing of social information, i.e. evaluating the level of adequacy and effectiveness of interaction. It should be noted that a special explanation is required of the relationship of intelligence as a cognitive ability linked to personality traits; intelligence and propensity to adapt to new expectations and events of the wedding, as well as the connection of intelligence, processes of self-regulation and control of the locus.&#x0D; Separately, it is necessary to theoretically and applied comprehend the specific features of the student's generation when designing the conditions for the development of intelligence in the conditions of the educational process of higher education.

Artificial General Intelligence (AGI) and Its Implications For Contract Law

Artificial General Intelligence (AGI) and Its Implications For Contract Law

Prospective research in the field of teaching creative skills to artificial intelligence

The research relevance is determined by the importance of a thorough study of methods, schemes and models used by artificial intelligence to mechanise creativity in modern conditions of active technological development. The study aims to analyse the main processes taking place in modern art in connection with active technologization of work processes, to identify the leading concepts regarding the possibility of creating machine art in the future, etc. The employed methods are theoretical, such as analysis, systematisation, generalisation, etc., for studying key problems and further development of creativity based on artificial intelligence. The study examines in detail the main developments of Artificial General Intelligence and Artificial Narrow Intelligence, in particular the achievements of Generative adversarial networks and Creative adversarial networks. Artificial intelligence-generated art demonstrates the remarkable capabilities of technologies. The evolving artificial intelligence in the arts introduces “digital art”. Generative Adversarial Networks are used as a foundational tool for artists who use digital methods and texture generation to create unique compositions. Furthermore, sculptors collaborate with artificial intelligence tools to convert drawings into 3D models or transform historical art databases into sculptures. Creative thinking, a hallmark of human intelligence, is determined as artificial intelligence’s ability to generate new and original ideas. The development of emotional intelligence in artificial intelligence enables empathetic responses and the identification of human emotions through voice and facial expressions. The issues of authorised internationality, awareness of the creative process, psychological foundations of artificial empathy and emotional intelligence define the prospects for the development of neuroscience. Challenges persist in defining creativity, authorship, and legal aspects of artificial intelligence-generated art. The study materials may be useful for artists, art educators, technologists, and researchers interested in the intersection of technology and art, legal professionals (especially intellectual property law), and individuals involved in artificial intelligence development may find these findings valuable