General Artificial Intelligence in Self-developing Reflective-Active Environments

Recent technological advances are challenging established conventions for creating, managing and communicating expertise. Technology is central to many occupations—social communities comprised of knowledge workers who act as gatekeepers to expert domains. The creative industries are full of such communities experiencing transformation in their work due to the increasing accessibility and computing power of artificial intelligence (AI). Nonetheless, the specificity of traditional AI technology has, hitherto, not heavily impacted creative workers. That was until the latest development in AI. Generative AI is different. Unlike traditional AI—designed to perform specific tasks—generative AI has a general intelligence with broad capabilities that can imitate inherent human knowledge and expertise. This research examines the dynamic pace of change and capability brought by generative AI by drawing on first-hand accounts from 100 in-depth interviews with design experts. An affordances lens is employed to examine and explain the space between designers and generative AI to understand the acceptance and use of the technology and its impact on their expertise and daily work. The proximity of expertise is introduced to theorise when, where, and how designers use generative AI in their daily work and to help predict its acceptance and use. It also provides a fertile foundation for future enquiry into creating, managing, and communicating expertise.

This paper traces the evolutionary trajectory of artificial intelligence from narrow artificial intelligence (ANI) through artificial general intelligence (AGI) to potential artificial superintelligence (ASI), critically examining the technological singularity as a transformative inflection point in technological and human development. The analysis covers key technical milestones required for this progression, including advances in machine learning architectures, knowledge representation, and cognitive architectures. Drawing from recent developments in neuroscience and deep learning, the paper proposes a framework for understanding the qualitative differences between these three stages of artificial intelligence development. The paper addresses critical questions about intelligence, consciousness and the challenges of maintaining human agency in a post-singularity world. Novel perspectives on safety mechanisms and technical guidelines necessary for managing the transition between these developmental stages are presented. The analysis acknowledges the uncertainty surrounding the path to AGI and ASI, highlighting the complex and unpredictable nature of advanced artificial intelligence development. The paper concludes by exploring potential trajectories of recursive self-improvement in artificial systems and their theoretical implications for the future of machine cognition.

This paper explains the ethical implications of artificial intelligence (AI) development towards achieving the level of artificial general intelligence (AGI) and analyzes the need for its social control. With the acceleration and intensification of AI growth and development, especially with the ongoing AI race, the transition from narrow AI to AGI becomes certain. The achievement of generative AI, which climaxes with chatbots (such as ChatGPT and others), transforms AI into a machine capable of creation. Although this AI application still appears relatively limited by algorithms, its learning ability is remarkable, and continuous advancements and the launch of increasingly sophisticated versions bring it ever closer to the AGI model. Each day brings us closer to that moment, which will signify AI’s transition from narrow AI to AGI. Unlike narrow AI, AGI deeply delves into the realm of ethics, and interpersonal and social relationships. Regulating AI-related policy and legally controlling AI represents one of the most serious and complex issues. In recent years, the community, led by corporate executives developing AI, prominent experts, researchers, scientists, writers, and other stakeholders, has made significant steps towards raising public awareness of the risks posed by advanced AI and making decisions, initiatives, and measures for monitoring, analyzing, and socially controlling the use of AI.

The present study investigates the potential impact of artificial intelligence (AI) on the future trajectory of human civilization. It focuses on topics such as super-exponential growth, the potential emergence of a galactic civilization, and the associated "doom" hazards. A significant advancement in machine intelligence with human-like consciousness, strong artificial intelligence (AI), also known as artificial general intelligence (AGI), creates new opportunities and capacities. There's growing anxiety about the risk that weak AI will eventually become strong AI. Every year, new transformer models that are more like human interactions are being created, and we have already witnessed some indications of AGI. It is anticipated that AI will reach a "singularity" and advance on its own without assistance from humans. This thesis explores the theoretical and practical foundations, model building blocks, development processes, challenges, and ethical issues surrounding the creation of Consciousness AI (AGI). This paper examines the meaning of the term "technological singularity," the various types of singularities that have no point of return idea, the philosophical risks associated with the development of AI, and the implications of AI singularity for monetary theory and the new economic order. As a new perspective on the deployment of ethical AI in the face of tremendous technological advancements, the study not only contributes to the theoretical discourse but also explores the possible practical implications of AI on our shared future. Several obstacles to AI advancement are covered in the paper, along with prospective directions for future research.

This study investigates how generative artificial intelligence (AI) could influence the media environment of that country. Given their prevalence in the industry, it seeks to uncover how general process of national advancement is supported by AI-powered technologies in media content generation, distribution, and personalisation. The research gathers data from media professionals, techies, and communication academics in major Chinese cities all around using properly crafted questionnaires in a quantitative manner. One examined the interactions of AI-driven media innovation, modernising pace, and consequences of national development using statistical methods like structural equation modelling and regression analysis. Linking modernism with national development projects, the indices of generative AI used in media show a definite positive link with their influence. Generative AI is becoming more and more important for China's attempts to modernise its communication infrastructure and undergo digital transformation, thereby enhancing the nation's cultural impact, technical capacity, and media creation. Modernism approaches enhance the possibilities presented by AI in media; this research reveals more dynamic storylines, audience interaction feasible, and global outreach. Every one of these components helps to forward objectives for national growth. Regarding developing plans to mix AI with goals for sustainable development, the findings give legislators, media outlets, and AI developers’ useful insights. This study offers a structure for further studies in new media technologies and national transformation by means of an experimental interaction between generative AI and national development seen from the perspective of modernism. It opens the conversation on the social opportunities AI offers.

Building a human-like integrative artificial cognitive system, that is, an artificial general intelligence (AGI), is the holy grail of the artificial intelligence (AI) field. Furthermore, a computational model that enables an artificial system to achieve cognitive development will be an excellent reference for brain and cognitive science. This paper describes an approach to develop a cognitive architecture by integrating elemental cognitive modules to enable the training of the modules as a whole. This approach is based on two ideas: (1) brain-inspired AI, learning human brain architecture to build human-level intelligence, and (2) a probabilistic generative model (PGM)-based cognitive architecture to develop a cognitive system for developmental robots by integrating PGMs. The proposed development framework is called a whole brain PGM (WB-PGM), which differs fundamentally from existing cognitive architectures in that it can learn continuously through a system based on sensory-motor information.In this paper, we describe the rationale for WB-PGM, the current status of PGM-based elemental cognitive modules, their relationship with the human brain, the approach to the integration of the cognitive modules, and future challenges. Our findings can serve as a reference for brain studies. As PGMs describe explicit informational relationships between variables, WB-PGM provides interpretable guidance from computational sciences to brain science. By providing such information, researchers in neuroscience can provide feedback to researchers in AI and robotics on what the current models lack with reference to the brain. Further, it can facilitate collaboration among researchers in neuro-cognitive sciences as well as AI and robotics.

Artificial General Intelligence is the idea that someday an hypothetical agent will arise from artificial intelligence (AI) progresses, and will surpass by far the brightest and most gifted human minds. This idea has been around since the early development of AI. Since then, scenarios on how such AI may behave towards humans have been the subject of many fictional and research works. This paper analyzes the current state of artificial intelligence progresses, and how the current AI race with the ever faster release of impressive new AI methods (that can deceive humans, outperform them at tasks we thought impossible to tackle by AI a mere decade ago, and that disrupt the job market) have raised concerns that Artificial General Intelligence (AGI) might be coming faster that we thought. In particular, we focus on 3 specific families of modern AIs to develop the idea that deep neural networks, which are the current backbone of nearly all artificial intelligence methods, are poor candidates for any AGI to arise due to their many limitations, and therefore that any threat coming from the recent AI race does not lie in AGI but in the limitations, uses, and lack of regulations of our current models and algorithms. This article appears in the AI & Society track.

Increasingly artificial intelligence (AI) has been cast in "god-like" roles (to name a few: film industry - Matrix, The Creator, Mission Impossible, Foundation, Dune etc.; literature - Children of Time, Permutation City, Neuromancer, I Have no Mouth and I Must Scream, Alphaville etc.). This trend has accelerated with the advent of sophisticated Large Language Models such as ChatGPT. For this phenomenon, where AI is perceived as divine, we use the term GPTheology, where ChatGPT and other AI models are treated as potential oracles of a semi-divine nature. This paper explores the emergence of GPTheology as a form of techno-religion, examining how narratives around AI echo traditional religious constructs. We draw on community narratives from online forums - Reddit - and recent projects - AI-powered Mazu Statue in Malaysia (Lu, 2025); "ShamAIn" Project in Korea (He-rim, 2025); AI Jesus in a Swiss Church (Kennedy, 2024). These examples show striking similarities to technological notions of the Singularity and the development of Artificial General Intelligence (AGI). Additionally, we analyse how daily interactions with AI are acquiring ritualistic associations and how AI-centric ideologies clash with or are integrated into established religions. This study uses a dataset of Reddit posts discussing AI to identify recurring themes of salvation, prophecy, and demonization surrounding AI. Our findings suggest that new belief systems are developing around AI, and this carries both philosophical and sociotechnical implications. Our paper critically analyses the benefits and dangers, as well as the social, political and ethical challenges of this development. This transdisciplinary inquiry highlights how AI and religion are increasingly intertwined, prompting necessary questions about humanity's relationship with its creations and the future of belief.

The amazing technological developments in Artificial Intelligence (AI) cast important questions for all scholars. Prominently, can AI replace human beings in all fields, which might be a double-edged weapon? Because, from one hand, it will have positive sides. For example, it will give more accurate results, increase production, save time and energy, make better use of natural resources, and find creative solutions for problems…etc. But, if it replaced human beings, AI will also have negative effects on them; varying from the socio-economic effects to the psychological and/or even the political ones. The control of the machines on most (or even all) fields of life may be startling. Moreover, can AI be misused by evil persons or competitive parties? These persons or parties may easily forge photos, videos, voices of their competitors. They are able to exploit fake documentations against their enemies using the powerful intelligent abilities of AI programmes. Hence, can mankind be ready to face AI future consequences? Will it be smarter than humans because of its surprising capabilities for quick self-learning? One of the astonishing developments of AI is Generative Artificial Intelligence (GAI), which has several language models. These models can do highly innovative tasks like writing neat poems of different styles, about numerous subjects, or from various literary ages. This complicated task poses new significant questions: Will GAI replace the poets? Will it put an end to human innovation? Yet, other sides of the matter make it dubious and controversial; as poetry mainly is the product of human emotions, feelings, and experiences. Thus, this research paper tries to find answers to these questions, differentiate between human-produced poetry and that generated by AI models, trace the effect of the GAI models on the production of poetry, and show how GAI turned from an imitator to an author. An example of this kind of poetry is the collection entitled: I Am Code: An Artificial Intelligence Speaks (2023). Samples of these poems are examined and discussed.

The advent of generative artificial intelligence (AI) represents a transformative leap in project management, offering significant capabilities in creativity and problem‐solving. This essay explores the impact of generative AI, highlighting its potential to support project planning and execution through dynamic resource management, improved stakeholder interaction, and predictive analytics. By understanding the differences between traditional AI and generative AI, project managers can harness these advanced tools to address a variety of challenges, from simple scheduling tasks to complex strategic planning. Generative AI enables project managers to interact with large language models (LLMs) through precise prompt engineering, ensuring tailored and actionable outputs. Practical examples illustrate how generative AI can provide innovative solutions to project delays and other common issues, showcasing its ability to transform traditional practices. Despite its advantages, the integration of generative AI in project management comes with significant risks, including job displacement, ethical concerns, data privacy, and the potential for overreliance on AI systems. Effective change management, robust ethics guidelines, and continuous learning are essential to mitigate these risks and maximize the benefits of AI. As project managers navigate this evolving landscape, they must remain proactive, balancing innovation with ethical considerations to lead their teams toward a future where AI‐driven project management is both effective and responsible.

Artificial intelligence (AI) has been integrated into various fields, accelerating innovation in existing ones. Consequently, AI has been employed in education to drive changes such as learning analytics and personalized learning. Recently, the development of generative AI has further transformed the educational landscape. Given the increasing use of generative AI in education, this study was conducted to explore its educational applications. We developed an educational program incorporating generative AI based on design thinking principles for high school students. To verify its effectiveness, high school students in Korea were selected as research subjects and divided into an experimental group (n=53) and a control group (n=42). A test tool aligned with the 2022 revised curriculum in Korea measured computational thinking skills. The study results showed that the group receiving AI convergence education using generative AI significantly improved their computational thinking. The improvement in computational thinking was also significant compared to the control group, providing strong evidence of the benefits of AI in education. This study confirmed that AI convergence education, utilizing generative AI grounded in design thinking, effectively develops computational thinking skills in high school students. The findings of this research highlight the potential educational value of integrating generative AI into both AI design thinking and convergence education. The study provides reassurance that generative AI can be a powerful tool in enhancing student learning experience and outcomes, paving the way for future educational innovations.

This chapter explores the nature of intelligence itself, conceptualizing it as a massive operating system that functions on biological technology as human intelligence (HI), or digital technology as artificial intelligence (AI). Through the lens of biological technology, the operating system contains many different biological individuals, each with an evolved range of dimensional “capabilities” needed to exist in the world environment. The operating system itself can be considered a hyperselfish intelligence (HYPERINT) development system that is relentlessly evolving, and exploitatively optimizing the development of the highest performing technologies within the world environment, regardless of the needs of individuals or a species, in order to ruthlessly maximize its capabilities. This chapter argues that HYPERINT is driving humans towards a situation where AI technologies could rapidly lead to the development of artificial general intelligence (AGI) with super intelligence that vastly exceeds HI and human controllability. Strong global regulation of AI is needed to protect human civilization from the most extreme risks of AI and AGI. In conclusion, the chapter argues that the global community must make a transition out of Industry 4.0, which focuses on progressive total automation of human work, and move towards the goals of Industry 5.0, which are more human-centric and globally sustainable.

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

The economic-legal analysis of the state and trends of the development of technologies of artificial intelligence (AI) has been carried out. The influence of AI on the development of society, eco­nomic effect, methods and the field of application, the state of developments in the world and Ukraine are analyzed. In the next decade, AI will become the main mar­ket trend and the best business tool. The contribution of intellectual technologies to global GDP is estimated at 15.7 trillion. dollars In the next 5-10 years, China will be the leader in the successful operation and adaptation of AI technologies. Ac­cording to analysts, the most benefit from AI technologies will be in the areas of fi­nancial services, retail and medicine.The scientific and inventive activity in the sphere of AI, the role of protection of in­tellectual property (patent and copyright), and the maintenance of the balance of com­peting interests are researched. Recently, the number of inventions based on AI has sharply increased. The leaders in the number of such inventions are American compa­nies IBM and Microsoft. This growth is due to the fact that in recent years AI has evolved from the theoretical concept into a real product that gains the world market. Since the advent of AI in the 50’s of the last century, inventors and researchers have applied for almost 340 thousand inventions based on AI (as of the end of 2016) and published more than 1.6 million scientific articles. The transport sector, including au­tonomous vehicles, is one of the sectors with the highest rates of growth in the appli­cation of AI. China has become a global leader in increasing the number of patents in the AI sphere over the past five years.By the number of companies working in the sphere of AI, Ukraine is among the three leaders among the countries of Eastern Europe. There are 57 AI companies in Ukraine and it has 11 investorsGeneralized practice of state regulation of activity in the sphere of AI in indus­trialized countries and EU countries. More and more countries are developing na­tional AI strategies. Thus, 17 countries, including Canada, China, Denmark, France, India, South Korea and Taiwan, have already announced their AI strate­gies. Some of them invest billions of dollars in this area. China, for example, has invested more than $ 10 billion in this technological trend, followed by South Korea — $ 2 billion and France — $ 1.5 billion. Governmental structures from dif­ferent countries are concerned about the need to develop relevant national strate­gies, programs and regulation of AI legislative level. Identified existing problems and suggested ways to solve them. Problems constraining the development of AI in Ukraine: the absence of a strategy for the development of AI, the domestic infra­structure for its work and the weakness of the business about existing fundamen­tal scientific developments in the field of AI, insufficient for the implementation of AI level of digitalization of companies, the lack of a high level of data work, and is also a misunderstanding of the implementation guidance in the AI company.

In this final set of explorations/meditations (of three), we examine the requirements for developing artificial general intelligence (AGI) through the lens of human cognitive architecture, with particular emphasis on the role of narrative selfhood and social cognition. Drawing on perspectives from cognitive science, philosophy of mind, and artificial intelligence research, we critically evaluate current claims about the capabilities of large language models, particularly regarding their purported achievements of theory of mind and self-awareness. We argue that genuinely human-like artificial intelligence may require more than sophisticated pattern recognition and language modeling, potentially necessitating the development of coherent narrative self-models and rich causal understanding. Special attention is given to the relationship between consciousness, conscience, and trustworthy AI systems, suggesting that meaningful artificial intelligence may require forms of richly-embodied and socially-embedded development to achieve robust and reliable functionality. We conclude by proposing that the path to artificial general intelligence may require recapitulating aspects of human cognitive development, particularly regarding the construction of narrative identity and social-moral reasoning capabilities. This analysis has implications for both the technical development of AI systems and the ethical frameworks through which we evaluate artificial minds.