Intelligent Entities Research Articles

PART I: The Singleton Paradox: On the Future of Human-Machine Teaming and Potential Disruption of War Itself

Technological innovation has historically been applied in war and security affairs as a new tool or means to accomplish clear political or societal goals. The rise of artificial intelligence posits a new, uncharted way forward that may be entirely unlike previous arms races and advancements in warfare, including nuclear weapons and quantum technology. This article introduces the concept of a singleton as a future artificial intelligent entity that could assume central decision making for entire organizations and even societies. In turn, this presents what is termed a “singleton paradox” for security affairs, foreign policy, and military organizations. An AI singleton could usher in a revolutionary new world free of war and conflict for all of human civilization or trigger a catastrophic new war between those with a functioning singleton entity against those attempting to develop one, along with myriad other risks, opportunities, and emergent consequences.

A Systematic Review on the Visualization of Avatars and Agents in AR & VR displayed using Head-Mounted Displays.

Augmented Reality (AR) and Virtual Reality (VR) are pushing from the labs towards consumers, especially with social applications. These applications require visual representations of humans and intelligent entities. However, displaying and animating photo-realistic models comes with a high technical cost while low-fidelity representations may evoke eeriness and overall could degrade an experience. Thus, it is important to carefully select what kind of avatar to display. This article investigates the effects of rendering style and visible body parts in AR and VR by adopting a systematic literature review. We analyzed 72 papers that compare various avatar representations. Our analysis includes an outline of the research published between 2015 and 2022 on the topic of avatars and agents in AR and VR displayed using head-mounted displays, covering aspects like visible body parts (e.g., hands only, hands and head, full-body) and rendering style (e.g., abstract, cartoon, realistic); an overview of collected objective and subjective measures (e.g., task performance, presence, user experience, body ownership); and a classification of tasks where avatars and agents were used into task domains (physical activity, hand interaction, communication, game-like scenarios, and education/training). We discuss and synthesize our results within the context of today's AR and VR ecosystem, provide guidelines for practitioners, and finally identify and present promising research opportunities to encourage future research of avatars and agents in AR/VR environments.

“WHAT THE FUTURE OF ARTIFICIAL INTELLIGENCE (AI) HOLDS FOR US IN DENTISTRY — A REVIEW”

Articial Intelligence (AI) is a branch of computer science that aims to understand and build intelligent entities. AI provides machines with the capability to adapt, reason & provide solutions. AI is classied into 2 broad categories – Weak & Strong both having numerous applications. In healthcare eld AI can save lives & improve health care for millions of patients around the world. In Dentistry AI application technology is progressing remarkably

The artificial intelligence entity as a legal person

ABSTRACT This article discusses the legal position of an Artificial Intelligence Entity (AIE) that is able to create something novel, like an artwork. Rather than examining a fictitious being, I inquire the position of human beings, comparing it with that of a conceivable AIE. The nature of an AIE in terms of matter and mind is compared with that of a human being, after which it is inquired whether it may, like a human being, be deemed a legal person. This analysis serves as a prelude to the question of whether an AIE may be a copyright owner.

Social Bots and Information Propagation in Social Networks: Simulating Cooperative and Competitive Interaction Dynamics

With the acceleration of human society’s digitization and the application of innovative technologies to emerging media, popular social media platforms are inundated by fresh news and multimedia content from multiple more or less reliable sources. This abundance of circulating and accessible information and content has intensified the difficulty of separating good, real, and true information from bad, false, and fake information. As it has been proven, most unwanted content is created automatically using bots (automated accounts supported by artificial intelligence), and it is difficult for authorities and respective media platforms to combat the proliferation of such malicious, pervasive, and artificially intelligent entities. In this article, we propose using automated account (bots)-originating content to compete with and reduce the speed of propagating a harmful rumor on a given social media platform by modeling the underlying relationship between the circulating contents when they are related to the same topic and present relative interest for respective online communities using differential equations and dynamical systems. We studied the proposed model qualitatively and quantitatively and found that peaceful coexistence could be obtained under certain conditions, and improving the controlled social bot’s content attractiveness and visibility has a significant impact on the long-term behavior of the system depending on the control parameters.

Vulnerability-Aware Task Scheduling for Edge Intelligence Empowered Trajectory Analysis in Intelligent Transportation Systems

In order to fulfill the requirements of Intelligent Transportation Systems (ITS) on ultra-delay service response, task scheduling for trajectory analysis is being shifted from the data center into the network edge of ITS. Such a decentralized paradigm motivates the computing power of the edge device and makes traditional analysis tasks open to the users around ITS. However, since these ITS users have differentiated identities and roles with differentiated security demands and privacy protection, assigning tasks for different users requires identifying and assessing the vulnerability of edge intelligence entities (EIEs). Otherwise, sensitive tasks assigned to the vulnerable EIEs will extremely increase the security risks of industrial control networks. To solve these problems, this paper proposes a vulnerability-aware task scheduling (VATS) mechanism, which integrates vulnerability assessment and access control. With VATS, secure EIEs can obtain more permissions and join in the privacy-sensitive trajectory analysis task, which is essential to enhance privacy protection at edges and ultimately improve the efficiency of task scheduling. The simulation results demonstrate the validity of the proposed scheme to defend insecure task scheduling like trajectory analysis.

How and why humans trust: A meta-analysis and elaborated model.

Trust exerts an impact on essentially all forms of social relationships. It affects individuals in deciding whether and how they will or will not interact with other people. Equally, trust also influences the stance of entire nations in their mutual dealings. In consequence, understanding the factors that influence the decision to trust, or not to trust, is crucial to the full spectrum of social dealings. Here, we report the most comprehensive extant meta-analysis of experimental findings relating to such human-to-human trust. Our analysis provides a quantitative evaluation of the factors that influence interpersonal trust, the initial propensity to trust, as well as an assessment of the general trusting of others. Over 2,000 relevant studies were initially identified for potential inclusion in the meta-analysis. Of these, (n = 338) passed all screening criteria and provided therefrom a total of (n = 2,185) effect sizes for analysis. The identified dependent variables were trustworthiness, propensity to trust, general trust, and the trust that supervisors and subordinates express in each other. Correlational results demonstrated that a large range of trustor, trustee, and shared, contextual factors impact each of trustworthiness, the propensity to trust, and trust within working relationships. The emphasis in the present work on contextual factors being one of several trust dimensions herein originated. Experimental results established that the reputation of the trustee and the shared closeness of trustor and trustee were the most predictive factors of trustworthiness outcome. From these collective findings, we propose an elaborated, overarching descriptive theory of trust in which special note is taken of the theory's application to the growing human need to trust in non-human entities. The latter include diverse forms of automation, robots, artificially intelligent entities, as well as specific implementations such as driverless vehicles to name but a few. Future directions as to the momentary dynamics of trust development, its sustenance and its dissipation are also evaluated.

Rage against robots: Emotional and motivational dimensions of anti-robot attacks, robot sabotage, and robot bullying

An assortment of kinds of attacks and aggressive behaviors toward artificial intelligence (AI)-enhanced robots has recently emerged. This paper explores questions of how the human emotions and motivations involved in attacks of robots are being framed as well as how the incidents are presented in social media and traditional broadcast channels. The paper analyzes how robots are construed as the “other” in many contexts, often akin to the perspectives of “machine wreckers” of past centuries. It argues that focuses on the emotions and motivations of robot attackers can be useful in mitigating anti-robot activities. “Hate crime” or “hate incident” characterizations of some anti-robot efforts should be utilized in discourse as well as some future legislative efforts. Hate crime framings can aid in identifying generalized antagonism and antipathy toward robots as autonomous and intelligent entities in the context of antirobot attacks. Human self-defense may become a critical issue in some anti-robot attacks, especially when apparently malfunctioning robots are involved. Attacks of robots present individuals with vicarious opportunities to participate in anti-robot activity and also potentially elicit other aggressive, copycat actions as videos and narrative accounts are shared via social media as well as personal networks.

Toward a Theory of Political Science and the Future of Exopolitics

The aim of this paper is to inform (or enlighten) the public about exopolitics, which is a sub-discipline of political science that puts a new spin on studying extraterrestrial life or non-human, intelligent entities — that is, as it especially relates to politics. And despite its contrary and controversial message, exopolitics pushes the political science envelope. Indeed, the discipline speaks volumes about a supposed relationship we (humans) may have with intelligent creatures outside our realm of understanding, particularly with an unprecedented wave of UFO sightings worldwide. Of course, human beings have always felt the need to connect with other humans; but will this position mean that we can also come together with humanoids from another planet? Exopolitics is also concerned with other alien worlds, and different academic thought processes that might led to profound misunderstandings about this specific political science discipline, and our understanding of the fabric of the universe. Further, we need objectivity and clarity when it comes to studying exopolitics. Finally, exopolitics, fortunately, has not caused some kind of academic backlash; nor is it some namby-pamby academic discipline that has no bearing on anything.

Erôs and Intelligible Desire in Plotinus’ Enneads

In Ennead III.5 On Love, Plotinus' discussion of erôs is underlined by Plato’s discourse on love in the Symposium and the Phaedrus.[1] Plotinus conceives erôs as a purified power, which directs the soul to the intelligible realm of beauty and the world of the Forms.[2] Modern scholarship considers the Plotinian erôs as an ascending power that is always directed to the higher realm of the Forms and never to the lower perceptible realm. Throughout the Enneads, the soul is described as purely and originally an intelligible entity in all its manifestations and expressions (ex. Ennead IV.8).[3] Plotinus particularly supports a dual aspect theory of the soul, in which the homogenous psychē consists of two interrelated aspects - a higher intelligible part related to Intellect, and a lower perceptible part related to the sensible bodies (Caluori, 2015; Remes, 2007; Stamatellos, 2013; Stern-Gillet, 2009). However, limited attention has been paid to the intelligible aspects of the soul's desire in Plotinus' conception of erôs. In this context, this paper aims to revisit the view that Plotinus completely refuted the desire of the physical bodies, and consequently refuted erôs as a power directed to the lower perceptible realm (Ferwerda, 1965; Friedländer, 1964; Hadot, 1963; Wallis, 1995). It is argued that in light of the soul's intelligibility, desire also has an intelligible aspect when it is directed, along with the power of love, to the earthly realm and thus the true intelligible beauty of the perceptible bodies is recognized.
 
 [1] Hereafter, all quotations from Plotinus’ Enneads will solely refer to Armstrong’s (1966-1988) translations.
 [2] See Bertozzi (2012, 2021); Tatarkiewicz (1980); Wallis (1995); Wiitala (2013), Vasilakis (2021).
 [3] For Plotinus’ theory of the soul, see his treatises in Ennead IV. Also see Blumenthal (1971) and Caluori (2015).

Organizing cyber capability across military and intelligence entities: collaboration, separation, or centralization

This paper explores how the Netherlands, France, and Norway organize their cyber capabilities at the intersection of intelligence services and military entities and provides recommendations for policy and research development in the field. Drawing out key organizational differences and ambiguities, the analysis identifies three models of organizing military and intelligence relations: A Dutch collaboration model, a French separation model, and a Norwegian centralization model. Despite their divergence in organizing cyber capabilities, the three countries converge on the assumption that both responding to cyber conflict short of war and developing military cyber power are dependent on the skills, information, and infrastructure of intelligence services. This calls for cooperation and coordination across military and intelligence entities. However, it remains unclear whether decision makers have systematically assessed the implications of the organizational structure for the ways in which the two dimensions relate to and shape one another at strategic, tactical, and operational levels. The paper concludes that there is a need for increased political attention and a deliberate approach to how the organizational model allows for the operational cyber capacity to travel from, translate into, and shape intelligence and military entities and to which political implications at both national and international levels.

Reasoning and interaction for social artificial intelligence

Current work on multi-agent systems at King’s College London is extensive, though largely based in two research groups within the Department of Informatics: the Distributed Artificial Intelligence (DAI) thematic group and the Reasoning & Planning (RAP) thematic group. DAI combines AI expertise with political and economic theories and data, to explore social and technological contexts of interacting intelligent entities. It develops computational models for analysing social, political and economic phenomena to improve the effectiveness and fairness of policies and regulations, and combines intelligent agent systems, software engineering, norms, trust and reputation, agent-based simulation, communication and provenance of data, knowledge engineering, crowd computing and semantic technologies, and algorithmic game theory and computational social choice, to address problems arising in autonomous systems, financial markets, privacy and security, urban living and health. RAP conducts research in symbolic models for reasoning involving argumentation, knowledge representation, planning, and other related areas, including development of logical models of argumentation-based reasoning and decision-making, and their usage for explainable AI and integration of machine and human reasoning, as well as combining planning and argumentation methodologies for strategic argumentation.

ROLE OF ARTIFICIAL INTELLIGENCE IN PSYCHOLOGY

This Article entitles that, the role of Artificial Intelligence in psychology states that Psychology is the study of mental processes and behaviour of individuals. It is about artificial cognitive processes required for an artificially intelligent entity to be intelligent, learning, autonomous and self-developing. In psychology there are several specialties or focuses of study. In cognitive psychology, how the brain thinks and works. This includes learning, memory, perception, language and Logic. There is also developmental psychology that considers how an individual adapts and changes during different developmental stages and what is appropriate to consider of a human based on development. Sports psychology considers how to affect individual performance and how performance affects the individual. So Artificial Psychology for the purposes of this paper contains the artificial mental process considered necessary to create intelligent, autonomous, self-evolving, artificially cognitive systems. “Real artificial intelligence” as the simulation of actual human behaviour is often referred to as artificial general intelligence (AGI). In AGI, machines are supposed to be built in a way that makes it impossible to distinguish them from real humans. There are three areas, in which psychology needs to play a leading role:1. User Experience (UX) in the interaction with artificial intelligence. The psychological impact of AI on humans 2. Other psychological concepts, such as emotion and empathy will have to be created in the same way as intelligence for example “Artificial Empathy” to recreate a fully functioning artificial general intelligence 3. “Mental” health of both machines and human beings.

Programmable design and self assembly of peptide conjugated AIEgens for biomedical applications

Aggregation-induced emission luminogens (AIEgens) possess enhanced fluorescence in highly aggregated states, thus enabling AIEgens as a promising module for highly emissive fluorescence biomaterials. So far, AIEgens-based nanomaterials and their hybrids have been reported for biomedical applications. Benefiting from the intrinsic biocompatibility and biofunction-editing properties of peptides, peptide-AIEgens hybrid biomaterials reveal unlimited possibilities including target capacity, specificity, stimuli-responsiveness, self-assembly, controllable structural transformation, etc.. In the last two decades, peptide-AIEgens hybrid nanomaterials with a unique design concept in aggregated states have achieved various biomedical applications such as biosensing, bioimaging, imaging-guided surgery, drug delivery and therapy. More recently, programmable design of peptide-AIEgens for in situ self-assembly provides a unique strategy for constructing intelligent entities with defined biological functions. In this review, we summarize the basic design principle of programmable peptide-AIEgens, structure-effect relationship and their unusual biomedical effects. Finally, an outlook and perspective toward future challenges and developments of peptide-AIEgens nanomaterials are concluded.

Let me drive you! The effect of change seeking and behavioral control in the Artificial Intelligence-based self-driving cars

This paper investigates the roles of product intelligence, change seeking, and behavioral control in determining consumers’ intention to use Artificial Intelligence-based self-driving cars. In an experimental study conducted with a sample of 343 respondents, we show that consumers might feel more in control when driving such cars, and such an increased sense of behavioral control, in turn, is associated with an increased intention to use them. This likely happens because such vehicles are perceived as intelligent entities that allow drivers to personalize their driving experiences. However, this effect is significant only among individuals with a greater change seeking tendency, who thus are more inclined to try new experiences.

A Semantic Model of Internet of Things for Intelligent Translation and Learning

There were a lot of multisource data and heterogeneous devices in the intelligent system of the Internet of things, and the existing methods were difficult to meet the service needs of users for intelligent entities. Therefore, this paper proposed a semantic model construction method of the Internet of things based on intelligent translation and learning. Firstly, on the basis of summarizing the relevant theories of semantic Internet of things, this paper analyzed the semantic data and its characteristics, and expounded the common ontology matching methods. Secondly, according to the characteristics of service ontology and user ontology in intelligent Internet of things system, a method of matching two different ontologies based on string and semantic relationship was proposed, and the cyclic neural network method was used to organically integrate the semantic data of ontology. Finally, in order to realize the perception and representation of the context information of the Internet of things, a semantic model of the Internet of things based on intelligent translation and learning was constructed. Through experimental comparative analysis, the results showed that compared with the traditional methods based on semantic similarity and semantic distance, the semantic model of the Internet of things proposed in this paper had better performance in accuracy and recall, and can achieve better application effect of the Internet of things system. The model proposed in this paper will provide a theoretical reference for further exploring the sharing and service of heterogeneous devices and data in the intelligent Internet of things system.

Use of AI Techniques on Photonic Crystal Sensing for the Detection of Tumor

Tumors can cause severe problem to human beings. Sometime it can be a cause of death. Earlier there were lack of treatment and technological deficiency, due to which it was unable to detect tumor cells and even unable to offer proper treatment for these diseases. This study aims to use Photonic crystal (PhC) due to their ample choice of structures and litheness to endure with every sphere of influence has been utilized them twenty decade back to now a day and have extremely huge prospects in imminent future also. They have revealed their incidence in the field of imaging, sensing, fabricating industries, automation, medical, mechatronics, computronics, mechanochromic, underwater acoustic detection, pharma industries and nanoimprinting etc. If we are discussing about current and impending applications of PhC then it comprises smart sensing and detection of disunite diseases, anonymous viruses and a range of tumors. Artificial intelligence (AI) is also playing incredibly essential role in analyzing and creating entities equivalent to the change in human behavior. AI tools and techniques are utilizing to create intelligent entities through which it is accomplishing countless feats. The PhC along with the artificial intelligence are utilizing as Optical Neural Network (ONN), Artificial Neural Network (ANN), Cellular Computing, Plasma Technology, Parallel Processing, Image Processing etc. Here in this study designated photonic crystal has been used for the detection of infected cell in human body. Sometimes these infected cells are unable to trace by normal pathological investigations and slowly they take a shape of Tumors. But thanks to Photonics crystal sensors that they have made it true not only for detection but we can say for early detection of such tumors in human body. These early detection and proper investigation is possible only because of AI impacts on photonics crystal. This study focuses on detection and observation of bio molecules for selectivity, sensitivity, reflectivity and concentration. By change in wavelength i.e. from 1.5 μm to 4 μm the refractive index (RI) of tumor cell can be measured which is observed by measuring sensitivity between 11258 nm/RIU to 32358 nm/RIU. Tumors have refractive indices varies between 1.3342 to 1.4251. It is observed that sarcoma level is directly proportional to the RI of tumor. Various AI algorithms like support vector machine (SVM) obtained accuracy as 96%, K- nearest neighbor (KNN) shows as 70%, logistic regression (LR) shows as 88%, random forest (RF) show it as 90%, fuzzy logic (FL) and artificial neural network (ANN) observed accuracy as 93% and 95% respectively.

Cyber conflict short of war: a European strategic vacuum

ABSTRACT Cyber conflict short of war plays an increasingly important role in contemporary security politics. Dedicated to a study of three European NATO members – the Netherlands, France and Norway, this article expands the existing focus of the study of cyber conflict short of war beyond its dominating US context. It compares and assesses how the countries perceive and respond to a changing strategic environment characterised by increasing cyber conflict short of war. The analysis demonstrates that all three countries acknowledge that cyber operations short of war alter the strategic environment and challenge the idea of deploying offencive cyber capabilities as purely a warfare matter. However, it also identifies a strategic vacuum, as none of them have formulated strategies that describe in detail how military and intelligence entities are supposed to approach and manage the new strategic environment. The article asserts that the current lack of strategic guidance is a fundamental challenge that puts European societies at risk and undermines democratic governance as navigating the new space of strategic cyber competition is a significant challenge to contemporary European statecraft. It concludes by noting three avenues for how to ameliorate this situation and fill the vacuum.

Engagement with Emerging Forms of Sextech: Demographic Correlates from a National Sample of Adults in the United States

ABSTRACT Social technology is ever-evolving, and increasingly offers novel domains for sexual experiences. In the current study, we investigated demographic correlates of engagement with emerging forms of sextech, defined here as internet-based applications, platforms, or devices used for sexual pleasure. Our web-based, demographically representative sample included 7,512 American adults aged 18–65 years, with a near-even gender split of men/women and moderate racial diversity (63% White). Participants indicated their engagement with eight forms of sextech, including six emerging forms of sexual technology (visiting erotic camming sites, participating in camming streams, teledildonic use, accessing virtual reality pornography, playing sexually explicit video games, and sexual messaging with chatbots or artificially intelligent entities) as well as two more common domains (online pornography and sexting). Participants who were younger, were men, had higher income, and were sexual minorities reported more frequent engagement with all forms of sextech assessed. Unlike prior work on pornography, religious individuals were more likely to engage with emerging sextech. Beyond online pornography (50%) and sexting (29%), visiting camming sites (18%) and playing sexually explicit video games (13%) were relatively common. Findings may contribute to the destigmatization of sextech engagement and forecast future norms in technologically-facilitated sexual behavior.

Survey of COVID-19 Prediction Models and Their Limitations

COVID-19 pandemic has been spreading globally and has been influencing the daily life of human beings in addition to the economies of most countries around the globe. Early and accurate detection of COVID-19 coronavirus is crucial to prevent and control its outbreak using medical treatment and timely quarantine. The daily massive increases in the cases of COVID-19 patients worldwide and the limited solutions of the available diagnosing techniques have resulted in difficulties in pointing out the presence of the disease. Wherefore, the necessity arises to find other alternatives by leveraging the artificial intelligence (AI) models which create intelligent entities that have demonstrated themselves particularly successful due to their spectacular innovations in video processing and image, in addition to their highly accurate projection models. This survey contributes to studying the state of the art of the AI models that have been fighting against the COVID-19, highlighting the limitations that are significant and present noteworthy barriers to struggle with a pandemic, and recommends the trends for the incoming research on the pandemic.