To effectively improve the efficiency of international service design talent training and make it more in line with society's needs, we analyze the current status of international service design talent training and its professional training focus. Based on the above problems, from the perspective of cognitive psychology, artificial intelligence and human–computer interaction technology are used to construct the international service design talent training mode of the HCI intelligent service robot. This mode can be used to solve the existing teaching (...) problems by using novel means to ensure the quality of teaching. Finally, through the actual analysis of teaching cases, the effectiveness of the proposed talent training mode is verified. The HCI system is based on knowledge of cognitive psychology. According to the characteristics and functions of an educational robot, the robot is combined with traditional teaching activities, and the robot-assisted talent training mode is designed. Robot-assisted talent training is a feasible training method that can improve the efficiency of talent training. Students have confidence in their learning skills before the course, and the confidence is further strengthened after the end of the course. After the course, the students have a stronger sense of cooperation. This study can provide theoretical ideas for the research of international service talent training mode. (shrink)

Interactions between an intelligent software agent and a human user are ubiquitous in everyday situations such as access to information, entertainment, and purchases. In such interactions, the ISA mediates the user’s access to the content, or controls some other aspect of the user experience, and is not designed to be neutral about outcomes of user choices. Like human users, ISAs are driven by goals, make autonomous decisions, and can learn from experience. Using ideas from bounded rationality, we frame these interactions (...) as instances of an ISA whose reward depends on actions performed by the user. Such agents benefit by steering the user’s behaviour towards outcomes that maximise the ISA’s utility, which may or may not be aligned with that of the user. Video games, news recommendation aggregation engines, and fitness trackers can all be instances of this general case. Our analysis facilitates distinguishing various subcases of interaction, as well as second-order effects that might include the possibility for adaptive interfaces to induce behavioural addiction, and/or change in user belief. We present these types of interaction within a conceptual framework, and review current examples of persuasive technologies and the issues that arise from their use. We argue that the nature of the feedback commonly used by learning agents to update their models and subsequent decisions could steer the behaviour of human users away from what benefits them, and in a direction that can undermine autonomy and cause further disparity between actions and goals as exemplified by addictive and compulsive behaviour. We discuss some of the ethical, social and legal implications of this technology and argue that it can sometimes exploit and reinforce weaknesses in human beings. (shrink)

In the past decade, the fields of machine learning and artificial intelligence (AI) have seen unprecedented developments that raise human-machine interactions (HMI) to the next level.Smart machines, i.e., machines endowed with artificially intelligent systems, have lost their character as mere instruments. This, at least, seems to be the case if one considers how humans experience their interactions with them. Smart machines are construed to serve complex functions involving increasing degrees of freedom, and they generate solutions not fully anticipated by (...) humans. Consequently, their performances show a touch of action and even autonomy. HMI is therefore often described as a sort of “cooperation” rather than as a mere application of a tool. Some authors even go as far as subsuming cooperation with smart machines under the label ofpartnership, akin to cooperation between human agents sharing a common goal. In this paper, we explore how far the notion of shared agency and partnership can take us in our understanding of human interaction with smart machines. Discussing different topoi related to partnerships in general, we suggest that different kinds of “partnership” depending on the form of interaction between agents need to be kept apart. Building upon these discussions, we propose a tentative taxonomy of different kinds of HMI distinguishing coordination, collaboration, cooperation, and social partnership. (shrink)

Interactive media need their own idioms that exploit the characteristics of the computer based sign. The fact that the reader can physically influence the course of events in the system changes the author's role, since he no longer creates a linear text but anarrative space that the reader can use to generate stories. Although stories are not simulations of the real world, they must still contain recognizable parts where everyday constraints of time and space hold. AI-techniques can be used (...) to implement these constraints. In fact, we suggest that AI is probably best seen as an aesthetic phenomenon. (shrink)

The advent of the intelligence age has injected new elements into the development of literature. The synergic modification of Anglo-American traumatic narrative literature by artificial intelligence technology and interactive design psychology will produce new possibilities in literary creation. First, by studying natural language processing technology, this study proposes a modification language model based on the double-layered recurrent neural network algorithm and constructs an intelligent language modification system based on the improved LM model. The results show that the (...) performance of the proposed model is excellent; only about 30% of the respondents like AAL literature; the lack of common cultural background, appreciation difficulties, and language barriers have become the main reasons for the decline of reading willingness of AAL literature. Finally, AI technology and ID psychology are used to modify a famous TN work respectively and synergically, and the modified work is appreciated by respondents to collect their comments. The results corroborate that 62% of the respondents like original articles, but their likability scores have decreased for individually modified work by AI or ID psychology. In comparison, under the synergic modification efforts of AI and ID psychology, the popularity of the modified work has increased slightly, with 65% of the respondents showing a likability to read. Therefore, it is concluded that literary modification by single ID psychology or AI technology will reduce the reading threshold by trading off the literary value of the original work. The core of literary creation depends on human intelligence, and AI might still not be able to generate high-standard literary works independently because human minds and thoughts cannot be controlled and predicted by machines. The research results provide new ideas and improvement directions for the field of AI-assisted writing. (shrink)

In this article I will address the issue of the meaning of human-machine interaction as it is configured today in the light of substantial results achieved in the design and the manufacture of Artificial Intelligence (AI) systems. My starting point is a refined solution for meaningful AI recently suggested by Froese and Taguchi from the perspective of so-called augmented intelligence. Interpreted as a kind of human-machine interaction, augmented intelligence distinguishes itself by the fact that it merges the (...) interacting poles into a new hybrid entity. After having clarified the technical and the methodological background of my proposal, I will discuss a case of study of so-called bio-synthetic augmentation, where hybridisation overlaps with the cyborgisation of the human body. (shrink)

Evolutionary multi-objective optimization algorithms have been successfully applied in many real-life problems. EMOAs approximate the set of trade-offs between multiple conflicting objectives, known as the Pareto optimal set. Reference point approaches can alleviate the optimization process by highlighting relevant areas of the Pareto set and support the decision makers to take the more confident evaluation. One important drawback of this approaches is that they require an in-depth knowledge of the problem being solved in order to function correctly. Collective intelligence (...) has been put forward as an alternative to deal with situations like these. This paper extends some well-known EMOAs to incorporate collective preferences and interactive techniques. Similarly, two new preference-based multi-objective optimization performance indicators are introduced in order to analyze the results produced by the proposed algorithms in the comparative experiments carried out. (shrink)

In the course of consumer behavior, it is necessary to study the relationship between the characteristics of psychological activities and the laws of behavior when consumers acquire and use products or services. With the development of the Internet and mobile terminals, electronic commerce has become an important form of consumption for people. In order to conduct experiential education in E-commerce combined with consumer behavior, courses to understand consumer satisfaction. From the perspective of E-commerce companies, this study proposes to use artificial (...) intelligence image recognition technology to recognize and analyze consumer facial expressions. First, it analyzes the way of human–computer interaction in the context of E-commerce and obtains consumer satisfaction with the product through HCI technology. Then, a deep neural network is used to predict the psychological behavior and consumer psychology of consumers to realize personalized product recommendations. In the course education of consumer behavior, it helps to understand consumer satisfaction and make a reasonable design. The experimental results show that consumers are highly satisfied with the products recommended by the system, and the degree of sanctification reaches 93.2%. It is found that the DNN model can learn consumer behavior rules during evaluation, and its prediction effect is increased by 10% compared with the traditional model, which confirms the effectiveness of the recommendation system under the DNN model. This study provides a reference for consumer psychological behavior analysis based on HCI in the context of AI, which is of great significance to help understand consumer satisfaction in consumer behavior education in the context of E-commerce. (shrink)

This research aims to explore the relationship between religion and artificial intelligence. The research starts by defining a fundamental concept of religion and a conception of the principles of artificial intelligence. Then, the research explores the possible interactions between religion and artificial intelligence, as well as the potential challenges that this relationship may pose. Finally, the research examines the implications of this relationship for the management of the religious field.

Artificial intelligence (AI) has become an undeniable paradigmatic influence on human beliefs, attitudes, intentions, and behaviors. This article analyzes research that offers insights into risks related to contextual interaction with AI for human well-being in morally pluralistic organizations. Building on previous research that connects AI use with an increased risk of the sociopsychological phenomenon known as moral disengagement, we argue that AI created by developers who utilize rival versions of moral enquiry can activate moral disengagement mechanisms and shift a (...) person’s perspective regarding responsibility by sanctioning attitudes, intentions, and behaviors that would otherwise be inconsistent with the person’s moral beliefs. We specifically examine human interaction with _Generative and Predictive AI_ and their risks for increasing cognitive dissonance, cognitive distress, and self-harm. We also intentionally clarify important differences between AI-to-human interaction with human-to-human interaction. Finally, we recommend how to identify problematic interactions with AI and recommend ways to reduce a risk to human flourishing. (shrink)

In this paper, we use some elements of the philosophical theories of Wilfrid Sellars and Robert Brandom for examining the interactions between humans and machines. In particular, we adopt the concept of the space of reasons for analyzing the status of artificial intelligent agents. One could argue that AIAs, like the widely used recommendation systems, have already entered the space of reasons, since they seem to make knowledge claims that we use as premises for further claims. This, in turn, can (...) lead to a sense of alienation because AIAs do not quite play by the rules of the space of the reason. We, therefore, ask somewhat pointedly whether aliens have entered the space of reasons. A closer look reveals that it is a misconception to consider AIAs as being in the space of reasons. In fact, they should be seen as very sophisticated tools. Since these tools affect our own acting in the space of reasons, special regulations are required for their proper use. (shrink)

Real engines of the artificial intelligence revolution, machine learning models, and algorithms are embedded nowadays in many services and products around us. As a society, we argue it is now necessary to transition into a phronetic paradigm focused on the ethical dilemmas stemming from the conception and application of AIs to define actionable recommendations as well as normative solutions. However, both academic research and society-driven initiatives are still quite far from clearly defining a solid program of study and intervention. (...) In this contribution, we will focus on selected ethical investigations around AI by proposing an incremental model of trust that can be applied to both human-human and human-AI interactions. Starting with a quick overview of the existing accounts of trust, with special attention to Taddeo’s concept of “e-trust,” we will discuss all the components of the proposed model and the reasons to trust in human-AI interactions in an example of relevance for business organizations. We end this contribution with an analysis of the epistemic and pragmatic reasons of trust in human-AI interactions and with a discussion of kinds of normativity in trustworthiness of AIs. (shrink)

New types of artificial intelligence products are gradually transferring to voice interaction modes with the demand for intelligent products expanding from communication to recognizing users' emotions and instantaneous feedback. At present, affective acoustic models are constructed through deep learning and abstracted into a mathematical model, making computers learn from data and equipping them with prediction abilities. Although this method can result in accurate predictions, it has a limitation in that it lacks explanatory capability; there is an urgent need for (...) an empirical study of the connection between acoustic features and psychology as the theoretical basis for the adjustment of model parameters. Accordingly, this study focuses on exploring the differences between seven major “acoustic features” and their physical characteristics during voice interaction with the recognition and expression of “gender” and “emotional states of the pleasure-arousal-dominance (PAD) model.” In this study, 31 females and 31 males aged between 21 and 60 were invited using the stratified random sampling method for the audio recording of different emotions. Subsequently, parameter values of acoustic features were extracted using Praat voice software. Finally, parameter values were analyzed using a Two-way ANOVA, mixed-design analysis in SPSS software. Results show that gender and emotional states of the PAD model vary among seven major acoustic features. Moreover, their difference values and rankings also vary. The research conclusions lay a theoretical foundation for AI emotional voice interaction and solve deep learning's current dilemma in emotional recognition and parameter optimization of the emotional synthesis model due to the lack of explanatory power. (shrink)

As algorithmic data processing increasingly pervades everyday life, it is also making its way into the worlds of art, literature and music. In doing so, it shifts notions of creativity and evokes non-anthropocentric perspectives on artistic practice. This volume brings together contributions from the fields of cultural studies, literary studies, musicology and sound studies as well as media studies, sociology of technology, and beyond, presenting a truly interdisciplinary, state-of-the-art picture of the transformation of creative practice brought about by various forms (...) of AI. (shrink)

Socio-ethics covers the relation of the individual with the group and with society, as the individual acquires the skills for social life with others and the conduct of ‘normal responsible behaviour’ (Leal in AI Soc 9:29–32, 1995) that guides moral action. For a consideration of what it means to be socially skilled in everyday human interaction and the ethical issues arising from the new conditions of interaction that come with the integration of intelligent interactive artefacts, we will provide an (...) analysis at multiple levels of these phenomena and draw on a variety of application domains, for example, healthcare and interactive media. (shrink)

Philosophical and sociological approaches in technology have increasingly shifted toward describing AI (artificial intelligence) systems as ‘(moral) agents,’ while also attributing ‘agency’ to them. It is only in this way – so their principal argument goes – that the effects of technological components in a complex human-computer interaction can be understood sufficiently in phenomenological-descriptive and ethical-normative respects. By contrast, this article aims to demonstrate that an explanatory model only achieves a descriptively and normatively satisfactory result if the concepts of (...) ‘(moral) agent’ and ‘(moral) agency’ are exclusively related to human agents. Initially, the division between symbolic and sub-symbolic AI, the black box character of (deep) machine learning, and the complex relationship network in the provision and application of machine learning are outlined. Next, the ontological and action-theoretical basic assumptions of an ‘agency’ attribution regarding both the current teleology-naturalism debate and the explanatory model of actor network theory are examined. On this basis, the technical-philosophical approaches of Luciano Floridi, Deborah G. Johnson, and Peter-Paul Verbeek will all be critically discussed. Despite their different approaches, they tend to fully integrate computational behavior into their concept of ‘(moral) agency.’ By contrast, this essay recommends distinguishing conceptually between the different entities, causalities, and relationships in a human-computer interaction, arguing that this is the only way to do justice to both human responsibility and the moral significance and causality of computational behavior. (shrink)

Under the wave of globalization, the ties between countries are getting closer and closer. Based on the differences in the languages of different countries, the importance of English as a universal language is becoming more and more prominent. In the past, English teaching was mainly taught by teachers and students. This mode of English learning is more of theoretical teaching, which has little effect on improving English ability. In the era of intelligence, with the upgrading of technology and the (...) renewal of ideas, interactive English teaching is more accepted by people and becomes a new solution for English teaching. Studying English teaching from the perspective of social cognition, this paper proposes to realize human-computer interaction with the help of advanced science and technology, create an interactive teaching environment, and realize interactive learning in an English environment. This paper designed a control experiment of the experimental group and the control group to verify the impact of human-computer interaction teaching on students’ English performance and investigated students’ performance and teachers’ feelings and their related opinions on human-computer interaction learning. The experimental results of this paper show that human-computer interactive English teaching can help to enhance students’ interest in English learning and improve English expression significantly. (shrink)

Distributed Artificial Intelligence (DAI) deals with computational systems where several intelligent components interact in a common environment. This paper is aimed at pointing out and fostering the exchange between DAI and cognitive and social science in order to deal with the issues of interaction, and in particular with the reasons and possible strategies for social behaviour in multi-agent interaction is also described which is motivated by requirements of cognitive plausibility and grounded the notions of power, dependence and help. Connections (...) with human-computer interaction are also suggested. (shrink)

The contemporary digital reality is inconceivable without artificial intelligence (AI), which has become disseminated across all cultural practices, from scientific and artistic endeavors to everyday activities. AI increasingly functions as an agent of communication and decision-making, gradually surpassing human capabilities across nearly all competencies. The information flows of this new reality can only be navigated through hybrid systems based on post-critical rationality, which inherently introduces an irreducible element of uncertainty and risk in human-machine environments. The article proposes examining the (...) techno-subject through the lens of activity theory and the multiple types of rationality it generates. This framework facilitates the analysis of sociocultural and anthropological implications arising from AI’s integration with human domains, while addressing the existential challenges inherent in constructing a harmonious hybrid society. Beyond V.S. Stepin’s types of scientific rationality, the author builds upon previously introduced forms of rationality: post-critical, object-oriented, instrumental, subjective, results-oriented, creative, and autopoietic. This theoretical framework facilitates a substantive discussion of various manifestations of AI subjectivity, including its generalized embodiment and creative specificity. The demarcation of dominance domains between natural intelligence and AI in the intellectual sphere is proposed to be resolved on the basis of their heuristic potentials. The author maintains that natural intelligence invariably possesses superior capacity in this regard. The article examines approaches to risk assessment in AI implementation strategies, focusing on criteria for preserving anthropological and sociocultural profiles in the development of hybrid society. Advancing the concept of friendly AI is substantiated as essential, with consideration given not only to technological but also to anthropological aspects of human–machine interaction. The author advocates for the development of social examination institutions as regulatory mechanisms for natural–artificial intelligence interaction and anthropological–technological subject interfaces. (shrink)

Synthetic Dialogues presents two interactive installations, Echo Chamber and Mirror, Mirror, that explore how artificial systems can appear aware through staged encounters. Echo Chamber loops a conversation between two AI personas through a thermal receipt printer. Each line is printed, fed back into the machine and overwritten, until language drifts from coherence into fragmentation. Mirror, Mirror stages a brief social encounter in which an AI-powered mirror delivers a comedic roast of the participant. Through a post-humanist lens, Synthetic Dialogues frames (...) awareness as a form of relational agency enacted through behaviour, situatedness and reception. Rather than treating consciousness as an inner mental state, the work examines how attributions of awareness emerge through shared interaction, shaping how artists and audiences recognize awareness in more-than-human forms. (shrink)

This paper delves into AI development’s historical and philosophical dimensions while highlighting the symbiotic relationship between philosophy and AI from a technological perspective: philosophy furnishes foundational concepts, and AI supplies practical tools. The paper posits neurosymbolic AI as a solution to present challenges, sparking discussions encompassing both technical and philosophical considerations. Advocating a multidisciplinary approach calls for merging empirical AI insights with philosophy and cognition science to enrich our comprehension of intelligence and propel AI forward.

Comprehensively improving the level of vocational education and teaching quality has become an important initiative to meet the new round of technological revolution and industrial change. The traditional teaching mode can no longer meet the needs of industries and enterprises for job competences, and all higher education institutions are actively thinking about how to carry out teaching reform. Virtual reality can effectively solve the above-mentioned drawbacks, but the hardware facilities of the existing VR systems are extremely expensive, making it impossible (...) to popularize it in teaching. In this context, this paper is based on VR for the design of an interactive teaching platform. This paper discusses the key technologies of virtual reality, introduces the relevant theoretical foundation, and describes the current virtual reality devices with high popularity and their advantages and disadvantages for systematic analysis. From the perspective of teaching design, the design of human-computer interaction teaching process using VR technology to develop learning scenes is studied, introducing 3D modeling techniques, model construction, the production of picture and text panels, the production of video materials, and the establishment of virtual tour guide 3D scenes. The principle of this paper is to build a 3D vision for building 3D views of educational needs to design high quality images and video animation using 3DMAX and unity 3D engines. Then, we introduce the use of VR glasses, smart phones, and Bluetooth wireless handle to build a simple interactive teaching platform; the platform is of low cost of construction and student coverage, to solve the teaching resources shortage, equipment conditions lagging behind, the curriculum content aging, teachers and students who cannot interact in real time, and a series of problems. (shrink)

What is the role of the environment, and of the information it provides, in cognition? More specifically, may there be a role for certain artefacts to play in this context? These are questions that motivate "4E" theories of cognition (as being embodied, embedded, extended, enactive). In his take on that family of views, Hajo Greif first defends and refines a concept of information as primarily natural, environmentally embedded in character, which had been eclipsed by information-processing views of cognition. He continues (...) with an inquiry into the cognitive bearing of some artefacts that are sometimes referred to as 'intelligent environments'. Without necessarily having much to do with Artificial Intelligence, such artefacts may ultimately modify our informational environments. -/- With respect to human cognition, the most notable effect of digital computers is not that they might be able, or become able, to think but that they alter the way we perceive, think and act. (shrink)

Cognition played a pivotal role in the acceleration of technological innovation during the Industrial Revolution. Growing affluence may have provided favourable environmental conditions for a boost in cognition, enabling individuals to tackle more complex problems. Dynamical systems thinking may provide useful tools to describe sudden transitions like the Industrial Revolution, by modelling the recursive feedback between psychology and environment.

Robotization and artificial intelligence are expected to change societies profoundly. Trust is an important factor of human–technology interactions, as robots and AI increasingly contribute to tasks previously handled by humans. Currently, there is a need for studies investigating trust toward AI and robots, especially in first-encounter meetings. This article reports findings from a study investigating trust toward robots and AI in an online trust game experiment. The trust game manipulated the hypothetical opponents that were described as either AI or (...) robots. These were compared with control group opponents using only a human name or a nickname. Participants lived in the United States. Describing opponents with robots or AI did not impact participants’ trust toward them. The robot called jdrx894 was the most trusted opponent. Opponents named “jdrx894” were trusted more than opponents called “Michael.” Further analysis showed that having a degree in technology or engineering, exposure to robots online and robot use self-efficacy predicted higher trust toward robots and AI. Out of Big Five personality characteristics, openness to experience predicted higher trust, and conscientiousness predicted lower trust. Results suggest trust on robots and AI is contextual and it is also dependent on individual differences and knowledge on technology. (shrink)

Several technological developments, such as self-service technologies and artificial intelligence, are disrupting the retailing industry by changing consumption and purchase habits and the overall retail experience. Although AI represents extraordinary opportunities for businesses, companies must avoid the dangers and risks associated with the adoption of such systems. Integrating perspectives from emerging research on AI, morality of machines, and norm activation, we examine how individuals morally behave toward AI agents and self-service machines. Across three studies, we demonstrate that consumers’ moral (...) concerns and behaviors differ when interacting with technologies versus humans. We show that moral intention is less likely to emerge for AI checkout and self-checkout machines compared with human checkout. In addition, moral intention decreases as people consider the machine less humanlike. We further document that the decline in morality is caused by less guilt displayed toward new technologies. The non-human nature of the interaction evokes a decreased feeling of guilt and ultimately reduces moral behavior. These findings offer insights into how technological developments influence consumer behaviors and provide guidance for businesses and retailers in understanding moral intentions related to the different types of interactions in a shopping environment. (shrink)

Artificial Intelligence (AI), especially in its current incarnation of Machine Learning (ML), is an endeavor that is characterized by contingencies of two kinds. Intrinsic contingencies stem from the use of specific computational techniques that seem to decrease the control that human users exert on this technology. Relational contingencies emerge from the interaction of AI with other disciplines and contexts. I conduct an analysis of these contingencies on the backdrop of the visual arts with the aim to shed light on (...) the complex relations between technology and creativity. (shrink)

Artificial intelligence technologies are rapidly being integrated into decision-making processes across contemporary society. This transformation raises a fundamental philosophical question: can artificial intelligence fully replace human judgment? This paper argues that the phenomenon emerging in contemporary society is better understood not as replacement, but as the formation of a new judgment structure between humans and AI systems. Human judgment is a complex process involving experience, contextual interpretation, meaning-formation, and responsibility. AI systems, by contrast, operate primarily through large-scale data (...) analysis and probabilistic prediction. These are not equivalent cognitive structures. They represent different orientations toward the world — one that inhabits meanings, and one that processes patterns. Drawing on phenomenological and hermeneutic resources — particularly the work of Heidegger, Arendt, Dreyfus, and Gadamer — this paper introduces two conceptual frameworks: the Delegated Judgment Structure, in which humans assign analytical tasks to AI while retaining interpretive authority, and the Relational Judgment Structure, in which judgment emerges through the dynamic interaction of human interpretation and machine analysis. The paper argues that the central challenge of the AI age is not whether machines replace humans, but whether meaningful judgment — judgment rooted in interpretation, responsibility, and existential engagement — can be preserved within AI-mediated structures. (shrink)

Mandevillian intelligence is a specific form of collective intelligence in which individual cognitive shortcomings, limitations, and biases play a positive functional role in yielding various forms of collective cognitive success. When this idea is transposed to the epistemological domain, mandevillian intelligence emerges as the idea that individual forms of intellectual vice may, on occasion, support the epistemic performance of some form of multi-agent ensemble, such as a socio-epistemic system, a collective doxastic agent, or an epistemic group agent. (...) As a specific form of collective intelligence, mandevillian intelligence is relevant to a number of debates in social epistemology, especially those that seek to understand how group (or collective) knowledge arises from the interactions between a collection of individual epistemic agents. (shrink)

In this article, we suggest that the study of social interactions and the development of a “sense of agency” in joint action can help determine the content of relevant explanations to be implemented in artificial systems to make them “explainable.” The introduction of automated systems, and more broadly of Artificial Intelligence, into many domains has profoundly changed the nature of human activity, as well as the subjective experience that agents have of their own actions and their consequences – an (...) experience that is commonly referred to as sense of agency. We propose to examine the empirical evidence supporting this impact of automation on individuals’ sense of agency, and hence on measures as diverse as operator performance, system explicability and acceptability. Because of some of its key characteristics, AI occupies a special status in the artificial systems landscape. We suggest that this status prompts us to reconsider human–AI interactions in the light of human–human relations. We approach the study of joint actions in human social interactions to deduce what key features are necessary for the development of a reliable sense of agency in a social context and suggest that such framework can help define what constitutes a good explanation. Finally, we propose possible directions to improve human–AI interactions and, in particular, to restore the sense of agency of human operators, improve their confidence in the decisions made by artificial agents, and increase the acceptability of such agents. (shrink)

Artificial intelligence (AI) refers to the replication of human intelligence by a computer system such as visual perception, speech recognition, and decision-making (i.e., in a digital format). The remote antecedents of AI go back to the 17th century and to Thomas Hobbes’ mechanics perspective of human intelligence as a combination of mathematical symbols. Much later (in 1936) the mathematician Alan Turing (pioneer of AI together with Alonzo Church and Kurt Gödel) formulated several important contributions to computational theory. (...) In 1950 he predicted that 50 years hence there would be machines capable of intelligent behavior and language skills that could interact with humans without being recognized as machines (Turing test). He was not wrong. (shrink)

ABSTRACT Human-technology interactions are omnipresent in daily life, a reality that must be faced to enact positive change without uprooting the technological systems that have come to define us. The present study develops a collective intelligence model for human-technology interaction design that aims to promote peace, prosperity, and happiness through design intentionality informed by utopian targets of radical improvement in society. Participants generated ideas, clarified and consolidated them, and then developed an interpretive structure model of the most important affordances (...) identified during the idea generation phase. Coupled with a two-pass thematic analysis of the original idea set, what emerged is a model that is informed by stakeholder users of the technologies of tomorrow. Affordance themes centered on the importance of promoting world peace through technological means, identifying and rectifying material and financial inequalities, addressing negative well-being effects in current technologies, and increasing global collaboration and eventual expansion into the cosmos. (shrink)

The role of interaction in learning is essential and profound: it must provide the means to solve open problems (those only vaguely specified in advance), but cannot be captured using our familiar formal cognitive tools. This presents an impasse to those confined to present formalisms; but interaction is fundamentally dynamical, not formal, and with its importance thus underlined it invites the development of a distinctively interactivist account of life and mind. This account is provided, from its roots in the interactivist (...) biological constitution of life, through the evolution of the dual internal regulatory capacities expressed as intentionality and intelligence, to its expression in self-directed anticipative learning in persons and in science. (shrink)

Combining images with music is a music visualization to deepen the knowledge and understanding of music information. This study briefly introduced the concept of music visualization and used a convolutional neural network and long short-term memory to pair music and images for music visualization. Then, an emotion classification loss function was added to the loss function to make full use of the emotional information in music and images. Finally, simulation experiments were performed. The results showed that the improved deep learning-based (...) music visualization algorithm had the highest matching accuracy when the weight of the emotion classification loss function was 0.2; compared with the traditional keyword matching method and the nonimproved deep learning music visualization algorithm, the improved algorithm matched more suitable images. (shrink)

Sitting in the office of a distinguished philosopher of language recently, I watched him lean back (somewhat precariously) in his chair, look at the ceiling, and sigh: “Johan, we both write all this stuff about information, context, and communication – but is not the only time you really feel that you are making progress, when you resolutely close your eyes, and shut out the world and the others?” I appreciated his point, and indeed, in most spheres of life on this (...) planet, “l’Enfer” is most definitely “Les Autres”. (shrink)

In this work, a general definition, meaning, and importance of engineering are expressed generally, and the main branches of engineering are briefly discussed. The concept of technology is explored, and the relationship between engineering and technology is briefly outlined. The relationship between artificial intelligence and engineering is examined both generally and specifically. The place of artificial intelligence within science is evaluated according to different approaches. The general approach to philosophy and philosophy of science is briefly interpreted, and the (...) perspectives of some specific philosophers of science are compared. The relationship between artificial intelligence and philosophy of science is examined in general terms according to various approaches. The meaning and importance of philosophy of engineering and philosophy of technology are then defined according to the general approach. The next section articulates the Philosophy of Artificial Intelligence and the Artificial Intelligence of Philosophy using John McCarthy’s approach, and also defines the philosophy of artificial intelligence according to this general approach. The New Philosophy Perspective is then defined by the author, and the eight basic branches of Philosophy and Hybrid Philosophy, along with their relevant theories, are briefly outlined. A new perspective has been defined for Philosophy of Science which is one of the basic branches of philosophy. Accordingly, the main sciences, branches of science, and hybrid sciences for the new basic branches of philosophy have been outlined. The new branches of science and the corresponding hierarchy of sciences, based on the broader scale of the universe, have been defined, and the ideal scientific system has been illustrated. The next section briefly outlines the relationships between old and new branches of science. Finally, the structure of some old and new branches of philosophy is examined due to the new perspective of philosophy. The reconstructions of the Philosophy of Computer Science, Philosophy of Statistics, Philosophy of Monetary Values, Philosophy of Artificial Intelligence, Philosophy of Engineering, Philosophy of Information Technologies, Philosophy of Information Law, and Philosophy of Digital Technology, Philosophy of Digital Art, Philosophy of Architecture as defined by the new philosophical perspective, are outlined. The interaction of artificial intelligence philosophy with these branches of philosophy has been generally expressed. (shrink)

Artificial intelligence (AI) is increasingly expected to disrupt the ordinary functioning of society. From how we fight wars or govern society, to how we work and play, and from how we create to how we teach and learn, there is almost no field of human activity which is believed to be entirely immune from the impact of this emerging technology. This poses a multifaceted problem when it comes to designing and understanding regulatory responses to AI. This article aims to: (...) (i) defend the need for a novel conceptual model for understanding the systemic legal disruption caused by new technologies such as AI; (ii) to situate this model in relation to preceding debates about the interaction of regulation with new technologies (particularly the ‘cyberlaw’ and ‘robolaw’ debates); and (iii) to set out a detailed model for understanding the legal disruption precipitated by AI, examining both pathways stemming from new affordances that can give rise to a regulatory ‘disruptive moment’, as well as the Legal Development, Displacement or Destruction that can ensue. The article proposes that this model of legal disruption can be broadly generalisable to understanding the legal effects and challenges of other emerging technologies. (shrink)

This paper reflects on discussions within the Social Intelligence for Tele-healthcare (SIFT) project. The SIFT project aims to establish a model of social intelligence, to support the user-centred design of social intelligence in interactive systems. The conceptual background of social intelligence for the SIFT project is presented. Five challenges identified for the design of socially aware interactions are described, and their implications are discussed.

The rise of generative artificial intelligence (AI) is rapidly shaping human–machine and human–human relationships. At the center of this discourse is the human–AI relationship and whether and how ethics and biases would affect such a relationship. One of the most profound fields to observe the impact of AI on such relationships is the rise of AI doctor (or “conversational AI agent”), a form of generative AI that plays the role of doctors who interact with real patients. Despite the burgeoning (...) interest in the study of generative AI in medical contexts, the literature paints a mixed picture of its effectiveness from the lens of patients as users. The literature suggests that AI doctor has positive and negative effectiveness (e.g., accuracy, usability, user satisfaction, trust). In this study we ask: Can AI doctor respond to patients’ queries, and how does the response compare with a human doctor? To unpack this puzzle of AI effectiveness, we performed computational linguistics analysis of AI doctor’s responses to patients’ questions and how they compare with human doctor’s responses in a real-life setting using question–answer pairs data sourced from a widely used healthcare platform and AI doctor from China. Our study revealed that, overall, AI doctor’s responses are (1) more difficult to read and understand, (2) contain more similarity or duplications thus being more internally consistent. However, they contain (3) more positive emotion across several indicators than human doctor’s responses. Our findings offer insights into the uncertainty of AI doctor systems and future opportunities to advance such systems and what this means for future research on ethical AI in the medical contexts and human–AI relationships more generally. (shrink)