Time is a necessary element in understanding AI art. Firstly, time reveals the historical process by which art-theoretical predicates move from the unmarked to the marked, which can thus be utilized as a defense for arguing the legitimacy of AI art as art. Furthermore, AI art should be seen as a “new” art that is temporally ahead of the descriptive forms of art theory. Secondly, time provides a unique interpretation of AI artworks’ characteristics and aesthetic experience. The absence of experience, (...) the de-depth of AI artworks, and the “short experience/short memory” aesthetic mode of the masses are closely linked to the scarcity of time in an age of acceleration. Finally, time reflects the loss of “aura” and the new end of art that AI art may bring about. Time provides a defense and explanation of AI art, as well as a perspective for reflecting on the development of art in contemporary times. (shrink)

Should you be targeted by police for a crime that AI predicts you will commit? In this paper, we analyse when, and to what extent, the person-based predictive policing (PP) — using AI technology to identify and handle individuals who are likely to breach the law — could be justifiably employed. We first examine PP’s epistemological limits, and then argue that these defects by no means refrain from its usage; they are worse in humans. Next, based on major AI ethics (...) guidelines (IEEE, EU, and RIKEN, etc.), we refine three basic moral principles specific to person-based PP. We also derive further requirements from case studies, including debates in Chicago, New Orleans, San Francisco, Tokyo, and cities in China. Instead of rejecting PP programs, we analyse what necessary conditions should be met for using the tool to achieve social good. While acknowledging its risks, we conclude that the person-based PP could be beneficial in community policing, especially when merging into a larger governance framework of the social safety net. (shrink)

Alcohol addiction can lead to health and social problems. It can also affect people's emotions. Emotion plays a key role in human communications. It is important to recognize the people's emotions at the court and infer the association between the people's emotions and the alcohol addiction. However, it is challenging to recognize people's emotions efficiently in the courtroom. Furthermore, to the best of our knowledge, no existing work is about the association between alcohol addiction and people's emotions at court. In (...) this paper, we propose a deep learning framework for predicting people's emotions based on sound perception, named ResCNN-SER. The proposed model combines several neural network-based components to extract the features of the speech signals and predict the emotions. The evaluation shows that the proposed model performs better than existing methods. By applying ResCNN-SER for emotion recognition based on people's voices at court, we infer the association between alcohol addiction and the defendant's emotion at court. Based on the sound source data from 54 trial records, we found that the defendants with alcohol addiction tend to get angry or fearful more easily at court comparing with defendants without alcohol addiction. (shrink)

In order to cope with the changing health needs in the community, an holistic approach on AIDS prevention and control with particular reference to essential quality was introduced at an educational seminar at Hebei Medical University in China, 1996. We have identified three major points in the present study through learning and research process: 1. The importance of ‘cultural norm’ for the unification of science and technology is identified for the community approach; 2. ‘community care’ emphasising human quality provides unity (...) in diversity for educational program; and 3. ‘community control’ emphasising quality assurance demonstrates the effectiveness for program analysis from the viewpoint of human centred systems. (shrink)

In this essay we explore extensive modes of enactive engagement among humans, physical and computational media richer than the modes represented by classical notions of interaction and relation. We make use of a radically material and a potential-theoretic account of event to re-conceive ad hoc, non-pre-schematized activity in responsive environments. We can regard such activity as sense-making via dehomogenization of material that co-articulates subjects and objects.

Given the current popularization of computer programming and the trends of informatization and digitization, colleges have actively responded by making programming lessons compulsory for students of all disciplines. However, students from different ethnic groups often have different learning responses to such lessons due to their respective cultural backgrounds, the environment in which they grew up, and their consideration for future employment. In this study, an AI-assisted programming module was developed and used to compare the differences between multi-ethnic college students in (...) terms of their theoretical and actual learning expectancy, motivation, and effectiveness. The module conducted analysis through the deep learning network and examined the relevant processes that the students underwent during programming lessons, as well as the types of errors they had committed. Their learning motivation for and actual learning performance in programming were then examined based on the cognitive learning theory. The results of the experiment, which involved 96 multi-ethnic college students, indicated that the two groups had dissimilar theoretical performance in terms of their expectancy and motivation for learning programming. The indigenous students’ main concern was whether programming would affect their families or tribes, and this concern affected and was reflected in their learning outcomes. In contrast, the learning motivation and goals of Han Chinese students were driven by the cognition of the value of programming to themselves. The research findings can contribute toward the cognition and understanding of multi-ethnic students when learning computer programming and development of the appropriate teaching methods, and serve as a reference for subsequent research on integrating multiculturalism into computer programming lessons. (shrink)

With the rapid development of computer science and information technology, artificial intelligence has been developed from theory to application. As a key technology in the modern society, AI is increasingly affecting all aspects of people’s daily lives, including sports training. AI can be considered as an assistive technology to provide specific support to athletes’ physical education training through various means such as data analysis and simulation of training scenarios. Although research on AI is still in the preliminary stage, it is (...) significant to explore how AI can be applied in sports training since this emerging technology could facilitate people’s physical training to some extent. This paper first reviews the existing research on AI applications. Then, based on the fundamental concept and related research results of AI, this study explores three specific cases of AI application in sports training and explains the main principles. This research focuses on discussing the strong relationship between AI technology and physical education training and highlights the advantages of AI, including utilization, convenience, and innovation. (shrink)

Artificial intelligence (AI) systems are increasingly adopted to make decisions in domains such as business, education, health care, and criminal justice. However, such algorithmic decision systems can have prevalent biases against marginalized social groups and undermine social justice. Explainable artificial intelligence (XAI) is a recent development aiming to make an AI system’s decision processes less opaque and to expose its problematic biases. This paper argues against technical XAI, according to which the detection and interpretation of algorithmic bias can be handled (...) more or less independently by technical experts who specialize in XAI methods. Drawing on resources from feminist epistemology, we show why technical XAI is mistaken. Specifically, we demonstrate that the proper detection of algorithmic bias requires relevant interpretive resources, which can only be made available, in practice, by actively involving a diverse group of stakeholders. Finally, we suggest how feminist theories can help shape integrated XAI: an inclusive social-epistemic process that facilitates the amelioration of algorithmic bias. (shrink)

This comprehensive volume features the proceedings of the Third International Workshop on Logics for New-Generation Artificial Intelligence and the International Workshop on Logic, AI and Law, held in Hangzhou, China on September 8-9 and 11-12, 2023. The collection offers a diverse range of papers that explore the intersection of logic, artificial intelligence, and law. With contributions from some of the leading experts in the field, this volume provides insights into the latest research and developments in the applications of logic in (...) these areas. It is an essential resource for researchers, practitioners, and students interested in the latest advancements in logic and its applications to artificial intelligence and law. (shrink)

This paper focuses on the potential of “equitech”—AI technology that improves equity. Recently, interventions have been developed to reduce the harm of implicit bias, the automatic form of stereotype or prejudice that contributes to injustice. However, these interventions—some of which are assisted by AI-related technology—have significant limitations, including unintended negative consequences and general inefficacy. To overcome these limitations, we propose a two-dimensional framework to assess current AI-assisted interventions and explore promising new ones. We begin by using the case of human (...) resource recruitment as a focal point to show that existing approaches have exploited only a subset of the available solution space. We then demonstrate how our framework facilitates the discovery of new approaches. The first dimension of this framework helps us systematically consider the analytic information, intervention implementation, and modes of human-machine interaction made available by advancements in AI-related technology. The second dimension enables the identification and incorporation of insights from recent research on implicit bias intervention. We argue that a design strategy that combines complementary interventions can further enhance the effectiveness of interventions by targeting the various interacting cognitive systems that underlie implicit bias. We end with a discussion of how our cognitive interventions framework can have positive downstream effects for structural problems. (shrink)

About 20 years ago, the ecology of media art practices proliferated in two domains: those that attached themselves to high technology labs or companies like Xerox PARC, and those that took advantage of personal computing to form collectives only loosely coupled to academic institutions or disciplines. In this essay, I closely examine the diverse epistemic cultures and diverse technical, political, and generational interests in such “cyber-anarchist” networks. I sketch the economy of knowledge in recent media arts and technology communities of (...) practice in the wake of Open Source. I use as my lens the experience of creating a responsive media space called the TGarden, with a collective that gathered more than 26 artists and engineers from 11 institutions and 7 nations. (shrink)

This study proposed a children’s digital art ability training system with artificial intelligence-assisted learning, which was designed to achieve the goal of improving children’s drawing ability. AI technology was introduced for outline recognition, hue color matching, and color ratio calculation to machine train students’ cognition of chromatics, and smart glasses were used to view actual augmented reality paintings to enhance the effectiveness of improving elementary school students’ imagination and painting performance through the diversified stimulation of colors. This study adopted the (...) quasi-experimental research method and designs the pre-test and post-test for different groups. The research subjects are the Grade 4 students of an elementary school in Taitung City, Taiwan. The test tools included an imagination test and an evaluation of painting performance ability. The test results of a total of 30 students before and after the experiment included the experimental group that received the children’s digital art ability training system with AI-assisted learning and 30 students in the control group that had not received the teaching were analyzed by covariance. These results were supplemented by the description and interpretation of student feedback, teachers’ reflection notes, and other qualitative data to understand the performance of the students in the experimental group in terms of imagination and painting performance. (shrink)

The TGarden is a genre of responsive environment in which actor–spectators shape dense media sensitive to their movements. These dense fields of light, sound, and material also evolve according to their own composed dynamics, so the agency is distributed throughout the multiple media. These TGardens explore open-ended questions like the following: what makes some time-based, responsive environments compelling, and others flat? How can people improvise gestures without words, that are individually or collectively meaningful? When and how is a movement intentional, (...) or collectively intentional? This paper introduces what has been at stake behind the experimental work: subjectivation, moving from technologies of representation to technologies of performance, and the potential for ethico-aesthetic novelty. (shrink)

Whereas using artificial intelligence (AI) to predict natural hazards is promising, applying a predictive policing algorithm (PPA) to predict human threats to others continues to be debated. Whereas PPAs were reported to be initially successful in Germany and Japan, the killing of Black Americans by police in the US has sparked a call to dismantle AI in law enforcement. However, although PPAs may statistically associate suspects with economically disadvantaged classes and ethnic minorities, the targeted groups they aim to protect are (...) often vulnerable populations as well (e.g., victims of human trafficking, kidnapping, domestic violence, or drug abuse). Thus, determining how to enhance the benefits of PPA while reducing bias through better management is important. In this paper, we propose a policy schema to address this issue. First, after clarifying relevant concepts, we examine major criticisms of PPAs and argue that some of them should be addressed. If banning AI or making it taboo is an unrealistic solution, we must learn from our errors to improve AI. We next identify additional challenges of PPAs and offer recommendations from a policy viewpoint. We conclude that the employment of PPAs should be merged into broader governance of the social safety net and audited publicly by parliament and civic society so that the unjust social structure that breeds bias can be revised. (shrink)

This work intends to solve the problem that the traditional education system cannot reasonably adjust the educational integration of children with the arrival of labor force in a short time, and support the education of migrant children in the education policy to integrate them into the local educational environment as soon as possible. Firstly, this work defines the surplus labor force and MC. Secondly, the principles of Artificial Intelligence and Deep Learning are introduced. Thirdly, it analyzes the education of MC (...) and relevant policies, and the data of the education effect of MC are collected and the evaluation effect model is built. Finally, the evaluation model of MC’s education effect is applied to test the effect of EP. The results show that using AI technology combined with DL technology to model the education effect of MC can establish an effective and accurate evaluation model of the education effect of MC, effectively evaluate the impact of local education policies on the education of MC, and give an effective effect analysis of relevant education policies in each period. The result of Adaptive Resonance Theory –Back Propagation algorithm is 65 ∼ 96%, which is much higher than the efficiency of traditional algorithms. This shows that the education integration evaluation model of MC based on AI technology and DL technology can effectively and accurately evaluate the integration effect of MC on the local education system, and then provide reference for local and even national adjustment of education policies. The results provide a new idea for the application of new technology in EP. (shrink)

Thinking, the process of considering or reasoning about something, is one of the most distinctive qualities that set humans apart from other species. Philosophers around the world, such as Socrates...

It is a platitude that belief is subject to a standard of correctness: a belief is correct if and only if it is true. But not all standards of correctness are authoritative or binding. Some standards of correctness may be arbitrary, unjustified or outrightly wrong. Given this, one challenge to proponents of the truth norm of belief, is to answer what Korsgaard (1996) calls ‘the normative question’. Is the truth norm of belief authoritative or binding regarding what one ought to (...) or may believe? If so, what grounds its authority? The aim of this paper is to offer a novel answer to the grounding challenge on a reason-based normative framework. I develop and defend a practice-based account of the truth norm, according to which, the authority of the truth norm of belief is grounded in what I call the T-practice, a justified social practice that functions to facilitate knowledge production, maintenance, and social cooperation. (shrink)

Aesthetic experiences play an important role in human culture and spiritual life and are closely related to aesthetic perception and appreciation of art, music, literature and natural landscapes. With the development of neuroscience and cognitive psychology, our understanding of aesthetic experiences continues to deepen; in this context, the study of neuroplasticity has attracted widespread attention. This study explores in detail how this process affects the perception of aesthetic cognition, thereby enhancing the aesthetic experience in several key ways. The study finds (...) that neuroplasticity plays a role in the evolution of an individual’s perception and appreciation of beauty, as it facilitates adjustments in perception, attention, emotion, and cross-perceptual integration based on individual experiences. These findings provide a theoretical basis for deepening the perception and appreciation of beauty and insights to better understand and advance the aesthetic experience provided by art, music and literature. Future research will explore how to maximise the use of neuroplasticity to enhance the quality and depth of the aesthetic experience, advance the field of aesthetic psychology and art research and further enrich and satisfy individuals’ perception and experience of beauty. (shrink)

Research investigating the underlying mechanisms and boundary conditions under which leader humility influences employee voice remains underdeveloped. Drawing from approach–inhibition theory of power and leader humility literature, we developed a moderated-mediation model in which personal sense of power (i.e., employees’ ability to influence other individuals such as their leader) was theorized as a unique mechanism underlining why employees feel motivated to speak up under the supervision of humble leaders. Additionally, the cultural value of power distance was proposed to be a (...) relevant boundary condition to influence such relationship. We tested the model using time-lagged supervisor–subordinate matched data. Results of mixed models analyses provided support for our hypotheses confirming that employees’ personal sense of power mediates the relationship between leader humility and employee voice, and such relationship was found to be stronger when employees’ power distance was lower rather than higher. (shrink)

This essay develops an inferential account of model explanation, based on Mauricio Suárez’s inferential conception of scientific representation and Alisa Bokulich’s counterfactual account of model explanation. It is suggested that the fact that a scientific model can explain is essentially linked to how a modeler uses an established model to make various inferences about the target system on the basis of results derived from the model. The inference practice is understood as a two-step activity, with the first step involving making (...) counterfactual statements about the model itself and the second step involving making hypothetical statements transferring over claims derived from the model onto the target. To illustrate how this two-step activity proceeds, an agent-based simulation model is discussed. (shrink)