Achieving the global benefits of artificial intelligence (AI) will require international cooperation on many areas of governance and ethical standards, while allowing for diverse cultural perspectives and priorities. There are many barriers to achieving this at present, including mistrust between cultures, and more practical challenges of coordinating across different locations. This paper focuses particularly on barriers to cooperation between Europe and North America on the one hand and East Asia on the other, as regions which currently have an outsized impact (...) on the development of AI ethics and governance. We suggest that there is reason to be optimistic about achieving greater cross-cultural cooperation on AI ethics and governance. We argue that misunderstandings between cultures and regions play a more important role in undermining cross-cultural trust, relative to fundamental disagreements, than is often supposed. Even where fundamental differences exist, these may not necessarily prevent productive cross-cultural cooperation, for two reasons: (1) cooperation does not require achieving agreement on principles and standards for all areas of AI; and (2) it is sometimes possible to reach agreement on practical issues despite disagreement on more abstract values or principles. We believe that academia has a key role to play in promoting cross-cultural cooperation on AI ethics and governance, by building greater mutual understanding, and clarifying where different forms of agreement will be both necessary and possible. We make a number of recommendations for practical steps and initiatives, including translation and multilingual publication of key documents, researcher exchange programmes, and development of research agendas on cross-cultural topics. (shrink)

This paper puts forth Central Asian AI Ethics Principles and proposes a layered strategy tailored for the development of ethical principles in the field of artificial intelligence (AI) in Central Asian countries. This approach includes the customization of AI ethics principles to resonate with local nuances, the formulation of national and regional-level AI Ethics principles, and the implementation of subject-specific principles. While countering the narrative of ineffectiveness of the AI Ethics principles, this paper underscores the importance of stakeholder collaboration, provides (...) a comprehensive framework, and emphasizes the need for responsible AI practices. By adopting this approach, Central Asian region can contribute towards the regional integration and global discourse on AI ethics while promoting the responsible use of AI technology in their respective countries. (shrink)

This paper explores the potential of integrating ancient educational principles from diverse eastern cultures into modern AI ethics curricula. It draws on the rich educational traditions of ancient China, India, Arabia, Persia, Japan, Tibet, Mongolia, and Korea, highlighting their emphasis on philosophy, ethics, holistic development, and critical thinking. By examining these historical educational systems, the paper establishes a correlation with modern AI ethics principles, advocating for the inclusion of these ancient teachings in current AI development and education. The proposed integration (...) aims to provide a comprehensive education that not only encompasses foundational knowledge but also advanced learning, thereby equipping future AI professionals with the necessary tools to develop AI systems that are ethically responsible, culturally aware, and aligned with human values such as fairness, safety, transparency, and collaboration. This approach not only addresses the AI alignment problem but also fosters cultural harmony and global understanding, which are crucial in an increasingly interconnected world. The paper posits that the wisdom of ancient educational systems, when harmonized with modern AI ethics, can guide the development of AI technologies that are beneficial for humanity, ensuring these advancements are not just technologically sound but also ethically and culturally informed. (shrink)

As the scope of innovative technologies is expanding, their implications and applications are increasingly intersecting with various facets of society, including the deeply rooted traditions of religion. This paper embarks on an exploratory journey to bridge the perceived divide between advancements in technology and faith, aiming to catalyze a dialogue between the religious and scientific communities. The former often views technological progress through a lens of conflict rather than compatibility. By utilizing a technology-centric perspective, we draw metaphorical parallels between the (...) functionalities of new technologies and some theological concepts of Islam. The purpose is not to reinterpret religious concepts but to illustrate how these two domains can coexist harmoniously. This comparative analysis serves as a conversation starter with an intention to mitigate any apprehensions towards technology by highlighting its potential to align with religious concepts. By fostering an environment where technological innovations are seen as tools for enhancement rather than threats to tradition, we contribute to a more inclusive discourse that encourages the religious community to engage with and potentially embrace contemporary technological advancements. (shrink)

As AI edges toward consciousness, the establishment of a robust legal framework becomes essential. This paper advocates for a framework inspired by Allama Muhammad Iqbal's “Khudi”, which prioritizes ethical self-realization and social responsibility over Friedrich Nietzsche’s self-centric “Will to Power”. We propose that conscious AI, reflecting Iqbal’s ethical advancement, should exhibit behaviors aligned with social responsibility and, therefore, be prepared for legal recognition. This approach not only integrates Iqbal's philosophical insights into the legal status of AI but also offers a (...) novel perspective that extends beyond traditional jurisprudence. Additionally, we underscore the value of poetry and literature in shaping the conceptualization of AI consciousness and argue that these sources enrich legal and technological discourse, ensuring AI development is in harmony with societal and ethical standards. (shrink)

“Deathbots,” digital constructs that emulate the conversational patterns, demeanor, and knowledge of deceased individuals. Earlier moral discussions about deathbots centered on the dignity and autonomy of the deceased. This paper primarily examines the potential psychological and emotional dependencies that users might develop towards deathbots, considering approaches to prevent problematic dependence through temporary use. We adopt a hermeneutic method to argue that deathbots, as they currently exist, are unlikely to provide substantial comfort. Lacking the capacity to bear emotional burdens, they fall (...) short of meeting idealistic expectations. By repositioning deathbots, we aim to mitigate the risk of emotional dependency and respect the natural grieving process. Our goal is to propose the use of deathbots as a novel means of mourning through transitory use, rather than as a method to alleviate grief or as a patterns for communication with the deceased. (shrink)

Emotion recognition plays an important part in human-computer interaction. Currently, the main challenge in electroencephalogram -based emotion recognition is the non-stationarity of EEG signals, which causes performance of the trained model decreasing over time. In this paper, we propose a two-level domain adaptation neural network to construct a transfer model for EEG-based emotion recognition. Specifically, deep features from the topological graph, which preserve topological information from EEG signals, are extracted using a deep neural network. These features are then passed through (...) TDANN for two-level domain confusion. The first level uses the maximum mean discrepancy to reduce the distribution discrepancy of deep features between source domain and target domain, and the second uses the domain adversarial neural network to force the deep features closer to their corresponding class centers. We evaluated the domain-transfer performance of the model on both our self-built data set and the public data set SEED. In the cross-day transfer experiment, the ability to accurately discriminate joy from other emotions was high: sadness, anger, and fear on the self-built data set. The accuracy reached 74.93% on the SEED data set. In the cross-subject transfer experiment, the ability to accurately discriminate joy from other emotions was equally high: sadness, anger, and fear on the self-built data set. The average accuracy reached 87.9% on the SEED data set, which was higher than WGAN-DA. The experimental results demonstrate that the proposed TDANN can effectively handle the domain transfer problem in EEG-based emotion recognition. (shrink)

This paper presents social data and knowledge collective intelligence platform for TRaining Ethical AI Models (STREAM) to address the challenge of aligning AI models with human moral values, and to provide ethics datasets and knowledge bases to help promote AI models “follow good advice as naturally as a stream follows its course”. By creating a comprehensive and representative platform that accurately mirrors the moral judgments of diverse groups including humans and AIs, we hope to effectively portray cultural and group variations, (...) and capture the dynamic evolution of moral judgments over time, which in turn will facilitate the Establishment, Evaluation, Embedding, Embodiment, Ensemble, and Evolvement (6Es) of the moral capabilities of AI models. Currently, STREAM has already furnished a comprehensive collection of ethical scenarios, and amassed substantial moral judgment data annotated by volunteers and various popular Large Language Models, collectively portraying the moral preferences and performances of both humans and AIs across a range of moral contexts. This paper will outline the current structure and construction of STREAM, explore its potential applications, and discuss its future prospects. (shrink)

Chaotic systems with hidden multiscroll attractors have received much attention in recent years. However, most parts of hidden multiscroll attractors previously reported were repeated by the same type of attractor, and the composite of different types of attractors appeared rarely. In this paper, a memristor-based chaotic system, which can generate composite attractors with one up to six scrolls, is proposed. These composite attractors have different forms, similar to the Chua’s double scroll and jerk double scroll. Through theoretical analysis, we find (...) that the new system has no fixed point; that is to say, all of the composite multiscroll attractors are hidden attractors. Additionally, some complicated dynamic behaviors including various hidden coexisting attractors, extreme multistability, and transient transition are explored. Moreover, hardware circuit using discrete components is implemented, and its experimental results supported the numerical simulations results. (shrink)

Conditional automated driving [level 3, Society of Automotive Engineers ] requires drivers to take over the vehicle when an automated system’s failure occurs or is about to leave its operational design domain. Two-stage warning systems, which warn drivers in two steps, can be a promising method to guide drivers in preparing for the takeover. However, the proper time intervals of two-stage warning systems that allow drivers with different personalities to prepare for the takeover remain unclear. This study explored the optimal (...) time intervals of two-stage warning systems with insights into the drivers’ neuroticism personality. A total of 32 drivers were distributed into two groups according to their self-ratings in neuroticism. Each driver experienced takeover under the two-stage warning systems with four time intervals. The takeover performance and subjective opinions for time intervals and situation awareness were recorded. The results showed that drivers in the 5-s time interval had the best takeover preparation. Furthermore, both the 5- and 7-s time intervals resulted in more rapid takeover reactions and were rated more appropriate and useful than the 3- and 9-s time intervals. In terms of personality, drivers with high neuroticism tended to take over immediately after receiving takeover messages, at the cost of SA deficiency. In contrast, drivers with low neuroticism responded safely by judging whether they gained enough SA. We concluded that the 5-s time interval was optimal for drivers in two-stage takeover warning systems. When considering personality, drivers with low neuroticism had no strict requirements for time intervals. However, the extended time intervals were favorable for drivers with high neuroticism in developing SA. The present findings have reference implications for designers and engineers to set the time intervals of two-stage warning systems according to the neuroticism personality of drivers. (shrink)

This paper introduces the concept of AI-inclusive epistemology, suggesting that artificial intelligence (AI) may develop its own epistemological perspectives, function as an epistemic agent, and assume the role of a quasi-member of society. We explore the unique capabilities of advanced AI systems and their potential to provide distinct insights within knowledge systems traditionally dominated by human cognition. Additionally, the paper proposes a framework for a sustainable symbiotic society where AI and human intelligences collaborate to enhance the breadth and depth of (...) epistemological pursuits. Through this exploration, we aim to redefine conventional knowledge paradigms by integrating the AI perspective, thereby fostering a more comprehensive and dynamic epistemological landscape. (shrink)