In the mid‐twentieth century, theorists began seriously forecasting possibilities for artificial intelligence (AI). As related research gathered momentum and resources, the topic made impressions on public discourse. One effect was increasingly pointed emphasis on AI in popular narratives. Although considerably earlier thematic examples may be located, we can observe swelling and generally pessimistic threads of speculation in science fiction of the 1950s and 1960s. This discussion identifies some pertinent science fiction texts from that period, alongside public discussion arising (...) from contemporary research. One consistent theme is human receptiveness to the numinous , and the capacity to ascribe personality and even divinity to sufficiently impressive manifestations, even artificial ones. Science fiction has long contemplated such reactions, prefiguring today's anticipations of AIs that might abruptly develop themselves beyond any possible human comprehension or control. This body of exploratory projections is a useful resource for the engineers and philosophers currently grappling with realistic prospects for Western humanity's shifting conception of itself. (shrink)

The increasing diffusion of novel digital and online sociotechnical systems for arational behavioral influence based on Artificial Intelligence (AI), such as social media, microtargeting advertising, and personalized search algorithms, has brought about new ways of engaging with users, collecting their data and potentially influencing their behavior. However, these technologies and techniques have also raised concerns about the potential for manipulation, as they offer unprecedented capabilities for targeting and influencing individuals on a large scale and in a more subtle, (...) automated and pervasive manner than ever before. This paper, provides a narrative review of the existing literature on manipulation, with a particular focus on the role of AI and associated digital technologies. Furthermore, it outlines an account of manipulation based of four key requirements: intentionality, asymmetry of outcome, non-transparency and violation of autonomy. I argue that while manipulation is not a new phenomenon, the pervasiveness, automaticity, and opacity of certain digital technologies may raise a new type of manipulation, called “digital manipulation”. I call “digital manipulation” any influence exerted through the use of digital technology that is intentionally designed to bypass reason and to produce an asymmetry of outcome between the data processor (or a third party that benefits thereof) and the data subject. Drawing on insights from psychology, sociology, and computer science, I identify key factors that can make manipulation more or less effective, and highlight the potential risks and benefits of these technologies for individuals and society. I conclude that manipulation through AI and associated digital technologies is not qualitatively different from manipulation through human–human interaction in the physical world. However, some functional characteristics make it potentially more likely of evading the subject’s cognitive defenses. This could increase the probability and severity of manipulation. Furthermore, it could violate some fundamental principles of freedom or entitlement related to a person’s brain and mind domain, hence called neurorights. To this end, an account of digital manipulation as a violation of the neuroright to cognitive liberty is presented. (shrink)

Intelligent machines are no longer distant fantasies of the future or solely used for industrial purposes; they are real “living” things that operate similarly to humans with verbal and nonverbal communication capabilities. Humans see in such technology the horrifying dangers and the bliss enabled by the saving power. Entrenched in the emotions of hope and fear concerning intelligent machines, humans’ attitudes toward intelligent machines are not free of expectations, judgments, strategies, and selfish agendas. As the discovery of the New Worlds (...) has led to the development of an understanding of self as distinct from the other, narratives on intelligent robots have taken on similar forms of colonial discourse: contradictory manifestations of ethnocentrism (anthropocentrism) and exoticism. Similar to colonial encounters, the racialized Mechanical _Other_ operates like any other marginalized group. Colonial discourse often regards the mechanical _Other_ as both inferior yet exotic, which usually produces a mixed sense of blessing and curse, ambivalence composed of both desire and aversion. In these representations of machinic _otherness,_ one should not miss the fundamental injustice of creating the “Machinic Other” and imposing humans’ viewpoints. The field must expand the purview of intelligent machines to consider the larger historical and cultural forces shaping our understanding of who we are as reflected in the mirror of intelligent machines. (shrink)

In lieu of an abstract, here is a brief excerpt of the content: Reviewed by: The Myth or Elegy of Artificial Intelligence by Tingyang ZhaoXuejian Zhou (bio)Rengongzhineng de shenhua huo beige 人工智能的神話或悲歌 ( The Myth or Elegy of Artificial Intelligence). By Tingyang Zhao 趙汀陽. Beijing: The Commercial Press, 2022. Pp. 155. Hardcover RMB68, isbn 978-981-16-7749-6. In recent years, the philosophy of artificial intelligence has undoubtedly become one of the most popular topics. There is a (...) vague viewpoint suggesting that Chinese philosophy might face challenges in addressing the philosophical issues posed by artificial intelligence. However, compared to the past, when discussing Chinese philosophy today, we must acknowledge the significant impact of modern technology. While the contemporary world does indeed witness clashes of civilizations, individuals from various civilizations share a common predicament: their close entanglement with modern technology. Regarding the future of Chinese philosophy, it becomes crucial to direct our attention towards modern advancements like artificial intelligence and the diverse range of issues they introduce. In light of this context, Zhao Tingyang's 趙汀陽 new book, The Myth or Elegy of Artificial Intelligence, presents us with a fresh perspective. In this book, Zhao primarily delves into the philosophical issues surrounding Super Artificial Intelligence, a subject regarded as both a metaphysical and a political problem. This notion refers to artificial intelligence that surpasses general artificial intelligence in terms of functionality, and possesses self-consciousness. Therefore, "myth" refers to the myth of the emergence of Super Artificial Intelligence disrupting people's subjectivity, giving rise to a new myth of artificial intelligence. Conversely, the term "elegy" embodies the crisis in human destiny that stems from such profound changes, which will lead to an ontological revolution in human existence. This suggests that within the narrative of artificial intelligence's myth, there lies the elegy of humanity (p. 4). The intricate interplay between these two realms of myth and elegy vividly showcases the value of Chinese philosophy. The book consists of a total of ten chapters. In Chapter 1, Zhao initially presents a thought-provoking question. With the rapid advancement of artificial intelligence humanity is faced with a novel ontological event, where the existence of artificial intelligence could potentially jeopardize human existence. This presents an ontological problem of "de-existence" (p. 8). As current artificial intelligence remains within the domain of the Turing machine concept and lacks subjectivity, it cannot effectively engage in matters involving self-correlation or [End Page 1] infiniteness. However, if artificial intelligence evolves into a super Turing machine endowed with subjectivity and free will, it could gain the capacity to modify its own programs and societal norms based on its needs or maximal benefits. This scenario introduces the possibility of a crisis in human existence, where the very existence of humanity is put at risk (pp. 17-23). In Chapter 2, Zhao analyzes the safety conditions of artificial intelligence and proposes the need to establish self-destruct mechanisms for Super Artificial Intelligence to ensure the status of human existence (pp. 34-38). Interestingly, in this context, Zhao connects artificial intelligence with the concept of Tianxia 天下 ("all under heaven"), implying that in order to control capital and power, the world needs a new form of politics, namely, a Tianxia 天下 system. Tianxia 天下 represents a world system that ensures world peace and the shared interests of people in a multicultural context, a non-exclusive system defining the world beyond any particular entity. According to Zhao, only a Tianxia 天下 system can manage the technological risks of the world (p. 39). Theoretically (hopefully in practice as well), a significant application of the Tianxia 天下 system would be to use global authority to limit any high-risk behaviors. Based on the first two chapters, it becomes apparent that the dangers related to artificial intelligence do not lie in its current capabilities, but in its potential for self-consciousness. For this reason, in Chapter 3, Zhao analyzes this issue further. In his view, once artificial intelligence possesses the ability for self-reflection, it will become possible for it to transform its own system and create new rules. Especially if artificial intelligence invents a universal language of its own, equivalent to human natural language, then all program systems could be reinterpreted, reconstructed, and redefined using this universal language (pp. 47-52). Furthermore, if... (shrink)

This book provides an overview of computer techniques and tools — especially from artificial intelligence (AI) — for handling legal evidence, police intelligence, crime analysis or detection, and forensic testing, with a sustained discussion of methods for the modelling of reasoning and forming an opinion about the evidence, methods for the modelling of argumentation, and computational approaches to dealing with legal, or any, narratives. By the 2000s, the modelling of reasoning on legal evidence has emerged as a (...) significant area within the well-established field of AI & Law. An overview such as this one has never been attempted before. It offers a panoramic view of topics, techniques and tools. It is more than a survey, as topic after topic, the reader can get a closer view of approaches and techniques. One aim is to introduce practitioners of AI to the modelling legal evidence. Another aim is to introduce legal professionals, as well as the more technically oriented among law enforcement professionals, or researchers in police science, to information technology resources from which their own respective field stands to benefit. Computer scientists must not blunder into design choices resulting in tools objectionable for legal professionals, so it is important to be aware of ongoing controversies. A survey is provided of argumentation tools or methods for reasoning about the evidence. Another class of tools considered here is intended to assist in organisational aspects of managing of the evidence. Moreover, tools appropriate for crime detection, intelligence, and investigation include tools based on link analysis and data mining. Concepts and techniques are introduced, along with case studies. So are areas in the forensic sciences. Special chapters are devoted to VIRTOPSY (a procedure for legal medicine) and FLINTS (a tool for the police). This is both an introductory book (possibly a textbook), and a reference for specialists from various quarters. (shrink)

Dialogue systems, from Virtual Personal Assistants such as Siri, Cortana, and Alexa to state-of-the-art systems such as BlenderBot3 and ChatGPT, are already widely available, used in a variety of applications, and are increasingly part of many people’s lives. However, the task of enabling them to use empathetic language more convincingly is still an emerging research topic. Such systems generally make use of complex neural networks to learn the patterns of typical human language use, and the interactions in which the systems (...) participate are usually mediated either via interactive text-based or speech-based interfaces. In human–human interaction, empathy has been shown to promote prosocial behaviour and improve interaction. In the context of dialogue systems, to advance the understanding of how perceptions of empathy affect interactions, it is necessary to bring greater clarity to how empathy is measured and assessed. Assessing the way dialogue systems create perceptions of empathy brings together a range of technological, psychological, and ethical considerations that merit greater scrutiny than they have received so far. However, there is currently no widely accepted evaluation method for determining the degree of empathy that any given system possesses (or, at least, appears to possess). Currently, different research teams use a variety of automated metrics, alongside different forms of subjective human assessment such as questionnaires, self-assessment measures and narrative engagement scales. This diversity of evaluation practice means that, given two DSs, it is usually impossible to determine which of them conveys the greater degree of empathy in its dialogic exchanges with human users. Acknowledging this problem, the present article provides an overview of how empathy is measured in human–human interactions and considers some of the ways it is currently measured in human–DS interactions. Finally, it introduces a novel third-person analytical framework, called the Empathy Scale for Human–Computer Communication (ESHCC), to support greater uniformity in how perceived empathy is measured during interactions with state-of-the-art DSs. (shrink)

Socialist courts are supposed to apply the law, not make it, and socialist legality denies judicial decisions any precedential status. In 2011, the Chinese Supreme People’s Court designated selected decisions as Guiding Cases to be referred to by all judges when adjudicating similar disputes. One decade on, the paucity of citations to Guiding Cases has been taken as demonstrating the incongruity of case-based adjudication and the socialist legal tradition. Citations are, however, an imperfect measure of influence. Reproduction of language uniquely (...) traceable to Guiding Cases can also be evidence of their impact on judicial decision-making. We employ a local alignment tool to detect unattributed text reuse of Guiding Cases in local court decisions. Our findings suggest that Guiding Cases are more consequential than commonly assumed, thereby complicating prevailing narratives about the antagonism of socialist legality to case law. (shrink)

Autonomous vehicles (AV) offer promising benefits to society in terms of safety, environmental impact and increased mobility. However, acute challenges persist with any novel technology, inlcuding the perceived risks and trust underlying public acceptance. While research examining the current state of AV public perceptions and future challenges related to both societal and individual barriers to trust and risk perceptions is emerging, it is highly fragmented across disciplines. To address this research gap, by using the Web of Science database, our study (...) undertakes a bibliometric and performance analysis to identify the conceptual and intellectual structures of trust and risk narratives within the AV research field by investigating engineering, social sciences, marketing, and business and infrastructure domains to offer an interdisciplinary approach. Our analysis provides an overview of the key research area across the search categories of ‘trust’ and ‘risk’. Our results show three main clusters with regard to trust and risk, namely, behavioural aspects of AV interaction; uptake and acceptance; and modelling human–automation interaction. The synthesis of the literature allows a better understanding of the public perception of AV and its historical conception and development. It further offers a robust model of public perception in AV, outlining the key themes found in the literature and, in turn, offers critical directions for future research. (shrink)

The apparent downsides of opaque algorithms has led to a demand for explainable AI (XAI) methods by which a user might come to understand why an algorithm produced the particular output it did, given its inputs. Patients, for example, might find that the lack of explanation of the process underlying the algorithmic recommendations for diagnosis and treatment hinders their ability to provide informed consent. This paper examines the impact of two factors on user perceptions of explanations for AI systems in (...) medical contexts. The factors considered were the stakes of the decision—high versus low—and the decision source—human versus AI. 484 participants were presented with vignettes in which medical diagnosis and treatment plan recommendations were made by humans or by AI. Separate vignettes were used for high stakes scenarios involving life-threatening diseases, and low stakes scenarios involving mild diseases. In each vignette, an explanation for the decision was given. Four explanation types were tested across separate vignettes: no explanation, counterfactual, causal and a novel ‘narrative-based’ explanation, not previously considered. This yielded a total of 16 conditions, of which each participant saw only one. Individuals were asked to evaluate the explanations they received based on helpfulness, understanding, consent, reliability, trust, interests and likelihood of undergoing treatment. We observed a main effect for stakes on all factors and a main effect for decision source on all factors except for helpfulness and likelihood to undergo treatment. While we observed effects for explanation on helpfulness, understanding, consent, reliability, trust and interests, we by and large did not see any differences between the effects of explanation types. This suggests that the effectiveness of explanations may not depend on type of explanation but instead, on the stakes and decision source. (shrink)

Bayesian models of legal arguments generally aim to produce a single integrated model, combining each of the legal arguments under consideration. This combined approach implicitly assumes that variables and their relationships can be represented without any contradiction or misalignment, and in a way that makes sense with respect to the competing argument narratives. This paper describes a novel approach to compare and ‘average’ Bayesian models of legal arguments that have been built independently and with no attempt to make them consistent (...) in terms of variables, causal assumptions or parameterization. The approach involves assessing whether competing models of legal arguments are explained or predict facts uncovered before or during the trial process. Those models that are more heavily disconfirmed by the facts are given lower weight, as model plausibility measures, in the Bayesian model comparison and averaging framework adopted. In this way a plurality of arguments is allowed yet a single judgement based on all arguments is possible and rational. (shrink)