The ability to interact in a natural language profoundly changes devices’ interfaces and potential applications of speaking technologies. Concurrently, this phenomenon challenges our mainstream theories of knowledge, such as how to analyze linguistic outputs of devices under existing anthropocentric theoretical assumptions. In section 1, I present the topic of machines that speak, connecting between Descartes and Generative AI. In section 2, I argue that accepted testimonial theories of knowledge and justification commonly reject the possibility that a speaking technological artifact can (...) give testimony. In section 3, I identify three assumptions underlying the view that rejects conversational AIs – AI-based technologies that converse, as testifiers: conversational AIs (1) lack intentions, (2) cannot be normatively assessed, and (3) cannot constitute an object in trust relations, while humans can. In section 4, I propose the concept ‘AI-testimony’ for analyzing outputs of conversational AIs, suggesting three conditions for technologies to deliver AI-testimony: (1) content is propositional, (2) generated and delivered with no other human directly involved, (3) the output is perceived as phenomenologically similar to that of a human. I conclude that this concept overcomes the limitations of the anthropocentric concept of testimony, opening future directions of research without associating conversational AIs with human-like agency. (shrink)

Speaking with conversational AIs, technologies whose interfaces enable human-like interaction based on natural language, has become a common phenomenon. During these interactions, people form their beliefs due to the say-so of conversational AIs. In this paper, I consider, and then reject, the concepts of testimony-based beliefs and instrument-based beliefs as suitable for analysis of beliefs acquired from these technologies. I argue that the concept of instrument-based beliefs acknowledges the non-human agency of the source of the belief. However, the (...) analysis focuses on perceiving signs and indicators rather than content expressed in natural language. At the same time, the concept of testimony-based beliefs does refer to natural language propositions, but there is an underlying assumption that the agency of the testifier is human. To fill the lacuna of analyzing belief acquisition from conversational AIs, I suggest a third concept: technology-based beliefs. It acknowledges the non-human agency-status of the originator of the belief. Concurrently, the focus of analysis is on the propositional content that forms the belief. Filling the lacuna enables analysis that considers epistemic, ethical, and social issues of conversational AIs without excluding propositional content or compromising accepted assumptions about the agency of technologies. (shrink)

The introduction of chatGPT illustrates the rapid developments within Conversational Artificial Intelligence (CAI) technologies (Gordijn and Have 2023). Ethical reflection and analysis of CAI are c...

With the public release of the large language model-driven ChatGPT in November 2022, the potential for Conversational Artificial Intelligence (CAI) has once again catapulted into the spotlight. CAI...

Sedlakova and Traschel (2023) propose limiting the scope and capabilities of psychotherapy-delivering conversational artificial intelligence (CAI), as (1) they deceive some users into thinking they...

One of the central questions in the epistemology of conversational AIs is how to classify the beliefs acquired from them. Two promising candidates are instrument-based and testimony-based beliefs. However, the category of instrument-based beliefs faces an intrinsic problem, and a challenge arises in its application. On the other hand, relying solely on the category of testimony-based beliefs does not encompass the totality of our practice of using conversational AIs. To address these limitations, I propose a novel classification of (...) beliefs that shifts the focus from the properties of the conversational AIs themselves to how recipients perceive AI output, specifically whether they take the output at face value. The proposed categories are beliefs by regarding as instruments and beliefs by regarding as testifiers. By using these complementary categories, a more comprehensive understanding of beliefs acquired from conversational AIs can be achieved while avoiding the problems associated with the traditional classification. (shrink)

Conversational agents (CA) are thought to be promising for psychotherapy because they give the impression of being able to engage in conversations with human users. However, given the high risk for therapy patients who are already in a vulnerable situation, there is a need to investigate the extent to which CA are able to contribute to therapy goals and to discuss CA’s limitations, especially in complex cases. In this paper, we understand psychotherapy as a way of dealing with existential (...) situations and position CAs in the context of the therapeutic experience of patients. This experience is determined by the patient’s unique personal context and specific therapy goals. We suggest that psychotherapy is a fundamentally dialogical activity, because it crucially involves work on the self and one’s self-narrative. This brings us to our central question: is it possible for CAs to engage in a productive therapeutic dialogue, given their limitations as epistemic agents? We will discuss several of those limitations, show how these undermine the possibility of engaging in a therapeutic dialogue, and illustrate those limitations through discussions of the cases of grief and abuse. (shrink)

Emotions are an integral part of human cognition and they guide not only our understanding of the world but also our actions within it. As such, whether we soothe or flame an emotion is not inconsequential. Recent work in conversational AI has focused on responding empathetically to users, validating and soothing their emotions without a real basis. This AI-aided emotional regulation can have negative consequences for users and society, tending towards a one-noted happiness defined as only the absence of (...) "negative" emotions. We argue that we must carefully consider whether and how to respond to users' emotions. (shrink)

According to Russell and Norvig’s (2009) classification, Artificial Intelligence (AI) is the field that aims at building systems which either think rationally, act rationally, think like humans, or...

Sedlakova and Trachsel (2023) identify a major benefit of conversational artificial intelligence (CAI) in psychotherapy as its ability to expand access to mental healthcare for vulnerable populatio...

Obtaining informed consent from patients prior to a medical or surgical procedure is a fundamental part of safe and ethical clinical practice. Currently, it is routine for a significant part of the consent process to be delegated to members of the clinical team not performing the procedure (eg, junior doctors). However, it is common for consent-taking delegates to lack sufficient time and clinical knowledge to adequately promote patient autonomy and informed decision-making. Such problems might be addressed in a number of (...) ways. One possible solution to this clinical dilemma is through the use of conversational artificial intelligence using large language models (LLMs). There is considerable interest in the potential benefits of such models in medicine. For delegated procedural consent, LLM could improve patients’ access to the relevant procedural information and therefore enhance informed decision-making.In this paper, we first outline a hypothetical example of delegation of consent to LLMs prior to surgery. We then discuss existing clinical guidelines for consent delegation and some of the ways in which current practice may fail to meet the ethical purposes of informed consent. We outline and discuss the ethical implications of delegating consent to LLMs in medicine concluding that at least in certain clinical situations, the benefits of LLMs potentially far outweigh those of current practices. (shrink)

Despite its elusiveness as a concept, ‘artificial intelligence’ (AI) is becoming part of everyday life, and a range of empirical and methodological approaches to social studies of AI now span many disciplines. This article reviews the scope of ethnomethodological and conversation analytic (EM/CA) approaches that treat AI as a phenomenon emerging in and through the situated organization of social interaction. Although this approach has been very influential in the field of computational technology since the 1980s, AI has only recently emerged (...) as such a pervasive part of daily life to warrant a sustained empirical focus in EM/CA. Reviewing over 50 peer-reviewed publications, we find that the studies focus on various social and group activities such as task-oriented situations, semi-experimental setups, play, and everyday interactions. They also involve a range of participant categories including children, older participants, and people with disabilities. Most of the reviewed studies apply CA’s conceptual apparatus, its approach to data analysis, and core topics such as turn-taking and repair. We find that across this corpus, studies center on three key themes: openings and closing the interaction, miscommunication, and non-verbal aspects of interaction. In the discussion, we reflect on EM studies that differ from those in our corpus by focusing on praxeological respecifications of AI-related phenomena. Concurrently, we offer a critical reflection on the work of literature reviewing, and explore the tortuous relationship between EM and CA in the area of research on AI. (shrink)

Generative Artificial Intelligence (AI) tools produce hallucinations exposing developers and users to a myriad of liabilities in courts. Given the absence of strict laws and regulations structuring how Generative AI content interact with potential allegations of defamation, libel, and slander, judges and attorneys are left with the semiotics of the fragmented articles and rules in each system attempting to settle such cases. The endless interpretations of written and non-verbal signs in the law across the world constitutes a new realm for (...) legal semiotics in the area of Generative AI and defamation. The present analysis examines existing civil liability articles in the Jordanian code to shed light on the litigation and defenses afforded in the defamation realm with respect to Generative AI content. The key finding is that like other countries, civil codes in Jordan are outdated concerning Generative AI content opening a plethora of liability scenarios in libel or slander cases. More importantly, the exercise of semiotic interpretation generates several defenses salvaging users and developers under strict sets of conditions. In sum, new amendments and updated legislative frameworks are needed to protect the healthy development of Generative AI while preserving citizens from damaging defamation, libel, and slander. (shrink)

Conversational artificial intelligence (CAI) presents many opportunities in the psychotherapeutic landscape—such as therapeutic support for people with mental health problems and without access to care. The adoption of CAI poses many risks that need in-depth ethical scrutiny. The objective of this paper is to complement current research on the ethics of AI for mental health by proposing a holistic, ethical, and epistemic analysis of CAI adoption. First, we focus on the question of whether CAI is rather a tool or (...) an agent. This question serves as a framework for the subsequent ethical analysis of CAI focusing on topics of (self-) knowledge, (self-)understanding, and relationships. Second, we propose further conceptual and ethical analysis regarding human-AI interaction and argue that CAI cannot be considered as an equal partner in a conversation as is the case with a human therapist. Instead, CAI’s role in a conversation should be restricted to specific functions. (shrink)

Apocalyptic AI, the hope that we might one day upload our minds into machines and live forever in cyberspace, has become commonplace. This view now affects robotics and AI funding, play in online games, and philosophical and theological conversations about morality and human dignity.

This study investigates the relationship between the usage of artificial intelligence (AI), specifically AI-based personalized recommendations (AI-PR), and its impact on consumers’ green product awareness (GPA) during online shopping. Recognizing that AI’s influence alone may not significantly affect green buying behaviours, we introduce emotional intelligence (EI) as a moderator to better understand human impact when using AI. The research framework is built upon the Interactive Recommendation Agents and the SOBC framework. A self-administered survey was conducted with 403 respondents, and the (...) data were analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The findings reveal that AI and AI-PR positively impact GPA, with partial mediation observed among the variables. Furthermore, emotional intelligence positively moderates the relationship between perceived AI usage and GPA. Specifically, individuals with higher emotional intelligence exhibit a stronger positive association between AI usage and GPA. Conversely, emotional intelligence negatively moderates the relationship between AI-based personalized recommendations and GPA, indicating that higher EI weakens the relationship between AI-PR and GPA, while lower EI strengthens it. The implications of this study are significant for marketers and retailers aiming to utilize AI-based personalized recommendations to encourage green behaviour and contribute to a sustainable future. These insights can help them understand the complex dynamics between AI, emotional intelligence, green product awareness, and behavioural intentions. (shrink)

The problem considered in this chapter emerges from the tension we find when looking at the design and architecture of chatbots on the one hand and their conversational aptitude on the other. In the way that LLM chatbots are designed and built, we have good reason to suppose they don't possess second-order capacities such as intention, belief or knowledge. Yet theories of conversation make great use of second-order capacities of speakers and their audiences to explain how aspects of interaction (...) succeed. As we can all bear witness to now though, at the point of use chatbots appear capable of performing language tasks at a level close to that of humans. This creates a tension when we consider something like, for example, the classic Gricean theory of implicature. On a broad summary of this type of account, to utter p and implicate q requires the reflexive occurrence of an audience supposing a speaker believes that q, and the speaker believing that their audience can determine they believe it when they utter p. So taken at face value, if a chatbot doesn’t have the capacity for belief, then either in their role as speaker or audience, they would not seem capable of either generating or comprehending implicatures. Yet on the surface it does seem that chatbots are capable of dealing with (some) implicatures, and as such it raises questions about how we should then correlate this with what we think occurs in cases of implicature with chatbots. (shrink)

Healthcare data warehousing test automation is becoming a success through the help of AI-based technology that results in accuracy, efficiency, and data integrity on the automated test. The one central to personalized patient data that forms the core of traditional data warehousing solutions frequently faces problems of complexity and dissatisfaction. Deep learning with test automation solutions makes data ingestion, processing, and testing conversant through machine learning algorithms [1]. These systems encompass separate acts such as testing for data integration, testing the (...) quality of data as well as performance testing removing the factors of time and human error. In healthcare organizations, this approach delivers the message of enhancing quality, compliance and organizational efficiency in value-based care and precision medicine initiatives. As such, artificial intelligence tools can be used to address the essential issues regarding data warehousing, and this can in turn enhance decision-making, and thus, enhance the health of patient and the overall population. (shrink)

This book offers a first glimpse into contemporary African Philosophical thought, which covers issues related to the mind-body relationships, the problem of consciousness, the ethics of artificial intelligence, the meaning of life and other topics. Taking inspiration from the conversational tradition in African philosophy, this book not only engages with and takes inspiration from traditional African thought, but also engages with philosophical views outside the philosophical tradition in a bid to present a holistic understanding of the problems that are (...) central to the book. The volume is relevant for professional African philosophers, philosophers of mind, philosophers of AI, undergraduate and postgraduate philosophy students, and African Studies scholars. (shrink)

Conversation of a particular sort holds the key to learning. I argue here that peer to peer conversation promotes two features that are essential to progressive learning, namely ‘contestation’ and ‘communication.’ Traditional learning is principally concerned with whether students have reached a standard of knowledge and skill prescribed by some authority whereas progressive learning values less predictable outcomes and interests itself on process rather than end product. Machine-based learning such as ChatGPT, if not skilfully used, hides the flexibility essential to (...) progressive learning and entices learners away from vagueness where much creativity begins. Even if ChatGPT presents itself as ‘conversational’, I argue here that this ‘conversation’ is contrived as a medium that lacks these two key ingredients. The knowledge stance presented in ChatGPT can easily obscure the fragility of human learning. Educators need to wonder about this situation. My argument follows the paths of Dewey and Mead and uses Latour and Habermas to sketch out these two important elements that feature typically in collaborative learning. This article concludes by following Dignum to note a real need for computer engineers to have an educational grounding in the arts and humanities. Indeed, the separation of the Arts from Science in Higher Education can no longer be justified in the age of AI. (shrink)

Artificial intelligence (AI) has sparked interest in various areas, including marketing. However, this exhilaration is being tempered by growing concerns about the moral and legal implications of using AI in marketing. Although previous research has revealed various ethical and legal issues, such as algorithmic discrimination and data privacy, there are no definitive answers. This paper aims to fill this gap by investigating AI’s ethical and legal concerns in marketing and suggesting feasible solutions.,The paper synthesises information from academic articles, industry reports, (...) case studies and legal documents through a thematic literature review. A qualitative analysis approach categorises and interprets ethical and legal challenges and proposes potential solutions.,The findings of this paper raise concerns about ethical and legal challenges related to AI in the marketing area. Ethical concerns related to discrimination, bias, manipulation, job displacement, absence of social interaction, cybersecurity, unintended consequences, environmental impact, privacy and legal issues such as consumer security, responsibility, liability, brand protection, competition law, agreements, data protection, consumer protection and intellectual property rights are discussed in the paper, and their potential solutions are discussed.,Notwithstanding the interesting insights gathered from this investigation of the ethical and legal consequences of AI in marketing, it is important to recognise the limits of this research. Initially, the focus of this study is confined to a review of the most important ethical and legal issues pertaining to AI in marketing. Additional possible repercussions, such as those associated with intellectual property, contracts and licencing, should be investigated more deeply in future studies. Despite the fact that this study gives various answers and best practices for tackling the stated ethical and legal concerns, the viability and efficacy of these solutions may differ depending on the context and industry. Thus, more research and case studies are required to evaluate the applicability and efficacy of these solutions in other circumstances. This research is mostly based on a literature review and may not represent the experiences or opinions of all stakeholders engaged in AI-powered marketing. Further study might involve interviews or surveys with marketing professionals, customers and other key stakeholders to offer a full knowledge of the practical difficulties and solutions. Because of the rapid speed of technical progress, AI’s ethical and regulatory ramifications in marketing are continually increasing. Consequently, this work should be a springboard for more research and continuing conversations on this subject.,This study’s findings have several practical implications for marketing professionals. Emphasising openness and explainability: Marketing professionals should prioritise transparency in their use of AI, ensuring that customers are fully informed about data collection and utilisation for targeted advertising. By promoting openness and explainability, marketers can foster customer trust and avoid the negative consequences of a lack of transparency. Establishing ethical guidelines: Marketing professionals need to develop ethical rules for the creation and implementation of AI-powered marketing strategies. Adhering to ethical principles ensures compliance with legal norms and aligns with the organisation’s values and ideals. Investing in bias detection tools and privacy-enhancing technology: To mitigate risks associated with AI in marketing, marketers should allocate resources to develop and implement bias detection tools and privacy-enhancing technology. These tools can identify and address biases in AI algorithms, safeguard consumer privacy and extract valuable insights from consumer data.,This study’s social implications emphasise the need for a comprehensive approach to address the ethical and legal challenges of AI in marketing. This includes adopting a responsible innovation framework, promoting ethical leadership, using ethical decision-making frameworks and conducting multidisciplinary research. By incorporating these approaches, marketers can navigate the complexities of AI in marketing responsibly, foster an ethical organisational culture, make informed ethical decisions and develop effective solutions. Such practices promote public trust, ensure equitable distribution of benefits and risk, and mitigate potential negative social consequences associated with AI in marketing.,To the best of the authors’ knowledge, this paper is among the first to explore potential solutions comprehensively. This paper provides a nuanced understanding of the challenges by using a multidisciplinary framework and synthesising various sources. It contributes valuable insights for academia and industry. (shrink)

This article poses a simple question: can AI lie? In response to this question, the article examines, as its point of inquiry, popular AI chatbots, such as, ChatGPT. In doing so, an examination of the psychoanalytic, philosophical, and technological significance of AI and its complexities are located in relation to the dynamics of truth, falsity, and deception. That is, by critically exploring the chatbot’s capacity to engage in natural language conversations and deliver contextually relevant responses, it is argued that what (...) distinguishes the AI chatbot from anthropocentric discussions, which suggest a form of conscious awareness in AI, is the importance of the lie—an importance which a psychoanalytic approach can reveal. Indeed, while AI technologies undoubtedly blur the line between lies and truth-speaking, in the case of the AI chatbot, it is detailed how such technology remains unable to lie authentically; or, in other words, is unable to lie like a human. For psychoanalysis, the capacity to lie bears witness to the unconscious, and, thus, plays an important role in determining the subject. It is for this reason that rather than uncritically accepting the chatbot’s authority—an authority that is easily reflected in its honest responses and frank admissions—a psychoanalytic (Lacanian) perspective can highlight the significance of the unconscious as a distorting factor in determining the subject. To help elucidate this argument, specific attention is given to introducing and applying Lacan’s subject of enunciation and subject of the enunciated. This is used to assert that what continues (for now) to set us apart from AI technology is not necessarily our ‘better knowledge’, but our capability to consciously engage in acts of falsehood that function to reveal the social nuances and significances of the lie. (shrink)

This proposal introduces a novel decision-making framework to advance safe economic activities in cyberspace. We focus on identifying anomalies within crypto-asset trading, recognized as potential sources of criminal activity, severely undermining the credibility of such assets. Detecting and mitigating such anomalies holds significant societal implications, particularly in fostering trust within blockchain networks. We aim to bolster the “social trust” inherent to blockchain technology by facilitating informed economic activities in cyberspace. To achieve this, we propose integrating two artificial intelligence (AI) systems (...) into a blockchain-based decentralized autonomous organization (DAO). The first AI application involves amalgamating various anomaly indicators, spanning from cluster coefficient, entropy, triangular motif analysis, correlation tensor analysis, loop component by Hodge decomposition, loop causality detection, network classification using graph Laplacian, and persistent homology analysis, into a comprehensive indicator using a Boltzmann machine. The second AI application entails deploying conversational AI to guide and support traders, aiding them in making informed trading decisions. This system is designed to alert DAO members to anomalies based on the integrated indicators, especially during massive price fluctuations. We operate under the assumption of close collaboration between governments, experts, traders, system developers, and operators to effectively organize DAOs. The primary technical challenge in our proposal lies in developing a wallet assisted by an intelligent software agent capable of safe interactions with traders within a unified DAO. With this organization, we envision fostering a global economic ecosystem where physical and cyber worlds converge, allowing democratic economic participation. (shrink)

Generative artificial intelligence (AI) has the potential to transform many aspects of scholarly publishing. Authors, peer reviewers, and editors might use AI in a variety of ways, and those uses might augment their existing work or might instead be intended to replace it. We are editors of bioethics and humanities journals who have been contemplating the implications of this ongoing transformation. We believe that generative AI may pose a threat to the goals that animate our work but could also be (...) valuable for achieving those goals. In the interests of fostering a wider conversation about how generative AI may be used, we have developed a preliminary set of recommendations for its use in scholarly publishing. We hope that the recommendations and rationales set out here will help the scholarly community navigate toward a deeper understanding of the strengths, limits, and challenges of AI for responsible scholarly work. (shrink)

The new wave of ‘foundation models’—general-purpose generative AI models, for production of text (e.g., ChatGPT) or images (e.g., MidJourney)—represent a dramatic advance in the state of the art for AI. But their use also introduces a range of new risks, which has prompted an ongoing conversation about possible regulatory mechanisms. Here we propose a specific principle that should be incorporated into legislation: that any organization developing a foundation model intended for public use must demonstrate a reliable detection mechanism for the (...) content it generates, as a condition of its public release. The detection mechanism should be made publicly available in a tool that allows users to query, for an arbitrary item of content, whether the item was generated (wholly or partly) by the model. In this paper, we argue that this requirement is technically feasible and would play an important role in reducing certain risks from new AI models in many domains. We also outline a number of options for the tool’s design, and summarize a number of points where further input from policymakers and researchers would be required. (shrink)

This paper presents an overview of the risks and benefits of Social AI, understood as conversational AI systems that cater to human social needs like romance, companionship, or entertainment. Section 1 of the paper provides a brief history of conversational AI systems and introduces conceptual distinctions to help distinguish varieties of Social AI and pathways to their deployment. Section 2 of the paper adds further context via a brief discussion of anthropomorphism and its relevance to assessment of human-chatbot (...) relationships. Section 3 of the paper provides a survey of potential and in some cases demonstrated harms associated with user interactions with Social AI systems. Finally, Section 4 discusses how the benefits and harms of Social AI can best be addressed, with a primary focus on how frameworks from AI ethics can inform their development. (shrink)

This article seeks to understand why femininity seems to be often present in artificial intelligence and tackle the questions that arise when this phenomenon is subject to closer inspection. It draws on a previous study on the relationship between gender and AI, complemented by an analysis of digital assistants such as Alexa, Cortana, Google Assistant and Siri that reveals how these entities tend to be feminized through their anthropomorphization, the tasks that they perform and their behavioural traits. Furthering this discussion, (...) this article addresses current trends of development of digital assistants and their stance towards gender, considering the functions or features that are being prioritized in AI evolution. It then focuses on the main questions raised by researchers and academics when examining the phenomenon and confronts these views with discussions around the feminization of AI in the context of online media coverage. This debate also highlights how common conceptions of AI and its portrayals of gender are influenced by bodies of fiction. Finally, the project Conversations with ELIZA seeks to comment on this phenomenon by ironically exposing and reinforcing common stereotypes and gender assumptions. In this manner, this study seeks to incite reflection on how artificial intelligence is reflecting our social and cultural views back to us. (shrink)

One of the challenges facing AI governance is the need for multiple scales. Universal human rights require a global scale. If someone asks AI if education is harmful to women, the answer should be “no” regardless of their location. But economic democratization requires local control: if AI’s power over an economy is dictated by corporate giants or authoritarian states, it may degrade democracy’s social and environmental foundations. AI democratization, in other words, needs to operate across multiple scales. Nature allows the (...) multiscale flourishing of biological systems through fractal distributions. In this paper, we show that key elements of the fractal scaling found in nature can be applied to the AI democratization process. We begin by looking at fractal trees in nature and applying similar analytics to tree representations of online conversations. We first examine this application in the context of OpenAI’s “Democratic Inputs” projects for globally acceptable policies. We then look at the advantages of independent AI ownership at local micro-levels, reporting on initial outcomes for experiments with AI and related technologies in community-based systems. Finally, we offer a synthesis of the two, micro and macro, in a multifractal model. Just as nature allows multifractal systems to maximize biodiverse flourishing, we propose a combination of community-owned AI at the micro-level, and globally democratized AI policies at the macro-level, for a more egalitarian and sustainable future. (shrink)

This paper explores the human experience of game-playing and its implications for artificial intelligence. The author uses phenomenology to examine game-playing from a human-centered perspective and applies it to language games played by artificial intelligences and humans. The paper argues that AI cannot truly play games because it lacks the intentionality, embodied experience, and social interaction that are fundamental to human game-playing. Furthermore, current AI lacks the ability to converse, which is argued to be equivalent to Wittgenstein’s view of engaging (...) in “language games.” The author presents a formal ontology of game playing, agents, and their intentional states, and contrasts human agents playing games with artificial agents “playing games.” The paper concludes that while artificial intelligence can simulate some aspects of human language games, it lacks the essential capacities for game playing, such as cognition, creativity, will, intentionality, understanding, and personhood. (shrink)

Purpose This paper aims to appraise current challenges in adopting generative AI by reviewers to evaluate the readability and quality of submissions. The paper discusses how to make the AI-powered peer-review process immune to unethical practices, such as the proliferation of AI-generated poor-quality or fake reviews that could harm the value of peer review. Design/methodology/approach This paper examines the potential roles of AI in peer review, the challenges it raises and their mitigation. It critically appraises current opinions and practices while (...) acknowledging the lack of consensus about best practices in AI for peer review. Findings The adoption of generative AI by the peer review process seems inevitable, but this has to happen (1) gradually, (2) under human supervision, (3) by raising awareness among stakeholders about all its ramifications, (4) through improving transparency and accountability, (5) while ensuring confidentiality through the use of locally hosted AI systems, (6) by acknowledging its limitations such as its inherent bias and unawareness of up-to-date knowledge, (7) by putting in place robust safeguards to maximize its benefits and lessen its potential harm and (8) by implementing a robust quality assurance to assess its impact on overall research quality. Originality/value In the current race for more AI in scholarly communication, this paper advocates for a human-centered oversight of AI-powered peer review. Eroding the role of humans will create an undesirable situation where peer review will gradually metamorphose into an awkward conversation between an AI writing a paper and an AI evaluating that paper. (shrink)

Conversational artificial agents and artificially intelligent voice assistants are becoming increasingly popular. Digital virtual assistants such as Siri, or conversational devices such as Amazon Echo or Google Home are permeating everyday life, and are designed to be more and more humanlike in their speech. This study investigates the effect this can have on one’s conformity with an AI assistant. In the 1950s, Solomon Asch’s already demonstrated the power and danger of conformity amongst people. In these classical experiments test (...) persons were asked to answer relatively simple questions, whilst others pretending to be participants tried to convince the test person to give wrong answers. These studies were later replicated with embodied robots, but these physical robots are still rare. In light of our increasing reliance on AI assistants, this study investigates to what extent an individual will conform to a disembodied virtual assistant. We also investigate if there is a difference between a group that interacts with an assistant that communicates through text, one that has a robotic voice and one that has a humanlike voice. The assistant attempts to subtly influence participants’ final responses in a general knowledge quiz, and we measure how often participants change their answer after having been given advice. Results show that participants conformed significantly more often to the assistant with a human voice than the one that communicated through text. (shrink)

The philosophical, legal, and HCI literature concerning artificial intelligence (AI) has explored the ethical implications and values that these systems will impact on. One aspect that has been only partially explored, however, is the role of deception. Due to the negative connotation of this term, research in AI and Human–Computer Interaction (HCI) has mainly considered deception to describe exceptional situations in which the technology either does not work or is used for malicious purposes. Recent theoretical and historical work, however, has (...) shown that deception is a more structural component of AI than it is usually acknowledged. AI systems that enter in communication with users, in fact, forcefully invite reactions such as attributions of gender, personality and empathy, even in the absence of malicious intent and often also with potentially positive or functional impacts on the interaction. This paper aims to operationalise the Human-Centred AI (HCAI) framework to develop the implications of this body of work for practical approaches to AI ethics in HCI and design. In order to achieve this goal, we take up the analytical distinction between “banal” and “strong” deception, originally proposed in theoretical and historical scholarship on AI (Natale in Deceitful media: artificial intelligence and social life after the turing test, Oxford University Press, New York, 2021), as a starting point to develop ethical reflections that will empower designers and developers with practical ways to solve the problems raised by the complex relationship between deception and communicative AI. The paper considers how HCAI can be applied to conversational AI (CAI) systems in order to design them to develop banal deception for social good and, at the same time, to avoid its potential risks. (shrink)

This paper documents a conversation between a philosopher and a human computer interaction researcher whose research has been enormously influenced by Wittgenstein. In particular, the in vivo use of categories in the design of communications and AI technologies are discussed, and how this meaning needs to evolve to allow creative design to flourish. The paper will be of interest to anyone concerned with philosophical tools in everyday action.

Purpose The purpose of this paper is to demonstrate the advancements in artificial intelligence (AI) and conversational agents, emphasizing their potential benefits while also highlighting the need for vigilant monitoring to prevent unethical applications. Design/methodology/approach As AI becomes more prevalent in academia and research, it is crucial to explore ways to ensure ethical usage of the technology and to identify potentially unethical usage. This manuscript uses a popular AI chatbot to write the introduction and parts of the body of (...) a manuscript discussing conversational agents, the ethical usage of chatbots and ethical concerns for academic researchers. Findings The authors reveal which sections were written entirely by the AI using a conversational agent. This serves as a cautionary tale highlighting the importance of ethical considerations for researchers and students when using AI and how educators must be prepared for the increasing prevalence of AI in the academy and industry. Measures to mitigate potential unethical use of this evolving technology are also discussed in the manuscript. Originality/value As conversational agents and chatbots increase in society, it is crucial to understand how they will impact the community and how we can live with technology instead of fighting against it. (shrink)

The value of testimony as a source of knowledge has been a subject of epistemological debates. The "trust theory of testimony" suggests that human testimony is based on an affective relationship supported by social norms. However, the advent of generative artificial intelligence challenges our understanding of genuine testimony. The concept of "quasi-testimony" seeks to characterize utterances produced by non-human entities that mimic testimony but lack certain fundamental attributes. This article analyzes these issues in depth, exploring philosophical perspectives on testimony and (...) the implications of conversational AI technologies on our epistemic practices. (shrink)

This methodological intervention proposes that the typical conversation sets up or modifies Micro Knowledge Profiles by using (partly anaphoric) discourse devices of Thick Cross-referencing; and that a certain type of translation procedure maps from such knowledge on to Macro Acquaintance Profiles. In a typical conversation, partners already acquainted with each other and with various matters renew their acquaintance. This renewal has consequences modifying their knowledge profiles and their action plans. The details that make the conversation flow have to be set (...) aside for the translation procedure to see the consequences of a conversation. The widespread desire to accurately profile the involvement of persons in conversations and the impossibility of telling any conversation-detached truth has been bringing about a mutation in the way we officially share and transmit knowledge; this mutation can be usefully called the Conversational Turn. (shrink)

We have developed a broadcasting agent system, public opinion channel (POC) caster, which generates understandable conversational form from text-based documents. The POC caster circulates the opinions of community members by using conversational form in a broadcasting system on the Internet. We evaluated its transformation rules in two experiments. In experiment 1, we examined our transformation rules for conversational form in relation to sentence length. Twenty-four participants listened to two types of sentence (long sentences and short sentences) with (...) conversational form or with single speech. In experiment 2, we investigated the relationship between conversational form and the user’s knowledge level. Forty-two participants (21 with a high knowledge level and 21 with a low knowledge level) were selected for a knowledge task and listened to two kinds of sentence (sentences about a well-known topic or sentences about an unfamiliar topic). Our results indicate that the conversational form aided comprehension, especially for long sentences and when users had little knowledge about the topic. We explore possible explanations and implications of these results with regard to human cognition and text comprehension. (shrink)

Large Language Models are one of the most prominent examples of current uses of AI, and one of the most urgently pursued normative tasks is to make them and their interactive user-interfaces—open-domain chatbots—safe. However, in this paper, we elaborate first on why such a limited view on the permissibility and desirability of their utterances falls conceptually flat, is philosophically insufficient, and leads to severe technological limits. We then propose a positive normative concept, appropriateness, that can provide the required orientation for (...) determining what chatbots may or may not say, and distinguish between technical-discursive, social, and moral appropriateness. Lastly, we explore the requirements for social and conversational contexts to fulfill appropriateness-requirements, and find that positionality is a key element for their position in discourse. (shrink)

This Open Forum contribution critically interrogates the use of space race rhetoric in current discussions about artificial intelligence (AI). According to this rhetoric, similar to the space race of the twentieth century, AI development is portrayed as a rivalry among superpowers where one country will win and reap major benefits, while others will be left behind. Using this rhetoric to frame AI development tends to prioritize narrow and short-term economic interests over broader and longer-term societal needs. Three particularly problematic aspects (...) of using space race narrative in AI discussions are highlighted: first, perceiving technology development globally as a zero-sum game; second, pressuring governments to regulate less; and third, prioritising high technologies over social issues. This contribution invites to challenge underlying political assumptions of the AI space race discourse and to open up conversations about alternative futures. (shrink)

Prologue -- Une enfance catholique -- Préparation -- Une initiation philosophique -- Dans le miroir des aînés -- En découvrant la théologie -- Les choix de Descartes -- Communion et communication -- Antitotalitaire -- Le tournant -- Premières percées -- Disputes -- Le cas Heidegger -- Augustin et Thomas -- Entre la Somme et la Réforme -- Dans l'ombre du cardinal -- Le vent de l'histoire -- Figures contemporaines -- Les mœurs et l'Église -- L'illusion des valeurs -- Eros -- (...) Les deux papes -- Les polémiques -- En Amérique -- À l'œuvre -- La France, toujours -- L'Europe malgré tout -- Des honneurs et de l'immortalité -- Nihil -- Tour du monde -- Épilogue. (shrink)

For those who find Dreyfus’s critique of AI compelling, the prospects for producing true artificial human intelligence are bleak. An important question thus becomes, what are the prospects for producing artificial non-human intelligence? Applying Dreyfus’s work to this question is difficult, however, because his work is so thoroughly human-centered. Granting Dreyfus that the body is fundamental to intelligence, how are we to conceive of non-human bodies? In this paper, I argue that bringing Dreyfus’s work into conversation with the work of (...) Mark Bickhard offers a way of answering this question, and I try to suggest what doing so means for AI research. (shrink)

Background Despite continuous performance improvements, especially in clinical contexts, a major challenge of Artificial Intelligence based Decision Support Systems (AI-DSS) remains their degree of epistemic opacity. The conditions of and the solutions for the justified use of the occasionally unexplainable technology in healthcare are an active field of research. In March 2024, the European Union agreed upon the Artificial Intelligence Act (AIA), requiring medical AI-DSS to be ad-hoc explainable or to use post-hoc explainability methods. The ethical debate does not seem (...) to settle on this requirement yet. This systematic review aims to outline and categorize the positions and arguments in the ethical debate. Methods We conducted a literature search on PubMed, BASE, and Scopus for English-speaking scientific peer-reviewed publications from 2016 to 2024. The inclusion criterion was to give explicit requirements of explainability for AI-DSS in healthcare and reason for it. Non-domain-specific documents, as well as surveys, reviews, and meta-analyses were excluded. The ethical requirements for explainability outlined in the documents were qualitatively analyzed with respect to arguments for the requirement of explainability and the required level of explainability. Results The literature search resulted in 1662 documents; 44 documents were included in the review after eligibility screening of the remaining full texts. Our analysis showed that 17 records argue in favor of the requirement of explainable AI methods (xAI) or ad-hoc explainable models, providing 9 categories of arguments. The other 27 records argued against a general requirement, providing 11 categories of arguments. Also, we found that 14 works advocate the need for context-dependent levels of explainability, as opposed to 30 documents, arguing for context-independent, absolute standards. Conclusions The systematic review of reasons shows no clear agreement on the requirement of post-hoc explainability methods or ad-hoc explainable models for AI-DSS in healthcare. The arguments found in the debate were referenced and responded to from different perspectives, demonstrating an interactive discourse. Policymakers and researchers should watch the development of the debate closely. Conversely, ethicists should be well informed by empirical and technical research, given the frequency of advancements in the field. (shrink)

Previous experimental findings support the hypothesis that laughter and positive emotions are contagious in face-to-face and mediated communication. To test this hypothesis, we describe four experiments in which participants communicate via a chat tool that artificially adds or removes laughter, without participants being aware of the manipulation. We found no evidence to support the contagion hypothesis. However, artificially exposing participants to more lols decreased participants’ use of hahas but led to more involvement and improved task-performance. Similarly, artificially exposing participants to (...) more hahas decreased use of haha but increased lexical alignment. We conclude that, even though the interventions have effects on coordination, they are incompatible with contagion as a primary explanatory mechanism. Instead, these results point to an interpretation that involves a more sophisticated view of dialogue mechanisms along the lines of Conversational Analysis and similar frameworks and we suggest directions for future research. (shrink)

In contemporary artificial intelligence, the challenge is making intricate connectionist systems—comprising millions of parameters—more comprehensible, defensible, and rationally grounded. Two prevailing methodologies address this complexity. The inaugural approach amalgamates symbolic methodologies with connectionist paradigms, culminating in a hybrid system. This strategy systematizes extensive parameters within a limited framework of formal, symbolic rules. Conversely, the latter strategy remains staunchly connectionist, eschewing hybridity. Instead of internal transparency, it fabricates an external, transparent proxy system. This ancillary system’s mandate is elucidating the principal system’s (...) decisions, essentially approximating its outcomes. Leveraging natural language processing as our analytical lens, this paper elucidates both methodologies: the hybrid method is underscored by the compositional vector semantics, whereas the purely connectionist method evolves as a derivative of neural semantic parsers. This discourse extols the merits of the purely connectionist approach for its inherent flexibility and for a pivotal delineation: segregating the explanatory apparatus from the operational core, thereby rendering artificial intelligence systems reminiscent of human cognition. (shrink)

Ai Weiwei is an installation artist who enjoyed great acclaim in the West after having absented himself from China, his homeland. He owes his global recognition to his dual identity as an artist/di...

This paper explores artificial intelligence (AI) ethics from an Islamic perspective at a critical time for AI ethical norm-setting. It advocates for a pluralist approach to ethical AI benchmarking. As rapid advancements in AI technologies pose challenges surrounding autonomy, privacy, fairness, and transparency, the prevailing ethical discourse has been predominantly Western or Eurocentric. To address this imbalance, this paper delves into the Islamic ethical traditions to develop a framework that contributes to the global debate on optimal norm setting for designing (...) and using AI technologies.The paper outlines Islamic parameters for ethical values and moral actions in the context of AI's ethical uncertainties. It emphasizes the significance of both textual and non-textual Islamic sources in addressing these uncertainties while placing a strong emphasis on the notion of "good" or "maṣlaḥa" as a normative guide for AI's ethical evaluation. Defining maṣlaḥa as an ethical state of affairs in harmony with divine will, the paper highlights the coexistence of two interpretations of maṣlaḥa: welfarist/utility-based and duty-based. Islamic jurisprudence allows for arguments supporting ethical choices that prioritize building the technical infrastructure for AI to maximize utility. Conversely, it also supports choices that reject consequential utility calculations as the sole measure of value in determining ethical responses to AI advancements. (shrink)

This article discusses the key existential stakes of implementing biometrics in human lifeworlds. In this pursuit, we offer a problematization and reinvention of central values often taken for granted within the “ethical turn” of AI development and discourse, such as autonomy, agency, privacy and integrity, as we revisit basic questions about what it means to be human and embodied. Within a framework of existential media studies, we introduce an existential ethics of care—through a conversation between existentialism, virtue ethics, a feminist (...) ethics of care and post-humanist ethics—aiming to deepen and nuance our understanding of the human behind “human-centered” AI directives. The key argument is that biometrics implicates humans through unprecedented forms of objectification, through which the existential body—the relational, intimate and frail human being—is at risk. We interrogate these risks as they become visible at three sites where embodied humans are challenged by biometrics, and thus where the existential body is challenged by the biometric body. This occurs through reductionism (biometric passports nailing bodies to identities, removing human judgment and compromising agency at the AI border), enforced transparency (smart home assistants surveying human intimacies and invading intimate spaces in the bedroom) and the breaching of bodily integrity (chipping bodies to capture sensory data, challenging the very concept of bodily integrity through self-invasive biohacking). Our existential ethics of care is importantly not a solutionist list of principles or suggestions, but a manifesto for a way of thinking about the ethical challenges of living with biometrics in today’s world, by raising the right questions. We argue that a revitalized discussion of the basic existential stakes within human lived experience is needed and should serve as the foundation on which comprehensive frameworks can be built to address the complexities and prospects for ethical machines, responsible biometrics and AI. (shrink)

This paper presents findings from a linguistic and psycho-social analysis of nine design dialogues which sets out to investigate the interweaving of transactional and interpersonal threads in collaborative work. We sketch a model of the participants' positioning towards their own or their partner's design proposals, from association to dissociation towards the proposals, together with the conversational cues which indicate this positioning. Our aim is to integrate the role of interpersonal relationships into the study of co-operation, to stress the importance (...) of this dimension for the quality of collective work and to reflect on its potential for integration into the design of dialogue systems. (shrink)

It is frequently demanded that AI-based Decision Support Tools (AI-DSTs) ought to be both explainable to, and trusted by, those who use them. The joint pursuit of these two principles is ordinarily believed to be uncontroversial. In fact, a common view is that AI systems should be made explainable so that they can be trusted, and in turn, accepted by decision-makers. However, the moral scope of these two principles extends far beyond this particular instrumental connection. This paper argues that if (...) we were to account for the rich and diverse moral reasons that ground the call for explainable AI, and fully consider what it means to “trust” AI in a descriptively rich sense of the term, we would uncover a deep and persistent tension between the two principles. For explainable AI to usefully serve the pursuit of normatively desirable goals, decision-makers must carefully monitor and critically reflect on the content of an AI-DST’s explanation. This entails a deliberative attitude. Conversely, calls for trust in AI-DSTs imply the disposition to put questions about their reliability out of mind. This entails an unquestioning attitude. As such, the joint pursuit of explainable and trusted AI calls on decision-makers to simultaneously adopt incompatible attitudes towards their AI-DST, which leads to an intractable implementation gap. We analyze this gap and explore its broader implications: suggesting that we may need alternate theoretical conceptualizations of what explainability and trust entail, and/or alternate decision-making arrangements that separate the requirements for trust and deliberation to different parties. (shrink)

This paper provides an in-depth analysis of the impact of AI technologies on the climate crisis beyond their mere resource consumption. To critically examine this impact, I introduce the concept of AI futurism. With this term I capture the ideology behind AI, and argue that this ideology is inherently connected to the climate crisis. This is because AI futurism construes a socio-material environment overly fixated on AI and technological progress, to the extent that it loses sight of the existential threats (...) ahead. In that way, the perceived significance of the planetary reality is softened, and the unsustainable paths charted by the AI industry remain opaque. To make this argument the paper unfolds in two main sections. (1) It delves into the ideology of AI futurism and its discursive impact on the societal perception of the climate crisis. (2) It employs a materialist perspective to elucidate the tangible effects of the AI industry on the climate crisis, and to show what is going on behind the façade of AI futurism. Adding to a critical theory of AI and the climate crisis, this paper starts a realistic conversation about the challenges posed by the intersection of these transformations. (shrink)