Limits need to be set on AI’s ability to simulate human feelings. Ensuring that chatbots don’t use emotive language, including emojis, would be a good start. Emojis are particularly manipulative. Humans instinctively respond to shapes that look like faces — even cartoonish or schematic ones — and emojis can induce these reactions.

Recent developments in artificial intelligence—AI--have caused considerable discussion among both philosophers of technology and psychotherapists. In particular, the question of whether or not new forms of AI will complement or even replace traditional psychotherapists has emerged as a major contemporary debate. This debate is not entirely new, as it has its origins in the Turing Test of 1950, and an early psychotherapy chatbot named Eliza, developed in 1966 at MIT. However, recent developments in AI technology, coupled with long waiting lists (...) and variable access to psychotherapists have raised the question of machine psychotherapists in an urgent manner. Already, there are psychotherapy apps that one can download onto a standard smartphone and use in lieu of a human psychotherapist. In the near future, this simulacrum of a human therapist may be enhanced by the use of android therapists, programed to duplicate the knowledge and behavior of human therapists instantly, appealing to convenience or self-gratification through technology. This raises a host of ethical questions: can such beings be equally effective, and if so, ought we to reason in a consequentialist manner in their favor so as to increase accessibility and reduce costs through technology? Would there be a psychological difference between automated and potentially anthropomorphic therapy and genuine human therapy, if only a subtle one? Even if a chatbot or robot therapist is transparently such, is there an element of emotional manipulation and potential dishonesty in this interaction? Can the security of clients and their data be thus secured? I will argue that key aspects of chatbot psychotherapy present major ethical and clinical challenges in these areas, although transparent forms of it should not be legally banned. Keywords: chatbots, technological momentum, automation, psychotherapy, trust, anthropomorphism, data. (shrink)

Developers and vendors of large language models (“LLMs”) — such as ChatGPT, Google Bard, and Microsoft’s Bing at the forefront—can be subject to Health Insurance Portability and Accountability Act of 1996 (“HIPAA”) when they process protected health information (“PHI”) on behalf of the HIPAA covered entities. In doing so, they become business associates or subcontractors of a business associate under HIPAA.

Generative AI enables automated, effective manipulation at scale. Despite the growing general ethical discussion around generative AI, the specific manipulation risks remain inadequately investigated. This article outlines essential inquiries encompassing conceptual, empirical, and design dimensions of manipulation, pivotal for comprehending and curbing manipulation risks. By highlighting these questions, the article underscores the necessity of an appropriate conceptualisation of manipulation to ensure the responsible development of Generative AI technologies.

Large language models now possess human-level linguistic abilities in many contexts. This raises the concern that they can be used to deceive and manipulate on unprecedented scales, for instance spreading political misinformation on social media. In future, agentic AI systems might also deceive and manipulate humans for their own purposes. In this paper, first, I argue that AI-generated content should be subject to stricter standards against deception and manipulation than we ordinarily apply to humans. Second, I offer new characterizations (...) of AI deception and manipulation meant to support such standards, according to which a statement is deceptive (resp. manipulative) if it leads human addressees away from the beliefs (resp. choices) they would endorse under “semi-ideal” conditions. Third, I propose two measures to guard against AI deception and manipulation, inspired by this characterization: “extreme transparency” requirements for AI-generated content and “defensive systems” that, among other things, annotate AI-generated statements with contextualizing information. Finally, I consider to what extent these measures can protect against deceptive behavior in future, agentic AI systems. (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)

Chatbots such as ChatGPT have the potential to change researchers’ lives in many ways. Despite all the advantages of chatbots, many challenges to using chatbots in medical research remain. Wrong and incorrect content presented by chatbots is a major possible disadvantage. The authors’ credibility could be tarnished if wrong content is presented in medical research. Additionally, ChatGPT, as the currently most popular generative AI, does not routinely present references for its answers. Double-checking references and resources used by chatbots might be (...) challenging. Researchers must also be careful not to harm copyright law or cause plagiarism issues using applications such as ChatGPT. Chatbots are trained on publicly available sources on the internet, increasing the risk of copyright or plagiarism issues. Therefore, chatbots such as ChatGPT should not be used routinely for professional medical research for now. However, further developments could make chatbots usable in medical research in the near future. (shrink)

In his article, “What should ChatGPT mean for bioethics?” I. Glenn Cohen explores the bioethical implications of Open AI’s chatbot ChatGPT and the use of similar Large Language Models (LLMs) (Cohen...

Artificial intelligence (AI) and its introduction into clinical pathways presents an array of ethical issues that are being discussed in the JME. 1–7 The development of AI technologies that can produce text that will pass plagiarism detectors 8 and are capable of appearing to be written by a human author 9 present new issues for medical ethics. One set of worries concerns authorship and whether it will now be possible to know that an author or student in fact produced (...) submitted work. That seems likely to be a general worry for secondary and higher education, as well as for all academic journals. Thus far generative AI chatbots do not seem to be able to produce a fully referenced and well-argued ethics article, but they probably could generate a blog or student essay that would... (shrink)

“Throw away anything that sounds too complicated. Only keep what is simple to grasp...If the information appears fuzzy and causes the brain to implode after two sentences, toss it away and stop listening. Doing so will make the news as orderly and simple to understand as the truth.” - In “GHG emissions,” The Kingfisher Story Collection, (Vuong 2022a).

This paper examines the impact and implications of ChatGPT and other generative AI technologies within the African context while looking at the ethical benefits and concerns that are particularly pertinent to the continent. Through a robust analysis of ChatGPT and other generative AI systems using established approaches for analysing the ethics of emerging technologies, this paper provides unique ethical benefits and concerns for these systems in the African context. This analysis combined approaches such as anticipatory technology ethics (ATE), (...) ethical impact assessment (EIA), and ethical issues of emerging ICT applications with AI (ETICA) with specific issues from the literature. The findings show that ChatGPT and other generative AI systems raise unique ethical concerns such as bias, intergenerational justice, exploitation of labour and cultural diversity in Africa but also have significant ethical benefits. These ethical concerns and benefits are considered crucial in shaping the design and deployment of ChatGPT and similar technologies responsibly. It further explores the potential applications of ChatGPT in critical domain areas such as education, agriculture, and healthcare, thereby demonstrating the transformative possibilities that these technologies can have on Africa. This paper underscores the critical role of AI governance as Africa increasingly adopts ChatGPT and similar AI systems. It argues that a comprehensive understanding of AI governance is essential not only for maximising the benefits of generative AI systems but also for facilitating a global dialogue. This dialogue aims to foster shared knowledge and insights between the Global North and the Global South, which is important for the development and creation of inclusive and equitable AI policies and practices that can be beneficial for all regions. (shrink)

Does undercover police work inevitably wrong its targets? Or are undercover activities justified by a general security benefit? In this article I argue that people can make themselves liable to deception and manipulation. The debate on undercover policing will proceed more fruitfully if the tactic can be conceptualised along those lines, rather than as essentially ‘dirty hands’ activity, in which people are wronged in pursuit of a necessary good, or in instrumentalist terms, according to which the harms of undercover (...) work are straightforwardly overcome by its benefits. This article motivates the ‘liability view’ and describes its attractions, challenges, and implications. (shrink)

The advent of ChatGPT by OpenAI has prompted extensive discourse on its potential implications for science and higher education. While the impact on education has been a primary focus, there is limited empirical research on the effects of large language models (LLMs) and LLM-based chatbots on science and scientific practice. To investigate this further, we conducted a Delphi study involving 72 researchers specializing in AI and digitization. The study focused on applications and limitations of LLMs, their effects on the science (...) system, ethical and legal considerations, and the required competencies for their effective use. Our findings highlight the transformative potential of LLMs in science, particularly in administrative, creative, and analytical tasks. However, risks related to bias, misinformation, and quality assurance need to be addressed through proactive regulation and science education. This research contributes to informed discussions on the impact of generative AI in science and helps identify areas for future action. (shrink)

The rapid evolution of scientific research has created a pressing need for efficient and versatile tools to aid researchers. While using artificial intelligence (AI) to write scientific articles is unethical and unreliable due to the potential for inaccuracy, AI can be a valuable tool for assisting with other aspects of research, such as language editing, reference formatting, and journal finding. Two of the latest AI-driven assistants that have become indispensable assets to scientists are ChatGPT and Gemini (Bard). These assistants offer (...) comprehensive support from literature review to journal suggestion, and they have the potential to revolutionize research. In the present study, a comprehensive set of queries and responses were designed to assess the capabilities of ChatGPT-3.5 and Gemini as scientific assistants. The results showed that Gemini achieved a perfect score of 100%, while ChatGPT-3.5 scored a less impressive 70%. Notably, ChatGP-3.5 fell short in specific areas that includes providing assistance with scientific paper explanations, exploring bibliographic databases, and formatting references. The qualitative assessment of responses also suggests that both the AI chatbots can be valuable tools for researchers, however, Gemini seems to be more appealing and accurate through the whole procedure of scientific writing. This work shall open new research dimensions in identifying adequate scientific utilization of the evolving AI tools and technologies, as embracing these advancements will be essential for staying at the forefront of scientific research. (shrink)

Artificial intelligence (AI) and robotics are digital technologies that will have significant impact on the development of humanity in the near future. They have raised fundamental questions about what we should do with these systems, what the systems themselves should do, what risks they involve, and how we can control these. - After the Introduction to the field (§1), the main themes (§2) of this article are: Ethical issues that arise with AI systems as objects, i.e., tools made and used (...) by humans. This includes issues of privacy (§2.1) and manipulation (§2.2), opacity (§2.3) and bias (§2.4), human-robot interaction (§2.5), employment (§2.6), and the effects of autonomy (§2.7). Then AI systems as subjects, i.e., ethics for the AI systems themselves in machine ethics (§2.8) and artificial moral agency (§2.9). Finally, the problem of a possible future AI superintelligence leading to a “singularity” (§2.10). We close with a remark on the vision of AI (§3). - For each section within these themes, we provide a general explanation of the ethical issues, outline existing positions and arguments, then analyse how these play out with current technologies and finally, what policy consequences may be drawn. (shrink)

Recent proposals for human-centered AI (HCAI) help avoid the challenging task of specifying an objective for AI systems, since HCAI is designed to learn the objectives of the humans it is trying to assist. We think the move to HCAI is an important innovation but are concerned with how an instrumental, economic model of human rational agency has dominated research into HCAI. This paper brings the philosophical debate about human rational agency into the HCAI context, showing how more substantive ways (...) to understand human objectives may improve HCAI. We contrast the economic approach with two more substantive modern alternatives: the realist and constructivist approaches to human rational agency. The realist approach holds that rational agents pursue what is good, while the constructivist approach holds that rational agents make autonomous choices. We illustrate each by considering its implications for fine-tuning large language models for chatbots such as ChatGPT. (shrink)

Deepfakes are highly realistic, albeit fake, audiovisual contents created with AI. This technology allows the use of deceptive audiovisual material that can impersonate someone’s identity to erode their reputation or manipulate the audience. Deepfakes are also one of the applications of AI that can be used in cultural industries and even to produce works of art. On the one hand, it is important to clarify whether deepfakes in arts and culture are free from the ethical dangers mentioned above. On the (...) other hand, there are specific ethical issues in this field of application. Deepfake technologies can be used to include the performance of deceased persons in audiovisual materials for the dissemination of cultural heritage, and to generate images or sounds in the style of real authors, but deepfakes are also potentially misleading by blurring the boundary between artwork and reality, and raise questions about the relationship between technology, artificial creativity and authorship. The answer to these problems requires an analysis of the normative foundations of copyright to accommodate the new role of AI. (shrink)

Our rapidly increasing reliance on frictionless AI interactions may increase cognitive and emotional distance, thereby letting our adaptive resilience slacken and our ethical virtues atrophy from disuse. Many trends already well underway involve the offloading of cognitive, emotional, and ethical labor to AI software in myriad social, civil, personal, and professional contexts. Gradually, we may lose the inclination and capacity to engage in critically reflective thought, making us more cognitively and emotionally vulnerable and thus more anxious and prone to manipulation (...) from false news, deceptive advertising, and political rhetoric. In this article, I consider the overarching features of this problem and provide a framework to help AI designers tackle it through system enhancements in smartphones and other products and services in the burgeoning internet of things (IoT) marketplace. The framework is informed by two ideas: psychologist Daniel Kahneman’s cognitive dual process theory and moral self-awareness theory, a four-level model of moral identity that I developed with Benjamin M. Cole. (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)

Exploring the relationship between humans and AI chatbots, as well as the ethical concerns surrounding their use, this paper argues that our relations with chatbots are not solely based on their function as a source of knowledge, but, rather, on the desire for the subject not to know. It is argued that, outside of the very fears and anxieties that underscore our adoption of AI, the desire not to know reveals the potential to embrace the very loss AI avers. Consequently, (...) rather than proposing a knowledge that seeks to disavow loss, we can instead recognize the potential in loss itself: an opportunity to assert and define the gap inherent to both the subject and AI we create. (shrink)

Large language models such as ChatGPT enable users to automatically produce text but also raise ethical concerns, for example about authorship and deception. This paper analyses and discusses some key philosophical assumptions in these debates, in particular assumptions about authorship and language and—our focus—the use of the appearance/reality distinction. We show that there are alternative views of what goes on with ChatGPT that do not rely on this distinction. For this purpose, we deploy the two phased approach of deconstruction (...) and relate our finds to questions regarding authorship and language in the humanities. We also identify and respond to two common counter-objections in order to show the ethical appeal and practical use of our proposal. (shrink)

The generative AI boom is unleashing its minions. Enterprise software vendors have rolled out legions of automated assistants that use large language model (LLM) technology, such as ChatGPT, to offer users helpful suggestions or to execute simple tasks. These so-called copilots and chatbots can increase productivity and automate tedious manual work. In this article, we explain how that leads to the risk that users' ethical competence may degrade over time — and what to do about it.

Moral reflection and deliberation on both deception and manipulation is hindered by lack of agreement on the precise meanings of these concepts. Specifically, there is disagreement on how to understand their relation vis-à-vis each other. Curiously, according to one prominent view, all deceptions are instances of manipulations, while according to another, all manipulations are instances of deceptions. This paper makes that implicit disagreement explicit, and argues that both views are untenable. It concludes that deception and manipulation partially overlap, (...) and takes further steps in delineating the border between these concepts. The paper ends with the conclusion that moral judgments regarding either manipulation or deception cannot be transferred wholesale from the one concept to the other just by virtue of the relations between the concepts. (shrink)

Ethically significant consequences of artificially intelligent artifacts will stem from their effects on existing social relations. Artifacts will serve in a variety of socially important roles—as personal companions, in the service of elderly and infirm people, in commercial, educational, and other socially sensitive contexts. The inevitable disruptions that these technologies will cause to social norms, institutions, and communities warrant careful consideration. As we begin to assess these effects, reflection on degrees and kinds of social agency will be required to make (...) properly informed decisions concerning the deployment of artificially intelligent artifacts in important settings. The social agency of these systems is unlike a human social agency, and this paper provides a methodological framework that is more suited for inquiry into artificial social agents than conventional philosophical treatments of the concept of agency. Separate aspects and dimensions of agency can be studied without assuming that agency must always look like adult human agency. This revised approach to the agency of artifacts is conducive to progress in the topics studied by AI ethics. (shrink)

ChatGPT is an artificial intelligence (AI) chatbot that processes and generates natural language text, offering human-like responses to a wide range of questions and prompts. Five days after its re...

In the wake of ChatGPT’s release, academics and journal editors have begun making important decisions about whether and how to integrate generative artificial intelligence (AI) into academic publishing. Some argue that AI outputs in scholarly works constitute plagiarism, and so should be disallowed by academic journals. Others suggest that it is acceptable to integrate AI output into academic papers, provided that its contributions are transparently disclosed. By drawing on Taylor’s work on academic norms, this paper argues against both views. Unlike (...) “traditional” forms of plagiarism, use of generative AI can be consistent with the norms that should underlie academic research. In these cases, its use should neither be prohibited nor required to be disclosed. However, some careless uses of generative AI do threaten to undermine the quality of academic research by mischaracterizing existing literature. This, not “AI plagiarism,” is the real concern raised by ChatGPT and related technologies. (shrink)

Ethics has powerful teeth, but these are barely being used in the ethics of AI today – it is no wonder the ethics of AI is then blamed for having no teeth. This article argues that ‘ethics’ in the current AI ethics field is largely ineffective, trapped in an ‘ethical principles’ approach and as such particularly prone to manipulation, especially by industry actors. Using ethics as a substitute for law risks its abuse and misuse. (...) This significantly limits what ethics can achieve and is a great loss to the AI field and its impacts on individuals and society. This article discusses these risks and then highlights the teeth of ethics and the essential value they can – and should – bring to AI ethics now. (shrink)

Interactions between humans and machines that include artificial intelligence are increasingly common in nearly all areas of life. Meanwhile, AI-products are increasingly endowed with emotional characteristics. That is, they are designed and trained to elicit emotions in humans, to recognize human emotions and, sometimes, to simulate emotions (EAI). The introduction of such systems in our lives is met with some criticism. There is a rather strong intuition that there is something wrong about getting attached to a machine, about having certain (...) emotions towards it, and about getting involved in a kind of affective relationship with it. In this paper, I want to tackle these worries by focusing on the last aspect: in what sense could it be problematic or even wrong to establish an emotional relationship with EAI-systems? I want to show that the justifications for the widespread intuition concerning the problems are not as strong as they seem at first sight. To do so, I discuss three arguments: the argument from self-deception, the argument from lack of mutuality, and the argument from moral negligence. (shrink)

This paper addresses the challenge of ethically integrating ChatGPT, a sophisticated AI language model, into K-14 economics education. Amidst the growing presence of AI in classrooms, it proposes the “Evaluate, Reflect, Assurance” model, a novel decision-making framework grounded in normative and virtue ethics, to guide educators. This approach is detailed through a theoretical decision tree, offering educators a heuristic tool to weigh the educational advantages and ethical dimensions of using ChatGPT. An educator can use the decision tree to reach (...) a conclusion on using ChatGPT within the classroom environment by using ethical considerations to promote personalized learning and upholding academic integrity. The paper stresses the importance of ongoing professional development for educators in ethical AI usage and calls for institutional support in this pursuit. It also identifies future research directions, including long-term impact studies of ChatGPT and comparative analyses of various AI tools in economics education, underscoring the paper’s relevance to current educational technology discourse. (shrink)

Cohen’s (2023) mapping exercise of possible bioethical issues emerging from the use of ChatGPT in medicine provides an informative, useful, and thought-provoking trigger for discussions of AI ethic...

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)

In recent years, prevalent global societal issues related to fake news, fakery, misinformation, and disinformation were brought to the fore, leading to the construction of descriptive labels such as “post-truth” to refer to the supposedly new emerging era. Thereby, the (mis-)use of technologies such as AI and VR has been argued to potentially fuel this new loss of “ground-truth”, for instance, via the ethically relevant deepfakes phenomena and the creation of realistic fake worlds, presumably undermining experiential veracity. Indeed, _unethical_ and (...) malicious actors could harness tools at the intersection of AI and VR (AIVR) to craft what we call _immersive falsehood_, fake immersive reality landscapes deliberately constructed for malicious ends. This short paper analyzes the ethically relevant nature of the background against which such malicious designs in AIVR could exacerbate the intentional proliferation of deceptions and falsities. We offer a reappraisal expounding that while immersive falsehood could manipulate and severely jeopardize the inherently affective constructions of social reality and considerably complicate falsification processes, humans may neither inhabit a post-truth nor a post-falsification age. Finally, we provide incentives for future AIVR safety work, ideally contributing to a future era of _technology-augmented critical thinking_. (shrink)

The increasing use of Generative AI raises many ethical, philosophical, and legal issues. A key issue here is uncertainties about how different degrees of Generative AI assistance in the production of text impacts assessments of the human authorship of that text. To explore this issue, we developed an experimental mixed methods survey study (N = 602) asking participants to reflect on a scenario of a human author receiving assistance to write a short novel as part of a 3 (high, medium, (...) or low degrees of assistance) X 2 (human or AI assistant) factorial design. We found that, for a human author, the degree of assistance they receive matters for our assessments of their level of authorship, creatorship, and responsibility, but not what or who rendered that assistance, although it was more important to disclose human rather than AI assistance. However, in our assessments of the assisting agent, human assistants were viewed as warranting higher rates of authorship, creatorship, and responsibility, compared to AI assistants rendering the same level of support. These results help us to better understand emerging norms around collaborative human-AI generated text, with implications for other types of collaborative content creation. (shrink)

In this article, we discuss ethical issues related to using and disclosing artificial intelligence (AI) tools, such as ChatGPT and other systems based on large language models (LLMs), to write or edit scholarly manuscripts. Some journals, such as Science, have banned the use of LLMs because of the ethical problems they raise concerning responsible authorship. We argue that this is not a reasonable response to the moral conundrums created by the use of LLMs because bans are unenforceable and would encourage (...) undisclosed use of LLMs. Furthermore, LLMs can be useful in writing, reviewing and editing text, and promote equity in science. Others have argued that LLMs should be mentioned in the acknowledgments since they do not meet all the authorship criteria. We argue that naming LLMs as authors or mentioning them in the acknowledgments are both inappropriate forms of recognition because LLMs do not have free will and therefore cannot be held morally or legally responsible for what they do. Tools in general, and software in particular, are usually cited in-text, followed by being mentioned in the references. We provide suggestions to improve APA Style for referencing ChatGPT to specifically indicate the contributor who used LLMs (because interactions are stored on personal user accounts), the used version and model (because the same version could use different language models and generate dissimilar responses, e.g., ChatGPT May 12 Version GPT3.5 or GPT4), and the time of usage (because LLMs evolve fast and generate dissimilar responses over time). We recommend that researchers who use LLMs: (1) disclose their use in the introduction or methods section to transparently describe details such as used prompts and note which parts of the text are affected, (2) use in-text citations and references (to recognize their used applications and improve findability and indexing), and (3) record and submit their relevant interactions with LLMs as supplementary material or appendices. (shrink)

Peer review facilitates quality control and integrity of scientific research. Although publishing policies have adapted to include the use of Artificial Intelligence (AI) tools, such as Chat Generative Pre-trained Transformer (ChatGPT), in the preparation of manuscripts by authors, there is a lack of guidelines or policies on whether peer reviewers can use such tools. The present article highlights the lack of policies on the use of AI tools in the peer review process (PRP) and argues that we need to go (...) beyond policies by creating transparent procedures that will enable journals to investigate allegations of non-compliance and take decisions that will protect the integrity of the peer review system. Reviewers found to violate relevant policies must be excluded from the process to safeguard the integrity of the peer review system. (shrink)

This paper focuses on the fact that AI is predominantly portrayed as white—in colour, ethnicity, or both. We first illustrate the prevalent Whiteness of real and imagined intelligent machines in four categories: humanoid robots, chatbots and virtual assistants, stock images of AI, and portrayals of AI in film and television. We then offer three interpretations of the Whiteness of AI, drawing on critical race theory, particularly the idea of the White racial frame. First, we examine the extent to which this (...) Whiteness might simply reflect the predominantly White milieus from which these artefacts arise. Second, we argue that to imagine machines that are intelligent, professional, or powerful is to imagine White machines because the White racial frame ascribes these attributes predominantly to White people. Third, we argue that AI racialised as White allows for a full erasure of people of colour from the White utopian imaginary. Finally, we examine potential consequences of the racialisation of AI, arguing it could exacerbate bias and misdirect concern. (shrink)

Recent developments in AI programming allow for new applications: individualized chatbots which mimic the speaking and writing behaviour of one specific living or dead person. ‘Deathbots’, chatbots of the dead, have already been implemented and are currently under development by the first start-up companies. Thus, it is an urgent issue to consider the ethical implications of deathbots. While previous ethical theories of deathbots have always been based on considerations of the dignity of the deceased, I propose to shift the focus (...) on the dignity and autonomy of the bereaved users of deathbots. Drawing on theories of internet-scaffolded affectivity and on theories of grief, I argue that deathbots may have a negative impact on the grief process of bereaved users and therefore have the potential to limit the emotional and psychological wellbeing of their users. Deathbot users are likely to become dependent on their bots which may make them susceptible to surreptitious advertising by deathbot providing companies and may limit their autonomy. At the same time, deathbots may prove to be helpful for people who suffer from prolonged, severe grief processes. I caution against the unrestricted usage of deathbots and suggest that they should be classified as medical devices. This classification would not the least mean that their non-harm, as well as their helpfulness for people suffering from prolonged grief needs to be proven and that their potential for autonomy infringements is reduced. (shrink)

Motivated by the question of responsible AI and value alignment, I seek to offer a uniquely Foucauldian reconstruction of the problem as the emergence of an ethical subject in a disciplinary setting. This reconstruction contrasts with the strictly human-oriented programme typical to current scholarship that often views technology in instrumental terms. With this in mind, I problematise the concept of a technological subjectivity through an exploration of various aspects of ChatGPT in light of Foucault’s work, arguing that current systems lack (...) the reflexivity and self-formative characteristics inherent in the notion of the subject. By drawing upon a recent dialogue between Foucault and phenomenology, I suggest four techno-philosophical desiderata that would address the gaps in this search for a technological subjectivity: embodied self-care, embodied intentionality, imagination and reflexivity. Thus I propose that advanced AI be reconceptualised as a subject capable of “technical” self-crafting and reflexive self-conduct, opening new pathways to grasp the intertwinement of the human and the artificial. This reconceptualization holds the potential to render future AI technology more transparent and responsible in the circulation of knowledge, care and power. (shrink)

This article articulates a framework for normatively assessing influence operations, undertaken by national security institutions. Section I categorizes the vast field of possible types of influence operations according to the communication’s content, its attribution, the rights of the target audience, the communication’s purpose, and its secondary effects. Section II populates these categories with historical examples and section III evaluates these cases with a moral framework. I argue that deceptive or manipulative communications directed at non-liable audiences are presumptively immoral and illegitimate (...) for liberal states, as are deceptive operations aimed at an unjust end, or even operations aimed at a just end where secondary effects are forecast to be disproportionate to the proximate end. (shrink)

Artificial intelligence (AI) is a digital technology that will be of major importance for the development of humanity in the near future. AI has raised fundamental questions about what we should do with such systems, what the systems themselves should do, what risks they involve and how we can control these. - After the background to the field (1), this article introduces the main debates (2), first on ethical issues that arise with AI systems as objects, i.e. tools made and (...) used by humans; here, the main sections are privacy (2.1), manipulation (2.2), opacity (2.3), bias (2.4), autonomy & responsibility (2.6) and the singularity (2.7). Then we look at AI systems as subjects, i.e. when ethics is for the AI systems themselves in machine ethics (2.8.) and artificial moral agency (2.9). Finally we look at future developments and the concept of AI (3). For each section within these themes, we provide a general explanation of the ethical issues, we outline existing positions and arguments, then we analyse how this plays out with current technologies and finally what policy conse-quences may be drawn. (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)

1. Michael A PetersBeijing Normal UniversityChatGPT is an AI chatbot released by OpenAI on November 30, 2022 and a ‘stable release’ on February 13, 2023. It belongs to OpenAI’s GPT-3 family (genera...

The integration of generative artificial intelligence (AI), particularly large language models like ChatGPT, presents new challenges as well as possibilities for scientific authorship. This paper draws on social systems theory to offer a nuanced understanding of the interplay between technology, individuals, society and scholarly authorial practices. This contrasts with orthodoxy, where individuals and technology are treated as essentialized entities. This approach offers a critique of the binary positions of sociotechnological determinism and accelerationist instrumentality while still acknowledging that generative AI presents (...) profound challenges to existing practices and meaning making in scientific scholarship. This holistic treatment of authorship, integrity, and technology involves comprehending the historical and evolutionary entanglement of scientific individuality, scientific practices, and meaning making with technological innovation. This addresses current needs for more robust theoretical approaches to address the challenges confronted by academicians, institutions, peer review, and publication processes. Our analysis aims to contribute to a more sophisticated discourse on the ethical and practical implications of AI in scientific research. (shrink)

Deception presents a distinctive ethical problem for democratic politicians. This is because there seem in certain situations to be compelling democratic reasons for politicians both to deceive and not to deceive the public. Some philosophers have sought to negotiate this tension by appeal to moral principle, but such efforts may misrepresent the felt ambivalence surrounding dilemmas of public office. A different approach appeals to the moral character of politicians, and to the variety of forms of manipulative communication at their (...) disposal. The public is usually more indulgent of politicians who ‘spin’ the truth than of those who tell bare-faced lies, but this could be a mistake. Spin expresses disdain for the democratic value of truthfulness, and so democratic ‘spin-doctors’ ought to trouble us more than they typically do. The cause of confusion here may reside in the failure to appreciate the distinctiveness of public morality, and in the misguided application of private standards of behaviour to a public context in which they are out of place. (shrink)

Imagine if, when broken-hearted by their romantic partner leaving them, a person could continue the relationship with a chatbot or avatar version of them. This might seem like a far-fetched scenario but a little thought reveals that, first, this is a product that could plausibly make its way to the market and, second, it would be harmful for both parties of the former relationship and plausibly abusive for the person who has been ‘bot-ed’ without their consent.

We appreciate the helpful commentaries on our paper, ‘AI and the falling sky: interrogating X-Risk’.1 We agree with many points commentators raise, which opened our eyes to concerns we had not previously considered. This reply focuses on the tension many commentators noted between AI’s existential risks (X-Risks) and justice here and now. In ‘Existential risk and the justice turn in bioethics’, Corsico frames the tension between AI X-Risk and justice here and now as part of a larger shift within bioethics.2 (...) They think the field is increasingly turning away from ‘big picture’ questions new technologies raise and focusing on narrower justice concerns of less significance. They compare our paper’s emphasis on justly transitioning to more AI-centred societies with the approach of environmentalists fretting about human protection against climate change while losing sight of the need to protect the planet and all living things. Corsico doubts there is much point to pressing for ‘justice on a dead planet’, so too Corsico questions our concern with just transitions. Presumably, that matters little if intelligent life on Earth is destroyed. Corsico’s recommends bioethicists return to big questions, like: ‘Should we develop AI at all, given AI X-Risk?’. Yet this question is increasingly moot. The genie is already out of the bottle. The Future of Life Institute’s 2023 call for a temporary pause on training AI systems more powerful than ChatGPT fell on deaf ears, in part because freely accessible source codes enable anyone to train systems and create AI applications.3 The focus now must be managing the genie. While we take AI X-Risk seriously, …. (shrink)

Until now, the mass spread of fake news and its negative consequences have implied mainly textual content towards a loss of citizens' trust in institutions. Recently, a new type of machine learning framework has arisen, Generative Adversarial Networks (GANs) – a class of deep neural network models capable of creating multimedia content (photos, videos, audio) that simulate accurate content with extreme precision. While there are several areas of worthwhile application of GANs – e.g., in the field of audio-visual production, human-computer (...) interactions, satire, and artistic creativity – their deceptive uses, at least as currently foreseeable, are just as numerous and worrying. The main concern is linked to the so-called “deepfakes”, fake images or videos that simulate real events with extreme precision. When trained on a human face, GANs can make the face assume hyper-realistic movements, expressions and (verbal and non-verbal) communication abilities. This technology poses an urgent threat to the governance of democratic processes concerning the production of public opinions and political discourses, with significant potential for reality-altering and disinformation. After a short introduction of their current technical state-of-the-art, in this paper we want to enquire the GANs` socio-technical system alongside different and intertwined philosophical accounts. Firstly, we will argue about the conditions that make perceived a GANs-generated content as trustworthy, arguing also about the general effects GANs might have on the perceived trustworthiness of individuals. Thereafter, we will discuss about the inadequacy to approach GANs only as perception-altering technology. Against this backdrop, we will propose a theoretical turn that considers the human-machine relationships of trustworthiness as elements of a broader hybrid socio-technical systems. This turn come up with political repercussions that we will discuss in the last part of the paper. (shrink)

Concerns about threats to human autonomy feature prominently in the field of AI ethics. One aspect of this concern relates to the use of AI systems for problematically manipulative influence. In response to this, the European Union’s draft AI Act (AIA) includes a prohibition on AI systems deploying subliminal techniques that alter people’s behavior in ways that are reasonably likely to cause harm (Article 5(1)(a)). Critics have argued that the term ‘subliminal techniques’ is too narrow to capture the target (...) cases of AI-based manipulation. We propose a definition of ‘subliminal techniques’ that (a) is grounded on a plausible interpretation of the legal text; (b) addresses all or most of the underlying ethical concerns motivating the prohibition; (c) is defensible from a scientific and philosophical perspective; and (d) does not over-reach in ways that impose excessive administrative and regulatory burdens. The definition is meant to provide guidance for design teams seeking to pursue responsible and ethically aligned AI innovation. (shrink)

This paper analyses the phenomenology and epistemology of chatbots such as ChatGPT and Bard. The computational architecture underpinning these chatbots are large language models (LLMs), which are generative artificial intelligence (AI) systems trained on a massive dataset of text extracted from the Web. We conceptualise these LLMs as multifunctional computational cognitive artifacts, used for various cognitive tasks such as translating, summarizing, answering questions, information-seeking, and much more. Phenomenologically, LLMs can be experienced as a “quasi-other”; when that happens, users anthropomorphise them. (...) For most users, current LLMs are black boxes, i.e., for the most part, they lack data transparency and algorithmic transparency. They can, however, be phenomenologically and informationally transparent, in which case there is an interactional flow. Anthropomorphising and interactional flow can, in some users, create an attitude of (unwarranted) trust towards the output LLMs generate. We conclude this paper by drawing on the epistemology of trust and testimony to examine the epistemic implications of these dimensions. Whilst LLMs generally generate accurate responses, we observe two epistemic pitfalls. Ideally, users should be able to match the level of trust that they place in LLMs to the degree that LLMs are trustworthy. However, both their data and algorithmic opacity and their phenomenological and informational transparency can make it difficult for users to calibrate their trust correctly. The effects of these limitations are twofold: users may adopt unwarranted attitudes of trust towards the outputs of LLMs (which is particularly problematic when LLMs hallucinate), and the trustworthiness of LLMs may be undermined. (shrink)

Beneficent clinical usage of placebos has been a problem for the application of Kant’s deontology in medical ethics, which, in its strictest form, rejects deception universally. Some defenders of deontology have countered this by arguing placebos can be used by a physician without necessarily being deceptive. In this paper we argue that such a manipulation of Kant’s absolutism is not credible, and therefore, that we should look beyond deontology in our consideration of placebo usage in clinical practice. We (...) conclude that Kant’s deontology cannot be made compatible with placebo use in clinical practice due to the primacy it affords to the principle of autonomy. (shrink)