The ever increasing use of generative artificial intelligence raises significant questions about authorship and related issues such as credit and accountability. In this paper, I consider whether works produced by means of users inputting natural language prompts into Generative Adversarial Networks are works of authorship. I argue that they are not. This is not due to concerns about randomness or machine-assistance compromising human labor or intellectual vision, but instead due to the syntactical and compositional limitations of (...) existing AI systems in handling natural language prompts. This, I argue, gives rise to ‘authorship gaps’. (shrink)

In this editorial essay, we argue that Generative Artificial Intelligence programs (GenAI) draw on what we term a “hypercommons”, involving collectively produced inputs and labour that are largely invisible or untraceable. We argue that automatizing the exploitation of common inputs, in ways that remix and reconfigure them, can lead to a crisis of academic authorship in which the moral agency involved in scholarly production is increasingly eroded. We discuss the relationship between the hypercommons and authorship in (...) terms of moral agency and the ethics of academic production, speculating on different responses to the crisis of authorship as posed by GenAI. (shrink)

Artifacts are often characterized as intentional products of human activities, suggesting that they must have authors. However, contrary to this common characterization, I argue that there exist novel examples of artifacts that lack authors. This novelty arises directly from the emergence of generative artificial intelligence applications. I provide several examples of such authorless artifacts and address potential objections to their existence.

The rapid spread and development of artificial intelligence technologies has raised important questions that have an impact on laws and regulations related to intellectual property. In light of this, the research aims to explore the impact of artificial intelligence on intellectual property laws and regulations, and to examine the legal implications of the innovations generated by artificial intelligence on authorship, invention, ownership, infringement, and enforcement of intellectual property laws. In light of the great (...) concerns about its impact on intellectual property laws and regulations and the uncertainty and ambiguity in the application of intellectual property laws, the researcher considered it a problem of the study as it leads to potential risks and challenges for creators, inventors, and intellectual property rights holders. The research followed the comparative approach to provide a view of the different approaches regarding this topic, and to help shed light on the main difficulties faced in applying the law in such an evolving context. The study reached many conclusions, but the most important of them is that artificial intelligence threatens office jobs due to its ability to generate high-quality content quickly and at a low cost, and intellectual property laws will continue to be breached, which necessitates the need for the law to adapt to establish rules of conduct and limits of human work, and recommends engaging in an international dialogue to unify laws and manage disputes related to intellectual property across borders. (shrink)

Arthur C. Danto did not live to witness the proliferation of AI in artistic creation. However, his philosophy of art offers key ideas about art that can provide an interesting perspective on artwork generated by artificial intelligence (AI). In this article, I analyze how his ideas about contemporary art, intention, interpretation, and authorship could be applied to the ongoing debate about AI and artistic creation. At the same time, it is also interesting to consider whether the incorporation (...) of AI into artistic creation marks a new chapter in the narrative, which seems to have reached its end, or if it represents a significant rupture with past artistic traditions. (shrink)

Artificial intelligence (AI) is rapidly changing the way that art is created and consumed, allowing artists to create unique, engaging works with high computing power that can supplement their creative process. This manuscript explores the creative process of using AI technology in digital art to create paintings and evaluates creativity based on the aesthetic value and components of works created by AI. This research seeks to understand how AI technology influences the art world through a practice-led methodology with (...) a descriptive qualitative approach and observational methodology. Pioneering artwork such as Edmond de Belamy, created by French collective obvious using generative adversarial networks (GANs), has raised questions among the creative fields concerning originality, creativity, and authorship. Through analyses of AI-generated artwork and comparison with traditional artwork, the research investigates potential opportunities and challenges that AI presents to the art world. Ultimately, AI technology can provide a creative spark for human artists who, with an appropriate understanding of the limitations of AI algorithms, can create incredible pieces of art that embrace the contributions of both humans and machines. This research seeks to fill in the gaps left by earlier works and provide a more multi-faceted look at the changing landscape of AI in art, gaining a better understanding of the ways AI is impacting the art world and what the future may look like in the coming years. (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)

1. In the last decade, technological systems based on Artificial Intelligence (AI) architectures entered our lives at an increasingly fast pace. Virtual assistants facilitate our daily tasks, recom...

The recent success of Generative AI (GenAI) has heralded a new era in content creation, dissemination, and consumption. This technological revolution is reshaping our understanding of content, challenging traditional notions of authorship, and transforming the relationship between content producers and consumers. As we approach an increasingly AI-integrated world, examining the implications of this paradigm shift is crucial. This article explores the future of content in the age of GenAI, analysing the evolving definition of content, the transformations brought about by (...) GenAI systems, and emerging models of content production and dissemination. By examining these aspects, we can gain valuable insights into the challenges and opportunities that lie ahead in the realm of content creation and consumption and, hopefully, manage them more successfully. (shrink)

The emergence of complex deep-learning models capable of producing novel images on a practically innumerable number of subjects and in an equally wide variety of artistic styles is beginning to highlight serious inadequacies in the ethical, aesthetic, epistemological and legal frameworks we have so far used to categorise art. To begin tackling these issues and identifying a role for AI in the production and protection of human artwork, it is necessary to take a multidisciplinary approach which considers current legal precedents, (...) the practice of software engineering, historical attitudes towards technological innovation and a sustained technical analysis of the models themselves. This paper queries the location and nature of substantive artistic work in the developmental stages of an AI-generated image, offering critiques of existing assumptions and posing questions for future research. The emergence of convincing AI creative output, artistic or literary, has significant long-term implications for the humanities, including the need for re-appraisal of foundational ideas about authorship and creativity in general. The effects of artificial intelligence, whether generalised or task-specific, cannot be ignored or displaced now that easy-access, scalable image and text production is a reality. (shrink)

Artificial Intelligence (AI) models are now capable of producing artifacts that mimic human creation, such as visual art, text or music. The remarkable sophistication of these results reignited the debate on authorship, calling into question issues such as intent, originality, autonomy or aesthetic engagement. I will present and explain the main positions on authorship that have emerged from this questioning, drawing on Emanuele Arielli’s recent account in AI-aesthetics and the artificial author (2023). Furthermore, I will (...) show how Roland Barthes’ The Death of the Author (1967) and Michel Foucault’s What is an Author? (1969) are central to understanding the philosophical implications of the debate and how conceptualisations pursued in these works inform current perspectives on authorship when AI is involved. (shrink)

Fictional realism is the view that creatures of fiction exist. Mythical realism is the view that creatures of myth and mistaken theories exist. Call the combined view “Ecumenical Realism.” We critically evaluate three arguments for Ecumenical Realism and argue they are unsound because fictional storytelling differs from mistaken theorizing in important ways. We think these considerations support a more conservative view, “Sectarian Realism,” which results from subtracting “creatures of mistaken theorizing” from Ecumenical Realism. We close by considering an important challenge (...) to Sectarian Realism involving immigrants in fiction. (shrink)

BackgroundAdvances in healthcare artificial intelligence (AI) are occurring rapidly and there is a growing discussion about managing its development. Many AI technologies end up owned and controlled by private entities. The nature of the implementation of AI could mean such corporations, clinics and public bodies will have a greater than typical role in obtaining, utilizing and protecting patient health information. This raises privacy issues relating to implementation and data security. Main bodyThe first set of concerns includes access, use (...) and control of patient data in private hands. Some recent public–private partnerships for implementing AI have resulted in poor protection of privacy. As such, there have been calls for greater systemic oversight of big data health research. Appropriate safeguards must be in place to maintain privacy and patient agency. Private custodians of data can be impacted by competing goals and should be structurally encouraged to ensure data protection and to deter alternative use thereof. Another set of concerns relates to the external risk of privacy breaches through AI-driven methods. The ability to deidentify or anonymize patient health data may be compromised or even nullified in light of new algorithms that have successfully reidentified such data. This could increase the risk to patient data under private custodianship.ConclusionsWe are currently in a familiar situation in which regulation and oversight risk falling behind the technologies they govern. Regulation should emphasize patient agency and consent, and should encourage increasingly sophisticated methods of data anonymization and protection. (shrink)

Cosgrove, Mary-Anne Below are 'talking points' based on an article in AH No. 121, 'AI on the Go: Notes on the current development and use of Artificial Intelligence', by Carl Mahoney. Carl is a Humanist Society of Victoria member, and was professor and Dean of the Faculty of Architecture and Building, University of Technology, Papua New Guinea.

Moving from a behavioral definition of intelligence, which describes it as the ability to adapt to the surrounding environment and deal effectively with new situations (Anastasi, 1986), this paper explains to what extent the performance obtained by ChatGPT in the linguistic domain can be considered as intelligent behavior and to what extent they cannot. It also explains in what sense the hypothesis of decoupling between cognitive and problem-solving abilities, proposed by Floridi (2017) and Floridi and Chiriatti (2020) should be (...) interpreted. The problem of symbolic grounding (Harnad, 1990) is then addressed to show the problematic relationship between ChatGPT and the natural environment, and thus the impossibility for it to understand the symbols it manipulates. To explain the reasons why ChatGPT does not succeed in this task, an investigation is carried out and a possible solution to the problem in the artificial domain is proposed by making a comparison with the natural ability of living beings to ground their own meanings from some basic cognitive-sensory aspects, which, it is explained, are directly related to the emergence of self-awareness in humans. Thus, the question is raised whether a possible and concrete solution to the Symbol Grounding Problem would involve in the artificial domain the development of cognitive abilities fully comparable to those of humans. Finally, I explain the difficulties that would have to be overcome before such a level could be reached, since human cognitive capacities are intimately linked to intersubjectivity and intercorporeality. (shrink)

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)

Machine-based automation has long been a key factor in the modern era. However, lately, many people have been shocked by artificial intelligence (AI) applications, such as ChatGPT (OpenAI), that can perform tasks previously thought to be human-exclusive. With recent advances in natural language processing (NLP) technologies, AI can generate written content that is similar to human-made products, and this ability has a variety of applications. As the technology of large language models continues to progress by making use of (...) colossal reservoirs of digital information, AI is becoming more capable of recognizing patterns and associations within given contexts, making it especially helpful in assisting with various professional writing tasks [1]. In this paper, we will discuss several key points regarding the current state and future of AI in academia. Furthermore, since in certain aspects, acts can speak louder than words, we will also present some of our hands-on experiences of working with ChatGPT. (shrink)

An exploration of the important philosophical issues and concerns related to artificial intelligence. The book focuses on the philosphical, rather than the technical or technological aspects of artificial intelligence.

There is a vast literature within philosophy of mind that focuses on artificial intelligence, but hardly mentions methodological questions. There is also a growing body of work in philosophy of science about modeling methodology that hardly mentions examples from cognitive science. Here these discussions are connected. Insights developed in the philosophy of science literature about the importance of idealization provide a way of understanding the neural implausibility of connectionist networks. Insights from neurocognitive science illuminate how relevant similarities between (...) models and targets are picked out, how modeling inferences are justified, and the metaphysical status of models. (shrink)

Semantic Engines: An Introduction to Mind Design, John C. Haugeland; Computer Science as Empirical Inquiry: Symbols and Search, Alan Newell and Herbert A. Simon; Complexity and the Study of Artificial and Human Intelligence, Zenon Pylyshyn; A Framework for Representing Knowledge, Marvin Minsky; Artificial Intelligence---A Personal View, David Marr; Artificial Intelligence Meets Natural Stupidity, Drew McDermott; From Micro-Worlds to Knowledge Representation: AI at an Impasse, Hubert L. Dreyfus; Reductionism and the Nature of Psychology, Hilary Putnam; (...) Intentional Systems, Daniel C. Dennett; The Nature and Plausibility of Cognitivism, John C. Haugeland; Minds, Brains, and Programs, John R. Searle; MethodologicalSolipsism Considered as a Research Strategy in Cognitive Psychology, Jerry A. Fodor; The Material Mind, Donald Davidson. (shrink)

This chapter presents an overview of the issues that arise when logic is used in helping to understand problems in intelligent reasoning and to guide the design of mechanized reasoning systems. It provides some historical and technical details concerning nonmonotonic logic and reasoning about action and change, a topic that is not only central in artificial intelligence but that is normally of considerable interest to philosophers. The remaining sections provide brief sketches of selected topics, with references to the (...) primary literature. (shrink)

Use of argumentation methods applied to legal reasoning is a relatively new field of study. The book provides a survey of the leading problems, and outlines how future research using argumentation-based methods show great promise of leading to useful solutions. The problems studied include not only these of argument evaluation and argument invention, but also analysis of specific kinds of evidence commonly used in law, like witness testimony, circumstantial evidence, forensic evidence and character evidence. New tools for analyzing these kinds (...) of evidence are introduced. (shrink)

The current study aimed at identifying the awareness level of artificial intelligence applications' risks among faculty members and its relation to the attitude towards digital culture at Imam Abdulrahman Bin Faisal University. The descriptive survey method was used. A questionnaire was designed to measure the awareness of the artificial intelligence applications' risks, and a scale for measuring the attitude towards digital culture. They were administered to a sample of [463] faculty members at Imam Abdulrahman Bin Faisal (...) University. The study concluded that there is an average awareness of the artificial intelligence applications' risks and the attitude towards digital culture among faculty members. A significant relationship was found out between awareness of the artificial intelligence applications' risks as a whole and the attitude towards digital culture. The results indicated that there are no differences in the awareness level of the artificial intelligence risks due to the variables of: gender, use duration of digital applications, and colleges. There are no differences in the variable of the attitude towards digital culture with its various dimensions: cognitive, psychomotor, and affective and its total score. The current study recommended designing a professional development plan for faculty members on the negative effects and risks of artificial intelligence, and launching an Arab platform based on artificial intelligence applications. (shrink)

Abstract This article delves into the intricate interplay between copyright laws, Artificial Intelligence (AI) technologies, and the evolving role of authors in the contemporary digital landscape, especially after the irruption of Generative AI systems, as ChatGPT. The paper scrutinizes Japan’s approach to copyright in the realm of AI training, highlighting the delicate balance between safeguarding creators’ rights and fostering competitiveness in the global market. By examining the concept of “the death of the Author” as elucidated by Roland Barthes, (...) the study explores how AI-generated content challenges traditional notions of authorship and creativity. (shrink)

In CyberPhilosophy: The Intersection of Philosophy and Computing, edited by James H. Moor and Terrell Ward Bynum (Oxford, UK: Blackwell, 2002), 66-77. Also in Metaphilosophy 33.1/2 (2002): 70-82.

For over a decade John Searle's ingenious argument against the possibility of artificial intelligence has held a prominent place in contemporary philosophy. This is not just because of its striking central example and the apparent simplicity of its argument. As its appearance in Scientific American testifies, it is also due to its importance to the wider scientific community. If Searle is right, artificial intelligence in the strict sense, the sense that would claim that mind can be (...) instantiated through a formal program of symbol manipulation, is basically wrong. No set of formal conditions can provide us with the characteristic feature of mind which is the intentionally of its mental contents. Formally regarded, such intentionally is an irreducible primitive. It cannot be analyzed into non-intentional (purely syntactic, symbolic) components. This paper will argue that this objection is based on a misunderstanding. Intentionality is not simply something given which is incapable of further analysis. It only appears so when we mistakenly abstract it from time. When we regard its temporal structure, it shows itself as a rule-governed, synthetic process, one capable of being instantiated both by machines and men. (shrink)

This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information and data-processing systems of all kinds, no matter whether human, (other) animal or machine. Its scope is intended to span the full range of interests from classical problems in the philosophy of mind and phi losophical psychology through issues in cognitive psychology and socio biology (concerning the mental capabilities of other species) to ideas related to artificial intelligence and computer science. (...) While primary emphasis will be placed upon theoretical, conceptual and epistemologi cal aspects of these problems and domains, empirical, experimental and methodological studies will also appear from time to time. Among the most challenging and difficult projects within the scope of artificial intelligence is the development and implementation of com puter programs suitable for processing natural language. Our purpose in compiling the present volume has been to contribute to the foundations of this enterprise by bringing together classic papers devoted to crucial problems involved in understanding natural language, which range from issues of formal syntax and logical form to those of possible-worlds and situation semantics. The book begins with a comprehensive introduc tion composed by Jack Kulas, the senior editor of this work, which pro vides a systematic orientation to this complex field, and ends with a selected bibliography intended to promote further research. If our efforts assist others in dealing with these problems, they will have been worthwhile. J. H. F. (shrink)

Temporal Logic: From Ancient Ideas to Artificial Intelligence deals with the history of temporal logic as well as the crucial systematic questions within the field. The book studies the rich contributions from ancient and medieval philosophy up to the downfall of temporal logic in the Renaissance. The modern rediscovery of the subject, which is especially due to the work of A. N. Prior, is described, leading into a thorough discussion of the use of temporal logic in computer science (...) and the understanding of natural language. Temporal Logic: From Ancient Ideas to Artificial Intelligence thus interweaves linguistic, philosophical and computational aspects into an informative and inspiring whole. (shrink)

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

HeartMath is a contemporary, scientific, coherent model of heart intelligence. The aim of this paper is to review this coherence model with special reference to its implications for artificial intelligence and robotics. Various conceptual issues, implications and challenges for AI and robotics are discussed. In view of seemingly infinite human capacity for creative, destructive and incoherent behaviour, it is highly recommended that designers and operators be persons of heart intelligence, optimal moral integrity, vision and mission. This (...) implies that AI and robotic design and production should be continuously optimized through vigilant and appropriate human and material quality control procedures. Evidence is provided for some value and effectiveness of the HeartMath coherence model in this context. (shrink)

The increasing accuracy of algorithms to predict values and preferences raises the possibility that artificial intelligence technology will be able to serve as a surrogate decision-maker for incapacitated patients. Following Camillo Lamanna and Lauren Byrne, we call this technology the autonomy algorithm. Such an algorithm would mine medical research, health records, and social media data to predict patient treatment preferences. The possibility of developing the AA raises the ethical question of whether the AA or a relative ought to (...) serve as surrogate decision-maker in cases where the patient has not issued a medical power of attorney. We argue that in such cases, and against the standard practice of vesting familial surrogates with decision making authority, the AA should have sole decision-making authority. This is because the AA will likely be better at predicting what treatment option the patient would have chosen. It would also be better at avoiding bias and, therefore, choosing in a more patient-centered manner. Furthermore, we argue that these considerations override any moral weight of the patient’s special relationship with their relatives. (shrink)

The goal of the paper is to develop and propose a general model of the state space of AI. Given the breathtaking progress in AI research and technologies in recent years, such conceptual work is of substantial theoretical interest. The present AI hype is mainly driven by the triumph of deep learning neural networks. As the distinguishing feature of such networks is the ability to self-learn, self-learning is identified as one important dimension of the AI state space. Another dimension is (...) recognized as generalization, the possibility to go over from specific to more general types of problems. A third dimension is semantic grounding. Our overall analysis connects to a number of known foundational issues in the philosophy of mind and cognition: the blockhead objection, the Turing test, the symbol grounding problem, the Chinese room argument, and use theories of meaning. It shall finally be argued that the dimension of grounding decomposes into three sub-dimensions. And the dimension of self-learning turns out as only one of a whole range of “self-x-capacities” (based on ideas of organic computing) that span the self-x-subspace of the full AI state space. (shrink)

I thank Jane Sedlakova and Manuel Trachsel for their work on situating conversational artificial intelligence’s (CAI) potential role in psychotherapy. In their article, Sedlakova and Trachsel argue...

Robotization and artificial intelligence are expected to change societies profoundly. Trust is an important factor of human–technology interactions, as robots and AI increasingly contribute to tasks previously handled by humans. Currently, there is a need for studies investigating trust toward AI and robots, especially in first-encounter meetings. This article reports findings from a study investigating trust toward robots and AI in an online trust game experiment. The trust game manipulated the hypothetical opponents that were described as either AI (...) or robots. These were compared with control group opponents using only a human name or a nickname. Participants lived in the United States. Describing opponents with robots or AI did not impact participants’ trust toward them. The robot called jdrx894 was the most trusted opponent. Opponents named “jdrx894” were trusted more than opponents called “Michael.” Further analysis showed that having a degree in technology or engineering, exposure to robots online and robot use self-efficacy predicted higher trust toward robots and AI. Out of Big Five personality characteristics, openness to experience predicted higher trust, and conscientiousness predicted lower trust. Results suggest trust on robots and AI is contextual and it is also dependent on individual differences and knowledge on technology. (shrink)

The current renewal of connectionist techniques using networks of neuron-like units has started to have an influence on cognitive modelling. However, compared with classical artificial intelligence methods, the position of connectionism is still not clear. In this article artificial intelligence and connectionism are systematically compared as cognitive models so as to bring out the advantages and shortcomings of each. The problem of structured representations appears to be particularly important, suggesting likely research directions.

The COVID-19 pandemic and its related policies (e.g., stay at home and social distancing orders) have increased people’s use of digital technology, such as social media. Researchers have, in turn, utilized artificial intelligence to analyze social media data for public health surveillance. For example, through machine learning and natural language processing, they have monitored social media data to examine public knowledge and behavior. This paper explores the ethical considerations of using artificial intelligence to monitor social media (...) to understand the public’s perspectives and behaviors surrounding COVID-19, including potential risks and benefits of an AI-driven approach. Importantly, investigators and ethics committees have a role in ensuring that researchers adhere to ethical principles of respect for persons, beneficence, and justice in a way that moves science forward while ensuring public safety and confidence in the process. (shrink)

This book constitutes the thoroughly refereed joint post-proceedings of three international workshops organized by the Japanese Society for Artificial Intelligence, held in Tokyo, Japan in June 2006 during the 20th Annual Conference JSAI 2006. The volume starts with eight award winning papers of the JSAI 2006 main conference that are presented along with the 21 revised full workshop papers, carefully reviewed and selected for inclusion in the volume.

This volume provides an extensive overview of the Ethics of Artificial Intelligence for the Sustainable Development Goals. The authors are experts contributing with perspectives from different fields. The comprehensive collection of chapters illustrates the pressing governance problems related to using AI for the SDGs, and case studies describing how AI is advancing and can advance the achievement of the Goals. Students, scholars, and practitioners working on AI for SDGs, the ethical governance of AI, sustainability, and the fourth revolution (...) can find this book a helpful reference. (shrink)

The advent of the intelligence age has injected new elements into the development of literature. The synergic modification of Anglo-American traumatic narrative literature by artificial intelligence technology and interactive design psychology will produce new possibilities in literary creation. First, by studying natural language processing technology, this study proposes a modification language model based on the double-layered recurrent neural network algorithm and constructs an intelligent language modification system based on the improved LM model. The results show that the (...) performance of the proposed model is excellent; only about 30% of the respondents like AAL literature; the lack of common cultural background, appreciation difficulties, and language barriers have become the main reasons for the decline of reading willingness of AAL literature. Finally, AI technology and ID psychology are used to modify a famous TN work respectively and synergically, and the modified work is appreciated by respondents to collect their comments. The results corroborate that 62% of the respondents like original articles, but their likability scores have decreased for individually modified work by AI or ID psychology. In comparison, under the synergic modification efforts of AI and ID psychology, the popularity of the modified work has increased slightly, with 65% of the respondents showing a likability to read. Therefore, it is concluded that literary modification by single ID psychology or AI technology will reduce the reading threshold by trading off the literary value of the original work. The core of literary creation depends on human intelligence, and AI might still not be able to generate high-standard literary works independently because human minds and thoughts cannot be controlled and predicted by machines. The research results provide new ideas and improvement directions for the field of AI-assisted writing. (shrink)

This is a draft of the written version of comments on a paper by David Cole, presented orally at the American Philosophical Association Central Division meeting in New Orleans, 27 April 1990. Following the written comments are 2 appendices: One contains a letter to Cole updating these comments. The other is the handout from the oral presentation.

There is a death by suicide in the world every 40 seconds, and suicide is the second leading cause of death for 15–29-year-olds. Experts say that one of the best ways to prevent suicide is for those in distress to hear from people who care about them. Facebook is in a unique position—through its support for networks and friendships on the site—to help connect a person in these difficult situations with people who can support them. Connecting people with the resources (...) they need is part of Facebook’s ongoing efforts to help build a safe community inside and outside of Facebook. This article provides a brief overview of how Facebook’s work to develop suicide prevention tools started and evolved, and the ethical considerations which surfaced during the process in the form of concrete product decisions around the implementation of these tools. This article is structured into three sections. Section 1 reviews what has been done in this space and lists and briefly describes other suicide prevention apps and tools. Section 2 describes Facebook’s overall approach to suicide prevention. Here, we’ll delve first into how that approach originated and how it was influenced by the external community’s proactive interactions with Facebook, highlighting our unique position to help address the problem. Afterwards, we’ll explain how that approach evolved, describing its various stages and iterations: understanding, reactive reporting, queue prioritization, and proactive reporting. This section describes the tools and resources Facebook has developed for people who may be at risk. Particular attention is devoted to the use of ArtificiaI Intelligence and Machine Learning to detect posts or live videos where someone might be expressing thoughts of suicide. Section 3 will elaborate on the ethical questions addressed when developing our approach and when making concrete product decisions to implement our suicide prevention tools. In this last section, we’ll expound the competing values and interests that were at stake during the product development process, and how we reached ethical balances between them. (shrink)