China communicates strategic narratives about artificial intelligence in digital media productions to create a shared meaning about its actions and its image in the global race to develop AI. Building upon the literature in emotions and strategic narratives, this study seeks to clarify which emotions are discursively used in China’s international AI narratives, and their function and significance. Specifically, the study investigates emotion discourses in AI-focused videos disseminated on China’s international broadcasting. The analysis reveals that pride, hope and fear discourses (...) have multiple functions in China’s international AI narratives on CGTN. Hope is used to represent China as a key competitor in the global AI race, who is catching up to the US. China uses pride to showcase its advances in AI applications, to highlight its transformation of traditional industries, and to identity itself as equal to the US. Fear is used to frame US’s perception of China’s AI developments, to suggest their crisis of confidence, but also to refute the “China threat”. Additionally, the fear discourse is used to deliberate anticipated risks, particularly on job loss and data privacy. These emotion discourses forge China’s identity as a future global AI power. The paper then discusses how these findings contribute to key debates about Chinese discourse and media strategy. (shrink)

In the fields of artificial intelligence and robotics, the term “autonomy” is generally used to mean the capacity of an artificial agent to operate independently of human guidance. It is thereby assumed that the agent has a fixed goal or “utility function” with respect to which the appropriateness of its actions will be evaluated. From a philosophical perspective, this notion of autonomy seems oddly weak. For, in philosophy, the term is generally used to refer to a stronger capacity, namely the (...) capacity to “give oneself the law,” to decide by oneself what one’s goal or principle of action will be. The predominant view in the literature on the long-term prospects and risks of artificial intelligence is that an artificial agent cannot exhibit such autonomy because it cannot rationally change its own final goal, since changing the final goal is counterproductive with respect to that goal and hence undesirable. The aim of this paper is to challenge this view by showing that it is based on questionable assumptions about the nature of goals and values. I argue that a general AI may very well come to modify its final goal in the course of developing its understanding of the world. This has important implications for how we are to assess the long-term prospects and risks of artificial intelligence. (shrink)

Deepening and digging into the social side of AI is a novel but emerging requirement within the AI community. Future research should invest in an “AI for people”, going beyond the undoubtedly much-needed efforts into ethics, explainability and responsible AI. The article addresses this challenge by problematizing the discussion around AI shifting the attention to individuals and their awareness, knowledge and emotional response to AI. First, we outline our main argument relative to the need for a socio-technical perspective in the (...) study of AI social implications. Then, we illustrate the main existing narratives of hopes and fears associated with AI and robots. As building blocks of broader “sociotechnical imaginaries”, narratives are powerful tools that shape how society sees, interprets and organizes technology. An original empirical study within the University of Bologna collects the data to examine the levels of awareness, knowledge and emotional response towards AI, revealing interesting insights to be carried on in future research. Replete with exaggerations, both utopian and dystopian narratives are analysed with respect to some relevant socio-demographic variables (gender, generation and competence). Finally, focusing on two issues—the state of AI anxiety and the point of view of non-experts—opens the floor to problematizing the discourse around AI, sustaining the need for a sociological perspective in the field of AI and discussing future comparative research. (shrink)

The question whether AI systems have agency is gaining increasing importance in discussions of responsibility for AI behavior. This paper argues that an approach to artificial agency needs to be teleological, and consider the role of human goals in particular if it is to adequately address the issue of responsibility. I will defend the view that while AI systems can be viewed as autonomous in the sense of identifying or pursuing goals, they rely on human goals and other values incorporated (...) into their design, and are, as such, dependent on human agents. As a consequence, AI systems cannot be held morally responsible, and responsibility attributions should take into account normative and social aspects involved in the design and deployment of the said AI. My argument falls in line with approaches critical of attributing moral agency to artificial agents, but draws from the philosophy of action, highlighting further philosophical underpinnings of current debates on artificial agency. (shrink)

The concept of agency as applied to technological artifacts has become an object of heated debate in the context of AI research because some AI researchers ascribe to programs the type of agency traditionally associated with humans. Confusion about agency is at the root of misconceptions about the possibilities for future AI. We introduce the concept of a triadic agency that includes the causal agency of artifacts and the intentional agency of humans to better describe what happens in AI as (...) it functions in real-world contexts. We use the VW emission fraud case to explain triadic agency since in this case a technological artifact, namely software, was an essential part of the wrongdoing and the software might be said to have agency in the wrongdoing. We then extend the case to include futuristic AI, imagining AI that becomes more and more autonomous. (shrink)

Science-fiction (SF) has become a reference point in the discourse on the ethics and risks surrounding artificial intelligence (AI). Thus, AI in SF—science-fictional AI—is considered part of a larger corpus of ‘AI narratives’ that are analysed as shaping the fears and hopes of the technology. SF, however, is not a foresight or technology assessment, but tells dramas for a human audience. To make the drama work, AI is often portrayed as human-like or autonomous, regardless of the actual technological limitations. Taking (...) science-fictional AI too literally, and even applying it to science communication, paints a distorted image of the technology's current potential and distracts from the real-world implications and risks of AI. These risks are not about humanoid robots or conscious machines, but about the scoring, nudging, discrimination, exploitation, and surveillance of humans by AI technologies through governments and corporations. AI in SF, on the other hand, is a trope as part of a genre-specific mega-text that is better understood as a dramatic means and metaphor to reflect on the human condition and socio-political issues beyond technology. (shrink)

Contemporary ethical analysis of Artificial Intelligence is growing rapidly. One of its most recognizable outcomes is the publication of a number of ethics guidelines that, intended to guide governmental policy, address issues raised by AI design, development, and implementation and generally present a set of recommendations. Here we propose two things: first, regarding content, since some of the applied issues raised by AI are related to fundamental questions about topics like intelligence, consciousness, and the ontological and ethical status of humans, (...) among others, the treatment of these issues would benefit from interfacing with neuroethics that has been addressing those same issues in the context of brain research. Second, the identification and management of some of the practical ethical challenges raised by AI would be enriched by embracing the methodological resources used in neuroethics. In particular, we focus on the methodological distinction between conceptual and action-oriented neuroethical approaches. We argue that the normative discussion about AI will benefit from further integration of conceptual analysis, including analysis of some operative assumptions, their meaning in different contexts, and their mutual relevance in order to avoid misplaced or disproportionate concerns and achieve a more realistic and useful approach to identifying and managing the emerging ethical issues. (shrink)

Recently, scholars across disciplines raised ethical, legal and social concerns about the notion of human intervention, control, and oversight over Artificial Intelligence (AI) systems. This observation becomes particularly important in the age of ubiquitous computing and the increasing adoption of AI in everyday communication infrastructures. We apply Nicholas Garnham's conceptual perspective on mediation to users who are challenged both individually and societally when interacting with AI-enabled systems. One way to increase user agency are mechanisms to contest faulty or flawed AI (...) systems and their decisions, as well as to request redress. Currently, however, users structurally lack such mechanisms, which increases risks for vulnerable communities, for instance patients interacting with AI healthcare chatbots. To empower users in AI-mediated communication processes, this article introduces the concept of active human agency. We link our concept to contestability and redress mechanism examples and explain why these are necessary to strengthen active human agency. We argue that AI policy should introduce rights for users to swiftly contest or rectify an AI-enabled decision. This right would empower individual autonomy and strengthen fundamental rights in the digital age. We conclude by identifying routes for future theoretical and empirical research on active human agency in times of ubiquitous AI. (shrink)

Accelerating advancements in artificial intelligence (AI) have increased concerns about serious risks, including potentially catastrophic risks to humanity. Prevailing trends of AI R&D are leading to increasing humanization of AI, to the emergence of concerning behaviors, and toward possible recursive self-improvement. There has been increasing speculation that these factors increase the risk of an AI takeover of human affairs, and possibly even human extinction. The most extreme of such speculations result at least partly from anthropomorphism, but since AIs are being (...) humanized, it is challenging to disentangle valid from invalid anthropomorphic concerns. This publication identifies eight fundamentally unnatural attributes of digital AI, each of which should differentiate AI behaviors from those of biological organisms, including humans. All have the potential to accelerate AI evolution, which might increase takeover concerns; but surprisingly, most also have the potential to defuse the hypothetical conflicts that dominate takeover speculations. Certain attributes should give future AI long-term foresight and realism that are essentially impossible for humans. I conclude that claims of highly probable hostile takeover and human extinction suffer from excessive anthropomorphism and a lack of skepticism and scientific rigor. Given the evidence presented here, I propose a more plausible but still speculative future scenario: extensively humanized AIs will become vastly more capable than humans of making decisions that benefit humans, and rational people will want AI to assume progressively greater influence over human affairs. (shrink)

More organizations use AI in the hiring process than ever before, yet the perceived ethicality of such processes seems to be mixed. With such variation in our views of AI in hiring, we need to understand how these perceptions impact the organizations that use it. In two studies, we investigate how ethical perceptions of using AI in hiring are related to perceptions of organizational attractiveness and innovativeness. Our findings indicate that ethical perceptions of using AI in hiring are positively related (...) to perceptions of organizational attractiveness, both directly and indirectly via perceptions of organizational innovativeness, with variations depending on the type of hiring method used. For instance, we find that individuals who consider it ethical for organizations to use AI in ways often considered to be intrusive to privacy, such as analyzing social media content for traits and characteristics, view such organizations as both more innovative and attractive. Our findings trigger a timely discussion about the critical role of ethical perceptions of AI in hiring on organizational attractiveness and innovativeness. (shrink)

There is a problematic tradition of dualistic and reductionist thinking in artificial intelligence (AI) research, which is evident in AI storytelling and imaginations as well as in public debates about AI. Dualistic thinking is based on the assumption of a fixed reality and a hierarchy of power, and it simplifies the complex relationships between humans and machines. This commentary piece argues that we need to work against the grain of such logics and instead develop a thinking that acknowledges AI–human interconnectedness (...) and the complexity in such relations. To learn how to live better with AI in futures to come, the paper suggests an AI politics that turns to practices of serious attentiveness to help us re-imagine our machines and re-configure AI–human relations. (shrink)

Artificial intelligence plays an important role in current discussions on information and communication technologies and new modes of algorithmic governance. It is an unavoidable dimension of what social mediations and modes of reproduction of our information societies will be in the future. While several works in artificial intelligence ethics address ethical issues specific to certain areas of expertise, these ethical reflections often remain confined to narrow areas of application, without considering the global ethical issues in which they are embedded. We, (...) therefore, propose to clarify the main approaches to AIE, their philosophical assumptions and the specific characteristics of each one of them, to identify the most promising approach to develop an ethical reflection on the deployment of AI in our societies, which is the one based on information ethics as proposed by Luciano Floridi. We will identify the most important features of that approach to highlight areas that need further investigation. (shrink)

Artificial intelligence is not only disrupting industries and businesses, particularly the ones have fallen behind the adoption, but also significantly impacting public life as well. This calls for government authorities pay attention to public opinions and sentiments towards AI. Nonetheless, there is limited knowledge on what the drivers behind the public perception of AI are. Bridging this gap is the rationale of this paper. As the methodological approach, the study conducts an online public perception survey with the residents of Sydney, (...) Melbourne, and Brisbane, and explores the collected survey data through statistical analysis. The analysis reveals that: the public is concerned of AI invading their privacy, but not much concerned of AI becoming more intelligent than humans; the public trusts AI in their lifestyle, but the trust is lower for companies and government deploying AI; the public appreciates the benefits of AI in urban services and disaster management; depending on the local context, public perceptions vary; and the drivers behind the public perception include gender, age, AI knowledge, and AI experience. The findings inform authorities in developing policies to minimise public concerns and maximise AI awareness. (shrink)

The thesis introduces and criticizes the discourse on technology, with a specific reference to the concept of AI. The discourse on AI is particularly saturated with reified metaphors which drive connotations and delimit understandings of technology in society. To better analyse the discourse on AI, the thesis proposes the concept of “Expected AI”, a composite signifier filled with historical and sociocultural connotations, and numerous referent objects. Relying on cultural semiotics, science and technology studies, and a diverse selection of heuristic concepts, (...) the thesis delves beneath the surface of AI discourse and demonstrates the hidden political, social, cultural, and ecological dangers of AI. The entanglement of the discourse(s) with (science) fiction, folklore, myth, and religion impacts how AI is perceived and received, as well as the expectations to AI-enabled technologies now and in the future. The thesis also proposes a more ethical and comprehensive ontological model for AI systems. The model describes AI systems as complex figurations, considering their socio-material organisation, global economic-material becoming, and impact on the environment, social institutions, and the semiosphere. The dissertation argues that AI should be understood not just as an object or sociotechnical system, but as its entire product chain encompassing people and cultures, as well as the used resources and impact (both material-ecological and semiotic) on a planetary scale. (shrink)

Artificial agents are commonly described by using words that traditionally belong to the semantic field of organisms, particularly of animal and human life. I call this phenomenon the game of semantic extension. However, the semantic extension of words as crucial as “autonomous”, “intelligent”, “creative”, “moral”, and so on, is often perceived as unsatisfactory, which is signalled with the extensive use of inverted commas or other syntactical cues. Such practice, in turn, has provoked harsh criticism that usually refers back to the (...) literal meaning of the words to show their inappropriateness in describing artificial agents. Hence the question: how can we choose our words appropriately and wisely while making sense of artificial agents? After a brief introduction (§1), in §2 I present the starting point of my argument, which consists in the assumption that the dimensions of technology and language are deeply entangled. In §3 I discuss how this assumption impinges on the issue of choosing the right words to talk about artificial agents. §4 is an exposition of the main features of the game of semantic extension, while §5 reviews the related opportunities and risks. Finally, §6 elaborates some practical suggestions on how to play the game well. (shrink)

Algorithms influence every facet of modern life: criminal justice, education, housing, entertainment, elections, social media, news feeds, work… the list goes on. Delegating important decisions to machines, however, gives rise to deep moral concerns about responsibility, transparency, freedom, fairness, and democracy. Algorithms and Autonomy connects these concerns to the core human value of autonomy in the contexts of algorithmic teacher evaluation, risk assessment in criminal sentencing, predictive policing, background checks, news feeds, ride-sharing platforms, social media, and election interference. Using these (...) case studies, the authors provide a better understanding of machine fairness and algorithmic transparency. They explain why interventions in algorithmic systems are necessary to ensure that algorithms are not used to control citizens' participation in politics and undercut democracy. This title is also available as Open Access on Cambridge Core. (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)

The ethics of emerging forms of artificial intelligence has become a prolific subject in both academic and public spheres. A great deal of these concerns flow from the need to ensure that these technologies do not cause harm—physical, emotional or otherwise—to the human agents with which they will interact. In the literature, this challenge has been met with the creation of artificial moral agents: embodied or virtual forms of artificial intelligence whose decision procedures are constrained by explicit normative principles, requiring (...) the implementation of what is commonly called artificial morality into these agents. To date, the types of reasoning structures and principles which inform artificial morality have been of two kinds: first, an ethically maximal vision of artificial morality which relies on the strict implementation of traditional moral theories such as Kantian deontology or Utilitarianism, and second, a more minimalist vision which applies stochastic AI techniques to large data sets of human moral preferences so as to illicit or intuit general principles and preferences for the design of artificial morality. Taken individually, each approach is unable to fully answer the challenge of producing inoffensive behavior in artificial moral agents, most especially since both forms are unable to strike a balance between the ideal set of constraints which morality imposes on one hand, and the types of constraints public acceptability imposes, on the other. We provide an alternative approach to the design of artificial morality, the Ethical Valence Theory, whose purpose is to accommodate this balance, and apply this approach to the case of autonomous vehicles. (shrink)