From a 4E cognition framework, this article compares earlier cultural and technologically mediated expert practices with contemporary use of digital technology. I discuss two case studies. First, the art of memory, where I look at how medieval monks constructed memory palaces inside their minds to enable creative thinking and how Renaissance thinker Giulio Camillo built on this tradition to create a complex machine to think. The second example is of literary writing, where I look at how writers engage with the (...) materiality of language and the writing material, creating new cognitive opportunities. Finally, I compare these earlier practices with contemporary digital technology, discussing both continuous and novel aspects. First, I examine how all practices engineer the cognitive surroundings of its practitioners to enable new cognitive possibilities. However, this comparative work also allows me to spot a worrisome novelty in digital technology. In many cases, the goals of such technology are contrary to those of its users. Drawing on discussions both outside and inside the 4E framework, I argue that digital technology introduces economic agency into our minds. I suggest that when we extend our minds in the digital ecology, we allow powerful economic actors to shape the direction of our cognitive lives in ways that are contrary to our own goals. Finally, I argue, building on the case studies, that my discussion might point to a new and more pragmatic approach to these issues. (shrink)

Enacting an AI system typically requires three iterative phases where AI engineers are in command: selection and preparation of the data, selection and configuration of algorithmic tools, and fine-tuning of the different parameters on the basis of intermediate results. Our main hypothesis is that these phases involve practices with ethical questions. This paper maps these ethical questions and proposes a way to address them in light of a neo-republican understanding of freedom, defined as absence of domination. We thereby identify different (...) types of responsibility held by AI engineers and link them to concrete suggestions on how to improve professional practices. This paper contributes to the literature on AI and ethics by focusing on the work necessary to configure AI systems, thereby offering an input to better practices and an input for societal debates. (shrink)

In 2023, online search engine provider Microsoft integrated a language model that provides direct answers to search queries into its search engine Bing. Shortly afterwards, Google also introduced a similar feature to its search engine with the launch of Google Gemini. This introduction of direct answers to search queries signals an important and significant change in online search. This article explores the implications of this new search paradigm. Drawing on Donna Haraway’s theory of _Situated Knowledges_ and Rainer Mühlhoff’s concept of (...) _Sealed Surfaces_, I introduce the term _Sealed Knowledges_ to draw attention to the increasingly difficult access to the plurality of potential answers to search queries through the output of a singular, authoritative, and plausible text paragraph. I argue that the integration of language models for the provision of direct answers into search engines is based on a de-situated and disembodied understanding of knowledge and affects the subjectivities of its users. At the same time, the _sealing of knowledges_ can lead to an increasing spread of misinformation and may make marginalized knowledge increasingly difficult to find. The paper concludes with an outlook on how to resist the increasing _sealing of knowledges_ in online search. (shrink)

The human-centered AI approach posits a future in which the work done by humans and machines will become ever more interactive and integrated. This article takes human-centered AI one step further. It argues that the integration of human and machine intelligence is achievable only if human organizations—not just individual human workers—are kept “in the loop.” We support this argument with evidence of two case studies in the area of predictive maintenance, by which we show how organizational practices are needed and (...) shape the use of AI/ML. Specifically, organizational processes and outputs such as decision-making workflows, etc. directly influence how AI/ML affects the workplace, and they are crucial for answering our first and second research questions, which address the pre-conditions for keeping humans in the loop and for supporting continuous and reliable functioning of AI-based socio-technical processes. From the empirical cases, we extrapolate a concept of “keeping the organization in the loop” that integrates four different kinds of loops: AI use, AI customization, AI-supported original tasks, and taking contextual changes into account. The analysis culminates in a systematic framework of keeping the organization in the loop look based on interacting organizational practices. (shrink)

The paper presents a new seven-step methodology for using narrative ethics and two case studies illustrating its application. A brief discussion of the importance of ethics to engineers and the need to consider outcomes and macroethics introduce the paper. This is followed by overviews of the literature on narrative ethics, the ethics of care, and virtue ethics and moral exemplars. The ethics of care and virtue ethics are included due to their relationship to narrative and the fact they are probably (...) less known to many engineers than other types of ethical theories. The paper also considers the important issues of culture, diversity and the ‘other’ and the need for support and collective responsibility. Understanding diversity and the ‘other’ are very important for engineers for a number of reasons, including the need to design technologies, goods and services for people who are not engineers and who are also different from them on other characteristics, such as gender, race and disability. Although ethical behaviour is often portrayed as an individual responsibility, it is much easier to behave ethically in a context which supports and encourages ethical behaviour. Collective action is frequently more effective than individual action and can prevent victimisation. (shrink)

There is a deluge of AI-assisted decision-making systems, where our data serve as proxy to our actions, suggested by AI. The closer we investigate our data (raw input, or their learned representations, or the suggested actions), we begin to discover “bugs”. Outside of their test, controlled environments, AI systems may encounter situations investigated primarily by those in other disciplines, but experts in those fields are typically excluded from the design process and are only invited to attest to the ethical features (...) of the resulting system or to comment on demonstrations of intelligence and aspects of craftmanship after the fact. This communicative impasse must be overcome. Our idea is that philosophical and engineering considerations interact and can be fruitfully combined in the AI design process from the very beginning. We embody this idea in the role of a philosopher engineer. We discuss the role of philosopher engineers in the three main design stages of an AI system: deployment management (what is the system’s intended use, in what environment?); objective setting (what should the system be trained to do, and how?); and training (what model should be used, and why?). We then exemplify the need for philosopher engineers with an illustrative example, investigating how the future decisions of an AI-based hiring system can be fairer than those contained in the biased input data on which it is trained; and we briefly sketch the kind of interdisciplinary education that we envision will help to bring about better AI. (shrink)

This study challenges the conventional boundaries of philosophy by asserting that organizations can function as legitimate subjects within philosophical discourse. Western philosophy, epitomized by Descartes, has long assumed that individual human beings are the fundamental units of thought and moral agency. However, in a significant oversight, this belief overlooks the idea that organizations can think independently, leading to both virtuous and malevolent results. Epistemology lacks a clear prioritization of morally sound knowledge over potentially harmful knowledge. The advent of artificial intelligence (...) (AI) has also transformed the landscape of cognition from a primarily individual human endeavor into a joint undertaking where humans collaborate with AI entities in collective thinking and decision-making. Nevertheless, AI lacks the innate ability to discern between ethical and unethical actions. This symbiosis creates organizations as fundamental philosophical subjects, marking a significant shift in philosophical emphasis where the organization takes the center stage. Accordingly, within this emerging field, we advance four propositions as the core subjects of organization philosophy: organizations can think, organizations can create knowledge, AI can be part of an organization, and humans in the organization control moral discipline. These propositions guide the ethical coexistence of AI and human agents in organizations, emphasizing the importance of ethical deliberation in knowledge use. Moreover, the malicious use of profound knowledge hinders human progress, as illustrated in this study by an ethical examination of military institutions within organization philosophy. (shrink)

This paper considers what liberal philosopher Michael Sandel coins the ‘moral limits of markets’ in relation to the idea of paying people for data about their biometrics and emotions. With Sandel arguing that certain aspects of human life (such as our bodies and body parts) should be beyond monetisation and exchange, others argue that emerging technologies such as Personal Information Management Systems can enable a fairer, paid, data exchange between the individual and the organisation, even regarding highly personal data about (...) our bodies and emotions. With the field of data ethics rarely addressing questions of payment, this paper explores normative questions about data dividends. It does so by conducting a UK-wide, demographically representative online survey to quantitatively assess adults’ views on being paid for personal data about their biometrics and emotions via a Personal Information Management System, producing a data dividend, a premise which sees personal data through the prism of markets and property. The paper finds diverse attitudes based on socio-demographic characteristics, the type of personal data sold, and the type of organisation sold to. It argues that (a) Sandel’s argument regarding the moral limits of markets has value in protecting fundamental freedoms of those in society who are arguably least able to (such as the poor); but (b) that contexts of use, in particular, blur moral limits regarding fundamental freedoms and markets. (shrink)

From the deployment of chatbots as procurement negotiators by corporations such as Walmart to autonomous agents providing ‘differentiated chat’ for managing overbooked flights, synthetic media are making the world of logistics their ‘natural’ habitat. Here, the coordination of commodities, parts and labour design the problems and produce the training sets from which ‘solutions’ can be synthesised. But to what extent might synthetic media, surfacing via platforms such as Midjourney and OpenAI, be understood as logistical media? This paper charts a selective (...) genealogy of synthetic media from early attempts to synthesise human sensory capacities in order to cybernetically integrate them into computational circuits. We see this integration as a pre-emption of their (computational) logistical coordination. It then details media experiments with ‘ChatFOS’, a GPT-based bot tasked with developing a logistics design business. Using its prompt-generated media outputs, we assemble a simulation and parody of AI’s emerging functionalities within logistical worlds. In the process, and with ‘human-in-the-loop’ stitching, we illustrate how large language models become media managers overseeing image prompts, graphical design, website code, promotional copy and investor pitch scenarios. The processes and methods of producing speculative scenarios via ChatFOS lead us to consider how the media of logistics and the logistics of media are increasingly enfolded. We ask: what can a (practice-based) articulation of this double-becoming of logistics and synthetic mediality tell us about the politics and aesthetics of contemporary computation and capital? (shrink)

Artificial intelligence is poised to eliminate millions of jobs, from finance to truck driving. But artisanal products are valued precisely because of their human origins, and thus have some inherent “immunity” from AI job loss. At the same time, artisanal labor, combined with technology, could potentially help to democratize the economy, allowing independent, small-scale businesses to flourish. Could AI, robotics and related automation technologies enhance the economic viability and environmental sustainability of these beloved crafting professions, perhaps even expanding their niche (...) to replace some job loss in other sectors? In this paper, we compare the problems created by the current mass production economy and potential solutions from an artisanal economy. In doing so, the paper details the possibilities of utilizing AI to support hybrid forms of human–machine production at the microscale; localized and sustainable value chains at the mesoscale; and networks of these localized and sustainable producers at the macroscale. In short, a wide range of automation technologies are potentially available for facilitating and empowering an artisanal economy. Ultimately, it is our hope that this paper will facilitate a discussion on a future vision for more “generative” economic forms in which labor value, ecological value and social value can circulate without extraction or alienation. (shrink)

Recent advances in natural language generation (NLG), such as public accessibility to ChatGPT, have sparked polarised debates about the societal impact of this technology. Popular discourse tends towards either overoptimistic hype that touts the radically transformative potentials of these systems or pessimistic critique of their technical limitations and general ‘stupidity’. Surprisingly, these debates have largely overlooked the exegetical capacities of these systems, which for many users seem to be producing meaningful texts. In this paper, we take an interdisciplinary approach that (...) combines hermeneutics—the study of meaning and interpretation—with prompt engineering—task descriptions embedded in input to NLG systems—to study the extent to which a specific NLG system, ChatGPT, produces texts of hermeneutic value. We design prompts with the goal of optimising hermeneuticity rather than mere factual accuracy, and apply them in four different use cases combining humans and ChatGPT as readers and writers. In most cases, ChatGPT produces readable texts that respond clearly to our requests. However, increasing the specificity of prompts’ task descriptions leads to texts with intensified neutrality, indicating that ChatGPT’s optimisation for factual accuracy may actually be detrimental to the hermeneuticity of its output. (shrink)

A major approach to the ethics of artificial intelligence is to use social choice, in which the AI is designed to act according to the aggregate views of society. This is found in the AI ethics of “coherent extrapolated volition” and “bottom–up ethics”. This paper shows that the normative basis of AI social choice ethics is weak due to the fact that there is no one single aggregate ethical view of society. Instead, the design of social choice AI faces three (...) sets of decisions: standing, concerning whose ethics views are included; measurement, concerning how their views are identified; and aggregation, concerning how individual views are combined to a single view that will guide AI behavior. These decisions must be made up front in the initial AI design—designers cannot “let the AI figure it out”. Each set of decisions poses difficult ethical dilemmas with major consequences for AI behavior, with some decision options yielding pathological or even catastrophic results. Furthermore, non-social choice ethics face similar issues, such as whether to count future generations or the AI itself. These issues can be more important than the question of whether or not to use social choice ethics. Attention should focus on these issues, not on social choice. (shrink)

In recent years, ethical questions related to the development of artificial intelligence are being increasingly discussed. However, there has not been enough corresponding increase in the research and development associated with AI technology that incorporates with ethical discussion. We therefore implemented an organic and dynamic tool for use with knowledge base of AI ethics for engineers to promote engineers’ practice of ethical AI design to realize further social values. Here, “organic” means that the tool deals with complex relationships among different (...) AI ethics. “Dynamic” means that the tool dynamically adopts new issues and helps engineers think in their own contexts. Data in the knowledge base of the tool is standardized based on the ethical design theory that consists of an extension of the hierarchical representation of artifacts to understand ethical considerations from the perspective of engineering, and a description method to express the design ideas. In addition, we apply the dynamic knowledge management model called knowledge liquidization and crystallization. To discuss the effects, we introduce three cases: a case for the clarification of differences in the structures among AI ethics and design ideas, a case for the presentation of semantic distance among them, and a case for the recommendation of the scenario paths that allow engineers to seamlessly use AI ethics in their own contexts. We discuss the effectiveness of the tool. We also show the probability that engineers can reconstruct AI ethics as a more practical one with professional ethicists. (shrink)

The implementation of cyber-physical and similar systems depends on prevailing social and economic conditions. It is here argued that, if the effect of these technologies is to be benign, the current neo-liberal economy must change to a radically more cooperative model. In this paper, economy change means a thorough change to a qualitatively different kind of economy. It is contrasted with economic change, which is the kind of minor change usually considered in mainstream discourse. The importance of language is emphasised, (...) including that of techno-optimism and that of economic conservatism. Problems of injustice, strife, and ecological overload cannot be solved by conventional growth together with technical efficiency gains. Rather, a change is advocated from economics-as-usual to a broader concept, oikonomia, which takes into account all that contributes to a good life, including what cannot be represented quantitatively. Some elements of such a broader economy are discussed. It is argued that the benefits of technology can be enhanced and the ills reduced in such an economy. This is discussed in the case of cyber-physical systems under the headings employment, security, standards and oligopoly, and energy efficiency. The paper concludes that such systems, and similar technological developments, cannot resolve the problems of sustainability within an economy-as-usual model. If, however, there is the will to create a cooperative and sustainable economy, technology can contribute significantly to the resolution of present problems. (shrink)

Given the pervasiveness of AI systems and their potential negative effects on people’s lives (especially among already marginalised groups), it becomes imperative to comprehend what goes on when an AI system generates a result, and based on what reasons, it is achieved. There are consistent technical efforts for making systems more “explainable” by reducing their opaqueness and increasing their interpretability and explainability. In this paper, we explore an alternative non-technical approach towards explainability that complement existing ones. Leaving aside technical, statistical, (...) or data-related issues, we focus on the very conceptual underpinnings of the design decisions made by developers and other stakeholders during the lifecycle of a machine learning project. For instance, the design and development of an app to track snoring to detect possible health risks presuppose some picture or another of “health”, which is a key notion that conceptually underpins the project. We take it as a premise that these key concepts are necessarily present during design and development, albeit perhaps tacitly. We argue that by providing “justificatory explanations” about how the team understands the relevant key concepts behind its design decisions, interested parties could gain valuable insights and make better sense of the workings and outcomes of systems. Using the concept of “health”, we illustrate how a particular understanding of it might influence decisions during the design and development stages of a machine learning project, and how making this explicit by incorporating it into ex-post explanations might increase the explanatory and justificatory power of these explanations. We posit that a greater conceptual awareness of the key concepts that underpin design and development decisions may be beneficial to any attempt to develop explainability methods. We recommend that “justificatory explanations” are provided as technical documentation. These are declarative statements that contain at its simplest: (1) a high-level account of the understanding of the relevant key concepts a team possess related to a project’s main domain, (2) how these understandings drive decision-making during the life-cycle stages, and (3) it gives reasons (which could be implicit in the account) that the person or persons doing the explanation consider to have plausible justificatory power for the decisions that were made during the project. (shrink)

Curiosity is having its moment in AI engineering. Governments and Big Tech alike frame the trait as a key characteristic of data scientists. This paper offers a qualitative analysis of the perspectives of AI engineers on the importance of curiosity in their profession. The results of this study—which took place at a technology multinational of over 250 k + employees—warn that unless curiosity is carefully defined, detached from masculinized interpretations of what it entails, and linked to ethical development practices, (...) the current emphasis on curiosity risks promoting harmful curiosity-based engineering practices. The paper begins by exposing the consequences of curiosity’s configuration within existing corporate and social inequalities. It then reviews theoretical literature on the gendering of skills and attributes in AI engineering. Having synthesized evidence of curiosity’s importance in corporate AI engineering, it draws on new qualitative data to draw out key themes that might be contributing to the gendering of curiosity, before exploring these themes in their wider context through the theoretical literature. It ends by outlining ways that curiosity-based engineering could promote rather than hinder ethical AI. (shrink)

In a world permeated by digital technology, engineering is involved in every aspect of human life. Engineers address a wider range of design problems than ever before, raising new questions and challenges regarding their work, as boundaries between engineering, management, politics, education and art disappear in the face of comprehensive socio-technical systems. It is therefore necessary to review our understanding of engineering practice, expertise and responsibility. This book advances the idea that the future of engineering will (...) not be driven by a static view of a closed discipline, but rather will result from a continuous dialogue between different stakeholders involved in the design and application of technical artefacts. Based on papers presented at the 2016 conference of the forum for Philosophy, Engineering and Technology in Nuremberg, Germany, the book features contributions by philosophers, engineers and managers from academia and industry, who discuss current and upcoming issues in engineering from a wide variety of different perspectives. They cover topics such as problem solving strategies and value-sensitive design, experimentation and simulation, engineering knowledge and education, interdisciplinary collaboration, sustainability, risk and privacy. The different contributions in combination draw a comprehensive picture of efforts worldwide to come to terms with engineering, its foundations in philosophy, the ethical problems it causes, and its effect on the ongoing development of society. (shrink)

Knowledge management is important in the construction industry, but there is a dramatic gap between rhetoric and reality, highlighting mistaken expectations of technology. We report on a case study of a major construction company. The UK construction industry, with scarce academic qualifications, and limited use of IT, depends on knowledge sharing, and, crucially, on tacit knowledge. Economic crisis presents particular problems, and recent trends in work organization have far-reaching implications. The industry depends on human knowledge, with limited systems support. A (...) shared concern for health and safety provides the surest guarantee of sustainability of both knowledge and the company. (shrink)

AI for social good is a thriving research topic and a frequently declared goal of AI strategies and regulation. This article investigates the requirements necessary in order for AI to actually serve a public interest, and hence be socially good. The authors propose shifting the focus of the discourse towards democratic governance processes when developing and deploying AI systems. The article draws from the rich history of public interest theory in political philosophy and law, and develops a framework for ‘public (...) interest AI’. The framework consists of (1) public justification for the AI system, (2) an emphasis on equality, (3) deliberation/ co-design process, (4) technical safeguards, and (5) openness to validation. This framework is then applied to two case studies, namely SyRI, the Dutch welfare fraud detection project, and UNICEF’s Project Connect, that maps schools worldwide. Through the analysis of these cases, the authors conclude that public interest is a helpful and practical guide for the development and governance of AI for the people. (shrink)

This study uses an artificial intelligence (AI) model to identify arbitrage opportunities in the retail marketplace. Specifically, we develop an AI model to predict the optimal purchasing point based on the price movement of products in the market. Our model is trained on a large dataset collected from an online marketplace in the United States. Our model is enhanced by incorporating user-generated content (UGC), which is empirically proven to be significantly informative. Overall, the AI model attains more than 90% precision (...) rate, while the recall rate is higher than 80% in an out-of-sample test. In addition, we conduct a field experiment to verify the external validity of the AI model in a real-life setting. Our model identifies 293 arbitrage opportunities during a one-year field experiment and generates a profit of $7.06 per arbitrage opportunity. The result demonstrates that AI performs exceptionally well in identifying arbitrage opportunities in retail markets with tangible economic values. Our results also yield important implications regarding the role of AI in the society, both from the consumer and firm perspectives. (shrink)

Mises’ and Hayek’s arguments against central economic planning have long been taken as definitive proof that a centrally planned economy managed by the government would be impossible. Today, however, the exponential rise in the capacities of AI has opened up the possibility that supercomputers could have what it takes to plan the national economy. The ‘economic calculation debate’ has thus reignited. Arguably, this is because neither Mises nor Hayek have given a clear and conclusive argument why central planning of the (...) economy is impossible in principle. The paper frames the problem of economic planning as an agent–environment interaction, offering a taxonomy of the different sets of agents at play a) in a market economy and b) in a centrally planned economy equipped with the most sophisticated AI technology. The argument is that public institutions as planning bodies cannot replace the market order, no matter the AI technology behind them, for the elimination of the market entails the elimination of crucial kinds of agents that cannot be recreated or emulated through AI or careful social planning: the proactive action of entrepreneurs driving market allocation. (shrink)

Artificial intelligence (AI)-based virtual influencers are now frequently used by brands in various categories to engage customers. However, little is known about who the followers of these AI-based virtual influencers are and more importantly, what drives the followers to use AI-based virtual influencers. The results from a survey support the notion that compensatory mechanisms and the need to belong play important roles in affecting usage intentions of AI-based virtual influencers. Specifically, the study finds that usage intentions are mediated and moderated (...) by compensatory mechanisms that arise from the perception of AI-based virtual influencers’ functional benefits and existential threats to human identity. Furthermore, the need for belonging moderates the effects of the following status (following versus non-following) on perceived personalization benefits of AI-based virtual influencers and behavioral intentions to use AI-based virtual influencers. This study provides important implications for academia delving into the social, cultural, and philosophical implications of AI-based virtual influencers for human societies as well as for brands that plan to use AI-based virtual influencers and gain a better understanding of their customers in AI-driven digital marketing. (shrink)

The problem that I present in this paper concerns the issue of ethical evaluation of algorithms, especially those used in social media and which create profiles of users of these media and new technologies that have recently emerged and are intended to change the functioning of technologies used in data management. Systems such as Overton, SambaNova or Snorkel were created to help engineers create data management models, but they are based on different assumptions than the previous approach in machine learning (...) and deep learning. There is a need to analyze both deep learning algorithms and new technologies in database management in terms of their actions towards a person who leaves their digital footprints, on which these technologies work. Then, the possibilities of applying the existing deep learning technology and new Big Data systems in the economy will be shown. The opportunities offered by the systems mentioned above seem to be promising for many companies and—if implemented on a larger scale—they will affect the functioning of the free market. (shrink)

One response to the existential threat posed by a super-intelligent AI is to design it to be friendly to us. Some have argued that even if this were possible, the resulting AI would treat us as we do our pets. Sparrow (AI & Soc. https://doi.org/10.1007/s00146-023-01698-x, 2023) argues that this would be a bad outcome, for such an AI would dominate us—resulting in our freedom being diminished (Pettit in Just freedom: A moral compass for a complex world. WW Norton & Company, (...) 2014). In this paper, I consider whether this would be such a bad outcome. (shrink)

The justification and rationality of this paper is to present some fundamental principles, theories, and concepts that we believe moulds the nucleus of a good artificial intelligence (AI) society. The morally accepted significance and utilitarian concerns that stems from the inception and realisation of an AI’s structural foundation are displayed in this study. This paper scrutinises the structural foundation, fundamentals, and cardinal righteous remonstrations, as well as the gaps in mechanisms towards novel prospects and perils in determining resilient fundamentals, accountability, (...) and AI’s convoluted and responsible implications. We outline a number of salient and practical benefits, in which to place moral norms within the mise en scène of AI, to delineate the rudimentary ethical dilemmas and decorous directions within the realms of AI. (shrink)

The progressive dissemination of artificial intelligence (AI) systems in work settings raises numerous questions and concerns regarding their consequences, whether positive or negative, on work activities and organizations. This paper presents an empirical study that was designed to identify and analyze these consequences in radiology. This study focuses on two AI systems: a voice recognition dictation system for radiological reports and a system for detecting fractures on X-rays images. Based on a qualitative analysis of field observations of work activities and (...) interviews with radiologists, emergency physicians, and medical secretaries, our findings help to provide a nuanced view on how AI may affect work in this sector. In contrast to the speculative discourse where AI is seen as a “positive” technology or as “threat” for workers, this study shows, on the one hand, how these kinds of AI systems help or may help these workers in their activities, and, on the other hand, how these systems raise problematic issues regarding their consequences not only for physicians but also for other workers such as medical assistants. (shrink)

This article tries to shed light on the difference between human autonomy and AI-driven machine autonomy. The breadth of the studies concerning this topic is constantly increasing, and for this reason, this discussion is very narrow and limited in its extent. Indeed, its hypothesis is that it is possible to distinguish two kinds of autonomy by analysing the way humans and robots narrate stories and the types of stories that, respectively, result from their capability of narrating stories on their own. (...) To approach the question of autonomy and its different interpretations in robots and humans, using narratives and stories as a lens, I proceed through four steps. First, I provide a brief summary concerning the state of the art with regard to issues concerning autonomy and AI. Second, I focus on specific issues concerning AI that are applied to storytelling. Third, I progressively approach narrative autonomy through what could seem a useless digression by addressing the problem of human creativity in relation to machine creativity. Fourth, I hypothesize a radical difference between narrative autonomy—which is proper to humans—and storytelling capability, which can be observed in both humans and machines. (shrink)

Before embarking on a discussion of the regulation of artificial intelligence (AI), it is first necessary to define the subject matter regulated. Defining artificial intelligence is a difficult endeavour, and many definitions have been proposed over the years. Although more than 70 years have passed since it was adopted, the most convincing definition is still nonetheless that proposed by Turing; in any case, it is important to be mindful of the risk of anthropomorphising artificial intelligence, which may arise in particular (...) from its very definition. Once we have established the subject matter regulated, we must ask ourselves whether lawmakers should pursue an approach that seeks to regulate artificial intelligence as a whole, or whether by contrast they should regulate applications of artificial intelligence in specific sectors or individual areas. The proposal for a regulation on artificial intelligence published on 21 April 2021 implements the former approach whilst also pursuing geopolitical goals. After providing an initial overview of the notion of artificial intelligence, this article investigates the geopolitical context to the proposal for a regulation, and then goes on to illustrate the regulatory model embraced by the proposal as well as related critical aspects. (shrink)

Ensuring the trustworthiness of autonomous systems and artificial intelligence is an important interdisciplinary endeavour. In this position paper, we argue that this endeavour will benefit from technical advancements in capturing various forms of responsibility, and we present a comprehensive research agenda to achieve this. In particular, we argue that ensuring the reliability of autonomous system can take advantage of technical approaches for quantifying degrees of responsibility and for coordinating tasks based on that. Moreover, we deem that, in certifying the legality (...) of an AI system, formal and computationally implementable notions of _responsibility_, _blame_, _accountability_, and _liability_ are applicable for addressing potential responsibility gaps (i.e. situations in which a group is responsible, but individuals’ responsibility may be unclear). This is a call to enable AI systems themselves, as well as those involved in the design, monitoring, and governance of AI systems, to represent and reason about who can be seen as responsible in prospect (e.g. for completing a task in future) and who can be seen as responsible retrospectively (e.g. for a failure that has already occurred). To that end, in this work, we show that across all stages of the design, development, and deployment of trustworthy autonomous systems (TAS), responsibility reasoning should play a key role. This position paper is the first step towards establishing a road map and research agenda on how the notion of responsibility can provide novel solution concepts for ensuring the _reliability_ and _legality_ of TAS and, as a result, enables an effective embedding of AI technologies into society. (shrink)

Social data mining has become an emerging area of research in information and communication technology fields. The scope of social data mining has expanded significantly in the recent years with the advance of telecommunication technologies and the rapidly increasing accessibility of computing resources and mobile devices. People increasingly engage in and rely on phone communications for both personal and business purposes. Hence, mobile phones become an indispensable part of life for many people. In this article, we perform social data mining (...) on mobile social networking by presenting a simple but efficient method to define social closeness and social grouping, which are then used to identify social sizes and scaling ratio of close to “8”. We conclude that social mobile network is a subset of the face-to-face social network, and both groupings are not necessary the same, hence the scaling ratios are distinct. Mobile social data mining. (shrink)

Cultural influences are pervasive throughout human behaviour, and as human–robot interactions become more common, roboticists are increasingly focusing attention on how to build robots that are culturally competent and culturally sustainable. The current treatment of culture in robotics, however, is largely limited to the definition of culture as national culture. This is problematic for three reasons: it ignores subcultures, it loses specificity and hides the nuances in cultures, and it excludes refugees and stateless persons. We propose to shift the focus (...) of cultural robotics to redefine culture as an emergent phenomenon. We make use of three research programmes in the social and cognitive sciences to justify this definition. Consequently, cultural behaviour cannot be explicitly programmed into a robot, rather, a robot must be designed with the capability to participate in the interactions that lead to the arising of cultural behaviour. In the final part of the paper, we explore which capacities and abilities are the most salient for a robot to do this. (shrink)

Much of the current work on AI ethics has lost its connection to the real-world impact by making AI ethics operable. There exist significant limitations of hyper-focusing on the identification of abstract ethical principles, lacking effective collaboration among stakeholders, and lacking the communication of ethical principles to real-world applications. This position paper presents challenges in making AI ethics operable and highlights key obstacles to AI ethics impact. A preliminary practice example is provided to initiate practical implementations of AI ethics. We (...) aim to inspire discussions on making AI ethics operable and focus on its impact on real-world applications. (shrink)

In combating the ongoing global health threat of the COVID-19 pandemic, decision-makers have to take actions based on a multitude of relevant health data with severe potential consequences for the affected patients. Because of their presumed advantages in handling and analyzing vast amounts of data, computer systems of algorithmic decision-making are implemented and substitute humans in decision-making processes. In this study, we focus on a specific application of ADM in contrast to human decision-making, namely the allocation of COVID-19 vaccines to (...) the public. In particular, we elaborate on the role of trust and social group preference on the legitimacy of vaccine allocation. We conducted a survey with a 2 × 2 randomized factorial design among n = 1602 German respondents, in which we utilized distinct decision-making agents and prioritization of a specific social group as design factors. Our findings show that general trust in ADM systems and preference for vaccination of a specific social group influence the legitimacy of vaccine allocation. However, contrary to our expectations, trust in the agent making the decision did not moderate the link between social group preference and legitimacy. Moreover, the effect was also not moderated by the type of decision-maker. We conclude that trustworthy ADM systems must not necessarily lead to the legitimacy of ADM systems. (shrink)

There are plenty of intelligent machines in our world today: digital computers and autonomous robots. At the heart of each of these machines there are automatic formal systems (programs running on a digital computer). Now, if the interpretation of a formal system does not belong to the formal system itself, if the interpretation has to be added, it is worth asking: in the case of these intelligent machines that are massively interspersed in our social interactions, where does the interpretation come (...) from? In this paper, we analyse what we call the invisibility of interpretation. Dealing with various types of formal systems (computers, robots, formalist approaches to Economics), the human source of the interpretation of these systems is sometimes concealed by a formalist restriction. To show how the formalist restriction produces the invisibility of interpretation allows us to underline our responsibility, as human agents, for all this interpretative work—and its importance for us as human beings. (shrink)

This paper explores the interplay between AI metrics and policymaking by examining the conceptual and methodological frameworks of global AI metrics and their alignment with National Artificial Intelligence Strategies (NAIS). Through topic modeling and qualitative content analysis, key thematic areas in NAIS are identified. The findings suggest a misalignment between the technical and economic focus of global AI metrics and the broader societal and ethical priorities emphasized in NAIS. This highlights the need to recalibrate AI evaluation frameworks to include ethical (...) and other social considerations, aligning AI advancements with the United Nations Sustainable Development Goals (SDGs) for an inclusive, ethical, and sustainable future. (shrink)

The research on technologies and methodologies for (accurate, real-time, spontaneous, three-dimensional…) facial expression recognition is ongoing and has been fostered in the past decades by advances in classification algorithms like deep learning, which makes them part of the Artificial Intelligence literature. Still, despite its upcoming application to contexts such as human–computer interaction, product and service design, and marketing, only a few literature studies have investigated the willingness of end users to share their facial data with the purpose of detecting (...) emotions. This study investigates the level of awareness and interest of 373 potential consumers towards this technology in the car insurance sector, particularly in the contract drafting phase, with a focus on differentiating the respondents between generation Y and Z. Results show that younger people, individuals with higher levels of education, and social network users feel more confident about this innovative technology and are more likely to share their expressive facial data. (shrink)

It is important to manage individuals’ personal data after their death to maintain their dignity or follow their wishes as much as possible. From this perspective, this report describes the real-world commercialization of immortal digital personalities, which gives eternal life to the deceased in a digital form. We identify the problems with the commercialization of deceased users’ images and personal data, which becomes postmortem entertainment. Considering these problems, we seek out the ideal form of deceased users’ personal data for commercialization. (...) We conduct a social survey to understand how ordinary Japanese people feel about the various types of publicly available services that use personal data after death, such as social network service logs. By analyzing our survey results approximately 20% of respondents would allow the commercial use of their personal data, such as browsing their social network service logs, if they could receive compensation during their lifetime. (shrink)

Amidst the surge in AI-oriented commercial ventures, music is a site of intensive efforts to innovate. A number of companies are seeking to apply AI to music production and consumption, and amongst them several are seeking to reinvent the music listening experience as adaptive, interactive, functional and infinitely generative. These are bold objectives, having no clear roadmap for what designs, technologies and use cases, if any, will be successful. Thus each company relies on speculative product visions. Through four case studies (...) of such companies, I consider how product visions must carefully provide a clear plan for developers and investors, whilst also remaining open to agile user-centred product development strategies, which I discuss in terms of the ‘blind search’ nature of innovation. I suggest that innovation in this area needs to be understood in terms of technological emergence, which is neither technologically determinist nor driven entirely by the visions of founders, but through a complex of interacting forces. I also consider, through these cases, how, through the accumulation of residual value, all such start-up work risks being exapted for more familiar extractive capitalist agendas under the general process that Doctorow calls “enshittification”. Lastly, I consider a number of other more specific ways in which these projects, if their growth is achieved, could influence music culture more broadly. (shrink)

The General Data Protection Regulation (GDPR) of the EU confirms the protection of personal data as a fundamental human right and affords data subjects more control over the way their personal information is processed, shared, and analyzed. However, where data are processed by artificial intelligence (AI) algorithms, asserting control and providing adequate explanations is a challenge. Due to massive increases in computing power and big data processing, modern AI algorithms are too complex and opaque to be understood by most data (...) subjects. Articles 15 and 22 of the GDPR provide a modest regulatory framework for automated data processing by, among other things, mandating that data controllers inform data subjects about when it is being used, and its logic and ramifications. Nevertheless, due to the phrasing of the articles and the numerous exceptions they allow, doubts have arisen about their effectiveness. In this paper, we empirically evaluate the quality and effectiveness of AI disclosures as mandated by the GDPR. By means of an online survey (N = 835), we investigated how data subjects expect to be informed about the automated processing of their data. We then conducted a content analysis of the AI disclosures of N = 100 companies and organizations. The combined findings reveal that current GDPR-mandated disclosures do not meet the expectations and needs of data subjects. Explanations drawn up following the guidelines of the generic formulations of the GDPR differ widely and are often vague, incomplete and lack transparency. In our conclusions we identify a path towards standardizing and optimizing AI information notices. (shrink)

Kazuo Ishiguro’s novel Klara and the Sun (2021) philosophizes on how in the current technologically saturated culture, the gradual evolution of the empathetic humanoids has, on one hand, problematized our normative notions of cognitive and affective categories, and on the other, has triggered an order of emotional uncanniness due to our reliance on hyperreal real objects for receiving solace and companionship. The novel may be conceived to be a commentary on the emerging discourse in the domain of cognitive and emotional (...) computing that aspires to transform the inner life and social relationships of the human community. The novelty of the paper lies in its ability to showcase how Kazuo Ishiguro’s Klara and the Sun (2021) creates a rupture in the existing research and literary narrative by critiquing the theoretical underpinnings of emotional computing that optimistically foresees a future where simulated empathetic minds will be able to decode the complexities of the human emotions. It discusses how literature turns into an apt tool to reflect on the limitations of the programmed machines to decode the elusiveness of the human mind that defies the one-to-one correlation between words, multiple connotations, and their underlying emotions. Through the lenses of the fictional narrative, the paper foregrounds how the concept of the social robot designed to offer empathy, care, and companionship turns into a failed project. The paper draws on critical perspectives from disposability theory, posthuman affect, and immaterial bodies to foreground the noncodified feature of affective experientialities that emerge as a result of the interface between humans and nonanimate beings. (shrink)

Whether or not we call a love-like relationship with robots true love, some people may feel and claim that, for them, it is a sufficient substitute for love relationship. The love relationship between humans has a special place in our social life. On the grounds of both morality and law, our significant other can expect special treatment. It is understandable that, precisely because of this kind of relationship, we save our significant other instead of others or will not testify against (...) her/him. How as a society should we treat love-like relationships humans with robots? Based on the assumption that robots do not have an inner life and are not moral patients, I defend the thesis that this kind of relationship should be protected by criminal law. (shrink)

Highly sophisticated capabilities of artificial intelligence (AI) have skyrocketed its popularity across many industry sectors globally. The public sector is one of these. Many cities around the world are trying to position themselves as leaders of urban innovation through the development and deployment of AI systems. Likewise, increasing numbers of local government agencies are attempting to utilise AI technologies in their operations to deliver policy and generate efficiencies in highly uncertain and complex urban environments. While the popularity of AI is (...) on the rise in urban policy circles, there is limited understanding and lack of empirical studies on the city manager perceptions concerning urban AI systems. Bridging this gap is the rationale of this study. The methodological approach adopted in this study is twofold. First, the study collects data through semi-structured interviews with city managers from Australia and the US. Then, the study analyses the data using the summative content analysis technique with two data analysis software. The analysis identifies the following themes and generates insights into local government services: AI adoption areas, cautionary areas, challenges, effects, impacts, knowledge basis, plans, preparedness, roadblocks, technologies, deployment timeframes, and usefulness. The study findings inform city managers in their efforts to deploy AI in their local government operations, and offer directions for prospective research. (shrink)

The effects that artificial intelligence (AI) technologies will have on society in the short- and long-term are inherently uncertain. For this reason, many governments are avoiding strict command and control regulations for this technology and instead rely on softer ethics-based approaches. The Russian approach to regulating AI is characterized by the prevalence of unenforceable ethical principles implemented via industry self-regulation. We analyze the emergence of the regulatory regime for AI in Russia to illustrate the limitations of this approach. The article (...) is based on 50 interviews with policymakers, representatives of AI companies, and academics in the country. The findings show that this regulatory regime was formed under the strong influence of Russian big tech companies, which saw an opportunity to avoid regulatory oversight by washing out concrete regulatory measures from the policy. This approach is part of a broader protectionist sanction-proofing strategy for the local IT sector designed by the government, which can be characterized by lifting regulatory barriers for local companies. Unenforceable ethics-based self-regulation is a _regulatory gift_ from the Russian government to the industry. This _gift_ was intentionally designed because the government thought that prioritizing local innovation over consumer protection would benefit the public. However, the _gift_ can also unintentionally undermine the public interest by providing an opportunity for _ethics washing_. (shrink)

This article aims to present the problem of the impact of artificial intelligence on respect for human dignity in the sphere of care for people who, for various reasons, are described as particularly vulnerable, especially seniors and people with various disabilities. In recent years, various initiatives and works have been undertaken on the European scene to define the directions in which the development and use of artificial intelligence should go. According to the human-centric approach, artificial intelligence should be developed, used (...) and monitored with people in mind, their needs and rights. It is artificial intelligence that should adapt to the rules set by people, not the other way around. The source of all human rights and freedoms is respect for human dignity. This is evidenced by numerous European, international, national regulations and documents. Respecting this value is also one of the works on the AI development. One of the areas of our life into which AI enters more and more boldly and which in the near future, due to demographic reasons and aging population, may be almost dominated by modern technologies, is the medical and care system. The usefulness of industrial co-robots made us think about the possibility of using similar devices in the non-industrial sphere, including in the sphere of care, nursing and therapy. Actually, despite the impressive development of technology and AI, intelligent robots/devices used for care, nursing or therapy (so-called care/nursing or therapy robots) perform rather simple activities. They provide information, navigate, bring something and give it (e.g. medicines, food), help to get up. They are an important support for medical staff in this respect. Performing tasks that are more complex in terms of technology and movement, such as feeding, washing, intimate hygiene, dressing or undressing, is still beyond the reach of the currently used robots. The question we must ask ourselves is whether, in the future, care robots will be able to perform such tasks, and should they do so? Will this lead to the replacement of human medical personnel in the performance of the above-mentioned activities with such robots. Would anyone want to be "looked after" by a soulless machine? Should potential wards/patients, in other words all of us in fact, have the right to object to being taken into the care of an intelligent robot? There is no doubt that intelligent robots have great potential, especially when it comes to ensuring or maintaining the independence or mobility of people with various health limitations. However, we must not forget about the risks and dangers they may generate. Even a simple robot generates serious legal and ethical problems. Who should be liable for damage caused in connection with improper care performed with the participation of a robot? Robots based on AI systems are able to collect a significant amount of sensitive data, for example through the face and speech recognition function. There is considerable scope for abuse in this area, not only in terms of personal data protection but also in terms of informational self-determination, privacy and dignity. Bearing in mind the above risks, the creation of a new right to object to being looked after by a robot should be considered. (shrink)