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 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)

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)

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)

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 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)

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)

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)

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)

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)

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)

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)

The relevance of this study's topic is supported by the argument that a philosophical understanding of the fundamental concepts of epistemology as they pertain to the educational process is crucial as the educational setting becomes increasingly digitalised. This paper aims to explore the epistemological component of the philosophy of learning in light of the educational process digitalisation. The research comprised a sample of 462 university students from Kazakhstan, with 227 participants assigned to the experimental and 235 to the control groups. (...) The research employed a scientific methodology that encompassed various scientific methods, including sociological, socio-philosophical, and culturological analysis. In addition, philosophical methods such as system analysis, structural and functional analysis, and comparative and hermeneutical approaches were utilised for the philosophical and epistemological interpretation of the cognitive activity mechanism of students and its dynamics in light of digitalising education. Furthermore, psychological diagnostic methods such as SAMOAL personality self-actualisation diagnostics, personality volitional potential diagnostics, and psychodiagnostic methods were employed. This study offers a theoretical rationale for the integration of digital technology in the realm of education, grounded in philosophical and epistemological principles. In addition, it challenges the null hypothesis that the philosophical and epistemological framework of the educational process does not influence its cognitive and personal aspects. Digital learning has been found to improve both cognitive and personal aspects of the learning process. All indicators of self-realization increased statistically significantly (p 0.05). The positive impact of digital technologies on increasing the communicative competence of students can be considered as a factor in mitigating epistemic risks in the learning process.The findings can be used to avoid epistemological risks and improve learning effectiveness in a digital learning environment. There are plans to investigate the gender dimension of digital learning epistemology in the future. (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)

In philosophy of mind, zombies are imaginary creatures that are exact physical duplicates of conscious subjects but for whom there is no first-personal experience. Zombies are meant to show that physicalism—the theory that the universe is made up entirely out of physical components—is false. In this paper, I apply the zombie thought experiment to the realm of morality to assess whether moral agency is something independent from sentience. Algorithms, I argue, are a kind of functional moral zombie, such that thinking (...) about the latter can help us better understand and regulate the former. I contend that the main reason why algorithms can be neither autonomous nor accountable is that they lack sentience. Moral zombies and algorithms are incoherent as moral agents because they lack the necessary moral understanding to be morally responsible. To understand what it means to inflict pain on someone, it is necessary to have experiential knowledge of pain. At most, for an algorithm that feels nothing, ‘values’ will be items on a list, possibly prioritised in a certain way according to a number that represents weightiness. But entities that do not feel cannot value, and beings that do not value cannot act for moral reasons. (shrink)

Due to G-7 countries' commitment to sustaining United Nations Sustainable Development Goal 8, which focuses on sustainable economic growth, there is a need to investigate the impact of tax revenue and institutional quality on economic growth, considering the role of artificial intelligence (AI) in the G-7 countries from 2012 to 2022. Cross-Sectional Augmented Autoregressive Distributed Lag (CS-ARDL) technique is used to analyze the data. The study's findings indicate a long-run equilibrium relationship among the variables under examination. The causality results can (...) be categorized as bidirectional, unidirectional, or indicating no causality. Based on the CS-ARDL results, the study recommends that G-7 governments and policymakers prioritize and strengthen the integration of AI into their institutions to stimulate growth in both the short- and long-term. However, the study cautions against overlooking the interaction between AI and tax revenue, as it did not demonstrate support for economic growth. While the interaction between AI and institutional quality shows potential for contributing to growth, it is crucial to implement robust measures to mitigate any potential negative effects that may arise from AI's interaction with tax systems. Therefore, the study suggests the development of AI-friendly tax policies within the G-7 countries, considering the nascent nature of the AI sector/industry. (shrink)

In this text, our question is what is the current regulatory trend in countries that are not considered central in the development of artificial intelligence, such as Brazil: a preventive approach, or an experimental approach? We will analyze the bills (PL) that are being processed in legislative houses at the state level, and at the federal level, highlighting some elements, such as: Delimitation of the object (conceptualization), fundamental principles, ethical guidelines, relationship with human work, human supervision, and guidelines for public (...) authorities. Based on these elements, we identified how the issues that drive the contemporary debate on AI have been addressed in these legislative initiatives. The results indicate that the strongest national regulation proposal mentions risks, rights, governance, economic agents; these mentions dialogue with the concerns discussed by researchers around the world, regarding the mitigation and prevention of risks, regarding the preservation of individual and collective rights, the role of the State as a regulator and supervisor, and, as was to be expected, the maintenance of economic policies that possibly tend to protect the market; proposes that the foundations of the development, implementation and use of AI have values consistent with ‘human centered AI’ (Bingley et al. 2023), but also points to the neoliberal matrix; introduces human supervision as an effective element in the AI systems cycle; the trend that we can observe in Brazil is the configuration of a regulation that harmonizes articles that favor the preventive approach, with the presence of articles that favor the experimentation approach. (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)

With the rapid advancement of AI, there exists a possibility of rogue human actor(s) taking control of a potent AI system or an AI system redefining its objective function such that it presents an existential threat to mankind or severely curtails its freedom. Therefore, some suggest an outright ban on AI development while others profess international agreement on constraining specific types of AI. These approaches are untenable because countries will continue developing AI for national defense, regardless. Some suggest having an (...) all-powerful benevolent one-AI that will act as an AI nanny. However, such an approach relies on the everlasting benevolence of one-AI, an untenable proposition. Furthermore, such an AI is itself subject to capture by a rogue actor. We present an alternative approach that uses existing mechanisms and time-tested economic concepts of competition and marginal analysis to limit centralization and integration of AI, rather than AI itself. Instead of depending on international consensus it relies on countries working in their best interests. We recommend that through regulation and subsidies countries promote independent development of competing AI technologies, especially those with decentralized architecture. The Sherman Antitrust Act can be used to limit the domain of an AI system, training module, or any of its components. This will increase the segmentation of potent AI systems and force technological incompatibility across systems. Finally, cross-border communication between AI-enabled systems should be restricted, something countries like China and the US are already inclined to do to serve their national interests. Our approach can ensure the availability of numerous sufficiently powerful AI systems largely disconnected from each other that can be called upon to identify and neutralize rogue systems when needed. This setup can provide sufficient deterrence to any rational human or AI system from attempting to exert undue control. (shrink)

Deepfakes, as hyperrealistic digital fabrications, reveal gaps and uncertainties in existing ontological frameworks. Neither simply images nor realities, deepfakes occupy an ambiguous metaphysical position between concepts such as representation/simulation, human/machine, and real/artificial. Their emergent generation via AI and experiential traction as credible synthetic media underscores limitations in prevailing paradigms reliant on purified binaries and anthropocentric assumptions. Rather than anomalies, deepfakes epitomize the imperative for new ontological cartographies and conceptual vocabularies attuned to increasingly unbounded algorithmic creation. The paper surveys debates about (...) digital objects and theories of representation to contextualize this argument. Deepfakes’ ontological novelty stems from their ambiguous origins, autonomous proliferation, and infiltration of perceivable situations with credible fictions. This destabilizes ontological foundations such as creative intentionality and indexical truth. I conclude deepfakes signal the insufficiency of existing ontology for navigating realities transformed by generative technologies. New paradigms are needed that grapple with their radical metaphysical challenges. (shrink)

The way in which agency is conceptualised has implications for understanding human–machine interactions and the governance of technology, especially artificial intelligence (AI) systems. Traditionally, agency is conceptualised as a capacity, defined by intrinsic properties, such as cognitive or volitional facilities. I argue that the capacity-based account of agency is inadequate to explain the dynamics of human–machine interactions and guide technology governance. Instead, I propose to conceptualise agency as impact. Agents as impactful entities can be identified at different levels: from the (...) low level of individual entities to the high level of complex socio-technical systems. Entities can impact their surroundings through different channels, and more influential channels of impact lead to higher degrees of agency. Technology governance must take into account different channels of impact in the contexts of use, design and regulation. (shrink)

This paper investigates the transformative influence of generative AI on the arts, connecting it with Walter Benjamin's insights regarding the aura of art in the mechanical reproduction era. It scrutinizes how generative AI not only redefines art's traditional aura but also introduces a dynamic interplay between technological liberation and dependency. The analysis extends to the democratization of artistic expression and its broader societal impacts, highlighting a shift in art creation, perception, and interpretation in the digital age. This research encapsulates the (...) evolving nature of authenticity, creativity, and human–machine collaboration, marking a significant paradigm shift in art's conception and its role in society. (shrink)

Much has been written about the need for trustworthy artificial intelligence (AI), but the underlying meaning of trust and trustworthiness can vary or be used in confusing ways. It is not always clear whether individuals are speaking of a technology’s trustworthiness, a developer’s trustworthiness, or simply of gaining the trust of users by any means. In sociotechnical circles, trustworthiness is often used as a proxy for ‘the good’, illustrating the moral heights to which technologies and developers ought to aspire, at (...) times with a multitude of diverse requirements; or at other times, no specification at all. In philosophical circles, there is doubt that the concept of trust should be applied at all to technologies rather than their human creators. Nevertheless, people continue to intuitively reason about trust in technologies in their everyday language. This qualitative study employed an empirical ethics methodology to address how developers and users define and construct requirements for trust throughout development and use, through a series of interviews. We found that different accounts of trust (rational, affective, credentialist, norms based, relational) served as the basis for individual granting of trust in technologies and operators. Ultimately, the most significant requirement for user trust and assessment of trustworthiness was the accountability of AI developers for the outputs of AI systems, hinging on the identification of accountable moral agents and perceived value alignment between the user and developer’s interests. (shrink)

National Artificial Intelligence (AI) strategies articulate imaginaries of the integration of AI into society and envision the governing of AI research, development and applications accordingly. To integrate these central aspects of national AI strategies under one coherent perspective, this paper presented an analysis of Germany’s strategy ‘AI made in Germany’ through the conceptual lens of ordoliberal political rationality. The first part of the paper analyses how the guiding vision of a human-centric AI not only adheres to ethical and legal principles (...) consistent with Germany’s liberal democratic constitutional system but also addresses the risks and promises inherent to the ordoliberal problematization of freedom. Second, it is scrutinized how the strategy cultivates the fear of not achieving technological sovereignty in the AI sector. Thereby, it frames the global AI race as a race of competing (national) approaches to governing AI and articulates an ordoliberal approach to governing AI (the ‘third way’), according to which government has to operate between the twin dangers of governing too much and not governing enough. Third, the paper analyses how this ordoliberal proportionality of governing structures Germany’s Science Technology & Innovation Policy. It is shown that the corresponding risk-based approach of regulating AI constitutes a security apparatus as it produces an assessment of fears: weighting the fear of the failure to innovate with the fear of the ramifications of innovation. Finally, two lines of critical engagement based on this analysis are conducted. (shrink)

Monitoring and assistive technologies (MATs) are being used more frequently in healthcare. A central ethical concern is the compatibility of these systems with the moral preferences of their users—an issue especially relevant to participatory approaches within the ethics-by-design debate. However, users’ incapacity to communicate preferences or to participate in design processes, e.g., due to dementia, presents a hurdle for participatory ethics-by-design approaches. In this paper, we explore the question of how the value preferences of users in the field of dementia (...) care can be integrated into AI-based MATs. First, we briefly introduce different ethics-by-design approaches and explain the challenges they face in dementia care. Next, we introduce a novel approach for addressing these challenges. Through a qualitative content analysis of interviews with persons with dementia and their family caregivers (n = 27), we identified multiple ideal–typical value preference profiles. We then applied these profiles in a computer simulation, by which we also introduce the concept of ethical compliance quantification to scale the moral preferences of the interviewees for the simulation. Finally, we discuss study results, the advantages of using computer simulations, and general study limitations before drawing conclusions for further research. The study contributes to the ongoing debate on participatory ethics-by-design by defining on the basis of empirical data ideal–typical value preference frameworks that can be used to guide MAT actions and their outcomes. Going forward, MAT end-users with dementia and other communication-impaired persons could be enabled to choose a value profile that best fits their moral preferences. (shrink)

Biases and misunderstanding stemming from pre-training in Generative Pre-Trained Transformers are more likely for users of underrepresented English varieties, since the training dataset favors dominant Englishes (e.g., American English). We investigate (potential) bias in GPT-4 when it interacts with Trinidadian English Creole (TEC), a non-hegemonic English variety that partially overlaps with standardized English (SE) but still contains distinctive characteristics. (1) Comparable responses: we asked GPT-4 18 questions in TEC and SE and compared the content and detail of the responses. (2) (...) Accurate translation: we assessed how accurate and authentic 29 TEC and 34 SE translations were. (3) Language knowledge and attitudes: we asked what language the prompts were written in and categorized the responses and examined any language attitudes that were exhibited. Content and detail in prompts were comparable. The model was proficient at translating TEC pronouns and many grammatical categories. It was weaker at processing spelling and vocabulary items. In addition, it produced several inauthentic features. Only 39% of TEC-generated sentences were fully grammatical. While GPT-4 was perfect at identifying SE, it was 21% accurate at identifying TEC, which it sometimes classified as English with “errors” and “corrected”. GPT-4’s scope of use is limited for non-hegemonic English users. It is problematic that some of its analyses perpetuate bias against underrepresented Englishes. Increased research on lesser-documented Englishes is necessary and we anticipate that this problem affects dialects of other languages. We intend to partner with Trinidadian stakeholders to train GPT-4 in the future. (shrink)

It is increasingly recognized that as artificial intelligence becomes more powerful and pervasive in society and creates risks and ethical issues that cross borders, a global approach is needed for the governance of these risks. But why, exactly, do we need this and what does that mean? In this Open Forum paper, author argues for global governance of AI for moral reasons but also outlines the governance challenges that this project raises.

This paper navigates the relationship between the growing influence of Artificial Intelligence (AI) and the foundational principles of academic integrity. It offers an in-depth analysis of how key academic stakeholders—publishers and universities—are crafting strategies and guidelines to integrate AI into the sphere of scholarly work. These efforts are not merely reactionary but are part of a broader initiative to harness AI’s potential while maintaining ethical standards. The exploration reveals a diverse array of stances, reflecting the varied applications of AI in (...) academic settings. These range from conservative approaches emphasizing the need for stringent AI regulations to more progressive strategies that seek to leverage AI’s capabilities. The paper accentuates the importance of guidelines that are adaptable, transparent, and culturally sensitive, acknowledging the global context of academic research. It also highlights the pressing need for effective implementation and enforcement of these guidelines to ensure that the integration of AI into academia does not compromise the integrity of scholarly work. The conclusion emphasizes the dynamic balance required between embracing AI’s transformative potential and upholding the timeless values of academic rigor and ethical research. This comprehensive analysis aims to provide a detailed perspective on the evolving role of AI in academia, fostering a dialog on how best to navigate this new technological frontier while preserving the sanctity of academic scholarship. (shrink)

A central issue in postphenomenology is how to explain the multistability of technologies: how can it be that specific technologies can be used for a wide variety of purposes (the “multi”), while not for all purposes (the “stability”)? For example, a table can be used for the purpose of sleeping, having dinner at, or even for staging a fencing match, but not for baking a cake. One explanation offered in the literature is that the (material) design of a technology puts (...) constraints on the purposes for which technologies can be used. In this paper, I argue that such an explanation—while partly correct—fails to address the role of the environment in which human beings operate in putting constraints on technology use. I suggest that James Gibson’s affordance theory helps highlighting how stabilities in technology use arise in the interaction between human being and environment. Building on more recent approaches in affordance theory, I suggest that the environment can be conceptualized as a “rich landscape of affordances” that solicits certain actions, which are not just cued by the environment’s material structure, but also by the normativity present in the form of life in which a human being participates. I briefly contrast the approach to affordances developed in this paper with how Klenk (2020) and Tollon (2021) have conceptualized the “affordance character” of technological artifacts, and highlight how a focus on the situated nature of affordances augments these earlier conceptualizations. (shrink)

Biometric technologies are becoming more pervasive in the workplace, augmenting managerial processes such as hiring, monitoring and terminating employees. Until recently, these devices consisted mainly of GPS tools that track location, software that scrutinizes browser activity and keyboard strokes, and heat/motion sensors that monitor workstation presence. Today, however, a new generation of biometric devices has emerged that can sense, read, monitor and evaluate the affective state of a worker. More popularly known by its commercial moniker, Emotional AI, the technology stems (...) from advancements in affective computing. But whereas previous generations of biometric monitoring targeted the exterior physical body of the worker, concurrent with the writings of Foucault and Hardt, we argue that emotion-recognition tools signal a far more invasive disciplinary gaze that exposes and makes vulnerable the inner regions of the worker-self. Our paper explores attitudes towards empathic surveillance by analyzing a survey of 1015 responses of future job-seekers from 48 countries with Bayesian statistics. Our findings reveal affect tools, left unregulated in the workplace, may lead to heightened stress and anxiety among disadvantaged ethnicities, gender and income class. We also discuss a stark cross-cultural discrepancy whereby East Asians, compared to Western subjects, are more likely to profess a trusting attitude toward EAI-enabled automated management. While this emerging technology is driven by neoliberal incentives to optimize the worksite and increase productivity, ultimately, empathic surveillance may create more problems in terms of algorithmic bias, opaque decisionism, and the erosion of employment relations. Thus, this paper nuances and extends emerging literature on emotion-sensing technologies in the workplace, particularly through its highly original cross-cultural study. (shrink)

Recommender Systems (RecSys) have been around since the early days of the Internet, helping users navigate the vast ocean of information and the increasingly available options that have been available for us ever since. The range of tasks for which one could use a RecSys is expanding as the technical capabilities grow, with the disruption of Machine Learning representing a tipping point in this domain, as in many others. However, the increase of the technical capabilities of AI-powered RecSys did not (...) come with a thorough consideration of their ethical implications and, despite being a well-established technical domain, the potential impacts of RecSys on their users are still under-assessed. This paper aims at filling this gap in regards to one of the main impacts of RecSys: personal autonomy. We first describe how technology can affect human values and a suitable methodology to identify these effects and mitigate potential harms: Value Sensitive Design (VSD). We use VSD to carry out a conceptual investigation of personal autonomy in the context of a generic RecSys and draw on a nuanced account of procedural autonomy to focus on two components: competence and authenticity. We provide the results of our inquiry as a value hierarchy and apply it to the design of a speculative RecSys as an example. (shrink)

All theories of world creation, whether scientific, philosophical, or religious, can readily acknowledge the fact that humans have primarily evolved to engage with nature, the individual self, fellow human beings, society, and other naturalistic aspect of existence. Nevertheless, several novel challenges ascend when the human mind engages with technology, media, machines, and related concepts such as—ChatGPT, artificial intelligence, and to name a few. For that reason, we need philosophy and critical assessment of the uncovered essence of advanced technologies, media and (...) machines and our way of life concerning them. In other words, protectively assessing their impact requires a thorough examination of ethical and existential concerns, including technology’s implications for freedom, AI’s evolving role, the essence of human being, and the unexamined transformative societal changes that follow. Building upon the premise that these phenomena share a common thread despite their apparent disparities, our interdisciplinary pursuit draws inspiration from philosophical luminaries such as Luciano Floridi, Karamjit S. Gill, David Kaplan, Aldous Huxley, Martin Heidegger, Hannah Arendt, and Gandhi. Through philosophical insights, we explore the essence of technology and its broad effects, with a focus on its impact on human freedom and essence in both public and private domains. (shrink)

Discoverability: the urgent need of an ecology of human creativity from the prolific Lorenzo Magnani is worthy of direct attention. The message may be of special interest to philosophers, ethicists and organizing scientists involved in the development of AI and related technologies which are increasingly directed at reinforcing conditions against which Magnani directly warns, namely the “overcomputationalization” of life marked by the gradual encroachment of technologically “locked strategies” into everyday decision-making until “freedom, responsibility, and ownership of our destinies” are ceded (...) and we, in parallel, build a future fit for artifacts over human beings. Professional educators - teachers and administrators serious about teaching - and policy-makers including the concerned public, parents and social activists concerned about the effects of technologies on development and well-being may benefit, as well. (shrink)

Research and activism have increasingly denounced the problematic environmental record of the infrastructure and value chain underpinning artificial intelligence (AI). Water-intensive data centres, polluting mineral extraction and e-waste dumping are incontrovertibly part of AI’s footprint. In this article, I turn to areas affected by AI-fuelled environmental harm and identify an ethics of resistance emerging from local activists, which I term ‘elemental ethics’. Elemental ethics interrogates the AI value chain’s problematic relationship with the elements that make up the world, critiques the (...) undermining of local and ancestral approaches to nature and reveals the vital and quotidian harms engendered by so-called intelligent systems. While this ethics is emerging from grassroots and Indigenous groups, it echoes recent calls from environmental philosophy to reconnect with the environment via the elements. In empirical terms, this article looks at groups in Chile resisting a Google data centre project in Santiago and lithium extraction (used for rechargeable batteries) in Lickan Antay Indigenous territory, Atacama Desert. As I show, elemental ethics can complement top-down, utilitarian and quantitative approaches to AI ethics and sustainable AI as well as interrogate whose lived experience and well-being counts in debates on AI extinction. (shrink)

To support the trustworthiness of AI systems, it is essential to have precise methods to determine what or who is to account for the behaviour, or the outcome, of AI systems. The assignment of responsibility to an AI system is closely related to the identification of individuals or elements that have caused the outcome of the AI system. In this work, we present an overview of approaches that aim at modelling responsibility of AI systems, discuss their advantages and shortcomings to (...) deal with various aspects of the notion of responsibility, and present research gaps and ways forward. (shrink)

When the social relevance of robotic applications is addressed today, the use of assistive technology in care settings is almost always the first example. So-called care robots are presented as a solution to the nursing crisis, despite doubts about their technological readiness and the lack of concrete usage scenarios in everyday nursing practice. We inquire into this interconnection of social robotics and care. We show how both are made available for each other in three arenas: innovation policy, care organization, and (...) robotic engineering. First, we analyze the discursive “logics” of care robotics within European innovation policy, second, we disclose how care robotics is encountering a historically grown conflict within health care organization, and third we show how care scenarios are being used in robotic engineering. From this diagnosis, we derive a threefold critique of robotics in healthcare, which calls attention to the politics, historicity, and social situatedness of care robotics in elderly care. (shrink)

There is general consensus that explainable artificial intelligence is valuable, but there is significant divergence when we try to articulate why, exactly, it is desirable. This question must be distinguished from two other kinds of questions asked in the XAI literature that are sometimes asked and addressed simultaneously. The first and most obvious is the ‘how’ question—some version of: ‘how do we develop technical strategies to achieve XAI?’ Another question is specifying what kind of explanation is worth having in the (...) first place. As difficult and important as the challenges are in answering these questions, they are distinct from a third question: why do we want XAI at all? There is vast literature on this question as well, but I wish to explore a different kind of answer. The most obvious way to answer this question is by describing a desirable outcome that would likely be achieved with the right kind of explanation, which would make the explanation valuable instrumentally. That is, XAI is desirable to attain some other value, such as fairness, trust, accountability, or governance. This family of arguments is obviously important, but I argue that explanations are also intrinsically valuable, because unexplainable systems can be dehumanizing. I argue that there are at least three independently valid versions of this kind of argument: an argument from participation, from knowledge, and from actualization. Each of these arguments that XAI is intrinsically valuable is independently compelling, in addition to the more obvious instrumental benefits of XAI. (shrink)

Much more than their machinic reality, current iterations of AI rely on imagined divisions of human and non-human properties and skills that have genealogical ties to colonization. For this reason, research efforts have recently been made to historicize these imaginaries, connecting them to colonial ideals that delegate black and brown colonized people into the realm of the non-human. Atanasoski and Vora (Surrogate humanity. Race, robots and the politics of technological futures, Duke, Durham and London, 2019) have called this a “surrogate (...) humanity”, where narratives of autonomous technologies function to disappear precisely the formerly colonized peoples that are enveloped in its production process. At the same time, the gendered and racialized roots of this maternal figure represents an opportunity to uncover and critique the invisibilization of embodied resources necessary to produce AI, precarious bodies labouring to produce algorithmic infrastructures in a manner that can be considered in a genealogy of carework and reproduction. These genealogies complicate the detachment suggested by the surrogate figure and go beyond it to proclaim a more generative function of the relationship between the black maternal figure and AI. The article analyses Tabita Rezaire’s multi-media artwork Sugar Walls Teardom to think through decolonial and queer renderings of the black female bodies upon which technological imaginaries rest, to extend beyond AI surrogacy and towards notions of kinship, care and world-making by producing an AI aesthetics that is relational, embodied, and celebratory of other ways of liveness. (shrink)

As non-biological machines come to be designed in ways which exhibit characteristics comparable to human mental states, the manner in which the law treats these entities will become increasingly important both to designers and to society at large. The direct question will become whether, given certain attributes, a non-biological machine could ever be viewed as a legal person. In order to begin to understand the ramifications of this question, this paper starts by exploring the distinction between the related concepts of (...) human, person, and property. Once it is understood that person in the legal sense can apply to a non-biological entity such as a corporation, the inquiry then goes on to examine the folk psychology view of intentionality and the concept of autonomy. The conclusion reached is that these two attributes can support the view that a non-biological machine, at least in theory, can be viewed as a legal person. (shrink)