Results for 'Engineering Economics, Organization, Logistics, Marketing'

988 found
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  1.  8
    Chatbots, search engines, and the sealing of knowledges.Nora Freya Lindemann - forthcoming - AI and Society:1-14.
    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 (...)
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  2.  42
    Training philosopher engineers for better AI.Brian Ball & Alexandros Koliousis - 2023 - AI and Society 38 (2):861-868.
    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 (...)
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  3.  25
    Getting into the engine room: a blueprint to investigate the shadowy steps of AI ethics.Johan Rochel & Florian Evéquoz - 2021 - AI and Society 36 (2):609-622.
    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 (...)
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  4.  35
    Engineers and the other: the role of narrative ethics.M. A. Hersh - 2016 - AI and Society 31 (3):327-345.
    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 (...)
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  5.  18
    Economic language and economy change: with implications for cyber-physical systems.Alan Cottey - 2018 - AI and Society 33 (3):323-333.
    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, (...)
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  6.  8
    Keeping the organization in the loop: a socio-technical extension of human-centered artificial intelligence.Thomas Herrmann & Sabine Pfeiffer - forthcoming - AI and Society:1-20.
    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 (...)
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  7.  24
    Justificatory explanations in machine learning: for increased transparency through documenting how key concepts drive and underpin design and engineering decisions.David Casacuberta, Ariel Guersenzvaig & Cristian Moyano-Fernández - 2024 - AI and Society 39 (1):279-293.
    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, (...)
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  8.  39
    Prompting meaning: a hermeneutic approach to optimising prompt engineering with ChatGPT.Leah Henrickson & Albert Meroño-Peñuela - forthcoming - AI and Society:1-16.
    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 (...)
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  9.  2
    AI at work: understanding its uses and consequences on work activities and organization in radiology.Tamari Gamkrelidze, Moustafa Zouinar & Flore Barcellini - forthcoming - AI and Society:1-19.
    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 (...)
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  10.  19
    Blurring the moral limits of data markets: biometrics, emotion and data dividends.Vian Bakir, Alexander Laffer & Andrew McStay - forthcoming - AI and Society:1-15.
    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 (...)
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  11.  17
    Economics of AI behavior: nudging the digital minds toward greater societal benefit.Emre Sezgin - forthcoming - AI and Society:1-2.
  12.  37
    The Future of Engineering: Philosophical Foundations, Ethical Problems and Application Cases.Albrecht Fritzsche & Sascha Julian Oks (eds.) - 2018 - Cham: Springer Verlag.
    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 (...)
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  13.  24
    Automation for the artisanal economy: enhancing the economic and environmental sustainability of crafting professions with human–machine collaboration.Ron Eglash, Lionel Robert, Audrey Bennett, Kwame Porter Robinson, Michael Lachney & William Babbitt - 2020 - AI and Society 35 (3):595-609.
    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 (...)
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  14.  6
    Blind search and flexible product visions: the sociotechnical shaping of generative music engines.Oliver Bown - forthcoming - AI and Society:1-19.
    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 (...)
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  15.  17
    “Threatened and empty selves following AI-based virtual influencers”: comparison between followers and non-followers of virtual influencers in AI-driven digital marketing.S. Venus Jin & Vijay Viswanathan - forthcoming - AI and Society:1-15.
    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 (...)
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  16.  14
    Identifying arbitrage opportunities in retail markets with artificial intelligence.Jitsama Tanlamai, Warut Khern-Am-Nuai & Yossiri Adulyasak - forthcoming - AI and Society:1-16.
    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 (...)
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  17.  22
    Artificial intelligence in marketing: friend or foe of sustainable consumption?Erik Hermann - 2023 - AI and Society 38 (5):1975-1976.
  18.  28
    Ethical problems in the use of algorithms in data management and in a free market economy.Rafał Szopa - 2023 - AI and Society 38 (6):2487-2498.
    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 (...)
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  19.  11
    Leveraging the potential of artificial intelligence (AI) in exploring the interplay among tax revenue, institutional quality, and economic growth in the G-7 countries.Charles Shaaba Saba & Nara Monkam - forthcoming - AI and Society:1-23.
    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 (...)
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  20. Moral zombies: why algorithms are not moral agents.Carissa Véliz - 2021 - AI and Society 36 (2):487-497.
    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 (...)
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  21.  11
    Willingness of sharing facial data for emotion recognition: a case study in the insurance market.Giulio Mangano, Andrea Ferrari, Carlo Rafele, Enrico Vezzetti & Federica Marcolin - forthcoming - AI and Society:1-12.
    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 (...)
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  22.  30
    Watch out! Cities as data engines.Fabio Duarte & Barbro Fröding - 2023 - AI and Society 38 (3):1249-1250.
  23.  6
    Innovation, risk and control: The true trend is ‘from tool to purpose’—A discussion on the standardization of AI.Oriana Chaves - forthcoming - AI and Society:1-12.
    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 (...)
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  24.  28
    On the hermeneutics of screen time.Jesper Aagaard, Emma Steninge & Yibin Zhang - 2023 - AI and Society 38 (6):2329-2337.
    Screen time has become a hot button issue in psychology with researchers fiercely debating its mental effects. If we want to understand the psychological dynamics of technology use, however, a numerical conceptualization of screen time will lead us to gloss over crucial distinctions. To make this point, the present article takes a hermeneutic approach to a negative form of screen time known as ‘phubbing’, which is the practice of snubbing conversational partners in favor of one’s phone. Using interview data, it (...)
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  25.  10
    Developing safer AI–concepts from economics to the rescue.Pankaj Kumar Maskara - forthcoming - AI and Society:1-13.
    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 (...)
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  26.  16
    Correction to: Are we inventing ourselves out of our own usefulness? Striking a balance between creativity and AI.Noel Carroll - forthcoming - AI and Society:1-1.
  27.  11
    The ontological quandary of deepfakes.Adeniyi Fasoro - forthcoming - AI and Society:1-9.
    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 (...)
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  28.  10
    Intelligence in animals, humans and machines: a heliocentric view of intelligence?Halfdan Holm & Soumya Banerjee - forthcoming - AI and Society:1-3.
  29.  17
    An analysis of informational power transformations: from modern state to the new regime of performativity.Francesco Abbate - forthcoming - AI and Society:1-12.
    This paper examines the role and power of the state in modernity and its transformation throughout it and into the present. First, it recognizes the centrality of the role of information control for the modern state constitution, which allows sovereign power to extend to the national level. Secondly, it discusses the shift of state power from a purely informational power to an informational and bargaining power, as well as the gradual transformation of sovereignty into governmentality. Finally, it analyzes the transformations (...)
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  30.  6
    A metaphysical account of agency for technology governance.Sadjad Soltanzadeh - forthcoming - AI and Society:1-12.
    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 (...)
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  31.  9
    Using AI to detect panic buying and improve products distribution amid pandemic.Yossiri Adulyasak, Omar Benomar, Ahmed Chaouachi, Maxime C. Cohen & Warut Khern-Am-Nuai - forthcoming - AI and Society:1-30.
    The COVID-19 pandemic has triggered panic-buying behavior around the globe. As a result, many essential supplies were consistently out-of-stock at common point-of-sale locations. Even though most retailers were aware of this problem, they were caught off guard and are still lacking the technical capabilities to address this issue. The primary objective of this paper is to develop a framework that can systematically alleviate this issue by leveraging AI models and techniques. We exploit both internal and external data sources and show (...)
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  32. Social choice ethics in artificial intelligence.Seth D. Baum - 2020 - AI and Society 35 (1):165-176.
    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 (...)
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  33.  7
    Responsible research in artificial intelligence: lessons from the past.Puneet Sharma - forthcoming - AI and Society:1-2.
  34.  10
    Imagining and governing artificial intelligence: the ordoliberal way—an analysis of the national strategy ‘AI made in Germany’.Jens Hälterlein - forthcoming - AI and Society:1-12.
    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 (...)
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  35.  8
    Adaptable robots, ethics, and trust: a qualitative and philosophical exploration of the individual experience of trustworthy AI.Stephanie Sheir, Arianna Manzini, Helen Smith & Jonathan Ives - forthcoming - AI and Society:1-14.
    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 (...)
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  36.  9
    Value preference profiles and ethical compliance quantification: a new approach for ethics by design in technology-assisted dementia care.Eike Buhr, Johannes Welsch & M. Salman Shaukat - forthcoming - AI and Society:1-17.
    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 (...)
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  37.  8
    The case for global governance of AI: arguments, counter-arguments, and challenges ahead.Mark Coeckelbergh - forthcoming - AI and Society:1-4.
    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.
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  38.  7
    GPT-4-Trinis: assessing GPT-4’s communicative competence in the English-speaking majority world.Samantha Jackson, Barend Beekhuizen, Zhao Zhao & Rhonda McEwen - forthcoming - AI and Society:1-17.
    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) (...)
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  39. In AI we trust? Perceptions about automated decision-making by artificial intelligence.Theo Araujo, Natali Helberger, Sanne Kruikemeier & Claes H. de Vreese - 2020 - AI and Society 35 (3):611-623.
    Fueled by ever-growing amounts of (digital) data and advances in artificial intelligence, decision-making in contemporary societies is increasingly delegated to automated processes. Drawing from social science theories and from the emerging body of research about algorithmic appreciation and algorithmic perceptions, the current study explores the extent to which personal characteristics can be linked to perceptions of automated decision-making by AI, and the boundary conditions of these perceptions, namely the extent to which such perceptions differ across media, (public) health, and judicial (...)
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  40. The hard problem of AI rights.Adam J. Andreotta - 2021 - AI and Society 36 (1):19-32.
    In the past few years, the subject of AI rights—the thesis that AIs, robots, and other artefacts (hereafter, simply ‘AIs’) ought to be included in the sphere of moral concern—has started to receive serious attention from scholars. In this paper, I argue that the AI rights research program is beset by an epistemic problem that threatens to impede its progress—namely, a lack of a solution to the ‘Hard Problem’ of consciousness: the problem of explaining why certain brain states give rise (...)
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  41.  61
    Big tech and societal sustainability: an ethical framework.Bernard Arogyaswamy - 2020 - AI and Society 35 (4):829-840.
    Sustainability is typically viewed as consisting of three forces, economic, social, and ecological, in tension with one another. In this paper, we address the dangers posed to societal sustainability. The concern being addressed is the very survival of societies where the rights of individuals, personal and collective freedoms, an independent judiciary and media, and democracy, despite its messiness, are highly valued. We argue that, as a result of various technological innovations, a range of dysfunctional impacts are threatening social and political (...)
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  42.  25
    Introduction: ways of machine seeing.Mitra Azar, Geoff Cox & Leonardo Impett - 2021 - AI and Society 36 (4):1093-1104.
  43. Varieties of transparency: exploring agency within AI systems.Gloria Andrada, Robert William Clowes & Paul Smart - 2023 - AI and Society 38 (4):1321-1331.
    AI systems play an increasingly important role in shaping and regulating the lives of millions of human beings across the world. Calls for greater _transparency_ from such systems have been widespread. However, there is considerable ambiguity concerning what “transparency” actually means, and therefore, what greater transparency might entail. While, according to some debates, transparency requires _seeing through_ the artefact or device, widespread calls for transparency imply _seeing into_ different aspects of AI systems. These two notions are in apparent tension with (...)
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  44.  15
    Balancing AI and academic integrity: what are the positions of academic publishers and universities?Bashar Haruna Gulumbe, Shuaibu Muhammad Audu & Abubakar Muhammad Hashim - forthcoming - AI and Society:1-10.
    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 (...)
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  45.  34
    Explaining multistability: postphenomenology and affordances of technologies.Bas de Boer - 2023 - AI and Society 38 (6):2267-2277.
    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 (...)
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  46.  55
    AI-powered recommender systems and the preservation of personal autonomy.Juan Ignacio del Valle & Francisco Lara - forthcoming - AI and Society:1-13.
    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 (...)
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  47.  38
    Bosses without a heart: socio-demographic and cross-cultural determinants of attitude toward Emotional AI in the workplace.Peter Mantello, Manh-Tung Ho, Minh-Hoang Nguyen & Quan-Hoang Vuong - 2023 - AI and Society 38 (1):97-119.
    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 (...)
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  48.  41
    Responsibility of AI Systems.Mehdi Dastani & Vahid Yazdanpanah - 2023 - AI and Society 38 (2):843-852.
    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 (...)
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  49.  35
    A critique of robotics in health care.Arne Maibaum, Andreas Bischof, Jannis Hergesell & Benjamin Lipp - 2022 - AI and Society 37 (2):467-477.
    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 (...)
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  50.  14
    Involving patients in artificial intelligence research to build trustworthy systems.Soumya Banerjee & Sarah Griffiths - forthcoming - AI and Society:1-3.
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