Philosophy of Artificial Intelligence

Edited by Eric Dietrich (State University of New York at Binghamton)
Assistant editor: Michelle Thomas (University of Western Ontario)
About this topic
Summary

The philosophy of artificial intelligence is a collection of issues primarily concerned with whether or not AI is possible -- with whether or not it is possible to build an intelligent thinking machine.  Also of concern is whether humans and other animals are best thought of as machines (computational robots, say) themselves. The most important of the "whether-possible" problems lie at the intersection of theories of the semantic contents of thought and the nature of computation. A second suite of problems surrounds the nature of rationality. A third suite revolves around the seeming “transcendent” reasoning powers of the human mind. These problems derive from Kurt Gödel's famous Incompleteness Theorem.  A fourth collection of problems concerns the architecture of an intelligent machine.  Should a thinking computer use discrete or continuous modes of computing and representing, is having a body necessary, and is being conscious necessary.  This takes us to the final set of questions. Can a computer be conscious?  Can a computer have a moral sense? Would we have duties to thinking computers, to robots?  For example, is it moral for humans to even attempt to build an intelligent machine?  If we did build such a machine, would turning it off be the equivalent of murder?  If we had a race of such machines, would it be immoral to force them to work for us?

Key works Probably the most important attack on whether AI is possible is John Searle's famous Chinese Room Argument: Searle 1980.  This attack focuses on the semantic aspects (mental semantics) of thoughts, thinking, and computing.   For some replies to this argument, see the same 1980 journal issue as Searle's original paper.  For the problem of the nature of rationality, see Pylyshyn 1987.  An especially strong attack on AI from this angle is Jerry Fodor's work on the frame problem: Fodor 1987.  On the frame problem in general, see McCarthy & Hayes 1969.  For some replies to Fodor and advances on the frame problem, see Ford & Pylyshyn 1996.  For the transcendent reasoning issue, a central and important paper is Hilary Putnam's Putnam 1960.  This paper is arguably the source for the computational turn in 1960s-70s philosophy of mind.  For architecture-of-mind issues, see, for starters: M. Spivey's The Contintuity of Mind, Oxford, which argues against the notion of discrete representations. See also, Gelder & Port 1995.  For an argument for discrete representations, see, Dietrich & Markman 2003.  For an argument that the mind's boundaries do not end at the body's boundaries, see, Clark & Chalmers 1998.  For a statement of and argument for computationalism -- the thesis that the mind is a kind of computer -- see Shimon Edelman's excellent book Edelman 2008. See also Chapter 9 of Chalmers's book Chalmers 1996.
Introductions Chinese Room Argument: Searle 1980. Frame problem: Fodor 1987, Computationalism and Godelian style refutation: Putnam 1960. Architecture: M. Spivey's The Contintuity of Mind, Oxford and Shimon Edelman's Edelman 2008. Ethical issues: Anderson & Anderson 2011 and Müller 2020.  Conscious computers: Chalmers 2011.
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  1. Exposing Implicit Biases and Stereotypes in Human and Artificial Intelligence: State of the Art and Challenges with a Focus on Gender.Ludovica Marinucci, Claudia Mazzuca & Aldo Gangemi - forthcoming - AI and Society.
    Biases in cognition are ubiquitous. Social psychologists suggested biases and stereotypes serve a multifarious set of cognitive goals, while at the same time stressing their potential harmfulness. Recently, biases and stereotypes became the purview of heated debates in the machine learning community too. Researchers and developers are becoming increasingly aware of the fact that some biases, like gender and race biases, are entrenched in the algorithms some AI applications rely upon. Here, taking into account several existing approaches that address the (...)
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  2. Strictly Human: Limitations of Autonomous Systems.Sadjad Soltanzadeh - 2022 - Minds and Machines 32 (2):269-288.
    Can autonomous systems replace humans in the performance of their activities? How does the answer to this question inform the design of autonomous systems? The study of technical systems and their features should be preceded by the study of the activities in which they play roles. Each activity can be described by its overall goals, governing norms and the intermediate steps which are taken to achieve the goals and to follow the norms. This paper uses the activity realist approach to (...)
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  3. Conformity Assessments and Post-market Monitoring: A Guide to the Role of Auditing in the Proposed European AI Regulation.Jakob Mökander, Maria Axente, Federico Casolari & Luciano Floridi - 2022 - Minds and Machines 32 (2):241-268.
    The proposed European Artificial Intelligence Act is the first attempt to elaborate a general legal framework for AI carried out by any major global economy. As such, the AIA is likely to become a point of reference in the larger discourse on how AI systems can be regulated. In this article, we describe and discuss the two primary enforcement mechanisms proposed in the AIA: the conformity assessments that providers of high-risk AI systems are expected to conduct, and the post-market monitoring (...)
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  4. What Might Machines Mean?Mitchell Green & Jan G. Michel - 2022 - Minds and Machines 32 (2):323-338.
    This essay addresses the question whether artificial speakers can perform speech acts in the technical sense of that term common in the philosophy of language. We here argue that under certain conditions artificial speakers can perform speech acts so understood. After explaining some of the issues at stake in these questions, we elucidate a relatively uncontroversial way in which machines can communicate, namely through what we call verbal signaling. But verbal signaling is not sufficient for the performance of a speech (...)
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  5. Is Your Neural Data Part of Your Mind? Exploring the Conceptual Basis of Mental Privacy.Abel Wajnerman Paz - 2022 - Minds and Machines 32 (2):395-415.
    It has been argued that neural data are an especially sensitive kind of personal information that could be used to undermine the control we should have over access to our mental states, and therefore need a stronger legal protection than other kinds of personal data. The Morningside Group, a global consortium of interdisciplinary experts advocating for the ethical use of neurotechnology, suggests achieving this by treating legally ND as a body organ. Although the proposal is currently shaping ND-related policies, it (...)
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  6. Dretske and Informational Closure.Yves Bouchard - 2022 - Minds and Machines 32 (2):311-322.
    Christoph Jäger has argued that Dretske’s information-based account of knowledge is committed to both knowledge and information closure under known entailment. However, in a reply to Jäger, Dretske defended his view on the basis of a discrepancy between the relation of information and the relation of logical implication. This paper shares Jäger’s criticism that Dretske’s externalist notion of information implies closure, but provides an analysis based on different grounds. By means of a distinction between two perspectives, the mathematical perspective and (...)
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  7. A Unified Model of Ad Hoc Concepts in Conceptual Spaces.Davide Coraci - 2022 - Minds and Machines 32 (2):289-309.
    Ad hoc concepts are highly-context dependent representations humans construct to deal with novel or uncommon situations and to interpret linguistic stimuli in communication. In the last decades, such concepts have been investigated both in experimental cognitive psychology and within pragmatics by proponents of so-called relevance theory. These two research lines have however proceeded in parallel, proposing two unconnected strategies to account for the construction and use of ad hoc concepts. The present work explores the relations between these two approaches and (...)
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  8. A Hybrid Theory of Event Memory.David H. Ménager, Dongkyu Choi & Sarah K. Robins - 2022 - Minds and Machines 32 (2):365-394.
    Amongst philosophers, there is ongoing debate about what successful event remembering requires. Causal theorists argue that it requires a causal connection to the past event. Simulation theorists argue, in contrast, that successful remembering requires only production by a reliable memory system. Both views must contend with the fact that people can remember past events they have experienced with varying degrees of accuracy. The debate between them thus concerns not only the account of successful remembering, but how each account explains the (...)
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  9. Correction to: What Might Machines Mean?Mitchell Green & Jan G. Michel - 2022 - Minds and Machines 32 (2):339-339.
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  10. Playing Games with Ais: The Limits of GPT-3 and Similar Large Language Models.Adam Sobieszek & Tadeusz Price - 2022 - Minds and Machines 32 (2):341-364.
    This article contributes to the debate around the abilities of large language models such as GPT-3, dealing with: firstly, evaluating how well GPT does in the Turing Test, secondly the limits of such models, especially their tendency to generate falsehoods, and thirdly the social consequences of the problems these models have with truth-telling. We start by formalising the recently proposed notion of reversible questions, which Floridi & Chiriatti propose allow one to ‘identify the nature of the source of their answers’, (...)
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  11. Using AI and ML to Optimize Information Discovery in Under-Utilized, Holocaust-Related Records.Kirsten Strigel Carter, Abby Gondek, William Underwood, Teddy Randby & Richard Marciano - forthcoming - AI and Society.
    Digital cultural assets are often thought to exist in separate spheres based on their two principal points of origin: digitized and born digital. Increasingly, advances in digital curation are blurring this dichotomy, by introducing so-called “collections as data,” which regardless of their origination make cultural assets more amenable to the application of new computational tools and methodologies. This paper brings together archivists, scholars, and technologists to demonstrate computational treatments of digital cultural assets using Artificial Intelligence and Machine Learning techniques that (...)
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  12. Every Word You Say: Algorithmic Mediation and Implications of Data-Driven Scholarly Communication.Luciana Monteiro-Krebs, Bieke Zaman, David Geerts & Sônia Elisa Caregnato - forthcoming - AI and Society.
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  13. Beyond Bias and Discrimination: Redefining the AI Ethics Principle of Fairness in Healthcare Machine-Learning Algorithms.Benedetta Giovanola & Simona Tiribelli - forthcoming - AI and Society.
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  14. Trust and Ethics in AI.Hyesun Choung, Prabu David & Arun Ross - forthcoming - AI and Society.
  15. A Call for Epistemic Analysis of Cultural Theories for AI Methods.Masoumeh Mansouri - forthcoming - AI and Society.
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  16. Watch Out! Cities as Data Engines.Fabio Duarte & Barbro Fröding - forthcoming - AI and Society.
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  17. Empathetic AI for Ethics-in-the-Small.Vivek Nallur & Graham Finlay - forthcoming - AI and Society.
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  18. COVID-19, Artificial Intelligence, Ethical Challenges and Policy Implications.Muhammad Anshari, Mahani Hamdan, Norainie Ahmad, Emil Ali & Hamizah Haidi - forthcoming - AI and Society.
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  19. Indexing, Enriching, and Understanding Brazilian Missing Person Cases From Data of Distributed Repositories on the Web.Jorão Gomes, Heder Soares Bernardino, Jairo Francisco de Souza & Enayat Rajabi - forthcoming - AI and Society.
    For decision making in government, it is necessary to have well-structured sources of information. In several countries, it is difficult to access government data as the information are dispersed, disconnected, and poorly structured. For this reason, this work presents a framework to gather, unify, and enrich missing person data from distributed web sources. The framework allows inserting new tasks specific to the user’s domain to improve data quality. In this study, Brazilian missing person data from non-governmental organizations and governmental websites (...)
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  20. Intelligent Service Robots for Elderly or Disabled People and Human Dignity: Legal Point of View.Katarzyna Pfeifer-Chomiczewska - forthcoming - AI and Society.
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  21. The Ethics of Algorithms From the Perspective of the Cultural History of Consciousness: First Look.Carlos Andres Salazar Martinez & Olga Lucia Quintero Montoya - forthcoming - AI and Society.
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  22. Applying Ethics to AI in the Workplace: The Design of a Scorecard for Australian Workplace Health and Safety.Andreas Cebulla, Zygmunt Szpak, Catherine Howell, Genevieve Knight & Sazzad Hussain - forthcoming - AI and Society.
    Artificial Intelligence is taking centre stage in economic growth and business operations alike. Public discourse about the practical and ethical implications of AI has mainly focussed on the societal level. There is an emerging knowledge base on AI risks to human rights around data security and privacy concerns. A separate strand of work has highlighted the stresses of working in the gig economy. This prevailing focus on human rights and gig impacts has been at the expense of a closer look (...)
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  23. How Virtue Signalling Makes Us Better: Moral Preferences with Respect to Autonomous Vehicle Type Choices.Robin Kopecky, Michaela Jirout Košová, Daniel D. Novotný, Jaroslav Flegr & David Černý - forthcoming - AI and Society.
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  24. “Please Understand We Cannot Provide Further Information”: Evaluating Content and Transparency of GDPR-Mandated AI Disclosures.Alexander J. Wulf & Ognyan Seizov - forthcoming - AI and Society.
    The General Data Protection Regulation of the EU confirms the protection of personal data as a fundamental human right and affords data subjects more control over the way their personal information is processed, shared, and analyzed. However, where data are processed by artificial intelligence algorithms, asserting control and providing adequate explanations is a challenge. Due to massive increases in computing power and big data processing, modern AI algorithms are too complex and opaque to be understood by most data subjects. Articles (...)
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  25. Explainable Artificial Intelligence in Data Science.Joaquín Borrego-Díaz & Juan Galán-Páez - forthcoming - Minds and Machines:1-47.
    A widespread need to explain the behavior and outcomes of AI-based systems has emerged, due to their ubiquitous presence. Thus, providing renewed momentum to the relatively new research area of eXplainable AI. Nowadays, the importance of XAI lies in the fact that the increasing control transference to this kind of system for decision making -or, at least, its use for assisting executive stakeholders- already affects many sensitive realms. The decision-making power handover to opaque AI systems makes mandatory explaining those, primarily (...)
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  26. Discussion of Ethical Decision Mode for Artificial Intelligence.Guoman Liu, Yufeng Luo & Jing Sheng - forthcoming - AI and Society.
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  27. Time to Re-Humanize Algorithmic Systems.Minna Ruckenstein - forthcoming - AI and Society.
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  28. Artificial Intelligence/Consciousness: Being and Becoming John Malkovich.Amar Singh & Shipra Tholia - forthcoming - AI and Society.
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  29. Investing in AI for Social Good: An Analysis of European National Strategies.Francesca Foffano, Teresa Scantamburlo & Atia Cortés - forthcoming - AI and Society.
    Artificial Intelligence has become a driving force in modern research, industry and public administration and the European Union is embracing this technology with a view to creating societal, as well as economic, value. This effort has been shared by EU Member States which were all encouraged to develop their own national AI strategies outlining policies and investment levels. This study focuses on how EU Member States are approaching the promise to develop and use AI for the good of society through (...)
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  30. Artificial Intelligence in Local Governments: Perceptions of City Managers on Prospects, Constraints and Choices.Tan Yigitcanlar, Duzgun Agdas & Kenan Degirmenci - forthcoming - AI and Society.
    Highly sophisticated capabilities of artificial intelligence have skyrocketed its popularity across many industry sectors globally. The public sector is one of these. Many cities around the world are trying to position themselves as leaders of urban innovation through the development and deployment of AI systems. Likewise, increasing numbers of local government agencies are attempting to utilise AI technologies in their operations to deliver policy and generate efficiencies in highly uncertain and complex urban environments. While the popularity of AI is on (...)
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  31. From representations in predictive processing to degrees of representational features.Danaja Rutar, Wanja Wiese & Johan Kwisthout - forthcoming - Minds and Machines:1-24.
    Whilst the topic of representations is one of the key topics in philosophy of mind, it has only occasionally been noted that representations and representational features may be gradual. Apart from vague allusions, little has been said on what representational gradation amounts to and why it could be explanatorily useful. The aim of this paper is to provide a novel take on gradation of representational features within the neuroscientific framework of predictive processing. More specifically, we provide a gradual account of (...)
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  32. Algorithmic Fairness Through Group Parities? The Case of COMPAS-SAPMOC.Francesca Lagioia, Riccardo Rovatti & Giovanni Sartor - forthcoming - AI and Society.
    Machine learning classifiers are increasingly used to inform, or even make, decisions significantly affecting human lives. Fairness concerns have spawned a number of contributions aimed at both identifying and addressing unfairness in algorithmic decision-making. This paper critically discusses the adoption of group-parity criteria as fairness standards. To this end, we evaluate the use of machine learning methods relative to different steps of the decision-making process: assigning a predictive score, linking a classification to the score, and adopting decisions based on the (...)
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  33. Legal and Ethical Aspects of Deploying Artificial Intelligence in Climate-Smart Agriculture.Mahatab Uddin, Ataharul Chowdhury & Muhammad Ashad Kabir - forthcoming - AI and Society.
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  34. Reclaiming Control: Extended Mindreading and the Tracking of Digital Footprints.Uwe Peters - 2022 - Social Epistemology 36 (3):267-282.
    It is well known that on the Internet, computer algorithms track our website browsing, clicks, and search history to infer our preferences, interests, and goals. The nature of this algorithmic tracking remains unclear, however. Does it involve what many cognitive scientists and philosophers call ‘mindreading’, i.e., an epistemic capacity to attribute mental states to people to predict, explain, or influence their actions? Here I argue that it does. This is because humans are in a particular way embedded in the process (...)
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  35. Development of Keyword Trend Prediction Models for Obesity Before and After the COVID-19 Pandemic Using RNN and LSTM: Analyzing the News Big Data of South Korea.Gayeong Eom & Haewon Byeon - 2022 - Frontiers in Public Health 10:894266.
    The Korea National Health and Nutrition Examination Survey (2020) reported that the prevalence of obesity (≥19 years old) was 31.4% in 2011, but it increased to 33.8% in 2019 and 38.3% in 2020, which confirmed that it increased rapidly after the outbreak of COVID-19. Obesity increases not only the risk of infection with COVID-19 but also severity and fatality rate after being infected with COVID-19 compared to people with normal weight or underweight. Therefore, identifying the difference in potential factors for (...)
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  36. Team Autonomy and Digital Transformation.Johan E. Ravn, Nils Brede Moe, Viktoria Stray & Eva Amdahl Seim - 2022 - AI and Society 37 (2):701-710.
    The organizational theory literature is reasonably unanimous that team autonomy is a key factor for employee well-being and motivation as well as organizational performance. However, team autonomy is challenged when its processes and outputs need to be aligned with actors and factors external to a team. There are likely challenges and conflicts between team autonomy and the need for coherence in the wider system. Team autonomy has a range of implications and is challenged by a number of factors, such as (...)
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  37. An Architecture Governance Approach for Agile Development by Tailoring the Spotify Model.Abdallah Salameh & Julian M. Bass - 2022 - AI and Society 37 (2):761-780.
    The role of software architecture in large-scale Agile development is important because several teams need to work together to release a single software product while helping to maximise teams’ autonomy. Governing and aligning Agile architecture across autonomous squads, when using the Spotify model, is a challenge because the Spotify model lacks practices for addressing Agile architecture governance. To explore how software architecture can be governed and aligned by scaling the Spotify model, we conducted a longitudinal embedded case study in a (...)
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  38. Moving Beyond the Mirror: Relational and Performative Meaning Making in Human–Robot Communication.Petra Gemeinboeck & Rob Saunders - 2022 - AI and Society 37 (2):549-563.
    Current research in human–robot interaction often focuses on rendering communication between humans and robots more ‘natural’ by designing machines that appear and behave humanlike. Communication, in this human-centric approach, is often understood as a process of successfully transmitting information in the form of predefined messages and gestures. This article introduces an alternative arts-led, movement-centric approach, which embraces the differences of machinelike robotic artefacts and, instead, investigates how meaning is dynamically enacted in the encounter of humans and machines. Our design approach (...)
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  39. Introduction: Special Issue—Critical Robotics Research.Sofia Serholt, Sara Ljungblad & Niamh Ní Bhroin - 2022 - AI and Society 37 (2):417-423.
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  40. Can Communication with Social Robots Influence How Children Develop Empathy? Best-Evidence Synthesis.Ekaterina Pashevich - 2022 - AI and Society 37 (2):579-589.
    Social robots are gradually entering children’s lives in a period when children learn about social relationships and exercise prosocial behaviors with parents, peers, and teachers. Designed for long-term emotional engagement and to take the roles of friends, teachers, and babysitters, such robots have the potential to influence how children develop empathy. This article presents a review of the literature in the fields of human–robot interaction, psychology, neuropsychology, and roboethics, discussing the potential impact of communication with social robots on children’s social (...)
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  41. Social Robots and the Risks to Reciprocity.Aimee van Wynsberghe - 2022 - AI and Society 37 (2):479-485.
    A growing body of research can be found in which roboticists are designing for reciprocity as a key construct for successful human–robot interaction. Given the centrality of reciprocity as a component for our moral lives, this paper confronts the possibility of what things would look like if the benchmark to achieve perceived reciprocity were accomplished. Through an analysis of the value of reciprocity from the care ethics tradition the richness of reciprocity as an inherent value is revealed: on the micro-level, (...)
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  42. A Critical Analysis of the Representations of Older Adults in the Field of Human–Robot Interaction.Dafna Burema - 2022 - AI and Society 37 (2):455-465.
    This paper argues that there is a need to critically assess bias in the representations of older adults in the field of Human–Robot Interaction. This need stems from the recognition that technology development is a socially constructed process that has the potential to reinforce problematic understandings of older adults. Based on a qualitative content analysis of 96 academic publications, this paper indicates that older adults are represented as; frail by default, independent by effort; silent and technologically illiterate; burdensome; and problematic (...)
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  43. Robotification & Ethical Cleansing.Marco Nørskov - 2022 - AI and Society 37 (2):425-441.
    Robotics is currently not only a cutting-edge research area, but is potentially disruptive to all domains of our lives—for better and worse. While legislation is struggling to keep pace with the development of these new artifacts, our intellectual limitations and physical laws seem to present the only hard demarcation lines, when it comes to state-of-the-art R&D. To better understand the possible implications, the paper at hand critically investigates underlying processes and structures of robotics in the context of Heidegger’s and Nishitani’s (...)
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  44. Development and Implementation Processes of Digitalization in Engineer-to-Order Manufacturing: Enablers and Barriers.Sylvi Thun, Ottar Bakås & Tore Christian Bjørsvik Storholmen - 2022 - AI and Society 37 (2):725-743.
    This study seeks to gain knowledge about key conditions in the process of digitalization using a socio-technical systems design as a theoretical framework and a case-study approach. Semi-structured interviews with 15 relevant stakeholders are conducted to learn about barriers to and enablers of the development and implementation process in a manufacturing company. After conducting a thematic analysis, eight higher-ranked themes relevant to the digitalization process are identified. These are grouped to describe the overarching phenomena, resulting in four enablers and four (...)
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  45. Autonomous Technologies in Human Ecologies: Enlanguaged Cognition, Practices and Technology.Rasmus Gahrn-Andersen & Stephen J. Cowley - 2022 - AI and Society 37 (2):687-699.
    Advanced technologies such as drones, intelligent algorithms and androids have grave implications for human existence. With the purpose of exploring their basis for doing so, the paper proposes a framework for investigating the complex relationship between such devices and human practices and language-mediated cognition. Specifically, it centers on the importance of the typically neglected intermediate layer of culture which not only drives both technophobia and philia but also, more fundamentally, connects pre-reflective experience and socio-material practices by placing advanced technologies in (...)
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  46. Microdecisions and Autonomy in Self-Driving Cars: Virtual Probabilities.Florian Sprenger - 2022 - AI and Society 37 (2):619-634.
    To operate in an unpredictable environment, a vehicle with advanced driving assistance systems, such as a robot or a drone, not only needs to register its surroundings but also to combine data from different sensors into a world model, for which it employs filter algorithms. Such world models, as this article argues with reference to the SLAM problem in robotics, consist of nothing other than probabilities about states and events arising in the environment. The model, thus, contains a virtuality of (...)
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  47. Alienation in a digitalized world.Trond Haga - 2022 - AI and Society 37 (2):801-814.
    In this paper, the aim is to study how the work organization in one specific company for one specific trade has changed over time and with these changes, the presence and absence of alienation of employees in this trade. Blauner’s U-shaped alienation development trend has been a reference in discussions on alienation. It displays a connection between the degree of alienation and technological development. The findings from this study verify the trend and the connection in the case company. However, although (...)
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  48. Empathic responses and moral status for social robots: an argument in favor of robot patienthood based on K. E. Løgstrup.Simon N. Balle - 2022 - AI and Society 37 (2):535-548.
    Empirical research on human–robot interaction has demonstrated how humans tend to react to social robots with empathic responses and moral behavior. How should we ethically evaluate such responses to robots? Are people wrong to treat non-sentient artefacts as moral patients since this rests on anthropomorphism and ‘over-identification’ —or correct since spontaneous moral intuition and behavior toward nonhumans is indicative for moral patienthood, such that social robots become our ‘Others’?. In this research paper, I weave extant HRI studies that demonstrate empathic (...)
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  49. Attribution of Autonomy and its Role in Robotic Language Acquisition.Frank Förster & Kaspar Althoefer - 2022 - AI and Society 37 (2):605-617.
    The false attribution of autonomy and related concepts to artificial agents that lack the attributed levels of the respective characteristic is problematic in many ways. In this article, we contrast this view with a positive viewpoint that emphasizes the potential role of such false attributions in the context of robotic language acquisition. By adding emotional displays and congruent body behaviors to a child-like humanoid robot’s behavioral repertoire, we were able to bring naïve human tutors to engage in so called intent (...)
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  50. “Magic through many minor measures”: How introducing a flowline production mode in six steps enables journalist team autonomy in local news organizations.Aina Landsverk Hagen, Ingrid M. Tolstad & Arne Lindseth Bygdås - 2022 - AI and Society 37 (2):745-759.
    While facing cuts, downsizing and revenue losses, media organizations experience paradoxical demands in being organized for print or linear production with daily deadlines and simultaneously striving to be ‘digital first’ and produce and publish stories online on a continuous basis throughout the day. In this paper, we describe efforts applied when introducing the metaphor flowline in a medium-sized newspaper organization in Norway with the aim of aligning their production and publishing processes to readers’ consumption of online news. Both the production (...)
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