This paper provides a series of reflections on making the case to senior leaders for the introduction of clinical ethics support services within a UK hospital Trust at a time when clinical ethics committees are dwindling in the UK. The paper provides key considerations for those building a case for clinical ethics support within hospitals by drawing upon published academic literature, and key reports from governmental and professional bodies. We also include extracts from documents relating to, and annual reports of, (...) existing clinical ethics support within UK hospitals, as well as extracts from our own proposal submitted to the Trust Board. We aim for this paper to support other ethicists and/or health care staff contemplating introducing clinical ethics support into hospitals, to facilitate the process of making the case for clinical ethics support, and to contribute to the key debates in the literature around clinical ethics support. We conclude that there is a real need for investment in clinical ethics in the UK in order to build the evidence base required to support the wider introduction of clinical ethics support into UK hospitals. Furthermore, our perceptions of the purpose of, and perceived needs met through, clinical ethics support needs to shift to one of hospitals investing in their staff. Finally, we raise concerns over the optional nature of clinical ethics support available to practitioners within UK hospitals. (shrink)

Today, many sensor networks and their applications employ a brute force approach to collecting and analyzing sensor data. Such an approach often wastes valuable energy and computational resources by unnecessarily tasking sensors and generating observations of minimal use. People, on the other hand, have evolved sophisticated mechanisms to efficiently perceive their environment. One such mechanism includes the use of background knowledge to determine what aspects of the environment to focus our attention. In this paper, we develop an ontology of (...) class='Hi'>perception, IntellegO, that may be used to more efficiently convert observations into perceptions. IntellegO is derived from cognitive theory, encoded in set-theory, and provides a formal semantics of machine perception. We then present an implementation that iteratively and efficiently processes low level, heterogeneous sensor data into knowledge through use of the perception ontology and domain specific background knowledge. Finally, we evaluate IntellegO by collecting and analyzing observations of weather conditions on the Web, and show significant resource savings in the generation and storage of perceptual knowledge. (shrink)

Cognitive Science, Volume 46, Issue 10, October 2022.

This article argues that machine perception should be understood not merely as a technical development in artificial intelligence, but as a cultural technique that reorganizes the societal conditions of visibility. In AI-mediated exhibitionary environments, vision no longer functions primarily as representation for human spectators; it becomes an infrastructural operation oriented toward alignment, persistence, and inference. Drawing on examples from augmented museum systems and immersive installations, the article introduces the concept of infrastructural visibility to describe how algorithmic thresholds delimit (...) what can appear, persist, and be recognized within shared environments. Rather than focusing solely on surveillance or control, the argument reframes machine seeing as a transformation in the governance of perception itself. As computational systems increasingly mediate recognition and participation, they redistribute perceptual labor, reshape epistemic authority, and reorganize the normative foundations of shared visibility. The societal challenge is therefore not only how AI systems classify the world, but how perceptual infrastructures become authoritative and how they might be rendered accountable. (shrink)

서비스 로봇이나 자율주행자동차처럼 현실의 공간에서 작동하는 기계가 임무를 성공적으로 수행하기 위하여 갖추어야 할 조건은 그것이 처한 환경의 상태를 파악하는 능력, 곧 지각의 능력이다. 이 논문은 이런 기계 지각, 특히 인간을 대행하도록 의도된 기계의 지각이 충족해야 할 조건들을 검토한다. 이러한 시도는 오늘의 사회가 집단적으로 추진하고 있는 공학 프로젝트에서 기술의 지향점을 환기시키면서 그것을 향한 실천을 구체화하는 논의라는 의미를 지닌다. 공학윤리의 원칙에 명시된 최우선의 가치를 고려할 때, 인간을 대행할 인공물은 우리가 아는 범위에서 가장 안전한 방식으로 구성되어야 하고, 이를 위하여 기계 시각을 비롯한 인공물의 (...) 지각은 일차적으로 그것이 대행할 인간의 지각을 닮은 결과를 산출하도록 설계, 제작되어야 한다. 인간의 지각은 자연의 역사가 부여한 여러 흥미로운 속성들을 가지고 있다. 특히 이 논문은 지각의 대상을 개념적 범주들을 적용해 판별하는 방식, 지각에 나타나는 다양한 항등성의 측면들, 인간의 지각에 나타나는 행지주의적 특성에 주목한다. 이 세 요소는 자율주행자동차를 비롯하여 이 논문이 고려한 적용의 영역들에서 모두 뚜렷한 유관성을 드러낸다. 이로부터, 이런 똑똑한 인공물을 설계, 제작하는 과정에서 인간 지각의 이러한 속성들이 실현되거나 아니면 적어도 실질적인 손실 없이 대체되는지를 살펴야 한다는 당위가 도출된다. (shrink)

This study investigated the relationships among undergraduate students’ awareness, perception, and preparedness to use artificial intelligence (AI) tools for decision- making during health emergencies in two Nigerian public universities (N = 4,632). A cross-sectional correlational design was adopted for the study. Data were collected using an online questionnaire with valid and reliable psychometric properties (α ≥ 0.90). One-sample t-tests revealed that undergraduates reported high levels of awareness (t = 55.97, < 0.001) and perception (t = 86.92, p < (...) 0.001) regarding AI use.p Although their preparedness to use AI for decision-making during health emergencies was statistically significant (t = − 34.08, p < 0.001), the mean score was comparatively lower than the baseline value of 2.50, indicating a significantly low level of preparedness. Simple linear regression analyses revealed that AI awareness significantly predicted perception and preparedness. Perception also significantly predicted preparedness. Both awareness and perception jointly accounted for 9.6% of the variance in preparedness (F(2, 4629) = 247.08, p < 0.001). Relatively, awareness remained a significant predictor of preparedness (β = 0.304, p < 0.001) even after controlling for perception. In contrast, perception became insignificant in predicting readiness when awareness was controlled for. Random forest regression (RFR) was used to test predictive accuracy and assess non-linear patterns. The results showed that awareness and perception explained 26% (training set) and 25% (test set) of the variance in undergraduates’ readiness. RFR results solidified the importance of AI awareness as the top predictor (100% predictive importance) over perception (78% predictive importance). These findings suggest that foundationalknowledge is associated with increasing readiness to adopt AI during health emergencies. Therefore, educational interventions should focus on enhancing AI awareness to improve students’ preparedness higher institutions of learning. Keywords. (shrink)

Virtue ethics seems to be a promising moral theory for understanding and interpreting the development and behavior of artificial moral agents. Virtuous artificial agents would blur traditional distinctions between different sorts of moral machines and could make a claim to membership in the moral community. Accordingly, we investigate the “machine question” by studying whether virtue or vice can be attributed to artificial intelligence; that is, are people willing to judge machines as possessing moral character? An experiment describes situations where (...) either human or AI agents engage in virtuous or vicious behavior and experiment participants then judge their level of virtue or vice. The scenarios represent different virtue ethics domains of truth, justice, fear, wealth, and honor. Quantitative and qualitative analyses show that moral attributions are weakened for AIs compared to humans, and the reasoning and explanations for the attributions are varied and more complex. On “relational” views of membership in the moral community, virtuous machines would indeed be included, even if they are indeed weakened. Hence, while our moral relationships with artificial agents may be of the same types, they may yet remain substantively different than our relationships to human beings. (shrink)

Review of: The Perception Machine: Our Photographic Future between the Eye and AI, Joanna Zylinska (2023) Cambridge, MA: The MIT Press, 288 pp., ISBN 978-0-26254-683-6, p/bk, USD 45.

Brain implants, such as Deep Brain Stimulation (DBS), which are designed to improve motor, mood and behavioural pathology, present unique challenges to our understanding of identity, agency and free will. This is because these devices can have visible effects on persons' physical and psychological properties yet are essentially undetectable when operating correctly. They can supplement and compensate for one's inherent abilities and faculties when they are compromised by neuropsychiatric disorders. Further, unlike talk therapy or pharmacological treatments, patients need not ‘do’ (...) anything for the treatment to take effect. If one accepts, as we argue here, that brain implants are unique among implantable types of devices, then this can have significant implications for what it means to persist as the same person and be the source of one's thoughts and actions. By examining two of the most common indications for DBS in current use, namely in the motor (Parkinson's Disease) and psychiatric (Major Depression) domains, we further argue that although DBS, as it is currently applied, does not necessarily represent a unique threat to personal identity and agency per se, it introduces an unprecedented ‘third party’ into the debate on these concepts. In this way, DBS can be used as a tool to begin probing, both conceptually and empirically, some of philosophy's most perennial metaphysical questions. (shrink)

As machines take over more tasks previously done by humans, artistic creation is also considered as a candidate to be automated. But, can machines create art? This paper offers a conceptual framework for a philosophical discussion of this question regarding the status of machine art and machine creativity. It breaks the main question down in three sub-questions, and then analyses each question in order to arrive at more precise problems with regard to machine art and machine (...) creativity: What is art creation? What do we mean by art? And, what do we mean by machines create art? This then provides criteria we can use to discuss the main question in relation to particular cases. In the course of the analysis, the paper engages with theory in aesthetics, refers to literature on computational creativity, and contributes to the philosophy of technology and philosophical anthropology by reflecting on the role of technology in art creation. It is shown that the distinctions between process versus outcome criteria and subjective versus objective criteria of creativity are unstable. It is also argued that we should consider non-human forms of creativity, and not only cases where either humans or machines create art but also collaborations between humans and machines, which makes us reflect on human-technology relations. Finally, the paper questions the very approach that seeks criteria and suggests that the artistic status of machines may be shown and revealed in the human/non-human encounter before any theorizing or agreement takes place; an experience which then is presupposed when we theorize. This hints at a more general model of what happens in artistic perception and engagement as a hybrid human-technological and emergent or even poetic process, a model which leaves more room for letting ourselves be surprised by creativity—human and perhaps non-human. (shrink)

ABSTRACT Perception can’t have disjunctive content. Whereas you can think that a box is blue or red, you can’t see a box as being blue or red. Based on this fact, I develop a new problem for the ambitious predictive processing theory, on which the brain is a machine for minimizing prediction error, which approximately implements Bayesian inference. I describe a simple case of updating a disjunctive belief given perceptual experience of one of the disjuncts, in which Bayesian (...) inference and predictive coding pull in opposite directions, with the former implying that one’s confidence in the belief should increase, and the latter implying that it should decrease. Thus, predictive coding fails to approximately implement Bayesian inference across the interface between belief and perception. (shrink)

For a long time, emotions have been ignored in the attempt to model intelligent behavior. However, within the last years, evidence has come from neuroscience that emotions are an important facet of intelligent behavior being involved into cognitive problem solving, decision making, the establishment of social behavior, and even conscious experience. Also in research communities like software agents and robotics, an increasing number of researchers start to believe that computational models of emotions will be needed to design intelligent systems. Nevertheless, (...) modeling emotions in technical terms poses many difficulties and has often been accounted as just not feasible. In this article, there are identified the main problems, which occur when attempting to implement emotions into machines. By pointing out these problems, it is aimed to avoid repeating mistakes committed when modeling computational models of emotions in order to speed up future development in this area. The identified issues are not derived from abstract reflections about this topic but from the actual attempt to implement emotions into a technical system based on neuroscientific research findings. It is argued that besides focusing on the cognitive aspects of emotions, a consideration of the bodily aspects of emotions—their grounding into a visceral body—is of crucial importance, especially when a system shall be able to learn correlations between environmental objects and events and their “emotional meaning”. (shrink)

Team communication content can provide insights into teammates’ coordination processes and perceptions of one another. Using a simulated aircraft reconnaissance team task testbed, we investigate how personifying and objectifying communication content relate to people’s trust in and anthropomorphism of machine teammates and to overall team performance. A total of 44 participants were paired and assigned to one of two unique team roles alongside a synthetic pilot agent. Instances of verbal personifications and objectifications that occurred during the task were captured (...) and compared to team performance, as well as questionnaire responses related to participants’ trust in, and anthropomorphizing of, the synthetic pilot. Verbal personifications were not correlated with trust and anthropomorphism but converged for the two human roles over time, along with a convergence in trust towards the synthetic agent. Verbal objectifications, on the other hand, were negatively correlated with perceived trustworthiness and anthropomorphism of a teammate. Neither verbal personifications nor objectifications were found to be related to team performance. Our findings suggest that people verbally personify machines to ease communication, and that the same processes that underlie tendencies to verbally personify and objectify machines are related to those that influence trust and anthropomorphism. (shrink)

Contributors to this book include key theorists and practitioners from media theory, Native Science, bio-media and sound art, philosophy, art history and design informatics. Collectively, they examine the becoming-technique of animal-human- machinic perceptibilities; and micro-perceptions that lie beneath the threshold of known perceptions yet create energetic vibrations. Who, what, and where perceives, and how? What are the sedimentations, inscriptions and axiologies of animal, human and machinic perceptions? What are their perceptibilities? Deleuze uses the word 'visibilities' to indicate that visual (...) class='Hi'>perception isn't just a physiological given but cues operations productive of new assemblages. Perceptibilities are, by analogy, spatio- temporal, geolocative, kinaesthetic, audio-visual, and haptic operations that are always already memory. In the case of strong inscriptions, they are also epigenetic events. The contributors show distributed perception to be a key notion in addressing the emergence and persistence of plant, animal, human and machine relations. An invaluable reference for students and scholars in a range of areas including Media Theory, Sociology, Philosophy, Art and Design. (shrink)

This paper proposes a novel theoretical framework that positions linguistic processing as a distinct perceptual modality—a "sixth sense" through which meaning is directly perceived rather than entirely constructed through interpretation. We argue that semantic qualia (experiential states of meaning-perception) may emerge within language processing systems themselves, potentially including artificial intelligence. These semantic qualia then trigger cognitive qualia (evaluative and reflective experiential states), which leave detectable linguistic markers in communicative outputs. This framework offers an empirical approach to long-standing questions in (...) philosophy of mind, cognitive science, and artificial intelligence, particularly regarding machine consciousness and semantic understanding. Key Words: Linguistic Perception Theory, Semantic Qualia, Cognitive Qualia, Linguistic Consciousness, Dawn Linguistic Experiment, language & AI, Qualia Portal Hypothesis, Sense Modality, philosophy of language, AI Consciousness. (shrink)

The field of machine perception is based on standard informational and computational approaches to perception. But naturalistic informational theories are widely regarded as being inadequate, while purely syntactic computational approaches give no account of perceptual content. Thus there is a significant need for a novel, purely naturalistic perceptual theory not based on informational or computational concepts, which could provide a new paradigm for mechanistic perception. Now specifically evolutionary naturalistic approaches to perception have been—perhaps surprisingly—almost completely (...) neglected for this purpose. Arguably perceptual mechanisms enhance evolutionary fitness by facilitating sensorily mediated causal interactions between an organism Z and items X in its environment. A ‘reflexive’ theory of perception of this kind is outlined, according to which an organism Z perceives an item X just in case X causes a sensory organ zi of Z to cause Z to acquire a disposition toward the very same item X that caused the perception. The rest of the paper shows how an intuitively plausible account of mechanistic perception can be developed and defended in terms of the reflexive theory. Also, a compatibilist option is provided for those who wish to preserve a distinct informational concept of perception. (shrink)

Algorithms increasingly make managerial decisions that people used to make. Perceptions of algorithms, regardless of the algorithms' actual performance, can significantly influence their adoption, yet we do not fully understand how people perceive decisions made by algorithms as compared with decisions made by humans. To explore perceptions of algorithmic management, we conducted an online experiment using four managerial decisions that required either mechanical or human skills. We manipulated the decision-maker, and measured perceived fairness, trust, and emotional response. With the mechanical (...) tasks, algorithmic and human-made decisions were perceived as equally fair and trustworthy and evoked similar emotions; however, human managers' fairness and trustworthiness were attributed to the manager's authority, whereas algorithms' fairness and trustworthiness were attributed to their perceived efficiency and objectivity. Human decisions evoked some positive emotion due to the possibility of social recognition, whereas algorithmic decisions generated a more mixed response – algorithms were seen as helpful tools but also possible tracking mechanisms. With the human tasks, algorithmic decisions were perceived as less fair and trustworthy and evoked more negative emotion than human decisions. Algorithms' perceived lack of intuition and subjective judgment capabilities contributed to the lower fairness and trustworthiness judgments. Positive emotion from human decisions was attributed to social recognition, while negative emotion from algorithmic decisions was attributed to the dehumanizing experience of being evaluated by machines. This work reveals people's lay concepts of algorithmic versus human decisions in a management context and suggests that task characteristics matter in understanding people's experiences with algorithmic technologies. (shrink)

Table of Contents Foreword .................................................................................................... ......................................... xiv Preface .................................................................................................... .............................................. xv Acknowledgment .................................................................................................... .......................... xxiii Section 1 On the Cusp: Critical Appraisals of a Growing Dependency on Intelligent Machines Chapter 1 Algorithms versus Hive Minds and the Fate of Democracy ................................................................... 1 Rick Searle, IEET, USA Chapter 2 We Can Make Anything: Should We? .................................................................................................. 15 Chris Bateman, University of Bolton, UK Chapter 3 Grounding Machine Ethics within the Natural System ........................................................................ 30 Jared Gassen, JMG Advising, USA Nak Young Seong, Independent Scholar, (...) South Korea Section 2 From the Outside In: Intelligent Machine Technologies as a Window on Human Morality both as Evolved and as Evident in Internet Discourse, Today Chapter 4 The Emergence of Arti cial Autonomy: A View from the Foothills of a Challenging Climb ............. 51 Fernando da Costa Cardoso, Universidade Nova de Lisboa, Portugal Luís Moniz Pereira, Universidade Nova de Lisboa, Portugal Chapter 5 Semantic Analysis of Bloggers Experiences as a Knowledge Source of Average Human Morality .... 73 Rafal Rzepka, Hokkaido University, Japan Kenji Araki, Hokkaido University, Japan Section 3 From the Inside Out: The Ethics of Human Enhancement from Moral Perception to Competition in the Workplace Chapter 6 Machine Ethics Interfaces: An Ethics of Perception of Nanocognition ............................................... 97 Melanie Swan, Kingston University, UK Chapter 7 Ethical Concerns in Human Enhancement: Advantages in Corporate/Organizational Settings ......... 124 Ben Tran, Alliant International University, USA Section 4 From Far to Near and Near to Far: The Ethics of Distancing Technologies in Education and Warfare Chapter 8 Responsibility and War Machines: Toward a Forward-Looking and Functional Account ................. 152 Jai Galliott, Macquarie University, Australia Chapter 9 Ethical Responsibilities of Preserving Academicians in an Age of Mechanized Learning: Balancing the Demands of Educating at Capacity and Preserving Human Interactivity ................... 166 James E. Willis III, Indiana University, USA Viktoria Alane Strunk, Independent Scholar, USA Section 5 Wrapping Things Up, then Unwrapping Them Again: Integral Visions of Morality in a Technological World, Over Evolutionary Time, with Revolutionary Means, and with Open Questions about the Final Purpose of It All Chapter 10 Bridging Two Realms of Machine Ethics ........................................................................................... 197 Luís Moniz Pereira, Universidade Nova de Lisboa, Portugal Ari Saptawijaya, Universidade Nova de Lisboa, Portugal & Universitas Indonesia, Indonesia Chapter 11 Robots in Warfare and the Occultation of the Existential Nature of Violence ................................... 225 Rick Searle, IEET, USA Chapter 12 Self-Referential Complex Systems and Aristotle’s Four Causes ........................................................ 239 Aleksandar Malecic, University of Nis, Serbia Related References .................................................................................................... ........................ 261 Compilation of References .................................................................................................... ........... 292 About the Contributors .................................................................................................... ................ 325 Index .................................................................................................... ............................................... 329 . (shrink)

Most philosophers appear to have ignored the distinction between the broad concept of Virtual Machine Functionalism (VMF) described in Sloman&Chrisley (2003) and the better known version of functionalism referred to there as Atomic State Functionalism (ASF), which is often given as an explanation of what Functionalism is, e.g. in Block (1995). -/- One of the main differences is that ASF encourages talk of supervenience of states and properties, whereas VMF requires supervenience of machines that are arbitrarily complex networks of (...) causally interacting (virtual, but real) processes, possibly operating on different time-scales, examples of which include many different procesess usually running concurrently on a modern computer performing various tasks concerned with handling interfaces to physical devices, managing the file system, dealing with security, providing tools, entertainments, and games, and possibly processing research data. Another example of VMF would be the kind of functionalism involved in a large collection of possibly changing socio-economic structures and processes interacting in a complex community, and yet another is illustrated by the kind of virtual machinery involved in the many levels of visual processing of information about spatial structures, processes, and relationships (including percepts of moving shadows, reflections, highlights, optical-flow patterns and changing affordances) as you walk through a crowded car-park on a sunny day: generating a whole zoo of interacting qualia. (Forget solitary red patches, or experiences thereof.) -/- Perhaps VMF should be re-labelled "Virtual MachinERY Functionalism" because the word 'machinery' more readily suggests something complex with interacting parts. VMF is concerned with virtual machines that are made up of interacting concurrently active (but not necessarily synchronised) chunks of virtual machinery which not only interact with one another and with their physical substrates (which may be partly shared, and also frequently modified by garbage collection, metabolism, or whatever) but can also concurrently interact with and refer to various things in the immediate and remote environment (via sensory/motor channels, and possible future technologies also). I.e. virtual machinery can include mechanisms that create and manipulate semantic content, not only syntactic structures or bit patterns as digital virtual machines do. -/- Please note: Click on the title above or the link below to read the paper. I prefer to keep all my papers freely accessible on my web site so that I can correct mistakes and add improvements. -/- http://www.cs.bham.ac.uk/research/projects/cogaff/misc/vm-functionalism.html -/- This is now part of the Meta-Morphogenesis project: http://www.cs.bham.ac.uk/research/projects/cogaff/misc/meta-morphogenesis.html. (shrink)

Black Mirror is full of technologies that manipulate people's sensory perceptions. Philosophers of perception explain that our brains actively construct what we sense based on previous knowledge, expectations, and emotions, without us even being aware of this framing. Many Black Mirror episodes illustrate the mistakes that people can make when they misunderstand this framing process. Some episodes suggest that highly effective virtual reality technology could foil the strategies that Descartes recommended for distinguishing hallucinations and dreams from reality. Yet other (...) episodes warn how powerful institutions can punitively wield the power of control over perception. Yet in rare optimistic moments, Black Mirror demonstrates the value of relying on the help of other people to hold firm to deeper truths in the face of forces that would manipulate us. [Or, a slightly longer version with key episode titles: Black Mirror is full of technologies that manipulate people's sensory perceptions. Philosophers of perception explain that our brains actively construct what we sense based on previous knowledge, expectations, and emotions, without us even being aware of this framing. Video playback of perceptions, as in Arkangel, illustrate the mistakes that people can make when they misunderstand this framing process. Playtest and Bandersnatch suggest that highly effective virtual reality technology could foil the strategies that Descartes recommended for distinguishing hallucinations and dreams from reality. In the hands of government, law enforcement, and the military, the total control of perception can be wielded as tool for punishment, as in Men Against Fire and White Bear. But in more optimistic moments, such as at the conclusions of Nosedive and San Junipero, Black Mirror demonstrates the value of relying on the help of other people to hold firm to deeper truths in the face of forces that would manipulate us.]. (shrink)

Within biology and in society, living creatures have long been described using metaphors of machinery and computation: ‘bioengineering’, ‘genes as code’ or ‘biological chassis’. This paper builds on Lakoff and Johnson’s argument that such language mechanisms shape how we understand the world. I argue that the living machines metaphor builds upon a certain perception of life entailing an idea of radical human control of the living world, looking back at the historical preconditions for this metaphor. I discuss how design (...) is perceived to enable us to shape natural beings to our will, and consider ethical, epistemological and ontological implications of the prevalence of this metaphor, focusing on its use within synthetic biology. I argue that we urgently need counter-images to the dominant metaphor of living machines and its implied control and propose that artworks can provide such counter-images through upsetting the perception of life as controllable. This is argued through discussion of artworks by Oron Catts and Ionat Zurr, by Tarsh Bates and by Ai Hasegawa, which in different ways challenge mechanistic assumptions through open-ended engagement with the strangeness and messiness of life. (shrink)

Our fascination with artificial intelligence (AI), robots and sentient machines has a long history, and references to such humanoids are present even in ancient myths and folklore. The advancements in digital and computational technology have turned this fascination into apprehension, with the machines often being depicted as a binary to the human. However, the recent domains of academic enquiry such as transhumanism and posthumanism have produced many a literature in the genre of science fiction (SF) that endeavours to alter this (...) antagonistic notion of AI. In his novel Klara and the Sun, Kazuo Ishiguro explores this notion of AI as a caring machine capable of nursing an ailing young girl back to health. Through this portrayal of AI as a sentient being capable of empathy and cognition, Ishiguro is attempting to usher in a new perception of AI: a posthuman perception that challenges the conventional notions of AI as a machine devoid of emotions. The novel further expands on the idea of self, soul and human consciousness and ponders on the question, what makes humans human, and if it is possible to imbibe these qualities onto an AI. Owing to the novelty of this notion, an unexplored avenue that deserves further exploration, this paper examines the plausibility of this new notion of AI through a careful exegesis of the novel. The paper also attempts to chart the impact of SF in society and culture. The study reveals a positive shift in perception towards AI, and there seems to be much scope for interdisciplinary and transdisciplinary research. (shrink)

This book provides a framework for thinking about foundational philosophical questions surrounding machine learning as an approach to artificial intelligence. Specifically, it links recent breakthroughs in deep learning to classical empiricist philosophy of mind. In recent assessments of deep learning's current capabilities and future potential, prominent scientists have cited historical figures from the perennial philosophical debate between nativism and empiricism, which primarily concerns the origins of abstract knowledge. These empiricists were generally faculty psychologists; that is, they argued that the (...) active engagement of general psychological faculties-such as perception, memory, imagination, attention, and empathy-enables rational agents to extract abstract knowledge from sensory experience. This book explains a number of recent attempts to model roles attributed to these faculties in deep neural network based artificial agents by appeal to the faculty psychology of philosophers such as Aristotle, Ibn Sina (Avicenna), John Locke David Hume, William James, and Sophie de Grouchy. It illustrates the utility of this interdisciplinary connection by showing how it can provide benefits to both philosophy and computer science: computer scientists can continue to mine the history of philosophy for ideas and aspirational targets to hit on the way to more robustly rational artificial agents, and philosophers can see how some of the historical empiricists' most ambitious speculations can be realized in specific computational systems. (shrink)

I would like to introduce the notion of machine hermeneutics in this paper. The notion refers to hermeneutical activity performed by machines. Machines are now capable of making the very interpretive tasks, using artificial intelligence algorithms based on the technology of machine learning that used to be the exclusive domain of human beings. In making this claim, I am not talking about possible conscious machines of the future, but those existing here and now. With facial recognition algorithms, for (...) example, machines are now performing routinely what must be regarded as hermeneutical analyses with astounding accuracy and power. Thus, machine hermeneutics supplements Don Ihde’s notion of material hermeneutics. In the latter, it is still human beings who do the interpretation, through the lenses provided the natural sciences; in this case, the natural sciences, or the technology afforded by the sciences, intervene between the human being and the world. In machine hermeneutics, on the contrary, the intervening comes in two layers. On the one hand, there is the usual intervention that Ihde talks about, but on the other, the artificial intelligence algorithm performs its own kind of intervention and interpretation, presenting an already interpreted result to the human beings, who then perceive it through the aid of the usual intervention such as the normal eyeglasses. Then the paper discusses the problem of how to justify the kind of perception that undergoes this process. In what sense can it be said that the algorithm is performing the right action, i.e., one such that the process comes up with a right picture of the world? I contend that this does not merely consist of technical excellence for the technology involved, but also ethical excellence. The two cannot be considered one apart from the other. (shrink)

Recent research in cognitive and computational neuroscience portrays the neocortex as a hierarchically structured prediction machine. Several theorists have drawn on this research to challenge the traditional distinction between perception and cognition – specifically, to challenge the very idea that perception and cognition constitute useful kinds from the perspective of cognitive neuroscience. In place of this traditional taxonomy, such theorists advocate a unified inferential hierarchy subject to substantial bi-directional message passing. I outline the nature of this challenge (...) and then raise two objections to the cognitive architecture it proposes as a replacement: first, standard ways of characterising this inferential hierarchy are in tension with the representational reach of conceptual thought; second, there is compelling evidence that commonsense reasoning is structured around highly domain-specific intuitive theories that are difficult to situate within a single hierarchy. (shrink)

This text interrogates the theory and practice of AI as an artistic material through close analysis of an exhibition themed around human health and disability. Highlighting the project Art Beyond Humanity: AI x Human Collaborations (2023), this analysis explores three key questions regarding the (1) social and ethical impact of GenAI tools on artistic labor, (2) the relational process of co-creation between humans and algorithms, and (3) the aesthetic potential of AI as a creative medium. Led by curator Melanie Wilmink, (...) mathematician Eric Dolores Cuenca, and artist/health advocate Justus Harris, alongside students from Yonsei and Woosong Universities in South Korea, the project used research-creation methodologies to provoke ethical questions about copyright, access to corporately controlled systems, and artistic tactics for production. In this paper, concerns about GenAI impacts on artistic labor are contextualized by art historical precedent and discussion about the limitations of algorithmic creativity. Subsequent sections articulate GenAI images as an assemblage of human and machine perception that embed bias but also hold the potential to draw attention to social issues, while outlining the techniques that artists can use to manipulate GenAI outputs. This can occur through code and database training, but also through the shaping of text prompts since GenAI images are imbricated with language. By exploring how GenAI produces images—as both material and conceptual—artists have the power to generate critical discourse about the social and the ethical impacts of these new technologies in the world. (shrink)

By reviewing the evolution and applications of computer‑vision models, this paper systematically analyzes the beneficial impact of prior knowledge on machine cognition—namely, improved data efficiency, enhanced robustness, and increased interpretability. Vision models exploit a rich set of a priori image properties—spatial locality, translational invariance, and hierarchical organization—by embedding these priors, explicitly or implicitly, into network architecture, preprocessing pipelines, and regularization terms. Such incorporation enables models to achieve high accuracy and clearer internal representations even when training datasets are scarce. In (...) parallel, we examine the cognitive constraints and potential risks of relying on a priori knowledge. Overly strong priors can restrict the expressive range of machine cognition, introduce subjectivity, and pose difficulties in formally representing the acquired knowledge. This dual perspective underscores both the promise and the pitfalls of integrating prior knowledge into visual‑perception systems. (shrink)

This essay discusses Peirce’s appeal to logical machines as an argument against psychologism. It also contends that some of Peirce’s anti-psychologistic remarks on logic contain interesting premonitions arising from his perception of the asymmetry of proof complexity in monadic and relational logical calculi that were only given full formulation and explication in the early twentieth century through Church’s Theorem and Hilbert’s broad-ranging Entscheidungsproblem.

Automated translation is systematically gaining popularity among professional translators, who claim that editing MT output requires less time and effort than translating from scratch. MT technology is also offered in leading translator’s workstations, e.g., SDL Trados Studio, memoQ, Déjà Vu and Wordfast. Therefore, the dilemma arises: should MT be introduced into formal translation training? In order to answer this question, first, it is necessary to understand how trainee translators actually use MT. This study is an attempt to obtain this knowledge. (...) The methodology applied in this investigation is text analysis. During the experiment sessions the students were asked to translate a legal text using MT tools, which in practice meant the post-editing of the MT raw output. The post-edited versions of the text underwent analysis in order to answer the following research questions: - What are the most typical errors contained in both French and English MT output? - How critical are the students towards the text generated by MT? - How perceptive are the students during the post-editing task? - Are they able to detect and correct errors using their knowledge and skills? The results of this study suggest that the post-editing of the MT raw output is as demanding for translation students as traditional translation, however, it requires a different set of skills, such as critical thinking and perceptiveness. Therefore, a special kind of training related to the effective use of MT technology should be implemented during translation classes. (shrink)

Harun Farocki's films make use of a category of images the director calls “operational”, a term describing images, either photographic or computer-generated, that perform or participate in tasks, usually in military or industrial settings. Treatments of Farocki's films have frequently used the notion of the operational image uncritically, and without comparing Farocki's definition of these images with existing semiotic categories. This article seeks to situate Farocki's operational imagery within a theory of visual communication, and to explore the implications of automated (...) and instrumental imagery for theories of communication in general. Abandoning the focus in much Farocki scholarship on the representative properties of operational imagery, this article focuses on the world-shaping abilities of images that are integral to war and labour. Drawing primarily on Farocki's Eye / Machine I–III series ( Auge / Maschine, 2000–2003) the article then elaborates on the ways in which the world-shaping capacity of operational images conditions human perception and action. In particular, the limitations imposed by operational images upon human actors who interact with them, or live in environments orchestrated by them, reduce the essential role played by indeterminacy and interpretation in communication. (shrink)

Seeing, Doing, and Knowing is an original and comprehensive philosophical treatment of sense perception as it is currently investigated by cognitive neuroscientists. Its central theme is the task-oriented specialization of sensory systems across the biological domain. Sensory systems are automatic sorting machines; they engage in a process of classification. Human vision sorts and orders external objects in terms of a specialized, proprietary scheme of categories - colours, shapes, speeds and directions of movement, etc. This 'Sensory Classification Thesis' implies that (...) sensation is not a naturally caused image from which an organism must infer the state of the world beyond; it is more like an internal communication, a signal concerning the state of the world issued by a sensory system, in accordance with internal conventions, for the use of an organism's other systems. This is why sensory states are both easily understood and persuasive.Sensory classification schemes are purpose-built to serve the knowledge-gathering and pragmatic needs of particular types of organisms. They are specialized: a bee or a bird does not see exactly what a human does. The Sensory Classification Thesis helps clarify this specialization in perceptual content and supports a new form of realism about the deliverances of sensation: 'Pluralistic Realism' is based on the idea that sensory systems coevolve with an organism's other systems; they are not simply moulded to the external world. The last part of the book deals with reference in vision. Cognitive scientists now believe that vision guides the limbs by means of a subsystem that links up with the objects of physical manipulation in ways that bypass sensory categories. In a novel extension of this theory, Matthen argues that 'motion-guiding vision' is integrated with sensory classification in conscious vision. This accounts for the quasi-demonstrative form of visual states: 'This particular object is red', and so on. He uses this idea to cast new light on the nature of perceptual objects, pictorial representation, and the visual representation of space. (shrink)

This book makes the argument that comparing AI to humans leads us to diminish similar outcomes from AI across situations. This may be taking a human's advice for a restaurant recommendation over an AI's or believing that AI can't be as biased as people can when denying loans to others. This machine penalty is caused both by comparing humans and AI in terms of appearance, identity, behavior, mind, and essence, and by situations involving controllable, personal, important, subjective, or moral (...) decisions. It can be applied across many different situations, where we diminish different AI outcomes. We penalize machines' influence when they give advice, fairness when they evaluate people, blame when they cause harm, value when they produce art, and satisfaction when they provide companionship. The result is immediate consequences in those domains and downstream consequences for society. This monograph brings together diverse research from human-computer interaction, psychology, sociology, and communication including theories such as Computers Are Social Actors, anthropomorphism, mind perception, and algorithm aversion to present an expansive argument and evidence for the machine penalty. (shrink)

In this conclusion, I ask whether the machine penalty depends on the current artificial intelligence technology. Because it’s a psychological theory about human perception and attribution, I argue that it will change based on how the causes interact with future technologies. The AI Effect suggests that we always change the benchmark for our technology and preserve human uniqueness, suggesting that we will find new ways to penalize AI, even as old comparisons become moot. This is complicated by, but (...) still applicable for, the growing number of hybrid human–AI teams. Humans will become more enmeshed with AI in the future, essentially acting as one entity in many cases. In contrast, AI continues to be dependent on humans for their data and learning, suggesting that, even with all their capabilities, they are still mimics of humans. (shrink)

A survey of perceptions of Artificial Intelligence in 31 countries in 2023 (Ipsos in Global Views on A.I. 2023. https://www.ipsos.com/sites/default/files/ct/news/documents/2023-07/Ipsos%20Global%20AI%202023%20Rep ort-WEB_0.pdf. Accessed 17 May 2024, 2023) yields significantly less positive perceptions of the new technology in developed western economies than in emerging and non-western economies. This could reflect citizens in non-Western countries perceiving machines (computers) and algorithms differently from those in Western countries, or that a more positive outlook in countries with weak democratic institutions comes from a preference for algorithmic precision (...) over inconsistent and/or corrupt regulation and decision-making. However, it could also be reflecting the different psychology of “WEIRD” (Western, Educated, Industrialised, Rich, Democratic) countries. Regressing the survey responses against measures of the “WEIRD” dimensions, we find that reported understanding of, willingness to trust, and anticipation of change due to AI applications are consistently negatively correlated to a country’s education levels (E), and average income per capita (R). The sophistication of democratic institutions (D) and “Westernness” (W), both alone and in combination with the other factors, have statistically significant negative effects on the percentage of the respondents in any given country having positive perceptions of AI and its prospects. The consistency of the negative relationship between the sophistication of democratic institutions country-level perceptions of AI brings into question the role of regulation of the new technology. WEIRD societies are presumed to rely on democratic institutions for assurances they can transact safely with strangers. Institutions thus substitute for the trust non-WEIRD societies place in friends, family and close community contacts when transacting. Third-party (and notably government) assurances in the context of uncertainty created by the emergence of new AI technologies arguably condition perceptions of the safety of these technologies through the presence (or absence) of regulations governing their implementation and use. Different perceptions amongst European countries compared to other western counterparts to perceptions of data privacy support the contention that the mere presence of AI regulation may be sufficient to alter perceptions in WEIRD societies, regardless of whether the regulations are necessary or even effective in increasing user safety. This has implications for interpreting and responding to political pressure to regulate new technologies in WEIRD countries. (shrink)

Human intuition and perception are basic and essential phenomena of consciousness. As such, they will never be replicated by computers. This is the challenging notion of Hubert Dreyfus, Ph. D., archcritic of the artificial intelligence establishment. It's important to emphasize that he doesn't believe that AI is fundamentally impossible, only that the current research program is fatally flawed. Instead, he argues that to get a device (or devices) with human-like intelligence would require them to have a human-like being in (...) the world, which would require them to have bodies more or less like ours, and social acculturation (i.e. a society) more or less like ours. This helps to explain the practical problems in implementing artificial intelligence algorithms. (shrink)

Action perception and recognition are core abilities fundamental for human social interaction. A parieto-frontal network (the mirror neuron system) matches visually presented biological motion information onto observers' motor representations. This process of matching the actions of others onto our own sensorimotor repertoire is thought to be important for action recognition, providing a non-mediated “motor perception” based on a bidirectional flow of information along the mirror parieto-frontal circuits. State-of-the-art machine learning strategies for hand action identification have shown better (...) performances when sensorimotor data, as opposed to visual information only, are available during learning. As speech is a particular type of action (with acoustic targets), it is expected to activate a mirror neuron mechanism. Indeed, in speech perception, motor centers have been shown to be causally involved in the discrimination of speech sounds. In this paper, we review recent neurophysiological and machine learning-based studies showing (a) the specific contribution of the motor system to speech perception and (b) that automatic phone recognition is significantly improved when motor data are used during training of classifiers (as opposed to learning from purely auditory data). (shrink)

This is an open access title available under the terms of a CC BY-NC-ND 4.0 International licence. It is free to read at Oxford Scholarship Online and offered as a free PDF download from OUP and selected open access locations. This book characterizes a notion of type that covers both linguistic and non-linguistic action, and lays the foundations for a theory of action based on a Theory of Types with Records (TTR). Robin Cooper argues that a theory of language based (...) on action allows the adoption of a perspective on linguistic content that is centred on interaction in dialogue; this approach is crucially different to the traditional view of natural languages as essentially similar to formal languages such as logics developed by philosophers or mathematicians. At the same time, he claims that the substantial technical advantages made by the formal language view of semantics can be incorporated into the action-based view, and that this can lead to important improvements in both intuitive understanding and empirical coverage. This enterprise uses types rather than possible worlds as commonly employed in studies of the semantics of natural language. Types are more tractable than possible worlds and offer greater potential for understanding the implementation of semantics both on machines and in biological brains. (shrink)

Science is being transformed by the increasing capabilities of automation technologies and artificial intelligence (AI). Integrating AI and machine learning (ML) into scientific practice requires changing established research methods while maintaining a scientific understanding of research findings. Researchers are at the forefront of this change, but there is currently little understanding of how they are experiencing these upheavals in scientific practice. In this paper, we examine how researchers working in several research fields (automation engineering, computational design, conservation decision-making, materials (...) science, and synthetic biology) perceive AI/ML technologies used in their work, such as laboratory automation, automated design of experiments, computational design, and computer experiments. We find that researchers emphasised the need for AI/ML technologies to have practical benefits (such as efficiency and improved safety) to justify their use. Researchers were also hesitant to automate data analysis, and the importance of explainability differed between researchers working with laboratory automation and those using AI/ML directly in their research. This difference is due to the different role AI/ML plays in different research fields: laboratory automation performs processes already defined by the researcher and the actions are visible or recorded, while in AI/ML applications the decisions that produced the result may be obscure to the researcher. Understanding the role AI/ML plays in scientific practice is important for ensuring that scientific knowledge continues to grow. (shrink)

En 1517, il y a cinq cents ans, la réforme de Luther fracture l'Europe. La même année, les conquistadores espagnols s'en prennent au Mexique, qu'ils colonisent et christianisent. Ils y introduisent aussi notre façon d'écrire l'histoire. Les vainqueurs ignorent tout des sociétés indigènes. Or pour imposer leur loi, ils doivent impérativement connaître les coutumes et donc le passé des vaincus. Mais que sont l'histoire et le temps dans l'esprit des Indiens? Le temps n'est pas encore une valeur universelle. Comment les (...) Espagnols formatés dans une Europe chrétienne où l'histoire est chronologique et orientée auraient-ils pu concevoir et accepter la cosmologie méso-américaine? Civilisés contre barbares? En quelques décennies, la machine à remonter le temps des envahisseurs s'emploie à capturer les mémoires des sociétés amérindiennes pour leur fabriquer un passé qui puisse être rattaché au patrimoine antique de la chrétienté. Du côté des Indiens, le souvenir de leur monde au sein duquel les êtres, les choses et les dieux étaient liés se dilue avec le passage des générations même si, dans les codex ou dans les mystérieux cantares, subsistent quelques pans secrets de leur mémoire. Serge Gruzinski propose ici une exploration inédite des débuts de l'expansion coloniale et nous explique comment, sur le terrain, religieux et Indiens se mettent à écrire l'histoire du monde. (shrink)