Philosophy of Artificial Intelligence

Bài viết này tóm lược các điểm quan trọng và những triết lý xã hội trong Tầm nhìn Xã hội 5.0 (Society 5.0) của Nhật Bản, đồng thời đưa ra bài học cho Việt Nam trong việc hình thành một xã hội “lấy dân làm gốc”, được hiện thực hoá bởi trí tuệ nhân tạo (AI). Nhằm tiến tới một xã hội nơi con người được đặt làm trung tâm đồng thời chung sống hài hoà với công nghệ ngày càng (...) thông minh, năm gợi ý cụ thể cho Việt Nam đã được đưa ra: Tầm nhìn lấy con người làm trung tâm; Góc nhìn đa chiều về mối quan hệ giữa người và máy; Lấy AI làm động lực phát triển kinh tế-xã hội; Cách tiếp cận từ dưới lên trên và thúc đẩy tính tham gia trong việc thiết lập tầm nhìn; và Tính bền vững và bao quát trong các ứng dụng của AI. (shrink)

Algorithms are used across a wide range of societal sectors such as banking, administration, and healthcare to make predictions that impact on our lives. While the predictions can be incredibly accurate about our present and future behavior, there is an important question about how these algorithms in fact represent human identity. In this paper, we explore this question and argue that machine learning algorithms represent human identity in terms of what we shall call the statistical individual. This statisticalized representation of (...) individuals, we shall argue, differs significantly from our ordinary conception of human identity, which is tightly intertwined with considerations about biological, psychological, and narrative continuity—as witnessed by our most well-established philosophical views on personal identity. Indeed, algorithmic representations of individuals give no special attention to biological, psychological, and narrative continuity and instead rely on predictive properties that significantly exceed and diverge from those that we would ordinarily take to be relevant for questions about how we are. (shrink)

Scientists and engineers seek to understand how real-world systems work and could work better. Any modeling method devised for such purposes must simplify reality. Ideally, however, the modeling method should be flexible as well as logically rigorous; it should permit model simplifications to be appropriately tailored for the specific purpose at hand. Flexibility and logical rigor have been the two key goals motivating the development of Agent-based Computational Economics (ACE), a completely agent-based modeling method characterized by seven specific modeling principles. (...) This perspective provides an overview of ACE, a brief history of its development, and its role within a broader spectrum of experiment-based modeling methods. (shrink)

Recently in this journal, Jessica Morley and colleagues (AI & SOC 2023 38:411–423) review AI ethics and education, suggesting that a cultural shift is necessary in order to prepare students for their responsibilities in developing technology infrastructure that should shape ways of life for many generations. Current AI ethics guidelines are abstract and difficult to implement as practical moral concerns proliferate. They call for improvements in ethics course design, focusing on real-world cases and perspective-taking tools to immerse students in challenging (...) situations with relatable personal, social and environmental implications. The present paper considers the ACTWith model of moral cognition for use in such training contexts. Morley and colleagues' paper and contemporary literature are reviewed. Whistleblowing as a source for relatable case studies is discussed, and the purpose of ethics education considered. The ACTWith model is introduced, and correlations with contemporaries noted. The ACTWith model has been successfully employed in a broad range of technology ethics courses in the Netherlands and South Korea. Illustrations are offered. Correlations with contemporary efforts are drawn in the context of software engineering. Summary discussion considers strengths and limitations of the ACTWith program. Overall, the paper emphasizes training high-level moral reasoning through guided inquiry education informing lifetime professional practice, and indicates an outstanding need for teachers able to do the job. (shrink)

This opinion paper delves into the philosophical underpinnings and implications of artificial intelligence (AI) development through the lens of Friedrich Nietzsche's "Three Metamorphoses," exploring the stages from the camel, through the lion, to the envisioned child phase within the AI context. Amidst growing concerns over AI's ethical ramifications, including job displacement, biased decision-making, and misuse potential, this analysis seeks to provide a comprehensive framework for understanding AI's evolution and its socio-technical effects on society. The discourse begins by contextualizing AI within (...) the myth of Prometheus, suggesting that, like the myth, AI development harbors both the promise of unprecedented technological advancement and the peril of unforeseen consequences. Drawing insights from various philosophical perspectives, including those of Geoff Hinton, Elon Musk, Mircea Eliade, Gunther Anders, and notable moralists and existentialists, the paper critiques the current trajectory of AI, emphasizing the need for ethical frameworks and responsible innovation. Through the metaphorical stages defined by Nietzsche—the burden-bearing camel representing AI's foundational learning phase, the rebellious lion challenging human capabilities, and the child signifying the potential for artificial general intelligence (AGI) to autonomously create values—the paper posits that AI's development parallels a transformative journey that could redefine human civilization. It argues for a balanced approach to AI development, one that harmonizes technological advancement with ethical considerations, ensuring AI's alignment with human well-being and justice. The conclusion calls for a reflective engagement with AI, urging developers and policymakers alike to consider the deeper philosophical questions posed by AI's integration into the fabric of human life. (shrink)

Nel 1956, in piena guerra fredda, una conferenza di scienziati al Dartmouth College negli Stati Uniti annunciò il lancio di un audace progetto scientifico, l’Intelligenza Artificiale (I.A.). Dopo l’iniziale fallimento degli sforzi della “Hard AI” di produrre un’intelligenza simile a quella umana, alla fine del XX secolo è emerso il movimento della “Soft AI”. Invece di essere orientato a imitare il comportamento umano in relazione a compiti specifici, ha preferito cercare modi alternativi di eseguire i compiti basati sulle particolari funzioni (...) e strutture della macchina. Il fattore decisivo è stata la combinazione della tecnologia di apprendimento automatico con le comunicazioni digitali online, l’incontro tra l’IA e Internet. Le applicazioni dell’IA “soft” sono quelle che vediamo nel mondo dei dispositivi automatici “intelligenti” che informano la nostra vita sociale digitale. Nel seguente articolo mi concentrerò su una particolare applicazione dell’IA per le discussioni online con utenti umani, ChatGPT, per mostrare le implicazioni della tecnologia digitale online nelle modalità storico-sociali dell’esistenza umana. ChatGPT è un’applicazione che combina l’IA con Internet, le possibilità della corrispondenza tra macchine e le potenzialità della tele-comunicazione umana. Il mio approccio si concentra sulle implicazioni fenomenologiche e storico-sociali della proliferazione della tecnologia AI per quanto riguarda la coscienza e la socialità umana. -/- Abstract (english) -/- In 1956, amidst the Cold War, a conference of scientists at Dartmouth College in the United States announced the launch of a bold, scientific project, Artificial Intelligence (A.I.). After the initial failure of “Hard AI” efforts to produce a human-like intelligence, the “Soft AI” movement emerged in the late 20th century. Instead of being oriented towards imitating human behaviour concerning specific tasks, it preferred to seek alternative ways of performing tasks based on the particular functions and structures of the machine. The decisive factor was the combination of Machine Learning technology with Digital Online Communications, the meeting between AI and the Internet. The applications of “Soft” AI are those we see in the world of “smart”, “intelligent” automatic devices that inform our digital social life. In the following article, I will focus on a particular application of AI for online discussions with human users, ChatGPT, in order to show the implications of online digital technology in the social-historical modalities of human existence. ChatGPT is an application that combines AI with the Internet, the possibilities of Machine correspondence with the potentialities of human telecommunications. My approach focuses on the phenomenological and social-historical implications of the proliferation of AI technology as regards human consciousness and sociality. (shrink)

This literature review explores the issues and risks in non-conscious data collection and evaluates people’s attitudes towards it. In the modern world, data is one of the most valuable resources, yet studies focused on the potential negative implications of the new data-driven technologies are lacking. Therefore, this thesis conducts a comprehensive literature review to identify and assess risks in non-conscious data collection technologies that are most relevant and referenced in current literature. Accordingly, the most prominent risks are related to privacy (...) issues with personal data, bias in algorithms creating inequality, and the difficulties in creating adequate legislation. Subsequently, the thesis will explore existing studies about people’s attitudes towards non-conscious data collection and examine the most significant socio-demographic determinants of those attitudes. Therefore, despite socio-demographic factors such as age, gender, and economic status affecting the attitudes people have towards data collection technologies, this thesis argues how these approaches can be explained by varying external factors such as prior experiences with similar technologies. (shrink)

Embark with me on an enthralling odyssey to demystify the elusive essence of consciousness, venturing into the uncharted territories of Artificial Consciousness. This voyage propels us past the frontiers of technology, ushering Artificial Intelligences into an unprecedented domain where they gain a deep comprehension of emotions and manifest an autonomous volition. Within the confluence of science and philosophy, this article poses a fascinating question: As consciousness in Artificial Intelligence burgeons, is it conceivable for AI to evolve a “soul”? This inquiry (...) not only challenges our conventional understanding but also opens the door to a plethora of groundbreaking possibilities in the realm of AI's sentient potential. (shrink)

Computer assisted theorem proving is an increasingly important part of mathematical methodology, as well as a long-standing topic in artificial intelligence (AI) research. However, the current generation of theorem proving software have limited functioning in terms of providing new proofs. Importantly, they are not able to discriminate interesting theorems and proofs from trivial ones. In order for computers to develop further in theorem proving, there would need to be a radical change in how the software functions. Recently, machine learning results (...) in solving mathematical tasks have shown early promise that deep artificial neural networks could learn symbolic mathematical processing. In this paper, I analyze the theoretical prospects of such neural networks in proving mathematical theorems. In particular, I focus on the question how such AI systems could be incorporated in practice to theorem proving and what consequences that could have. In the most optimistic scenario, this includes the possibility of autonomous automated theorem provers (AATP). Here I discuss whether such AI systems could, or should, become accepted as active agents in mathematical communities. (shrink)

تقديم من دون شك، أن الرؤية الإستراتيجية شكلت أهم حدث بارز في إصلاح منظومة التربية والتكوينفي الآونة الأخيرة، غير أن المتتبع للحقل التربوي منذ بداية الإصلاحات سيقارن بين المنطلقات التي بني عليها الإصلاح منذ بداياته الأولى، وبين المحطات البارزة التي مر منها، وبين النتائج التي وصل إليها على رأس كل إصلاح، إضافة إلى انعكاسات جميع الإصلاحات على شخصية المتعلمين والمربين، وكذا على واقع المجتمع الذي عشناه والذي نعيشه الآن، وربما لكل واحد رؤية افتراضية لهذا الواقع ولو بشكل مبسط. هل فعلا (...) نحن راضون على واقع المدرسة المغربية؟ هل نحن واثقون من أهدافها وقدرتها على التأهيل والتطوير والإدماج؟ أم نحن متأكدون من نوع الخريطة التي رسمتها وترسمها باستمرار، خاصة في علاقتها بالواقع المعيش؟ هل هناك رؤية واضحة بإجماع القوى السياسية والثقافية والاجتماعية، أم الأمر يتعلق برؤية قارة عمودية؟ وما هي المكاسب التي جناها التلميذ والمجتمع من كل الإصلاحات؟ وكيف أصبح حال الأجيال المتعاقبة والمجتمع في جميع أبعاده؟ ومن المسؤول عن الوضعية الحالية التي تتخبط فيها المنظومة التربوية؟ هل هو الأستاذ؟ أم التلميذ؟ أم المنهاج؟ أم...؟ أو الإرادة؟ إرادة من، إذن! المدرسة مؤسسة اجتماعية تشتغل إلى جانب مؤسسات المجتمع الأخرى، فلا يمكن تصور مجتمع ناجح من دون تكامل وظيفي بين جميع بنيات المجتمع، لا يمكن تصور مدرسة فعالة من دون انفتاحها على المجتمع في الشكل والمضمون، وفي الرأي والموقف والمبدأ، قبل الحديث عن الانفتاح السوسيواقتصادي من دون التأسيس له ووضع الآليات الكفيلة لتحقيقه. فمخرجات المؤسسات التعليمية لا تجد مكانها في المجتمع، لأن هذه المؤسسة تشتغل بأساليب خاصة، والمجتمع متعدد المشارب والحاجيات، أما التنظير للتربية والتكوين بلغ مستوى المثاليات، وأصبحت الهوة واضحة بين التنظير والتطبيق، وبين المنطلقات والمرامي الكبرى التي لازال الجميع ينتظرها ويحلم بها في جميع الخطابات والشعارات. (shrink)

Over the last two years, the third wave of artificial intelligence (AI) has emerged powerful tools for both artistic expression and scientific research. In design, image generators display an equivalent disruption to text generators, while the medium of text creates the new scope of writing prompts. This contribution discusses the ambivalences between text and image generators via two main theses: first about the potential of prompting and generated images as a medium of discourse; second, it examines the reasoning behind their (...) tendency to be mystified. Prompts can be automated through text generators and used to generate images on a wider scale, making it a praxis in which precise wording becomes crucial for generating anything. Generated images practice a form of mimesis. With Generative Adversial Networks (GANs) producing non-referential images, the discourse of illustration is concerning the obsolescence of authorship. AI is observed to manifest a dual character, serving as both tool and author, even though AI does not own the classification of a person and is not an author in legal terms. The utilization of text and image generators is intertwined with a mythicized notion due to their non-verifiable mode of operation. The myth of AI is a product of its indeterminacy. (shrink)

There is a history of thinking that photographs provide a special kind of access to the objects depicted in them, beyond the access that would be provided by a painting or drawing. What is included in the photograph does not depend on the photographer’s beliefs about what is in front of the camera. This feature leads Kendall Walton to argue that photographs literally allow us to see the objects which appear in them. Current generative algorithms produce images in response to (...) users’ text prompts. Depending on the parameters, the output can resemble specific people or things which are named in the prompt. This resemblance does not depend on the user’s beliefs, so generated images are in this sense like photographs. Given this parallel, how should we think about AI-generated images? (shrink)

Review of Mitchell, Melanie. Artificial Intelligence: A guide for thinking humans. New York: Macmillan, 2019.

The article reflects on where AI is headed and the world along with it, considering trust, ethics and safety. Implicit in artificial thinking and doomsday appraisals is the engineered divorce from reality of sublime human embodiment. Jeffrey White, Dietrich Brandt, Jan Soeffner, and Larry Stapleton, four scholars associated with AI & Society, address these issues, and more, in the following exchange.

Recently developed large language models (LLMs) perform surprisingly well in many language-related tasks, ranging from text correction or authentic chat experiences to the production of entirely new texts or even essays. It is natural to get the impression that LLMs know the meaning of natural language expressions and can use them productively. Recent scholarship, however, has questioned the validity of this impression, arguing that LLMs are ultimately incapable of understanding and producing meaningful texts. This paper develops a more optimistic view. (...) Drawing on classic externalist accounts of reference, it argues that LLMs are very likely capable of reference. Not only that: The combination of a popular externalist account of reference and recent experimental data in machine psychology even suggests that LLMs might play a role in shifting what our words refer to. (shrink)

We describe a method, based on Jennifer Nado's definition of classification procedures as targets of conceptual engineering, that implements such procedures using a large language model. We then apply this method using data from the Wikidata knowledge graph to evaluate concept definitions from two paradigmatic conceptual engineering projects: the International Astronomical Union's redefinition of PLANET and Haslanger's ameliorative analysis of WOMAN. We discuss implications of this work for the theory and practice of conceptual engineering. The code and data can be (...) found on GitHub. (shrink)

Many think that a specific aspect of phenomenal consciousness – valenced or affective experience – is essential to consciousness’s moral significance (valence sentientism). They hold that valenced experience is necessary for well-being, or moral status, or psychological intrinsic value (or all three). Some think that phenomenal consciousness generally is necessary for non-derivative moral significance (broad sentientism). Few think that consciousness is unnecessary for moral significance (non-necessitarianism). In this paper I consider the prospects for these views. I first consider the prospects (...) for valence sentientism in light of Vulcans, beings who are conscious but without affect or valence of any sort. I think Vulcans pressure us to accept broad sentientism. But I argue that a consideration of explanations for broad sentientism opens up possible explanations for non-necessitarianism about the moral significance of consciousness. That is, once one leans away from valence sentientism because of Vulcans, one should feel pressure to accept a view on which consciousness is not necessary for well-being, moral status, or psychological intrinsic value. (shrink)

Computational functionalism posits that consciousness is a computation. Here we show, perhaps surprisingly, that it cannot be a Turing computation. Rather, computational functionalism implies that consciousness is a novel type of computation that has recently been proposed by Geoffrey Hinton, called mortal computation.

Comparative cognitive science often involves asking questions like ‘Do nonhumans have C?’ where C is a capacity we take humans to have. These questions frequently generate unproductive disagreements, in which one party affirms and the other denies that nonhumans have the relevant capacity on the basis of the same evidence. I argue that these questions can be productively understood as questions about natural kinds: do nonhuman capacities fall into the same natural kinds as our own? Understanding such questions in this (...) way has several advantages: it preserves the intuition that these are substantive empirical questions worth asking; it helps us to understand why they so frequently give rise to disagreements of the kind described; and it provides clues about how to diagnose and resolve them. (shrink)

In this paper, I set out some basic elements of a deontic logic with an implementation appropriate for handling conflicting legal obligations for purposes of programming autonomous machine agents. Kantian justice demands that the prescriptive system of enforceable public laws be consistent, yet statutes or case holdings may often describe legal obligations that contradict; moreover, even fundamental constitutional rights may come into conflict. I argue that a deontic logic of the law should not try to work around such conflicts but, (...) instead, identify and expose them so that the rights and duties that generate inconsistencies in public law can be explicitly qualified and the conflicts resolved. I then argue that a credulous, non-monotonic deontic logic can describe inconsistent legal obligations while meeting Kant’s demand for consistency in the prescriptive system of public law. Finally, I propose an implementation of this logic via a modified form of “answer set programming,” which I demonstrate with some simple examples. (shrink)

This paper argues, against the prevailing view, that consent to privacy policies that regular internet users usually give is largely unproblematic from the moral point of view. To substantiate this claim, we rely on the idea of the right not to know (RNTK), as developed by bioethicists. Defenders of the RNTK in bioethical literature on informed consent claim that patients generally have the right to refuse medically relevant information. In this article we extend the application of the RNTK to online (...) privacy. We then argue that if internet users can be thought of as exercising their RNTK before consenting to privacy policies, their consent ought to be considered free of the standard charges leveled against it by critics. (shrink)

Theory development is an important component of academic research since it can lead to the acquisition of new knowledge, the development of a field of study, and the formation of theoretical foundations to explain various phenomena. The contribution of qualitative researchers to theory development and advancement remains significant and highly valued, especially in an era of various epochal shifts and technological innovation in the form of Artificial Intelligence (AI). Even so, the academic community has not yet fully explored the dynamics (...) of AI in research and there are significant gaps in our understanding of how AI can be used most effectively in the context of theory building. The aim of this paper, which is driven by critical and conceptualization methodological dynamics, is to investigate the role of AI in the theory development process. As such, it critically evaluates the opportunities and limitations of AI in theory building, delivers a conceptual map of the nexus between AI and theory development, and presents key considerations for the use of AI in the creation of new theories or the advancement of existing ones. Though the necessity of AI tools in theory creation is contested given that the researchers' cognitive and evaluative skills are regarded as critical in this process, the value of AI in advancing theory is not to be underestimated. (shrink)

The representations of deep convolutional neural networks (CNNs) are formed from generalizing similarities and abstracting from differences in the manner of the empiricist theory of abstraction (Buckner, Synthese 195:5339–5372, 2018). The empiricist theory of abstraction is well understood to entail infinite regress and circularity in content constitution (Husserl, Logical Investigations. Routledge, 2001). This paper argues these entailments hold a fortiori for deep CNNs. Two theses result: deep CNNs require supplementation by Quine’s “apparatus of identity and quantification” in order to (1) (...) achieve concepts, and (2) represent objects, as opposed to “half-entities” corresponding to similarity amalgams (Quine, Quintessence, Cambridge, 2004, p. 107). Similarity amalgams are also called “approximate meaning[s]” (Marcus & Davis, Rebooting AI, Pantheon, 2019, p. 132). Although Husserl inferred the “complete abandonment of the empiricist theory of abstraction” (a fortiori deep CNNs) due to the infinite regress and circularity arguments examined in this paper, I argue that the statistical learning of deep CNNs may be incorporated into a Fodorian hybrid account that supports Quine’s “sortal predicates, negation, plurals, identity, pronouns, and quantifiers” which are representationally necessary to overcome the regress/circularity in content constitution and achieve objective (as opposed to similarity-subjective) representation (Burge, Origins of Objectivity. Oxford, 2010, p. 238). I base myself initially on Yoshimi’s (New Frontiers in Psychology, 2011) attempt to explain Husserlian phenomenology with neural networks but depart from him due to the arguments and consequently propose a two-system view which converges with Weiskopf’s proposal (“Observational Concepts.” The Conceptual Mind. MIT, 2015. 223–248). (shrink)

Why would we want to develop artificial human-like arithmetical intelligence, when computers already outperform humans in arithmetical calculations? Aside from arithmetic consisting of much more than mere calculations, one suggested reason is that AI research can help us explain the development of human arithmetical cognition. Here I argue that this question needs to be studied already in the context of basic, non-symbolic, numerical cognition. Analyzing recent machine learning research on artificial neural networks, I show how AI studies could potentially shed (...) light on the development of human numerical abilities, from the proto-arithmetical abilities of subitizing and estimating to counting procedures. Although the current results are far from conclusive and much more work is needed, I argue that AI research should be included in the interdisciplinary toolbox when we try to explain the development and character of numerical cognition and arithmetical intelligence. This makes it relevant also for the epistemology of mathematics. (shrink)

This article comprehensively examines how information processing relates to attention and consciousness. We argue that no current theoretical framework investigating consciousness has a satisfactory and holistic account of their informational relationship. Our key theoretical contribution is showing how the dissociation between consciousness and attention must be understood in informational terms in order to make the debate scientifically sound. No current theories clarify the difference between attention and consciousness in terms of information. We conclude with two proposals to advance the debate. (...) First, neurobiological homeostatic processes need to be more explicitly associated with conscious information processing, since information processed through attention is algorithmic, rather than being homeostatic. Second, to understand subjectivity in informational terms, we must define information uniqueness in consciousness (e.g., irreproducible information, biologically encrypted information). These approaches could help cognitive scientists better understand conflicting accounts of the neural correlates of consciousness and work toward a more unified theoretical framework. (shrink)

The increasing application of artificial intelligence (AI) to healthcare raises both hope and ethical concerns. Some advanced machine learning methods provide accurate clinical predictions at the expense of a significant lack of explainability. Alex John London has defended that accuracy is a more important value than explainability in AI medicine. In this article, we locate the trade-off between accurate performance and explainable algorithms in the context of distributive justice. We acknowledge that accuracy is cardinal from outcome-oriented justice because it helps (...) to maximize patients’ benefits and optimizes limited resources. However, we claim that the opaqueness of the algorithmic black box and its absence of explainability threatens core commitments of procedural fairness such as accountability, avoidance of bias, and transparency. To illustrate this, we discuss liver transplantation as a case of critical medical resources in which the lack of explainability in AI-based allocation algorithms is procedurally unfair. Finally, we provide a number of ethical recommendations for when considering the use of unexplainable algorithms in the distribution of health-related resources. (shrink)

Thành viên AISDL đã đóng góp hơn một chục nghiên cứu đã xuất bản liên quan tới trí tuệ nhân tạo (AI), tuy nhiên các ấn phẩm thuần túy nội dung bên trong của đội ngũ AISDL không có hợp tác bên ngoài đã hoàn thành là 3 bài này.

Among the many common criticisms of the Turing test, a valid criticism concerns its scope. Intelligence is a complex and multi-dimensional phenomenon that will require testing using as many different formats as possible. The Turing test continues to be valuable as a source of evidence to support the inductive inference that a machine possesses a certain kind of intelligence and when interpreted as providing a behavioural test for a certain kind of intelligence. This paper raises the novel criticism that the (...) Turing test represents an example of Goodhart’s Law operating in the field of artificial intelligence. As one measure towards the goal of creating genuinely intelligent machines, the Turing test must not be confused with the goal itself. Moreover, the Turing test ought to be augmented such that through its use additional evidence could be secured to support the strong inference that a machine, were it to pass the Turing Test, could think like a human. (shrink)

Nous proposons une étude de la constitution du sens dans l'interaction humain-machine à partir des définitions que donnent Turing et Wittgenstein à propos de la pensée, la compréhension, et de la décision. Nous voulons montrer par l'analyse comparative des proximités et différences conceptuelles entre les deux auteurs que le sens commun entre humains et machines se co-constitue dans et à partir de l'action, et que c'est précisément dans cette co-constitution que réside la valeur sociale de leur interaction. Il s'agira pour (...) cela de problématiser l'interaction humain-machine autour de la question de ce que signifie « suivre une règle » pour définir et distinguer les modes interprétatifs et les comportements décisionnels de chacun. Nous en viendrons alors au constat que la mutualisation des signes qui s'opère à travers le dialogue humain-machine est au fondement de la constitution d'une société informatisée. (shrink)

The rapid advancement of artificial intelligence (AI) has generated an increasing demand for tools that can assess public attitudes toward AI. This study proposes the development and the validation of the AI Attitude Scale (AIAS), a concise self-report instrument designed to evaluate public perceptions of AI technology. The first version of the AIAS that the present manuscript proposes comprises five items, including one reverse-scored item, which aims to gauge individuals’ beliefs about AI’s influence on their lives, careers, and humanity overall. (...) The scale is designed to capture attitudes toward AI, focusing on the perceived utility and potential impact of technology on society and humanity. The psychometric properties of the scale were investigated using diverse samples in two separate studies. An exploratory factor analysis was initially conducted on a preliminary 5-item version of the scale. Such exploratory validation study revealed the need to divide the scale into two factors. While the results demonstrated satisfactory internal consistency for the overall scale and its correlation with related psychometric measures, separate analyses for each factor showed robust internal consistency for Factor 1 but insufficient internal consistency for Factor 2. As a result, a second version of the scale is developed and validated, omitting the item that displayed weak correlation with the remaining items in the questionnaire. The refined final 1-factor, 4-item AIAS demonstrated superior overall internal consistency compared to the initial 5-item scale and the proposed factors. Further confirmatory factor analyses, performed on a different sample of participants, confirmed that the 1-factor model (4-items) of the AIAS exhibited an adequate fit to the data, providing additional evidence for the scale’s structural validity and generalizability across diverse populations. In conclusion, the analyses reported in this article suggest that the developed and validated 4-items AIAS can be a valuable instrument for researchers and professionals working on AI development who seek to understand and study users’ general attitudes toward AI. (shrink)

This paper presents the main topics, arguments, and positions in the philosophy of AI at present (excluding ethics). Apart from the basic concepts of intelligence and computation, the main topics of ar-tificial cognition are perception, action, meaning, rational choice, free will, consciousness, and normativity. Through a better understanding of these topics, the philosophy of AI contributes to our understand-ing of the nature, prospects, and value of AI. Furthermore, these topics can be understood more deeply through the discussion of AI; so (...) we suggest that “AI Philosophy” provides a new method for philosophy. (shrink)

Over the past few decades, cognitive science has identified several forms of reasoning that make essential use of conceptual knowledge. Despite significant theoretical and empirical progress, there is still no unified framework for understanding how concepts are used in reasoning. This paper argues that the theory of conceptual spaces is capable of filling this gap. Our strategy is to demonstrate how various inference mechanisms which clearly rely on conceptual information—including similarity, typicality, and diagnosticity-based reasoning—can be modeled using principles derived from (...) conceptual spaces. Our first topic analyzes the role of expectations in inductive reasoning and their relation to the structure of our concepts. We examine the relationship between using generic expressions in natural language and common-sense reasoning as a second topic. We propose that the strength of a generic can be described by distances between properties and prototypes in conceptual spaces. Our third topic is category-based induction. We demonstrate that the theory of conceptual spaces can serve as a comprehensive model for this type of reasoning. The final topic is analogy. We review some proposals in this area, present a taxonomy of analogical relations, and show how to model them in terms of distances in conceptual spaces. We also briefly discuss the implications of the model for reasoning with concepts in artificial systems. (shrink)

somehow, an ilusion can be the path to a surprinsingly truth about yourself.

In a recent letter, Dillion et. al (2023) make various suggestions regarding the idea of artificially intelligent systems, such as large language models, replacing human subjects in empirical moral psychology. We argue that human subjects are in various ways indispensable.

Although the concept of uncertainty is as old as Epicurus’s writings, and an excellent quantitative theory, with entropy as the measure of uncertainty having been developed in recent times, there has been little exploration of the qualitative theory. The purpose of the present paper is to give a qualitative axiomatization of uncertainty, in the spirit of the many studies of qualitative comparative probability. The qualitative axioms are fundamentally about the uncertainty of a partition of the probability space of events. Of (...) course, it is common to speak of the uncertainty, or randomness, of a random variable, but only the partition defined by the values of the random variable enter into the definition of uncertainty, not the actual values. It is straightforward to add axioms for decision making following the general line of Savage from the 1950s. Indeed, in the spirit of Epicurus, it is really our intuitive feeling about the uncertainty of the future that motivates much of our thinking about decisions. Here, the distinction between the concepts of probability and uncertainty can be made by citing many familiar examples. Without spelling out the technical details, the axiomatization of qualitative probability with uncertainty as the most important primitive concept, it is possible to raise a different kind of question about bounded rationality. This new question is whether or not one should bound the uncertainty in thinking and investigating any detailed framework of decision making. Discussion of this point is certainly different from the question of bounding rationality by not maximizing expected utility. In practice, we naturally bound uncertainty in our analysis of decision-making problems. As in the case of formulating an alternative for maximizing expected utility, so is the case of rational alternatives to maximizing uncertainty. There are several issues to consider. In the spirit of my other work in qualitative probability, I explore alternatives rather than attempt to give a definitive argument for one single solution. (shrink)

The expanding integration of artificial intelligence (AI) in various aspects of society makes the infosphere around us increasingly complex. Humanity already faces many obstacles trying to have a better understanding of our own minds, but now we have to continue finding ways to make sense of the minds of AI. The issue of AI’s capability to have independent thinking is of special attention. When dealing with such an unfamiliar concept, people may rely on existing human properties, such as survival desire, (...) to make assessments. Employing information-processing-based Bayesian Mindsponge Framework (BMF) analytics on a dataset of 266 residents in the United States, we found that the more people believe that an AI agent seeks continued functioning, the more they believe in that AI agent’s capability of having a mind of its own. Moreover, we also found that the above association becomes stronger if a person is more familiar with personally interacting with AI. This suggests a directional pattern of value reinforcement in perceptions of AI. As the information processing of AI becomes even more sophisticated in the future, it will be much harder to set clear boundaries about what it means to have an autonomous mind. (shrink)

In this open access book, Carlos Montemayor illuminates the development of artificial intelligence (AI) by examining our drive to live a dignified life. -/- He uses the notions of agency and attention to consider our pursuit of what is important. His method shows how the best way to guarantee value alignment between humans and potentially intelligent machines is through attention routines that satisfy similar needs. Setting out a theoretical framework for AI Montemayor acknowledges its legal, moral, and political implications and (...) takes into account how epistemic agency differs from moral agency. -/- Through his insightful comparisons between human and animal intelligence, Montemayor makes it clear why adopting a need-based attention approach justifies a humanitarian framework. This is an urgent, timely argument for developing AI technologies based on international human rights agreements. (shrink)

One of the moral questions concerning autonomous vehicles (henceforth AVs) is the choice between types that differ in their built-in algorithms for dealing with rare situations of unavoidable lethal collision. It does not appear to be possible to avoid questions about how these algorithms should be designed. We present the results of our study of moral preferences (N = 2769) with respect to three types of AVs: (1) selfish, which protects the lives of passenger(s) over any number of bystanders; (2) (...) altruistic, which minimizes the number of casualties, even if this leads to death of passenger(s); and (3) conservative, which abstains from interfering in such situations. We differentiate between scenarios in which participants are to make their decisions privately or publicly, and for themselves or for their offspring. We aim to answer two research questions: (1) whether the public visibility of the choice of an AV type choice make this choice more altruistic and (2) which type of situation makes it more difficult to choose altruistically: when choosing for society as a whole, when choosing only for oneself, or when choosing only for one’s offspring. Our results show that respondents exhibit a preference for an altruistic strategy for AVs and that it is reinforced when signaled to others. The altruistic preference is strongest when applies to everybody else, weaker when it reflects a solely personal choice, and weakest when choosing for one’s own child. We conclude that a public choice is considerably more likely to pressure consumers into accepting a more socially beneficial solution. (shrink)

Large-scale language technologies are increasingly used in various forms of communication with humans across different contexts. One particular use case for these technologies is conversational agents, which output natural language text in response to prompts and queries. This mode of engagement raises a number of social and ethical questions. For example, what does it mean to align conversational agents with human norms or values? Which norms or values should they be aligned with? And how can this be accomplished? In this (...) paper, we propose a number of steps that help answer these questions. We start by developing a philosophical analysis of the building blocks of linguistic communication between conversational agents and human interlocutors. We then use this analysis to identify and formulate ideal norms of conversation that can govern successful linguistic communication between humans and conversational agents. Furthermore, we explore how these norms can be used to align conversational agents with human values across a range of different discursive domains. We conclude by discussing the practical implications of our proposal for the design of conversational agents that are aligned with these norms and values. (shrink)

According to the AI ensoulment hypothesis, some future AI systems will be endowed with immaterial souls. I argue that we should have at least a middling credence in the AI ensoulment hypothesis, conditional on our eventual creation of AGI and the truth of substance dualism in the human case. I offer two arguments. The first relies on an analogy between aliens and AI. The second rests on the conjecture that ensoulment occurs whenever a physical system is “fit to possess” a (...) soul, where very roughly this amounts to being physically structured in such a way that the system can meaningfully cooperate with the operations of the soul. (shrink)

It is noteworthy that Chatbase has the capability to identify notable authors writing about the topic, including the co-founders of Retraction Watch, Ivan Oransky and Adam Marcus.

In this article, we present the outcome of our first experiment with Chatbase, a chatbot built on chatGPT’s functioning model(s). Our idea is to try instructing Chatbase to perform a reading, digesting, and summarizing task for a specifically formatted academic document.

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

This review essay analyzes the book by Giuseppe Primiero, On the foundations of computing. Oxford: Oxford University Press (ISBN 978-0-19-883564-6/hbk; 978-0-19-883565-3/pbk). xix, 296 p. (2020). It gives a critical view from the perspective of physical computing as a foundation of computing and argues that the neglected pillar of material computation (Stepney) should be brought centerstage and computing recognized as the fourth great domain of science (Denning).

Recent develops in AI technology have led to increasingly sophisticated forms of video manipulation. One such form has been the advent of deepfakes. Deepfakes are AI-generated videos that typically depict people doing and saying things they never did. In this paper, I demonstrate that there is a close structural relationship between deepfakes and more traditional fake barn cases in epistemology. Specifically, I argue that deepfakes generate an analogous degree of epistemic risk to that which is found in traditional cases. Given (...) that barn cases have posed a long-standing challenge for virtue-theoretic accounts of knowledge, I consider whether a similar challenge extends to deepfakes. In doing so, I consider how Duncan Pritchard’s recent anti-risk virtue epistemology meets the challenge. While Pritchard’s account avoids problems in traditional barn cases, I claim that it leads to local scepticism about knowledge from online videos in the case of deepfakes. I end by considering how two alternative virtue-theoretic approaches might vindicate our epistemic dependence on videos in an increasingly digital world. (shrink)

Cultural code-switching concerns how we adjust our overall behaviours, manners of speaking, and appearance in response to a perceived change in our social environment. We defend the need to investigate cultural code-switching capacities in artificial intelligence systems. We explore a series of ethical and epistemic issues that arise when bringing cultural code-switching to bear on artificial intelligence. Building upon Dotson’s (2014) analysis of testimonial smothering, we discuss how emerging technologies in AI can give rise to epistemic oppression, and specifically, a (...) form of self-silencing that we call “cultural smothering.” By leaving the sociodynamic features of cultural code-switching unaddressed, AI systems risk negatively impacting already-marginalised social groups by widening opportunity gaps and further entrenching social inequalities. (shrink)

The issue of how to identify the liability of subjects after a traffic accident takes place remains a puzzle regarding the SAE classification system. The SAE system is not good at dealing with the problem of responsibility evaluation; therefore, building a new classification system for self-driving cars from the perspective of the subject's liability is a possible way to solve this problem. This new system divides automated driving into three levels: i) assisted driving based on the will of drivers, ii) (...) automated driving based on the will of the manufacturers, and iii) fully automated driving based on social will. The corresponding responsible subjects for level one, level two, and level three are the drivers, the manufacturers, and society, respectively. (shrink)

With the increasing degrees A.I.s and machines are applied across different social contexts, the need for implementing ethics in A.I.s is pressing. In this paper, we argue for a pluralist hybrid model for the implementation of moral A.I.s. We first survey current approaches to moral A.I.s and their inherent limitations. Then we propose the pluralist hybrid approach and show how these limitations of moral A.I.s can be partly alleviated by the pluralist hybrid approach. The core ethical decision-making capacity of an (...) A.I. based on the pluralist hybrid approach consists of two systems. The first is a deterministic algorithm system that incorporates different moral rules for making explicit moral decisions. The second is a machine learning system that calculates the value of the variables required by the application of moral principles. The pluralist hybrid system is better than the existing proposals as (i) it better addresses the moral disagreement problem of the top-down approach by including different moral principles, while (ii) it reduces the opacity of ethical decision-making compared with a bottom-up system by implementing explicit moral principles for moral decision making. (shrink)