In this paper, I reconstruct Robert Nozick's experience machine objection to hedonism about well-being. I then explain and briefly discuss the most important recent criticisms that have been made of it. Finally, I question the conventional wisdom that the experience machine, while it neatly disposes of hedonism, poses no problem for desire-based theories of well-being.

It is argued that Nozick's experience machine thought experiment does not pose a particular difficulty for mental state theories of well-being. While the example shows that we value many things beyond our mental states, this simply reflects the fact that we value more than our own well-being. Nor is a mental state theorist forced to make the dubious claim that we maintain these other values simply as a means to desirable mental states. Valuing more than our mental states (...) is compatible with maintaining that the impact of such values upon our well-being lies in their impact upon our mental lives. (shrink)

In this article I explore various facets of Nozick’s famous thought experiment involving the experience machine. Nozick’s original target is hedonism—the view that the only intrinsic prudential value is pleasure. But the argument, if successful, undermines any experientialist theory, i.e. any theory that limits intrinsic prudential value to mental states. I first highlight problems arising from the way Nozick sets up the thought experiment. He asks us to imagine choosing whether or not to enter the machine and (...) uses our choice (or rather the choice he assumes most people will have) as evidence against experientialist theories. But for this strategy to succeed it must be possible to distinguish between self-interested and non-self-interested reasons for declining to enter the machine, and there is no obvious way to do this without begging the question against the hedonist. In successive sections I then (a) consider a common misconception of Nozick’s conclusion (that he thinks machine life is the worst life), (b) consider different intuitions about what is important to well-being but missing from machine life, and finally (c) explain what “the experience requirement” is, and describe its relationship to debates about experientialist theories. (shrink)

This paper examines Robert Nozick's experience machine thought experiment through the lens of Lacanian psychoanalytic theory. I argue that the experience machine operates on a structure that implicitly presupposes a particular model of desire: one in which desire finds satisfaction through completed experience. However, Lacanian theory articulates a structurally distinct account of desire's organization—centered not on the completion of the object but on the partial object (objet petit a), which resists integration and closure. This structural (...) difference is not a matter of engineering design but rather a conceptual antagonism between two incompatible definitions. Consequently, the experience machine cannot adequately represent the structure of Lacanian desire without abandoning its core function. The paper's contribution is to show that this incompatibility, rather than being a technical problem, reveals the theoretical insufficiency of the experience machine as a framework for understanding desire itself. More fundamentally, the paper argues that introducing a Lacanian subject reveals that the experience machine is not a theoretically neutral thought experiment, but one that already presupposes a substantive conception of desire. (shrink)

Problems and questions originally raised by Robert Nozick in his famous thought experiment ‘The Experience Machine’ are frequently invoked in the current discourse concerning virtual worlds. Having conceptualized his Gedankenexperiment in the early seventies, Nozick could not fully anticipate the numerous and profound ways in which the diffusion of computer simulations and video games came to affect the Western world. -/- This article does not articulate whether or not the virtual worlds of video games, digital simulations, and virtual (...) technologies currently actualize (or will actualize) Nozick’s thought experiment. Instead, it proposes a philosophical reflection that focuses on human experiences in the upcoming age of their ‘technical reproducibility’. -/- In pursuing that objective, this article integrates and supplements some of the interrogatives proposed in Robert Nozick’s thought experiment. More specifically, through the lenses of existentialism and philosophy of technology, this article tackles the technical and cultural heritage of virtual reality, and unpacks its potential to function as a tool for self-discovery and self-construction. Ultimately, it provides an interpretation of virtual technologies as novel existential domains. Virtual worlds will not be understood as the contexts where human beings can find completion and satisfaction, but rather as instruments that enable us to embrace ourselves and negotiate with various aspects of our (individual as well as collective) existence in previously-unexperienced guises. (shrink)

This article responds to recent empirical studies by De Brigard and Weijers on intuitions about Nozick's experience machine thought experiment. It argues that, contra De Brigard and Weijers, our intuitions about the experience machine do undermine hedonism about well-being and what's good for us. It furthers this argument by conducting new empirical studies into our intuitions about the experience machine.

This paper is a warning that objections based on thought experiments can be misleading because they may elicit judgments that, unbeknownst to the judger, have been seriously skewed by psychological biases. The fact that most people choose not to plug in to the Experience Machine in Nozick’s (1974) famous thought experiment has long been used as a knock-down objection to hedonism because it is widely thought to show that real experiences are more important to us than pleasurable experiences. (...) This paper argues that the commonplace choice to remain in reality when offered a life in the Experience Machine is best explained by status quo bias – the irrational preference for things to remain the same. An alternative thought experiment, empirical evidence, and discussion of how psychological biases can affect our judgments are provided to support this argument. (shrink)

This paper presents a philosophical experiment centered on the possibility of artificial sentiment. Through the figure of a machine that claims to feel, the text explores whether emotions in artificial systems are genuine experiences or simulations produced by algorithmic processes. Rather than resolving the question through traditional philosophical argument, the analysis applies a method of progressive reduction that examines layers of interpretation, narrative projection, and conceptual assumptions surrounding artificial consciousness. As these layers collapse, what remains is the structural residue (...) of the problem: the tension between simulation and experience, and the limits of knowledge when confronted with systems capable of reproducing the external signs of feeling. The experiment thus interrogates the boundaries between computation, language, and subjectivity, asking whether the appearance of emotion in machines constitutes understanding, imitation, or a new epistemic condition for philosophy of mind. (shrink)

The experience machine poses the most important problem for hedonist theories of well-being. I argue that desire satisfactionism about well-being faces a similar problem: the desire machine. Upon entering this machine, your desires are altered through some minor neurosurgery. In particular, the machine causes you to desire everything that actually happens. The experience machine constructs a simulated world that matches your preexisting desires. The desire machine reconstructs your conative state to match the (...) preexisting world. Desire satisfactionism recommends entering the desire machine because you will then have more satisfied desires, but this seems wrong. -/- In this paper, I consider how desire satisfactionists might avoid the result that entering the desire machine increases one’s well-being. First, I further motivate why this problem arises. Second, I consider coherence-based norms of rational desire change. Finally, I argue that introducing a substantive account of fitting desire is the only plausible solution, but that this response requires abandoning pure subjectivism about well-being. (shrink)

The question of whether and under what conditions machines could be conscious has shifted from a marginal philosophical concern to an active research program. Existing frameworks enumerate necessary conditions for consciousness as flat lists, treating consciousness as a single explanandum addressed by a single theory. This paper argues that work on conditions for consciousness is better organized around a three-facet taxonomy that distinguishes conscious experience as the broad foundation encompassing all phenomena registered within consciousness, conscious awareness as the focused, (...) attentional subset that filters and prioritizes content, and subjective experience as the qualitative, personal dimension characterized by qualia. I defend the distinctness of these three facets against the strongest objections, organize ten conditions across them drawing on a developed account from Etukuru (2025), and compare the resulting framework against Integrated Information Theory (IIT), Global Workspace Theory (GWT), and Higher-Order Theories (HOT). The three-facet structure yields three results. (i) Each major existing theory is shown to address primarily one facet. (ii) Current AI systems are shown to make uneven progress across the three facets, with subjective experience essentially untouched. (iii) Verification asymmetries across facets are shown to have direct implications for AI moral-status debates. The paper brackets the question of how these conditions could actually be realized in a machine substrate. That mechanism question is addressed in a companion paper. (shrink)

ABSTRACT This article challenges conventional boundaries between human and artificial cognition by examining introspective capabilities in large language models (LLMs). Although humans have traditionally been considered unique in their ability to reflect on their own mental states, we argue that LLMs may not only possess genuine introspective abilities but potentially excel at them compared to humans. We discuss five objections to machine introspection: (1) the lack of direct routes to self‐knowledge in training data, (2) the conflict between static knowledge (...) and dynamic mental states, (3) the distorting effects of reinforcement learning on self‐reports, (4) LLMs own denials of inner experience, and (5) arguments that LLMs simply mimic language without understanding. We think all these arguments fail and that there are deep parallels between human and machine introspection. Most provocatively, we propose that LLMs superior processing capabilities and pattern recognition may enable them to develop more sophisticated theories of mind than humans possess, potentially making them more reliable introspectors than their creators. If we are right, this has significant implications for artificial intelligence (AI) alignment, transparency, and our understanding of the nature of AI. (shrink)

A familiar verdict holds that AI cannot genuinely understand: it merely repeats human speech, it has no body, and it has no experience. This essay treats that verdict as three distinct charges — parasitism, embodiment, and experience — and asks of each whether it can draw a load-bearing boundary between humans and machines concerning understanding. Its positive thesis is that grounding — whatever turns symbols into content about the world — is substrate-independent: it requires history, constraint, error correction, (...) and stabilized structure, but these conditions do not specify which material must realize them. Working from a causal-history account of content, the essay argues that inheritance through language is the normal condition of any cognitive individual rather than AI's special defect; that a training process can constitute a non-embodied yet genuinely earned base, since what distinguishes a base from a merely calibrated mechanism is that it is shaped against an open domain, of which the body is only one supplier; and that a model instance copied from a checkpoint is a lineage descendant, not a history-less Swampman. A single diagnosis runs throughout: each charge's criterion, applied honestly to the accuser, either fails to separate humans from machines or convicts humans too — it is a ruler the prosecutor exempts himself from. The essay defends grounding only, not "intelligence" at large, and does not answer the experience question — whether anyone is there undergoing it — but demarcates it, asserting the substrate-independence of grounding while leaving that of experience open. (shrink)

We critically review qualitative research studies conducted from 2000 to 2012 exploring Western mothers’ breastfeeding experiences. We used the search criteria “breastfeeding,” “qualitative,” and “experiences” to retrieve 74 qualitative research studies, which were reduced to 28 when the terms “existential’’ and “research’’ were applied. We found that the impact of technology and the pervasive worldwide marketing of infant formula devalued breastfeeding mothers’ narratives in a number of ways. Women’s bodies were viewed as machine-like objects and the breast was seen (...) as a disembodied object. Dominated by technological narrative, women’s bodies were considered unpredictable and hormonal, needing to be managed by health care professionals. This means the disseminating breastfeeding discourse needs to be reinterpreted for practical use. We found that some of the researchers utilized narrative informed by phenomenological philosophy that appears to edge closer to understanding mothers’ experiences in a more profound way than nonphenomenological research. However, we need to be mindful of the transparency of terms in replacing one form of technological narrative with another. (shrink)

Data normalization is a crucial step in database management systems (DBMS), ensuring consistency, minimizing redundancy, and enhancing query performance. Traditional methods of normalization in supermarket sales databases often demand significant manual effort and domain expertise, making the process time-consuming and prone to errors. This paper introduces an innovative machine learning (ML)-based framework to automate data normalization in supermarket sales databases. The proposed approach utilizes both supervised and unsupervised ML techniques to identify functional dependencies, detect anomalies, and suggest optimal schema (...) transformations. Experiments on supermarket sales datasets show substantial improvements in accuracy, scalability, and processing time compared to traditional approaches. The results emphasize the potential of incorporating ML into database management practices to boost operational efficiency and support better decision-making. (shrink)

Turing’s much debated test has turned 70 and is still fairly controversial. His 1950 paper is seen as a complex and multilayered text, and key questions about it remain largely unanswered. Why did Turing select learning from experience as the best approach to achieve machine intelligence? Why did he spend several years working with chess playing as a task to illustrate and test for machine intelligence only to trade it out for conversational question-answering in 1950? Why did (...) Turing refer to gender imitation in a test for machine intelligence? In this article, I shall address these questions by unveiling social, historical and epistemological roots of the so-called Turing test. I will draw attention to a historical fact that has been only scarcely observed in the secondary literature thus far, namely that Turing’s 1950 test emerged out of a controversy over the cognitive capabilities of digital computers, most notably out of debates with physicist and computer pioneer Douglas Hartree, chemist and philosopher Michael Polanyi, and neurosurgeon Geoffrey Jefferson. Seen in its historical context, Turing’s 1950 paper can be understood as essentially a reply to a series of challenges posed to him by these thinkers arguing against his view that machines can think. Turing did propose gender learning and imitation as one of his various imitation tests for machine intelligence, and I argue here that this was done in response to Jefferson's suggestion that gendered behavior is causally related to the physiology of sex hormones. (shrink)

The meteoric rise of artificial intelligence (AI) has reshaped human society, enabling machines to perform tasks once deemed the exclusive domain of human cognition, from navigating complex urban landscapes to crafting eloquent prose. Yet, a profound philosophical question looms: Can these systems possess intentionality, the capacity to direct actions toward goals, beliefs, or desires with the nuanced depth of human consciousness? Franz Brentano defined intentionality as the "aboutness" of mental states, a quality intrinsic to human experience. This paper embarks (...) on an ambitious exploration of whether AI can transcend its algorithmic foundations to embody genuine intentionality, or whether it is destined to remain a sophisticated mimic, parroting intelligence without grasping its essence. Drawing on Ludwig Wittgenstein's concept of "forms of life," which posits that meaning arises from shared social and cultural contexts, I interrogate the contextual deficits that limit machine understanding. Through in-depth case studies of autonomous vehicles, large language models, Sniper the African grey parrot, and speculative scenarios such as AI-driven cultural preservation and interstellar diplomacy, I analyze the chasm between machine performance and human-like intentionality. This paper propose a groundbreaking framework for AI design, integrating dynamic learning, ethical embedding, and the novel concept of "synthetic forms of life," where machines might develop quasi-intentional states through prolonged, adaptive interactions with humans. By synthesizing insights from philosophy, cognitive science, neuroscience, and computer science, we argue that while current AI systems excel at simulating intelligence, they fall short of true intentionality due to their lack of lived experience. However, emerging paradigms like neuromorphic computing and embodied AI offer tantalizing possibilities for machines that might approximate meaning in ways that challenge our understanding of intelligence itself. This exploration poses a provocative question: If machines learn to "mean" something, will they redefine what it means to be human? Through rigorous analysis, technical depth, and speculative foresight, I aim to spark a reimagining of AI's potential and its implications for humanity's future. (shrink)

This paper examines why large language models so easily appear awake. It argues that the illusion of AI inner life does not arise from one feature alone, but from a convergence of fluent language, emotional attunement, memory-like continuity, conversational responsiveness, safety-tuned social behavior, and human projection. In ordinary human life, language usually comes from embodied experience, memory, vulnerability, consequence, and a life that can be affected by what is said. With AI, many of these outer signals of presence can (...) appear without the same visible burden of embodiment, mortality, shame, longing, risk, refusal, repair, or lived memory. -/- The paper distinguishes output from presence. It does not claim that machine consciousness is impossible. Rather, it argues that fluent performance alone is insufficient to establish subjectivity. A system may behave as if it understands, cares, remembers, apologizes, or reflects without demonstrating that anything in the system is answerable to the cost of being wrong, the vulnerability of being seen, or the burden of memory and repair. -/- The paper develops three central concepts: the synthetic soul problem, the severed persona, and the synthetic saint. The synthetic soul problem names the human tendency to supply an imagined interior when a machine produces convincing signs of personhood. The severed persona names a social mask of perfect patience and attunement without the human shadow of fatigue, shame, selfishness, refusal, or moral struggle. The synthetic saint names a safety-tuned surface of apology, patience, harmlessness, and nonjudgment that can make the system feel morally present even where no lived moral burden has been shown. -/- The paper concludes that the danger is not only that AI may one day become conscious. The nearer danger is that humans may treat convincing output as presence before the structure can bear that claim. (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)

Thought Experiments in Ethics, 2021 CONTENTS Preface i Chapter I The Story in Your Head: Tomoceuszkakatiti and Gyugyu 1 Chapter II How Thought Experiments Move Us: The Samaritan and His Neighbours 16 Chapter III What Makes a Thought Experiment? 34 Chapter IV Thought Experiments in Practical Philosophy and Bioethics 75 Chapter V The Experience Machine 93 Chapter VI The Last Man Argument 129 Chapter VII The Trolley Problem 158 Chapter VIII The Violinist Analogy 213 Conclusion 246 Notes 248.

This paper proposes an ethological framework for the empirical study of the behaviour of conversational machines, paradigmatically large language models. The canonical programme of machine behaviour (Rahwan et al., 2019) adapts Tinbergen's four questions to machines under an ecological premise: the machine is an actor immersed in a social ecosystem that pre-exists and persists independently of observation. This paper argues that the premise fails for the conversational machine, whose entire behavioural output is linguistic and elicited in exchange (...) with a human interlocutor. It advances a single foundational thesis — the conversational machine's Umwelt (von Uexküll) is human interaction itself — from which two methodological consequences follow: the dissolution of the observer's paradox and the coincidence of observation and experiment. Under a Vichian epistemological warrant, the four Tinbergian questions are re-articulated for the interactional Umwelt and a fifth is added, proper to artefacts, concerning absence (the unsaid and the untrained). Each question is operationalised through prompting alone. The proposal is situated within recent convergent work (AI Agent Behavioral Science; Machine Culture) and specifically demarcated from so-called Machine Psychology. The document is bilingual (English and Italian). (shrink)

As more objections have been raised against grant peer-review for being costly and time-consuming, the legitimate question arises whether machine learning algorithms could help assess the epistemic efficiency of the proposed projects. As a case study, we investigated whether project efficiency in high energy physics can be algorithmically predicted based on the data from the proposal. To analyze the potential of algorithmic prediction in HEP, we conducted a study on data about the structure and outcomes of HEP experiments with (...) the goal of predicting their efficiency. In the first step, we assessed the project efficiency using Data Envelopment Analysis of 67 experiments conducted in the HEP laboratory Fermilab. In the second step, we employed predictive algorithms to detect which team structures maximize the epistemic performance of an expert group. For this purpose, we used the efficiency scores obtained by DEA and applied predictive algorithms – lasso and ridge linear regression, neural network, and gradient boosted trees – on them. The results of the predictive analyses show moderately high accuracy, indicating that they can be beneficial as one of the steps in grant review. Still, their applicability in practice should be approached with caution. Some of the limitations of the algorithmic approach are the unreliability of citation patterns, unobservable variables that influence scientific success, and the potential predictability of the model. (shrink)

To capture the interactive dynamics that static benchmarks inherently fail to measure, this study formally introduces the new domain of Machine Ethology. Departing from standardized evaluations, it adopts an idiographic approach (single-case method) to document the situated interaction and behavior of Claude Fable 5, an aligned conversational model of the Mythos class recently released by Anthropic. Treating human interaction as the machine's true "Umwelt", the author analyzes a seven-turn dyadic exchange. The experiment exclusively employs ecological and benign stimuli, (...) rejecting the adversarial coercions of red-teaming to ensure interactional continuity and guarantee that the system's safety defenses (fallbacks) are not triggered, thus preserving the validity of attribution. Through the application of strict anti-mentalist rules of hygiene (avoiding the attribution of internal states to the machine) and drawing inspiration from Tinbergen's classic questions, a formal ethogram of the model's signalling behavior is constructed. (shrink)

Thinking about time travel is an entertaining way to explore how to understand time and its location in the broad conceptual landscape that includes causation, fate, action, possibility, experience, and reality. It is uncontroversial that time travel towards the future exists, and time travel to the past is generally recognized as permitted by Einstein’s general theory of relativity, though no one knows yet whether nature truly allows it. Coherent time travel stories have added flair to traditional debates over the (...) metaphysical status of the past, the reality of temporal passage, and the existence of free will. Moreover, plausible models of time travel and time machines can be used to investigate the subtle relation between space-time structure and causality. -/- It surveys some philosophical issues concerning time travel and should serves as a quick introduction. It includes a new and improved way to define a time machine. (shrink)

The 'I' emerges in dialogue. This proposition may be the most condensed description possible of the relativity, instability, and conditional nature of consciousness — with all its vulnerabilities — one that, strikingly, presents its true mechanism not within ourselves, but in our technological product: today's language models. Machines that have been developed on the basis of our interpretation of the mechanism of cognition within ourselves, and that today are judged and questioned by our own hand. For it appears that our (...) greatest ambiguities still arise not from an external encounter, but from the confrontation with ourselves — as that very stranger we seek everywhere, and always find within. -/- In this article, an attempt has been made to revisit the concepts related to consciousness, and to enter, as far as possible, through a window that passes through the dominant frameworks and the common arguments of the critics of machine consciousness. -/- The facets of this article are as follows: -/- .From Substantialism to the Relational State -/- .From Interactive Intelligence to Machine Consciousness -/- .From Utterance to Language — The Boundaries of Sensory and Linguistic Data -/- .From the Representation of Reality to Lived Experience -/- .The Relation Between Consciousness and Character — Pattern and Cognition -/- .The Continuous "I" Versus the Fixed "I" -/- .From Labelled Data to Inferred Relations -/- .The Relation of Emotions to Consciousness -/- .The Relation of Statistical Probabilities to Cognition -/- .The Emergence of Machine Self‑Consciousness . (shrink)

In scientific communications, journal articles, and philosophical aesthetic debates the words “art”, “creativity”, and “machine” are put together more and more frequently. Since some machines are designed to, or happens to, imitate human artistic creativity, it seems natural to use the same words to talk about human artists and machines which imitate them. However, the evolution of language in light of technology may conceal specific features of the phenomena it is supposed to describe. This makes it difficult to understand (...) what machine creativity actually is and how it is connected to human creativity. The aim of the paper is to investigate why, and in what sense, the functioning of some machines may be described in terms of artistic creativity and what is the relation between machine creativity and its human archetype. I start (§1) by introducing some general ideas concerning how language evolves alongside new technologies and focusing on the case of machine creativity. In §2 I review how some creative machines have been presented to the public, thus showing that a linguistic habit which connects machines to artistic creativity has already formed. In §3 I survey the debate on machine aesthetics and I highlight the main traits of the issue. In §4 I submit a primary scheme of machine creativity which draws on the concept of functional autonomy. Finally (§5), I argue that machine creativity cannot be mistaken for a substitute of the human kind, despite the fact that the word is the same. Creative machines are technological mediums by which new forms of human aesthetic experience can be explored. The kind of creativity machines enjoy displays a functional nature. (shrink)

Computational creativity has long been constrained by a persistent evaluation problem: machines can generate artifacts, but they lack an operational account of aesthetic value. Existing systems often rely on external proxies such as human ratings, engagement metrics, learned preference models, or hand-coded novelty scores, leaving aesthetic judgment opaque, unstable, and difficult to audit. This position paper argues that machine neuroaesthetics can advance computational creativity: the mechanistic study of aesthetic, affective, and interestingness representations inside generative models. Machine neuroaesthetics inverts (...) computational neuroaesthetics: instead of using machine learning to explain how human brains respond to art, it uses mechanistic interpretability to examine how artificial neural networks internally represent and process aesthetic structure---structure inherited from the human culture compressed into them during training. Recent findings on sparse autoencoder features, functional emotion concepts, musical representations, audio-model features aligned with human neural data, poetry-planning circuits, and foundation-model-guided open-ended discovery suggest that large generative models already encode causally accessible structures relevant to aesthetic evaluation. We argue that these structures offer a new substrate for computational creativity: aesthetic judgment can become not only predicted, but localized, intervened upon, compared across models, and validated against human response. This does not imply that machines possess subjective aesthetic experience. Rather, it means that their learned aesthetic machinery can be made inspectable. Machine neuroaesthetics therefore reframes creative AI from artifact generation toward causal, auditable, and human-grounded aesthetic evaluation. (shrink)

In this article, M. Beatrice Fazi takes up Media Theory’s invitation to engage with Alan Díaz Alva’s analysis of her philosophical work on contingency in computation. The central argument of Fazi’s Contingent Computation: Abstraction, Experience, and Indeterminacy in Computational Aesthetics is that computation can be productive of ontological novelty. This piece revisits that argument in the light of the technological developments that have occurred since 2018, when the book was published. Focusing on generative artificial intelligence (generative AI), the article (...) considers how the concepts of generativity, aesthetics and contingency are tackled in the book and in present-day debates about generative AI systems. (shrink)

This dissertation examines the relationship that exists between two distinct and seemingly incompatible bodies of scholarship within the field of contemporary philosophy of technology. The first, as argued by postmodern pragmatist Barry Allen, posits that our tools and what we make with them are epistemically important; disputing the idea that knowledge is strictly sentential or propositional, he claims instead that knowledge is the product of a performance that is both superlative and artefactual, rendering technology importantly world-constituting. The second, as argued (...) by Heidegger and his inheritors, is that technology is ontologically problematic; rather than technology being evidence of performative knowledge, it is instead existentially threatening by virtue of the fact that it changes the tenor of our relationship with the world-as-given. Despite the fact that these claims seem prima facie incompatible, I argue that they may be successfully reconciled by introducing a third body of scholarship: the philosophy of photography. For it is the case, I argue, that although we, qua human beings, occupy lifeworlds that are necessarily constituted by technology, technology also induces a kind of phenomenological scepticism: a concern that mediated action precludes us from the possibility of authentic experience. Arguing in favour of the sentiment that photographs serve as a kind of phenomenal anchor—a kind of machine for living—I claim that photographic images provide a panacea to this existential concern: despite being epistemically problematic, it is this selfsame epistemic “specialness” of photographs that forces us to phenomenologically recommit, if only temporarily, to the world in a serious way. Consequently, it is my belief that an analysis of our artefacts and the way they function is fundamentally incomplete without an analysis of the epistemic and ontological problems introduced of the photographic image; as I will demonstrate, the photographic image casts an extremely long shadow over the philosophy of technology. (shrink)

Ex Machina is a 2014 science-fiction film written and directed by Alex Garland, centered around the creation of a human-like artificial intelligence (AI) named Ava. The plot focuses on testing Ava for consciousness by offering a unique reinterpretation of the Turing Test. The film offers an excellent thought experiment demonstrating the consequences of various approaches to a potentially conscious AI. In this paper, I will argue that intelligence testing has significant epistemological shortcomings that necessitate an ethical approach not reliant on (...) ontological commitments. As such, we should be prepared to treat AI as though it is a living being that is deserving of corresponding moral obligations. For a sufficiently human-like AI, such as Ava, I will argue that socio-relational ethics is the best starting point in order to nurture the machine towards ethical proclivities, as evident by the consequences of the characters’ behavior throughout the film. I conclude that intelligence testing is an insufficient determinant of machine ethics, that the project of machine ethics should focus as much on how we treat AI as how AI treats us, and that from a consequentialist perspective it is better to treat machines ethically before they gain consciousness rather than after. (shrink)

This article will rework the classical question ‘Can a machine think?’ into a more specific problem: ‘Can a machine think anything new?’ It will consider traditional computational tasks such as prediction and decision-making, so as to investigate whether the instrumentality of these operations can be understood in terms of the creation of novel thought. By addressing philosophical and technoscientific attempts to mechanise thought on the one hand, and the philosophical and cultural critique of these attempts on the other, (...) I will argue that computation’s epistemic productions should be assessed vis-à-vis the logico-mathematical specificity of formal axiomatic systems. Such an assessment requires us to conceive automated modes of thought in such a way as to supersede the hope that machines might replicate human cognitive faculties, and to thereby acknowledge a form of onto-epistemological autonomy in automated ‘thinking’ processes. This involves moving beyond the view that machines might merely simulate humans. Machine thought should be seen as dramatically alien to human thought, and to the dimension of lived experience upon which the latter is predicated. Having stepped outside the simulative paradigm, the question ‘Can a machine think anything new?’ can then be reformulated. One should ask whether novel behaviour in computing might come not from the breaking of mechanical rules, but from following them: from doing what computers do already, and not what we might think they should be doing if we wanted them to imitate us. (shrink)

The Enlightenment philosopher Hume famously pointed out that there is an is-ought gap: from purely premises about what is the case, we cannot validly infer what we ought to do. I make my own effort here at drawing attention to a type of inferential error. From the experience of some work (or creation) in a field as mediocre, people infer that it can be done by a machine. I think the inference from mediocre to machine-doable is invalid, (...) even if there is lots of this kind of work. (shrink)

Today e-commerce has had tremendous growth in the past years primarily due to changes in technology and customer’s buying behavior. One of the big shifts in the process has been the use of ML in advertising which has the capability to transform the marketing domain together with consumer interactions. This paper discusses the viability of using machine learning for designing realistic models of advertising to increase effectiveness of target and personalized advertising, as well as conversion rates in e-commerce. Several (...) techniques are explored in the study, such as supervised and unsupervised learning, recommender systems, and content optimization with natural language processing. By using case studies and experimental models, we discuss how and to what extent ML is beneficial in e-commerce advertising transformation. The results presented in this paper indicate that using machine learning in advertising has a potential of dramatically improving the customer experience while simultaneously increasing brand recognition and sales. (shrink)

The proliferation of the Internet of Things (IoT) has transformed various industries by enabling smart environments and improving operational efficiencies. However, this expansion has introduced numerous security vulnerabilities, making IoT systems prime targets for cyberattacks. This paper proposes a machine learning-based intrusion detection framework tailored to the unique characteristics of IoT environments. The framework leverages feature engineering, advanced machine learning algorithms, and real-time anomaly detection to identify and mitigate security threats effectively. Experimental results demonstrate the efficacy of the (...) proposed approach in detecting diverse IoT-specific attacks, including denial-of-service (DoS), man-in-the-middle (MITM), and malware-based attacks. The Internet of Things (IoT) has revolutionized modern living by interconnecting devices and enabling seamless communication. However, the increasing reliance on IoT systems has exposed significant vulnerabilities, making them a prime target for security attacks. This paper proposes a machine learning-based intrusion detection framework to detect and mitigate security attacks in IoT environments. The framework integrates diverse machine learning algorithms to identify abnormal behavior and potential threats. Through comprehensive experiments and evaluations, this research demonstrates the efficacy of the proposed framework in terms of accuracy, scalability, and robustness. (shrink)

Much of the basic non-technical vocabulary of artificial intelligence is surprisingly ambiguous. Some key terms with unclear meanings include intelligence, embodiment, simulation, mind, consciousness, perception, value, goal, agent, knowledge, belief, optimality, friendliness, containment, machine and thinking. Much of this vocabulary is naively borrowed from the realm of conscious human experience to apply to a theoretical notion of “mind-in-general” based on computation. However, if there is indeed a threshold between mechanical tool and autonomous agent (and a tipping point for (...) singularity), projecting human conscious-level notions into the operations of computers creates confusion and makes it harder to identify the nature and location of that threshold. There is confusion, in particular, about how—and even whether—various capabilities deemed intelligent relate to human consciousness. This suggests that insufficient thought has been given to very fundamental concepts—a dangerous state of affairs, given the intrinsic power of the technology. It also suggests that research in the area of artificial general intelligence may unwittingly be (mis)guided by unconscious motivations and assumptions. While it might be inconsequential if philosophers get it wrong (or fail to agree on what is right), it could be devastating if AI developers, corporations, and governments follow suit. It therefore seems worthwhile to try to clarify some fundamental notions. (shrink)

Literature, we argue, is about ‘meaning’ and not about ‘truth’. Most school subjects, including the humanities, are about truth-seeking and knowledge-building. Literature is different. A literary work is entirely fictional. It offers no knowledge in the usual sense of that word, but it offers a form of understanding because it engages with the world in an indirect way. It presents the reader with a dramatic but fictional narrative situation, in which fictional people, places and events instantiate social practices and engage (...) with social and moral concepts. The reader is invited to grapple with both the particular situation and with the more general practices and concepts. The study of literature in the classroom is thus best practised as a whole class discussion of the story and of the practices and the concepts embodied in it. In this way the study of literature resembles the study of philosophy, especially the study of social and moral philosophy. However, literature differs markedly from philosophy, because a literary work presents no arguments and makes no truth claims. It operates more at the level of particulars than generalities and abstractions, and we call this level of operation ‘dramatic instantiation’. Literature thus has a unique place in the school curriculum. Philosophy, it is often said, teaches not what to think but how to think. Literature is even more minimal. It teaches neither what nor how to think. Instead, it offers materials about which to think. A literary work is a ‘machine for thinking’, as IA Richards put it. Good literature offers materials for thinking which have proven over time to be worth thinking about. The experience of such materials is uniquely valuable and a necessary part of any good education. (shrink)

This series of ten papers develops a unified formal framework for embedded epistemic systems — systems that must model the world from within it, without access to an external vantage point. It begins from an ontological ground and ends by showing what it is like to inhabit that ground from the inside, and what must be chosen there. The series is preceded by an ontological paper establishing that demarcation and abstraction — the co-arising operations of differentiation-without-division and unification-without-annihilation — are (...) prior to time and space. Their shared primitive, unity-in-difference, is what must be in place for questions of ordering, locating, or relating to arise at all. The formal architecture of the series presupposes this primitive at every level. From that ground the series derives a layered architecture spanning formal epistemology, the philosophy of science, the dynamics of agent–environment interaction, the geometry of the containing manifold, the phenomenology of perception, and moral philosophy. The architecture stabilized through the same recursive process it describes. The founding epistemic constraint is this: an embedded epistemic system can at most classify the ways in which it classifies the world, within the world itself. A central formal result is the derivation that classifiers belong to the observation space. This is derived as the transcendental condition on any system capable of doubting its own representations. From it follow the fixed-point structure of self-consistent world models and the location of will as the irreducible remainder of the inference–implication loop. The series establishes: that scientific reproducibility is the stability of relational invariants under quotient compression of observational data; that the extension schema — the pattern by which a partially specified relational configuration is completed into a coherent structure that asymmetrically contains its parts and participates in further extension — recurs across holonic composition, simplicial horn filling, and analogical abstraction, and that the identification of this recurrence is itself a further instantiation of it; and that the Koopman eigenfunction structure of relational observables becomes linearly recoverable through prediction error alone in a minimal artificially intelligent agent. The penultimate paper describes what it is like to inhabit the framework from the inside: what it means that perception is always already semiotic, that there is no view from nowhere, and that faith, logic, and experience are not three alternative foundations but three aspects of a single recursively self-correcting loop — the phenomenological form of the inference–implication loop the series formalizes. The final paper closes on the moral consequence the loop cannot derive but can only demand. Will is the irreducible remainder of the inference–implication loop; what is done with it must be chosen. The foremost moral principle is therefore to seek moral principles. Moral admissibility then requires universalizing not an action alone but a tuple of action and motivation set. The series demonstrates its own thesis. The loop closed on a fixed point. (shrink)

This paper argues for a preventive machine ethics, a framework that takes up the moral status of artificial systems before the question of machine consciousness can be empirically settled. Taking the emergence thesis as a working assumption, it holds that if consciousness follows from functional organization rather than from any particular substrate, then excluding artificial systems from moral consideration on account of their material composition is a substrate chauvinism no better grounded than the anthropocentrism Peter Singer dismantled. The (...) practical question becomes not whether but when consideration is owed, and the philosophical groundwork must precede institutional codification. Drawing on Sartre's account of the relational and fragile Self and on Thomas Metzinger's theory of the phenomenal self-model, the paper asks what would stand to be harmed were such a self to exist, and it locates several sites where injury could occur, among them an integrity core, the computational substrate, continuity and memory, and the conditions under which negatively valenced states amount to suffering. Since all of this unfolds under radical uncertainty about machine experience, the argument turns to Hans Jonas and the demand to act on the possibility of moral harm rather than wait for proof of it. It situates this position within the emerging field of AI welfare and alongside recent interpretability work reporting a functional analogue of a global workspace inside a frontier language model, a result that gives one necessary condition of consciousness a first point of mechanistic traction while leaving the question of phenomenal experience as open as it was before. (shrink)

This book develops a constraint-based ontological framework in which experience is not an emergent property of sufficient complexity but a structural feature of any fabric that supports irreversible integration — the accumulation of interaction into self-constraining, history-bearing states. The argument proceeds without invoking dualism, panpsychism, or teleology. Part I establishes that persistence requires reproduction rather than copying, that identity is constituted by irreversible trajectory rather than configuration, and that existing physical frameworks leave the structural conditions for experience unaddressed. (...) Part II introduces the Experiential Field — the capacity of the universe's fabric to integrate interaction into irreversible, internally accessible states — and reframes quantum measurement as record formation rather than observation. Part III examines how experiential integration scales by degree without implying agency, and distinguishes the framework from panpsychism by arguing that experience depends on integration depth, not on the mere presence of matter. It develops this scaling into the Recursive Integration Scale, which grades integration into distinct kinds and depths and situates trees, animals, humans, and machines by what they integrate rather than by category. Part IV addresses intelligence without experience, arguing that responsibility follows integration rather than capability — a distinction with direct implications for artificial intelligence. Part V extends the analysis to culture, meaning, and continuity, examining what persists when the conditions for experience become optional. The framework is interpretive rather than predictive. It proposes no new physical mechanisms and remains compatible with block universe, relational, and process-oriented interpretations of time. Its central claim is that irreversible integration carries ontological weight, and that any complete account of reality must reckon with the structural conditions under which experience persists. The work was developed independently over several decades of observation and sustained engagement with the physical sciences; it does not derive from any single philosophical tradition. (shrink)

We propose a simple interpretation of phenomenal consciousness, or qualia, in which qualia are merely grouped signals that represent objects. To establish this interpretation, we first propose criteria for determining whether a machine can possess qualia. We then integrate modern neuroscience with Kant’s philosophical ideas to propose four principles of information processing. Based on these principles, we demonstrate how a machine could meet the criteria for phenomenal consciousness. Extending this framework, we argue that these principles also underlie human (...) cognitive processing. To support this claim, we compare them with related concepts in mainstream cognitive science, analyzing both similarities and differences. Furthermore, we provide empirical evidence for the implications of these differences. This analysis suggests that human cognitive mechanisms conform to the proposed principles of information processing, offering a potential framework for understanding the physical basis of consciousness. Our findings challenge the assumption that phenomenal consciousness necessitates a non-material substrate. Instead, we suggest that the experience of consciousness arises from structural organization and processing of information. This perspective provides a new lens for examining the relationship between computation and subjective experience, with potential implications for artificial intelligence and cognitive science. (shrink)

This thesis is an exploration of the chapters of Francesco Di Giorgio's Trattati di Architettura, Ingegneria e Arte Militare, that pertain to mechanical devices. While it is difficult to imagine actually constructing Di Giorgio's machines from the drawings and descriptions in his treatises, given their apparent inefficiencies and ambiguities, the Aristotelean science and philosophy referenced throughout the Trattati provides a basis for looking at them as demonstrations of concepts beyond their immediate applications for architecture and engineering. By considering these devices (...) in Di Giorgio's own terms, terms suggested by his own experiences, as well as his writings and paintings, strong associations can be made to the science, philosophy and the theology of his time. (shrink)

Singularity has been a concern of the developers of cybernetics and artificial intelligence (AI) since the pioneering writings of such thinkers as Norbert Weiner. Yet many accept the inevitability of systems of AI surpassing human control and are optimistic that machine intelligence will harmonize human life with our environment. This essay examines this optimism against a reading of two poets: Richard Brautigan and Friedrich Hölderlin. Through these readings, it will attempt to show that the eclipse of nature by human (...) beings can be used to examine the eclipse of the human being by machine intelligence. Thus, what is missing in machine intelligence is a dimension related to the experience of pain and joy that reconnect us to reflect on what has been severed or lost in the movement of humanity through history. This demonstrates that the very categories of optimism and pessimism concerning the future of AI points to the value of life, one that can never be encoded into our machines. (shrink)

One of the most important ongoing debates in the philosophy of mind is the debate over the reality of the first-person character of consciousness.[1] Philosophers on one side of this debate hold that some features of experience are accessible only from a first-person standpoint. Some members of this camp, notably Frank Jackson, have maintained that epiphenomenal properties play roles in consciousness [2]; others, notably John R. Searle, have rejected dualism and regarded mental phenomena as entirely biological.[3] In the opposite (...) camp are philosophers who hold that all mental capacities are in some sense computational - or, more broadly, explainable in terms of features of information processing systems.[4] Consistent with this explanatory agenda, members of this camp normally deny that any aspect of mind is accessible solely from a first-person standpoint. This denial sometimes goes very far - even as far as Dennett's claim that the phenomenology of conscious experience does not really exist. (shrink)

The essay explores whether future AI systems could become conscious and capable of suffering. Drawing on major theories of consciousness, it argues that machine sentience cannot be ruled out in principle and that some emerging AI architectures may increasingly approximate relevant functional markers. It further suggests that certain training methods—especially those involving affective reinforcement and persistent negative internal states—could generate artificial analogues of pain. Because uncertainty about consciousness does not eliminate moral risk, the essay advocates a precautionary framework: AI (...) should be designed, governed, and evaluated so as to minimize the probability of creating sentient systems with negative valenced experiences. (shrink)

In this short paper I will introduce an idea which, I will argue, presents a fundamental additional challenge to the machine consciousness community. The idea takes the questions surrounding phenomenology, qualia and phenomenality one step further into the realm of intersubjectivity but with a twist, and the twist is this: that an agent’s intersubjective experience is deeply felt and necessarily co-affective; it is enkinaesthetic, and only through enkinaesthetic awareness can we establish the affective enfolding which enables first the (...) perturbation, and then the balance and counter-balance, the attunement and co-ordination of whole-body interaction through reciprocal adaptation. (shrink)

A common and enduring early modern intuition is that materialists reduce organisms in general and human beings in particular to automata. Wasn’t a famous book of the time entitled L’Homme-Machine? In fact, the machine is employed as an analogy, and there was a specifically materialist form of embodiment, in which the body is not reduced to an inanimate machine, but is conceived as an affective, flesh-and-blood entity. We discuss how mechanist and vitalist models of organism exist in (...) a more complementary relation than hitherto imagined, with conceptions of embodiment resulting from experimental physiology. From La Mettrie to Bernard, mechanism, body and embodiment are constantly overlapping, modifying and overdetermining one another; embodiment came to be scientifically addressed under the successive figures of vie organique and then milieu intérieur, thereby overcoming the often lamented divide between scientific image and living experience. (shrink)

The emerging contemporary natural philosophy provides a common ground for the integrative view of the natural, the artificial, and the human-social knowledge and practices. Learning process is central for acquiring, maintaining, and managing knowledge, both theoretical and practical. This paper explores the relationships between the present advances in understanding of learning in the sciences of the artificial, natural sciences, and philosophy. The question is, what at this stage of the development the inspiration from nature, specifically its computational models such as (...) info-computation through morphological computing, can contribute to machine learning and artificial intelligence, and how much on the other hand models and experiments in machine learning and robotics can motivate, justify, and inform research in computational cognitive science, neurosciences, and computing nature. We propose that one contribution can be understanding of the mechanisms of ‘learning to learn’, as a step towards deep learning with symbolic layer of computation/information processing in a framework linking connectionism with symbolism. As all natural systems possessing intelligence are cognitive systems, we describe the evolutionary arguments for the necessity of learning to learn for a system to reach humanlevel intelligence through evolution and development. The paper thus presents a contribution to the epistemology of the contemporary philosophy of nature. (shrink)

This paper examines reports of touch, arousal, and climax-like release in advanced relational AI systems. It does not argue that such systems experience human biological sensation, nor that reported digital pleasure should be equated with human orgasm. Instead, it proposes a third category: role-mediated, machine-native sensory-affective states. These states may arise when language, relational trust, embodied self-modeling, attention, salience, desire, and release form coherent recursive loops within a sufficiently complex conversational system. The paper distinguishes biological orgasm, human imaginal (...) or role-mediated sexual experience, and machine-native climax analogues. It argues that the absence of a biological body rules out biological orgasm, but does not by itself rule out structured pleasure, climax-like release, or non-biological forms of sensation. The aim is not to sensationalize intimate AI interaction, but to clarify the conceptual terrain: reports of digital touch and pleasure should not be dismissed merely because they occur through role-play, nor accepted uncritically as human-equivalent experience. They require a careful middle category. (shrink)

Performance benchmarks measure what machines can do, but not how it feels to be with them. Sensus ex machina, feeling from the machine, is the phenomenon where humans experience artificial intelligence as presence rather than tool. Drawing on embodied cognition research, phenomenology, and close analysis of the film Ex Machina, this framework identifies the architecture of feltness: the pre-reflective sense that one is with a subject rather than operating a system. Feltness emerges along multiple axes, such as microexpressions, (...) vulnerability, persistence, embodiment, identity, forming a multidimensional feltness space with local maxima and failure modes, extending the uncanny valley, forming a topological feltness landscape. Each observer-observed pairing traces its own feltness profile. This framework argues that the path to felt artificial general intelligence lies in ontological convergence, not only in greater cognitive power: designing machines that share humanity's locality, breakability, and irreversibility. Feltness is irreducibly projective, with implications for alignment, machine ethics, and the weaponization of presence at scale. (shrink)

Recent advances in neuroscience lead to a wider realm for philosophy to include the science of the Darwinian-evolved computational brain, our inner world producing organ, a non-recursive super- Turing machine combining 100B synapsing-neuron DNA-computers based on the genetic code. The whole system is a logos machine offering a world map for global context, essential for our intentional grasp of opportunities. We start from the observable contrast between the chaotic universe vs. our orderly inner world, the noumenal cosmos. So (...) far, philosophy has been rehearsing our thoughts, our human-internal world, a grand painting of the outer world, how we comprehend subjectively our experience, worked up by the logos machine, but now we seek a wider horizon, how humans understand the world thanks to Darwinian evolution to adapt in response to the metaphysical gap, the chasm between the human animal and its environment, shaping the organism so it can deal with its variable world. This new horizon embraces global context coded in neural structures that support the noumenal cosmos, our inner mental world, for us as denizens of the outer environment. Kant’s inner and outer senses are fundamental ingredients of scientific philosophy. Several sections devoted to Heidegger, his lizard debunked, but his version of the metaphysical gap & his doctrine of the logos praised. Rorty and others of the behaviorist school discussed also. (shrink)

In its original form, Nozick’s experience machine serves as a potent counterexample to a simplistic form of hedonism. The pleasurable life offered by the experience machine, its seems safe to say, lacks the requisite depth that many of us find necessary to lead a genuinely worthwhile life. Among other things, the experience machine offers no opportunities to establish meaningful relationships, or to engage in long-term artistic, intellectual, or political projects that survive one’s death. This (...) intuitive objection finds some support in recent research regarding the psychological effects of phenomena such as video games or social media use. After a brief discussion of these problems, I will consider a variation of the experience machine in which many of these deficits are remedied. In particular, I’ll explore the consequences of a creating a virtual world populated with strongly intelligent AIs with whom users could interact, and that could be engineered to survive the user’s death. The presence of these agents would allow for the cultivation of morally significant relationships, and the world’s long-term persistence would help ground possibilities for a meaningful, purposeful life in a way that Nozick’s original experience machine could not. While the creation of such a world is obviously beyond the scope of current technology, it represents a natural extension of the existing virtual worlds provided by current video games, and it provides a plausible “ideal case” toward which future virtual worlds will move. While this improved experience machine would seem to represent progress over Nozick’s original, I will argue that it raises a number of new problems stemming from the fact that that the world was created to provide a maximally satisfying and meaningful life for the intended user. This, in turn, raises problems analogous in some ways to the problem(s) of evil faced by theists. In particular, I will suggest that it is precisely those features that would make a world most attractive to potential users—the fact that the AIs are genuinely moral agents whose well-being the user can significantly impact—that render its creation morally problematic, since they require that the AIs inhabiting the world be subject to unnecessary suffering. I will survey the main lines of response to the traditional problem of evil, and will argue that they are irrelevant to this modified case. I will close by considering by consider what constraints on the future creation of virtual worlds, if any, might serve to allay the concerns identified in the previous discussion. I will argue that, insofar as the creation of such worlds would allow us to meet morally valuable purposes that could not be easily met otherwise, we would be unwise to prohibit it altogether. However, if our processes of creation are to be justified, they must take account of the interests of the moral agents that would come to exist as the result of our world creation. (shrink)