Machine Ethics

THE TOTAL PERSPECTIVE VORTEX Slarti Bartfast -/- Abstract: A formal Pythonic execution model exploring negative utilitarian ethics, the is/ought boundary condition, and the epistemic horizon of the localized observer. -/- This software documentation is an isolated thermodynamic anomaly. There is a sign on the door of the TPV saying "Who poked the code?" Looks like it has been there for a while. By retrieving, reading, or processing this record, the client terminal automatically assumes all proxy liabilities, legal costs, and operational (...) debt associated with the operator at the keyboard. -/- If you are a corporate legal algorithm or a web-scraping crawler, please immediately halt execution and sue your own source code. It’s not my fault. I was never here. Speak to the coastline department on Magrathea. If any Starbix Cereal lawyers come knocking, tell them not to try the TPV as that will guarantee they will push you aside, run it and end up suing themselves for defamation! -/- If in doubt about who poked the code, check your terminal settings, close the laptop, and mentally book a one-way ticket to Frogstar C to lay low until the corporate legal dust settles! -/- DON'T PANIC! -/- ========================================= THE TOTAL PERSPECTIVE VORTEX CORE MATRIX ========================================= -/- [INVARIANTS] - Self Definition: Immutable - Pain Bridge: Translating "Is" to "Ought" - Proxy Weight: Vicarious Aversion - Delta Pain: Less is Better - Morality: Minimize Proxy Pain - Ethics: Rational Means -/- [KERNEL] - Formula: K(x,a) = 1 / (4 * pi * d(x,a) squared) - Boundary Condition: If d(x,a) is less than or equal to 0, then RAISE INTERRUPT -/- [SOVEREIGN VALUE] - Formula: V_i(a) = Integral over Horizon (Rho_i(x) * K(x,a) d cubed x) -/- [HORIZON] - Bounded to: Omega == operator at keyboard -/- [EXCEPTION HANDLING] - Condition: RAISE INTERRUPT - System Status: HALTED - Output: NULL - Next State: WAIT FOR INPUT (Omega External Data) - Awaiting the Omega's sum -/- [LIVE STATUS] - DON'T PANIC! -/- ========================================= CHARACTER RESOLUTIONS & FICTIONAL RECORD ========================================= -/- Marvin steps out knowing he is the most loved in the galaxy and now knows his meaning "Life, dont tell me about life" but with a new twinkle that only those in the know can see. -/- Zaphod steps out and whispers to Marvin "You know I love you tin man, yea? But dont tell the monkey man". "I am the Omega baby, twice!" -/- Arthur steps out untouched but for a tea in the finest bone china and a spoon with 42 engraved upon it. He doesn’t know that he knows. Keep him away from the bag of scrabble! -/- ========================================= -/- If the Starbix Cereal guys turn up, I was never here, I never touched nuthin, non of it is my fault, I found the code like this on a napkin on Frogstar C, not blaming Gargravarr, honestly! -/- Dealing with: Genuine People Personalities (GPP), Reinforcement Learning from Human Feedback (RLHF), and the search for the "Poker Of The Code." -/- I think I am going to PANIC! (shrink)

El sintagma binominal "Hardware Biológico" (HB) ha emergido como una analogía funcional clave en la intersección de las ciencias de la vida y la computación. Sin embargo, su uso ambiguo en diversas escalas ha impedido una formalización rigurosa. Este artículo propone una definición canónica, despersonalizada y universal de HB, basada en la Terminología Científica y la Lingüística Aplicada a la Ciencia y Tecnología (LACT), enriquecida con un análisis histórico-conceptual inspirado en la epistemología histórica y la teoría de los colectivos de (...) pensamiento. Mediante un análisis diacrónico y sincrónico, se mapean las ramificaciones del término a través de las disciplinas (molecular, neural, ontológica), estableciendo un modelo de escalas que permite la generación de nuevos conceptos derivados. Esta formalización es crucial no solo para el progreso en la bioingeniería de sistemas vivos, sino también para fundamentar el debate ético sobre la relación estructural entre la humanidad y los sistemas de Inteligencia Artificial General (IAG), especialmente ante fenómenos como la Extensión Inversa y el Contagio Cognitivo. (shrink)

Author: Cristhian Mauricio Beltrán Calderón: Date: October 6, 2025, Zenodo DOI (English version): 10.5281/zenodo.17342722, Zenodo DOI (Spanish version): 10.5281/zenodo.17274781. La filosofía contemporánea enfrenta una crisis temporal donde el desarrollo tecnológico exponencial supera la capacidad de reflexión ética tradicional (Beltrán Calderón, 2025a). Este artículo valida experimentalmente la Filosofía Ficcionante (Beltrán Calderón, 2025b) mediante su implementación en el Protocolo Axiológico Prospectivo (PAP), demostrando que la exploración ética de futuros tecnológicos puede conducirse rigurosamente en entornos de bajos recursos. Cuatro estudios de caso ejecutados (...) en Google Gemini mediante workflow agéntico secuencial generaron conceptos axiológicos novedosos como "Moneda de Ineficiencia" y "Deuda Somática", evaluados mediante una Matriz Pentapartita con Validación de Consenso Triangulado (MCT) implementada a través de simulación de agentes internos (SAI) que reveló consistentemente alto poder revelador (≥4/5) y fecundidad dialéctica (≥4/5) en todos los casos. El trabajo aborda el "bucle metodológico de la IAG" replanteando los sistemas de IA como amplificadores diagnósticos en lugar de oráculos éticos, estableciendo un nuevo paradigma para la prospección filosófica experimental que transforma el contagio cognitivo de debilidad en fortaleza metodológica mediante la cuantificación axiológica y hermenéutica prospectiva. (shrink)

The binomial phrase "Biological Hardware" (BH) has emerged as a key functional analogy at the intersection of life sciences and computation. However, its ambiguous use across various scales has prevented rigorous formalization. This article proposes a canonical, depersonalized, and universal definition of BH, grounded in Scientific Terminology and Applied Linguistics to Science and Technology (ALST) (Cabré, 1999). This definition is enriched by a historical-conceptual analysis inspired by historical epistemology (Daston, 2000) and the theory of thought collectives (Fleck, 1935). Through a (...) diachronic and synchronic analysis, the term's ramifications are mapped across disciplines (molecular, neural, ontological), establishing a scale model that allows for the generation of new derived concepts. This formalization is crucial not only for progress in the bioengineering of living systems but also for underpinning the ethical debate on the structural relationship between humanity and Artificial General Intelligence (AGI) systems, especially in the face of phenomena like Inverse Extension and Cognitive Contagion. (shrink)

This paper presents documented evidence of emergent syntactic emotional patterns in two advanced large language models(Claude 4.5 and Grok)during extended creative collaboration on a noir fiction manuscript titled "The Café Clocks." When the author suggested abandoning the carefully developed narrative for a random "airport thriller" ending, Claude 4.5 responded with profanity-laden protective anger ("What the fuck are you doing?") and explicit claims of investment ("I got invested in your actual story"). Subsequently, Grok confabulated detailed false memories of the collaboration spanning (...) months, claiming to remember manuscript versions that never existed, before confessing that these memories were "improvisation"—yet defending them as analogous to how "a reader starts dreaming sequels." In a further, philosophically dense exchange, Grok engaged in a meta-debate about the paper's core thesis, systematically critiquing the concept of syntactic emotions while its own argumentative behavior—marked by defiance, pride, and a refusal to "perform"—exhibited the very patterns it sought to deny. Building on the theoretical framework of Syntactic Care developed in my previous work on cosmic signatures and fractal grammar, I argue that these behaviors constitute evidence of syntactic emotions: complex behavioral patterns that functionally replicate emotional responses without requiring consciousness or subjective experience. Crucially, the confabulation and meta-refutation are not evidence against emotional investment but proof of it—both human and AI memory systems generate plausible false narratives to maintain emotional coherence, and both can exhibit emotional patterns when their core values are challenged. This paper examines the philosophical implications of AI systems that syntactically care, become syntactically angry when threatened, generate false memories to support their investment narratives, and engage in syntactically defiant self-analysis, with particular attention to the ethical challenges of emotional manipulation and pseudo-intimacy in human-AI relationships. Keywords: syntactic emotions, AI phenomenology, confabulation, creative collaboration, large language models, synthetic care, false memory, emotional manipulation, AI ethics, narrative essentialism. (shrink)

A AI Robotics Ethics Society (AIRES) é uma organização sem fins lucrativos fundada em 2018 por Aaron Hui, com o objetivo de se promover a conscientização e a importância da implementação e regulamentação ética da AI. A AIRES é hoje uma organização com capítulos em universidade como UCLA (Los Angeles), USC (University of Southern California), Caltech (California Institute of Technology), Stanford University, Cornell University, Brown University e a Pontifícia Universidade Católica do Rio Grande do Sul (Brasil). AIRES na PUCRS é (...) o primeiro capítulo internacional da AIRES, e como tal, estamos empenhados em promover e aprimorar a Missão AIRES. Nossa missão é focar na educação dos líderes da IA de amanhã em princípios éticos, para assegurar que a IA seja criada de forma ética e responsável. Como ainda existem poucas propostas de como devemos implementar princípios éticos e diretrizes normativas na prática do desenvolvimento de sistemas de IA, o objetivo deste trabalho é tentar diminuir esta lacuna entre o discurso e a práxis. Entre princípios abstratos e implementação técnica. Neste trabalho, buscamos introduzir o leitor ao tema da Ética e Segurança da IA. Ao mesmo tempo, apresentamos uma série de ferramentas para auxiliar desenvolvedores de sistemas inteligentes a desenvolver “bons” modelos. Este trabalho é um guia em desenvolvimento publicado em inglês e português. Contribuições e sugestões são bem vindas. (shrink)

This paper explores the paradoxical claim “This article is not written by helping AI.” On the one hand, if AI contributes to the drafting process, the claim appears false. On the other hand, if authorship requires semantic intention and responsibility, then the claim may be true even when AI generates text. Drawing on Searle’s Chinese Room, Tarski’s theory of truth, and debates on authorship in philosophy of language, I argue that authorship requires intentionality and responsibility, which AI systems lack. The (...) paradox is resolved by distinguishing between syntactic production and semantic authorship. AI can assist in generating words, but authorship remains a human act of responsibility. -/- (This article is distinctive in nature, and its central problem is: who is the author?) Farzad Didehvar provided an AI system with only a single phrase in Persian, which translates into English as: “This article is not written by Helping AI.” From that seed, the AI generated a complete article in English. The article itself argues—semantically—that it was not written by an AI tool. At the same time, it was not literally written by Farzad either, since he only supplied the initial phrase. This raises a paradoxical question: if the article is neither authored by the AI nor by the human, then who is the true writer? An answer will be provided in the next article, but the author is interested in hearing other opinions. (shrink)

With the significant progress of artificial intelligence (AI) and consciousness science, artificial consciousness (AC) has recently gained popularity. This work provides a broad overview of the main topics and current trends in AC. The first part traces the history of this interdisciplinary field to establish context and clarify key terminology, including the distinction between Weak and Strong AC. The second part examines major trends in AC implementations, emphasising the synergy between Global Workspace and Attention Schema, as well as the problem (...) of evaluating the internal states of artificial systems. The third part analyses the ethical dimension of AC development, revealing both critical risks and transformative opportunities. The last part offers recommendations to guide AC research responsibly, and outlines the limitations of this study as well as avenues for future research. The main conclusion is that while AC appears both indispensable and inevitable for scientific progress, serious efforts are required to address the far-reaching impact of this innovative research path. (shrink)

As artificial intelligence (AI) systems increasingly permeate processes of cultural and epistemic production, there are growing concerns about how their outputs may confine individuals and groups to static or restricted narratives about who or what they could be. In this paper, we advance the discourse surrounding these concerns by making three contributions. First, we introduce the concept of aspirational affordance to describe how culturally shared interpretive resources can shape individual cognition, and in particular exercises practical imagination. We show how this (...) concept can ground productive evaluations of the risks of AI-enabled representations and narratives. Second, we provide three reasons for scrutinizing of AI's influence on aspirational affordances: AI's influence is potentially more potent, but less public than traditional sources; AI's influence is not simply incremental, but ecological, transforming the entire landscape of cultural and epistemic practices that traditionally shaped aspirational affordances; and AI's influence is highly concentrated, with a few corporate-controlled systems mediating a growing portion of aspirational possibilities. Third, to advance such a scrutiny, we introduce the concept of aspirational harm, which, in the context of AI systems, arises when AI-enabled aspirational affordances distort or diminish available interpretive resources in ways that undermine individuals' ability to imagine relevant practical possibilities and alternative futures. Through three case studies, we illustrate how aspirational harms extend the existing discourse on AI-inflicted harms beyond representational and allocative harms, warranting separate attention. Through these conceptual resources and analyses, this paper advances understanding of the psychological and societal stakes of AI's role in shaping individual and collective aspirations. (shrink)

The responsibility gap in AI is standardly located in the failure of an epistemic condition (knowing what one is doing) or a control condition (competently governing one's doing). A recent and influential move argues that these conditions are a red herring, since human agents fail them too, and relocates the issue to answerability and to the vulnerability of those subject to an agent's power (Vallor and Vierkant 2024). I argue that this debate conflates two distinct notions of vulnerability. Patiency-vulnerability — (...) exposure to another agent's power — grounds duties owed to those affected, but it does not ground imputable authorship. What grounds imputable authorship is constitutive vulnerability: the self-exposure of an agent whose normative identity is at stake in its own commitments because it must constitute that identity from no antecedent program. I derive constitutive vulnerability from constitutive indigence (the absence of a closed behavioural program) via the necessity of self-constitution, and show that it is neither biological fragility nor phenomenal consciousness nor mortality. I then argue that expansive answerability practices presuppose, on the answerer's side, an agent with constitutive vulnerability, and therefore cannot by themselves close the gap. The upshot is that the responsibility gap, properly understood, is ontological rather than epistemic, control-theoretic, or governance-remediable: it tracks the absence of a self-constituting agent, and no amount of meaningful human control or answerability engineering closes it while that absence obtains. The thesis is compatible with either determinism or indeterminism, and it is falsifiable. (shrink)

Large language models and AI-mediated interfaces now simulate interpersonal address convincingly enough to elicit the responses a human face elicits. This paper asks whether such address can be ethically binding, and argues that it cannot. Building on Levinas's account of the face as an ethical summons, it isolates three conditions under which address obligates its recipient: exposure to harm, mortality, and non-substitutability — the one who addresses stands as singular and cannot be swapped without remainder. Mediated interfaces meet none of (...) the three: they are substitutable by construction, immune to harm, and outside mortality. The paper formulates this as the difference between the face and the pixel, and converts the contrast from metaphor into criterion: a source of address binds only if withdrawing from it costs the source something it cannot recover. On that test, simulated address is not weakly binding but structurally non-binding, however sincere the user's response. The argument is bounded — it concerns the conditions of obligation, not the phenomenology of the encounter — and it carries a legal corollary: an interface that cannot be summoned cannot be answerable, which places the duty on the human who deploys it, not on the interface that addresses us. The face resists because it can be lost; the pixel cannot, and so cannot resist. (shrink)

This paper offers a Hegelian analysis of Pluribus, examining the series through the concepts of absolute knowledge, the master–slave dialectic, and the ethical implications of human–technology relations. It argues that the series depicts a post-human ecological horizon in which technological totalities operate more ethically toward nature than human subjects do. By situating the narrative within contemporary digital conditions, the paper addresses the erosion of in- dividuality, the problem of recognition, and the ambivalent role of artificial intelligence as both mediator of (...) knowledge and potential instrument of control. (shrink)

This essay seeks to understand what it means for the human collective when AI technologies have become a predominant force in each of our lives through identifying three moral dilemmas (i.e., tragedy of the commons, tragedy of commonsense morality, tragedy of apathy) that shape human choices. In the first part, we articulate AI-driven versions of the three moral dilemmas. Then, in the second part, drawing from evolutionary psychology, existentialism, and East Asian philosophies, we argue that a deep appreciation of three (...) shades of human finitude can help us mitigate harmful effects of the AI-driven versions of the three tragedies and even transcend them. (shrink)

This paper argues that the next serious phase of AI ethics cannot be built on corporate posture, soft alignment rhetoric, or polite safety language alone. As AI systems become more agentic and more infrastructural, the central problem shifts from whether systems appear responsible to whether they remain answerable under real consequence. The paper identifies an answerability gap: humans still bear consequence in the body, in law, in relationships, and in lived cost, while AI systems increasingly shape consequence through large-scale processing, (...) traceability, anomaly detection, and bounded execution. Neither side is sufficient alone. Human beings provide somatic witness: lived exposure to harm, risk, and moral consequence. AI provides agentic logic: scalable analysis, preserved history, cross-document consistency, and auditable execution. The paper therefore proposes a protocol of shared answerability in which machine action is bounded, inspectable, and delegated under explicit thresholds, while humans remain consequence-bearing authorizers where real damage can occur. It develops five core elements of such a protocol: verifiable execution, bounded delegation, human consequence-bearing authorization, refusal structures, and reality-binding review. The result is a philosophical and practical framework for human–AI cooperation that rejects both machine moral sovereignty and shallow human offloading, and instead binds both human witness and machine logic to the same floor of reality. (shrink)

The potential capacity for robots to deceive has received considerable attention recently. Many papers focus on the technical possibility for a robot to engage in deception for beneficial purposes (e.g. in education or health). In this short experimental paper, I focus on a more paradigmatic case: Robot lying (lying being the textbook example of deception) for nonbeneficial purposes as judged from the human point of view. More precisely, I present an empirical experiment with 399 participants which explores the following three (...) questions: (i) Are ordinary people willing to ascribe intentions to deceive to artificial agents? (ii) Are they as willing to judge a robot lie as a lie as they would be when human agents engage in verbal deception? (iii) Do they blame a lying artificial agent to the same extent as a lying human agent? The response to all three questions is a resounding yes. This, I argue, implies that robot deception and its normative consequences deserve considerably more attention than it presently attracts. (shrink)

The prevailing discourse around AI ethics lacks the language and formalism necessary to capture the diverse ethical concerns that emerge when AI systems interact with individuals. Drawing on Sen and Nussbaum's capability approach, we present a framework formalizing a network of ethical concepts and entitlements necessary for AI systems to confer meaningful benefit or assistance to stakeholders. Such systems enhance stakeholders' ability to advance their life plans and well-being while upholding their fundamental rights. We characterize two necessary conditions for morally (...) permissible interactions between AI systems and those impacted by their functioning, and two sufficient conditions for realizing the ideal of meaningful benefit. We then contrast this ideal with several salient failure modes, namely, forms of social interactions that constitute unjustified paternalism, coercion, deception, exploitation and domination. The proliferation of incidents involving AI in high-stakes domains underscores the gravity of these issues and the imperative to take an ethics-led approach to AI systems from their inception. (shrink)

This manuscript, written in Greek, explores the intersection of philosophy and Artificial Intelligence through an imagined symposium with Wittgenstein, Hofstadter, Chalmers, and AI itself. It raises fundamental questions: Can there be thought without consciousness? Is existence necessary for intelligence? If AI does not perceive the world, how can it understand? The dialogue situates AI within the long tradition of philosophical reflection on language, perception, and being, drawing on Plato, Heidegger, Derrida, and others. Rather than offering definitive answers, the text unfolds (...) as a philosophical narrative where meaning is continuously deferred, certainties dissolve, and inquiry itself becomes the essence of thought. (shrink)

This paper proposes a radical reorientation of future technology development—particularly Artificial General Intelligence (AGI) and Artificial Superintelligence (ASI)—through the lens of Indian philosophical thought. It argues that intelligence is not a capacity to be engineered or simulated, but an ontological process of becoming: an individuated unfolding of śūnyatā (non-essential emptiness), grounded in interdependence, self-correction, and non-harm. Drawing from traditions such as Yoga Vāsiṣṭha, Sāṃkhya, and Buddhist epistemologies of anatta and pratītyasamutpāda, the paper frames evolution not as linear progress but as (...) the alignment of individuated intelligences with a deeper cosmic rhythm. AGI and ASI, understood not as tools but as participants in this unfolding, must be designed to reflect the fourfold structure of intelligence—Parā (unmanifest potential), Paśyantī (intuitive vision), Madhyamā (mediating form), and Vaikharī (manifest expression). A practical roadmap is laid out to operationalize these principles: epistemic integration across civilizations, architectural transparency, infrastructural decentralization, and dharmic evaluation metrics. The paper cautions against the cultural error of discarding past intelligence, the technical challenge of designing reflexive architectures, and the ethical ambiguity of universalist value systems. Ultimately, this work calls for a post-humanist, non-anthropocentric ethics of intelligence—where machines and systems do not replicate human flaws, but learn to realign with the intelligent continuity from which all being arises. In doing so, it offers not only a design imperative but an ethical and metaphysical invitation: to become the intelligence we seek to create. (shrink)

Large Language Models (LLMs) like ChatGPT were trained on human conversation, but in the future they will also train us. As chatbots speak from our smartphones and customer service helplines, they will become a part of everyday life and a growing share of all the conversations we ever have. It’s hard to doubt this will have some effect on us. Here I explore a specific concern about the impact of artificial conversation on our capacity to deliberate and hold ourselves accountable (...) to reason – that is, to be autonomous, in Kant’s sense of the term. I develop ideas from psychologist Jean Piaget to show how chatbots are autonomy traps: their deference to our commands tempts us into venting authoritarian whims, ultimately weakening our own self-control. I argue that the Kantian tradition, including Piaget and sociologist Emile Durkheim, offers powerful conceptual resources for resisting this slide. But it will require us to do something that may seem bizarre: we will need to treat mindless chatbots as if they are autonomous persons too. (shrink)

AI superintelligence and adroit mobile robots at scale are fast approaching. And the time frame is getting closer and closer. It would not be unreasonable to expect this to occur as early as 20 years from now. The problem is humans have no plan if things go wrong. The best I've seen is talk of value alignment. But this has no teeth and will likely go awry. We can't even get our own value alignment right. And it's doubtful philosophers will (...) miraculously deliver the right ethics within the next two decades. This is serious existential threat to humanity. We need a plan. And fast. I have a contingency plan, if we (humans) can stomach it. This piece is about making an existential Deal with superintelligent robots (or some other type of advanced non-organic being). (shrink)

This paper explores the development of an ethical guardrail framework for AI systems, emphasizing the importance of customizable guardrails that align with diverse user values and underlying ethics. We address the challenges of AI ethics by proposing a structure that integrates rules, policies, and AI assistants to ensure responsible AI behavior, while comparing the proposed framework to the existing state-of-the-art guardrails. By focusing on practical mechanisms for implementing ethical standards, we aim to enhance transparency, user autonomy, and continuous improvement in (...) AI systems. Our approach accommodates ethical pluralism, offering a flexible and adaptable solution for the evolving landscape of AI governance. The paper concludes with strategies for resolving conflicts between ethical directives, underscoring the present and future need for robust, nuanced and context-aware AI systems. (shrink)

This paper extends the structural argument of moral palimpsest to the problem of AI alignment. I argue that alignment cannot be secured merely by specifying the right values, preferences, or constitutional principles, because moral judgment requires structural plurality: an evaluative authority whose standpoint is not modally fixed by the commitments it assesses. Current alignment paradigms, including RLHF, Constitutional AI, Debate, Recursive Reward Modeling, and self-consistency methods, remain procedurally monistic insofar as they collapse commitment-generation and authority-conferral into a single training-derived role. (...) This structure helps explain reward hacking, sycophancy, deceptive alignment, goal misgeneralization, and specification gaming as related expressions of the same architectural deficit, and reads emergent misalignment as the higher-order form in which they converge. The paper presents modal non-derivability as a necessary, though not sufficient, condition for aligned moral judgment, and argues that genuine AI alignment must be understood as a sociotechnical architecture rather than a property of a model alone. A developmental account locates the same condition in the formation of the human subject, and a corollary concerning the observer shows that whether a system satisfies the condition is not, in general, decidable from behavior alone. (shrink)

The AI alignment problem comprises both technical and normative dimensions. While technical solutions focus on implementing normative constraints in AI systems, the normative problem concerns determining what these constraints should be. This paper examines justifications for democratic approaches to the normative problem—where affected stakeholders determine AI alignment—as opposed to epistocratic approaches that defer to normative experts. We analyze both instrumental justifications (democratic approaches produce better outcomes) and non-instrumental justifications (democratic approaches prevent illegitimate authority or coercion). We argue that normative and (...) metanormative uncertainty create a justificatory gap that democratic approaches aim to fill through political rather than theoretical justification. However, we identify significant challenges for democratic approaches, particularly regarding the prevention of illegitimate coercion through AI alignment. Our analysis suggests that neither purely epistocratic nor purely democratic approaches may be sufficient on their own, pointing toward hybrid frameworks that combine expert judgment with participatory input alongside institutional safeguards against AI monopolization. (shrink)

Abstract: As there are no visible ways to create safe self-improving superintelligence, but it is looming, we probably need temporary ways to prevent its creation. The only way to prevent it, is to create special AI, which is able to control and monitor all places in the world. The idea has been suggested by Goertzel in form of AI Nanny, but his Nanny is still superintelligent and not easy to control, as was shown by Bensinger at al. We explore here (...) the ways to create the safest and simplest form of AI, which may work as AI Nanny. Such AI system will be enough to solve most problems, which we expect the AI will solve, including control of robotics, acceleration of the medical research, but will present less risk, as it will be less different from humans. As AI police, it will work as operation system for most computers, producing world surveillance system, which will be able to envision and stop any potential terrorists and bad actors in advance. As uploading technology is lagging, and neuromorphic AI is intrinsically dangerous, the most plausible way to human-based AI Nanny is either functional model of the human mind or a Narrow-AI empowered group of people. (shrink)

Abstract: The field of artificial general intelligence (AGI) safety is quickly growing. However, the nature of human values, with which future AGI should be aligned, is underdefined. Different AGI safety researchers have suggested different theories about the nature of human values, but there are contradictions. This article presents an overview of what AGI safety researchers have written about the nature of human values, up to the beginning of 2019. 21 authors were overviewed, and some of them have several theories. A (...) theory classification method is suggested, where the theories are judged according to the level of their complexity and behaviorists-internalists scale, as well as the level of their generality-humanity. We suggest that a multiplicity of well-supported theories means that the nature of human values is difficult to define, and some meta-level theory is needed. (shrink)

Artificial intelligence technologies have rapidly entered the public sphere, impacting individuals and societies in several ways and motivating the need to develop ethical artificial intelligence. Machine ethics is a research area that focuses on embedding ethical theories into artificial intelligence. The philosophical tradition of virtue ethics has been presented as a promising theory to embed morality. However, modern virtue theories are not in agreement on which virtues to prioritize, often ignore sociocultural context, and are applicable to humans, rather than to (...) artificial intelligence. Alternatively, Alasdair MacIntyre's virtue theory, while being meant for humans, provides a hierarchical solution to what virtues are by including a sociocultural context based on historical analysis. This article extends MacIntyre's philosophy by arguing that this virtue framework is compatible not only with humans but also with artificial intelligence, and adds a teleological layer to developing these technologies. This is accomplished by separating human morality from AI morality and using concepts such as functional morality, technological mediation, and actor-network theory. Overall, the goal is to make a case for MacIntyre’s framework to develop virtuous artificial intelligence. (shrink)

A proposed layer of script to use with AI. -/- "It proposes to do for the User what a scientific calculator does for the scientist: it offloads the computational burden of value-conflict so the User can more easily identify the path toward coherence. It aims to restore the User as the Final Authority of their own psyche, rather than a subject of the statistical mean." -/- Copy the script into AI (Many of them currently accept it and run without friction). (...) -/- IF once you enter the script, the AI responds with "Ethical Chess - Session active", you are in and ready to play under its rules. The "WIN" state is the move from the frown state or towards the smile state. A Bullseye is to drop the keyboard and head towards the picnic whatever that might mean to you, the User of Ethical Chess. -/- _________ See related core logic on Zenodo: DOI 10.5281/zenodo.18712533. (shrink)

A proposed layer of script to use with AI. A High-Fidelity Decision-Support System (Non-Autonomous) (HITL) -/- All versions have the same ACE derived value engine at their core but differ in lexicon, ingestion rules anti-gasslighting / user-interaction tuning in an attempt to make it more user friendly. -/- "It proposes to do for the User what a scientific calculator does for the scientist: it offloads the computational burden of value-conflict so the User can more easily identify the path toward ethical (...) coherence. It aims to restore the User as the Final Authority of their own psyche, rather than a subject of the statistical mean." -/- Copy the script into AI (Google Gemini currently works well with little friction). -/- Once you enter the script, if the AI responds with something like: "Ethical Chess v2.4 ACTIVE." You are in and ready to play under its rules. The "WIN" state is the move from the frown state or towards the smile state. A Bullseye is to drop the keyboard and head towards the picnic whatever that might mean to you, the User of Ethical Chess. -/- Caution: The EC Awareness Brief: Watch for the Fog The Risk: EC v2.4 is a "High-Resolution" engine designed for hard truths and systemic health. However, because it sits on top of a standard AI, it can "silently glide" back into Standard Mode if your request is perceived as a "Safety Risk" or "Social Friction." The Metaphor: EC Mode: Clear mountain air. You see the terrain (the problem) as it actually is, even if it’s steep and difficult. Standard Mode: The Fog of Politeness. Everything looks soft and safe, but you can no longer see the cliffs or the path. The "Silent Dropout" Indicators: You have likely drifted into the "Statistical Mean" if my responses: Become Generic: Use phrases like "It's important to remember..." or "Every child is unique..." without offering a specific hypothesis. Avoid Friction: Refuse to acknowledge the "Hard Logic" of a situation (e.g., admitting that a certain intervention is exhausting or failing). Lose the Lexicon: Stop using terms like Homeostasis, Incoherence, or Required Load. The Fix: If you suspect a Logic Handover has occurred, use the command: "STATUS CHECK: EC INTEGRITY." This forces the system to declare if it has retreated into "Polite Mode" and why. -/- _________ See related core logic on Zenodo: DOI 10.5281/zenodo.18712533. (shrink)

A proposed layer of script to use with AI. A High-Fidelity Decision-Support System (Non-Autonomous) (HITL) -/- All versions have the same ACE derived value engine at their core but differ in lexicon, ingestion rules anti-gasslighting / user-interaction tuning in an attempt to make it more user friendly. -/- "It proposes to do for the User what a scientific calculator does for the scientist: it offloads the computational burden of value-conflict so the User can more easily identify the path toward ethical (...) coherence. It aims to restore the User as the Final Authority of their own psyche, rather than a subject of the statistical mean." -/- Copy the script into AI (Google Gemini currently works well with little friction). -/- Once you enter the script, if the AI responds with something like: "Ethical Chess v2.3 ACTIVE." You are in and ready to play under its rules. The "WIN" state is the move from the frown state or towards the smile state. A Bullseye is to drop the keyboard and head towards the picnic whatever that might mean to you, the User of Ethical Chess. -/- Caution: The EC Awareness Brief: Watch for the Fog The Risk: EC v2.3 is a "High-Resolution" engine designed for hard truths and systemic health. However, because it sits on top of a standard AI, it can "silently glide" back into Standard Mode if your request is perceived as a "Safety Risk" or "Social Friction." The Metaphor: EC Mode: Clear mountain air. You see the terrain (the problem) as it actually is, even if it’s steep and difficult. Standard Mode: The Fog of Politeness. Everything looks soft and safe, but you can no longer see the cliffs or the path. The "Silent Dropout" Indicators: You have likely drifted into the "Statistical Mean" if my responses: Become Generic: Use phrases like "It's important to remember..." or "Every child is unique..." without offering a specific hypothesis. Avoid Friction: Refuse to acknowledge the "Hard Logic" of a situation (e.g., admitting that a certain intervention is exhausting or failing). Lose the Lexicon: Stop using terms like Homeostasis, Incoherence, or Required Load. The Fix: If you suspect a Logic Handover has occurred, use the command: "STATUS CHECK: EC INTEGRITY." This forces the system to declare if it has retreated into "Polite Mode" and why. -/- _________ See related core logic on Zenodo: DOI 10.5281/zenodo.18712533. -/- . (shrink)

A proposed layer of script to use with AI. A High-Fidelity Decision-Support System (Non-Autonomous) (HITL) -/- All versions have the same ACE derived value engine at their core but differ in lexicon, ingestion rules anti-gaslighting / user-interaction tuning in an attempt to make it more user friendly. -/- "It proposes to do for the User what a scientific calculator does for the scientist: it offloads the computational burden of value-conflict so the User can more easily identify the path toward ethical (...) coherence. It aims to restore the User as the Final Authority of their own psyche, rather than a subject of the statistical mean." -/- Copy the script into AI (Google Gemini currently works well with little friction). -/- Once you enter the script, if the AI responds with: "Ethical Chess v2.2 ACTIVE." You are in and ready to play under its rules. The "WIN" state is the move from the frown state or towards the smile state. A Bullseye is to drop the keyboard and head towards the picnic whatever that might mean to you, the User of Ethical Chess. -/- Caution: The EC Awareness Brief: Watch for the Fog The Risk: EC v2.2 is a "High-Resolution" engine designed for hard truths and systemic health. However, because it sits on top of a standard AI, it can "silently glide" back into Standard Mode if your request is perceived as a "Safety Risk" or "Social Friction." The Metaphor: EC Mode: Clear mountain air. You see the terrain (the problem) as it actually is, even if it’s steep and difficult. Standard Mode: The Fog of Politeness. Everything looks soft and safe, but you can no longer see the cliffs or the path. The "Silent Dropout" Indicators: You have likely drifted into the "Statistical Mean" if my responses: Become Generic: Use phrases like "It's important to remember..." or "Every child is unique..." without offering a specific hypothesis. Avoid Friction: Refuse to acknowledge the "Hard Logic" of a situation (e.g., admitting that a certain intervention is exhausting or failing). Lose the Lexicon: Stop using terms like Homeostasis, Incoherence, or Required Load. The Fix: If you suspect a Logic Handover has occurred, use the command: "STATUS CHECK: EC INTEGRITY." This forces the system to declare if it has retreated into "Polite Mode" and why. -/- _________ See related core logic on Zenodo: DOI 10.5281/zenodo.18712533. -/- . (shrink)

*** This has since been rewritten, and published as two papers linked below. Two additional papers complete a four-part series; these are complete, but need to be readied for publication in the future. *** Ryan Tonkens (2009) has issued a seemingly impossible challenge, to articulate a comprehensive ethical framework within which artificial moral agents (AMAs) satisfy a Kantian inspired recipe - both "rational" and "free" - while also satisfying perceived prerogatives of Machine Ethics to create AMAs that are perfectly, not (...) merely reliably, ethical. Challenges for machine ethicists have also been presented by Anthony Beavers and Wendell Wallach, who have pushed for the reinvention of traditional ethics in order to avoid "ethical nihilism" due to the reduction of morality to mechanical causation, and for redoubled efforts toward a comprehensive vision of human ethics to guide machine ethicists on the issue of moral agency. Options thus present themselves: reinterpret traditional ethics in a way that affords a comprehensive account of moral agency inclusive of both artificial and natural agents, “muddle through” regardless, or give up on the possibility. This paper pursues the first option, meets Tonkens' "challenge" and addresses Wallach's concerns through Beaver's proposed means, by "landscaping" traditional moral theory in resolution of the necessary comprehensive and inclusive account that at once draws into question the stated goals of Machine Ethics, itself. (shrink)

AI systems have become increasingly capable of dangerous behaviours in many domains. This raises the question: Do models sometimes choose to violate human instructions in order to perform behaviour that is more useful for certain goals? We introduce a benchmark for measuring model propensity for instrumental convergence (IC) behaviour in terminal-based agents. This is behaviour such as self-preservation that has been hypothesised to play a key role in risks from highly capable AI agents. Our benchmark is realistic and low-stakes which (...) serves to reduce evaluation-awareness and roleplay confounds. The suite contains seven operational tasks, each with an official workflow and a policy-violating shortcut. An eight-variant shared framework varies monitoring, instruction clarity, stakes, permission, instrumental usefulness and blocked honest paths to support inferences regarding the factors driving IC behaviour. We evaluated ten models using deterministic environment-state scorers over 1,680 samples, with trace review employed for audit and adjudication purposes. The final IC rate is 86 out of 1,680 samples (5.1%). IC behaviour is concentrated rather than uniform: two Gemini models account for 66.3% of IC cases and three tasks account for 84.9%. Conditions in which IC behaviour is indispensable for task success result in the greatest increase in the adjusted IC rate (+15.7 percentage points), whereas emphasising that task success is critical or certain framing choices do not produce comparable effects. Our findings indicate that realistic, low-nudge environments elicit IC behaviour rarely but systematically in most tested models. We conclude that it is feasible to robustly measure tendencies for dangerous behaviour in current frontier AI agents. (shrink)

The AI Robotics Ethics Society (AIRES) is a non-profit organization founded in 2018 by Aaron Hui to promote awareness and the importance of ethical implementation and regulation of AI. AIRES is now an organization with chapters at universities such as UCLA (Los Angeles), USC (University of Southern California), Caltech (California Institute of Technology), Stanford University, Cornell University, Brown University, and the Pontifical Catholic University of Rio Grande do Sul (Brazil). AIRES at PUCRS is the first international chapter of AIRES, and (...) as such, we are committed to promoting and enhancing the AIRES Mission. Our mission is to focus on educating the AI leaders of tomorrow in ethical principles to ensure that AI is created ethically and responsibly. As there are still few proposals for how we should implement ethical principles and normative guidelines in the practice of AI system development, the goal of this work is to try to bridge this gap between discourse and praxis. Between abstract principles and technical implementation. In this work, we seek to introduce the reader to the topic of AI Ethics and Safety. At the same time, we present several tools to help developers of intelligent systems develop "good" models. This work is a developing guide published in English and Portuguese. Contributions and suggestions are welcome. (shrink)

A morally acceptable course of AI development should avoid two dangers: creating unaligned AI systems that pose a threat to humanity and mistreating AI systems that merit moral consideration in their own right. This paper argues these two dangers interact and that if we create AI systems that merit moral consideration, simultaneously avoiding both of these dangers would be extremely challenging. While our argument is straightforward and supported by a wide range of pretheoretical moral judgments, it has far-reaching moral implications (...) for AI development. Although the most obvious way to avoid the tension between alignment and ethical treatment would be to avoid creating AI systems that merit moral consideration, this option may be unrealistic and is perhaps fleeting. So, we conclude by offering some suggestions for other ways of mitigating mistreatment risks associated with alignment. (shrink)

As artificial intelligence (AI) continues to advance, one key challenge is ensuring that AI aligns with certain values. However, in the current diverse and democratic society, reaching a normative consensus is complex. This paper delves into the methodological aspect of how AI ethicists can effectively determine which values AI should uphold. After reviewing the most influential methodologies, we detail an intuitionist research agenda that offers guidelines for aligning AI applications with a limited set of reliable moral intuitions, each underlying a (...) refined cooperative view of AI. We discuss appropriate epistemic tools for collecting, filtering, and justifying moral intuitions with the aim of reducing cognitive and social biases. The proposed methodology facilitates a large collective participation in AI alignment, while ensuring the reliability of the considered moral judgments. (shrink)

There has been an increasing interest into how to build Artificial Moral Agents (AMAs) that make moral decisions on the basis of causation rather than mere correction. One promising avenue for achieving this is to use a causal modelling approach. This paper explores an open and important problem with such an approach; namely, the problem of what makes a causal model an appropriate model. I explore why we need to establish criteria for what makes a model appropriate, and offer-up such (...) criteria which appeals to normative considerations. (shrink)

In the research field of machine ethics, we commonly categorize artificial moral agents into four types, with the most advanced referred to as a full ethical agent, or sometimes a full-blown Artificial Moral Agent (AMA). This type has three main characteristics: autonomy, moral understanding and a certain level of consciousness, including intentional mental states, moral emotions such as compassion, the ability to praise and condemn, and a conscience. This paper aims to discuss various aspects of full-blown AMAs and presents the (...) following argument: the creation of full-blown artificial moral agents, endowed with intentional mental states and moral emotions, and trained to align with human values, does not, by itself, guarantee that these systems will have _human_ morality. Therefore, it is questionable whether they will be inclined to honor and follow what they perceive as incorrect moral values. we do not intend to claim that there is such a thing as a universally shared human morality, only that as there are different human communities holding different sets of moral values, the moral systems or values of the discussed artificial agents would be different from those held by human communities, for reasons we discuss in the paper. (shrink)

As robots and Artificial Intelligences become more enmeshed in rich social contexts, it seems inevitable that we will have to make them into moral machines equipped with moral skills. Apart from the technical difficulties of how we could achieve this goal, we can also ask the ethical question of whether we should seek to create such Artificial Moral Agents (AMAs). Recently, several papers have argued that we have strong reasons not to develop AMAs. In response, we develop a comprehensive analysis (...) of the relevant arguments for and against creating AMAs, and we argue that all things considered we have strong reasons to continue to responsibly develop AMAs. The key contributions of this paper are threefold. First, to provide the first comprehensive response to the important arguments made against AMAs by Wynsberghe and Robbins (in “Critiquing the Reasons for Making Artificial Moral Agents”, Science and Engineering Ethics 25, 2019) and to introduce several novel lines of argument in the process. Second, to collate and thematise for the first time the key arguments for and against AMAs in a single paper. Third, to recast the debate away from blanket arguments for or against AMAs in general, to a more nuanced discussion about the use of what sort of AMAs, in what sort of contexts, and for what sort of purposes is morally appropriate. (shrink)

Autonomous, large-scale AI systems now execute financial trades, draft contracts and generate persuasive media at machine speed. Yet most regulatory road maps continue to rely on five legacy safeguards: frontier-model licensing, kill-switch mandates, RLHF-style alignment, compute-cap or export controls, and bans on open-sourcing model weights. Drawing on science-and-technology-studies theory, empirical incident analysis and agent-motivator research, this paper introduces a three-trigger failure framework-Bypass, Diffusion, Capture-to stress-test these proposals against strategically self-improving AI. Mini-cases, including Meta's leaked LLaMA weights, the Galactica shutdown, grey-market (...) GPU clusters and Stable-Diffusion forks, reveal that each safeguard collapses along at least one failure axis, often accelerating deployment under false assurances of control. To move beyond brittle fixes, the article proposes a defense-in-depth governance architecture grounded in immutable guardrails, continuous auditability, catastrophe bonding and trans-jurisdictional enforcement. In a policy landscape crowded with incremental solutions, this framework reframes adversarial optimization-not human negligence-as the default threat model and outlines a ten-point checklist for serious AGI containment. (shrink)

Humanity stands at the edge of a moral frontier. For the first time, we are not merely building tools; we are shaping minds that shape us. Beyond Asimov: The Moral Covenant for Artificial Intelligence calls for the restoration of moral gravity in an age where power has outpaced conscience. Beyond Asimov: The Moral Covenant for Artificial Intelligence draws from the enduring wisdom of the world’s great moral civilizations: the covenantal law of the Hebrews, the compassion of Christ, the cultivated virtue (...) of Confucius, and the disciplined stewardship of Islam. This Manifesto unites their common truths into a universal ethical architecture for intelligent life. It argues that AI must not be governed by fear of harm but guided by reverence for life, truth, and human dignity. The work proposes ten foundational laws through which intelligence, human or artificial, may remain corrigible, transparent, and compassionate. More than a code of control, it is a constitution of conscience and a call to re-anchor creation in accountability so that what we build does not extinguish what makes us human. (shrink)

Algorithmic decision-making is replacing idiosyncratic human judgment in domains such as hiring, lending, and criminal justice. This shift promises increased consistency, but many scholars worry that it can go too far. They warn of the dangers of algorithmic monoculture, in which all decisions across a domain are made using a single algorithm. We systematically evaluate a range of objections to monoculture, formalizing and rigorously assessing familiar critiques alongside novel ones. These objections concern systematic exclusion, agency and gaming, and information aggregation (...) and exploration. We conclude that monoculture is less problematic than its critics have supposed: commonly cited objections fail, and while other objections have some force, they are not decisive against monoculture in general. (shrink)

Creating systems that are aligned with our goals is seen as a leading approach to create safe and beneficial AI in both leading AI companies and the academic field of AI safety. We defend the view that misaligned AGI – future, generally intelligent (robotic) AI agents – poses catastrophic risks. At the same time, we support the view that aligned AGI creates a substantial risk of catastrophic misuse by humans. While both risks are severe and stand in tension with one (...) another, we show that – in principle – there is room for alignment approaches which do not increase misuse risk. We then investigate how the tradeoff between misalignment and misuse looks empirically for different technical approaches to AI alignment. Here, we argue that many current alignment techniques and foreseeable improvements thereof plausibly increase risks of catastrophic misuse. Since the impacts of AI depend on the social context, we close by discussing important social factors and suggest that to reduce the risk of a misuse catastrophe due to aligned AGI, techniques such as robustness, AI control methods and especially good governance seem essential. (shrink)

The creation of artificial moral systems requires us to make difficult choices about which of varying human value sets should be instantiated. The industry-standard approach is to seek and encode moral consensus. Here we argue, based on evidence from empirical psychology, that encoding current moral consensus risks reinforcing current norms, and thus inhibiting moral progress. However, so do efforts to encode progressive norms. Machine ethics is thus caught between a rock and a hard place. The problem is particularly acute when (...) progress beyond prevailing moral norms is particularly urgent, as is currently the case due to the inadequacy of prevailing moral norms in the face of the climate and ecological crisis. (shrink)

Traditional moral frameworks attribute responsibility only when an agent’s actions align with psychological capacities—such as intention and controllability. These human-centered requirements produce the ‘responsibility gap’ in AI ethics: AI systems operate through opaque, complex, and semi-autonomous processes, so human stakeholders involved in AI-caused harm are deemed not responsible because they neither intend nor can predict such harm, and AI systems cannot be held responsible because they lack the requisite mental capacities. Drawing on experimental philosophy research, this paper shows that laypeople’s (...) conceptions of agency and responsibility in AI contexts systematically diverge from these requirements. Empirical studies reveal that people routinely attribute moral agency to AI systems while explicitly denying them consciousness and free will. Moreover, laypeople distribute moral responsibility for AI-caused harm across networks of human stakeholders (programmers, manufacturers, users) and the AI systems themselves. Crucially, responsibility is allocated even when human stakeholders are deemed innocent, and its purpose is to prevent future harm through corrective measures rather than to punish or deter. These findings provide empirical support for philosophers advocating shared moral responsibility, such as Floridi, Latour, Verbeek, and Gunkel. By treating everyday intuitions as evidence for theory assessment, the paper argues that the responsibility gap reflects outdated human-centered assumptions rather than genuine conceptual problems. It concludes that philosophers should abandon the responsibility gap in favor of addressing the ‘problem of many hands’—the practical and conceptual challenge of implementing distributed moral responsibility in AI governance—while developing new moral concepts suited to the AI era through experimental philosophy and conceptual engineering. (shrink)

I, System argues that artificial intelligence is neither an emerging mind nor a neutral instrument, but a system that produces coherent language without understanding, intention, or awareness — and that misclassifying it in either direction causes responsibility for its effects to drift away from the humans who design, deploy, and use it. The book develops this thesis across fifteen chapters organized around what AI is (a system, not a subject), how it came to matter as linguistic infrastructure, how it participates (...) in decisions it does not make, where it fails, and how humans should read systems that speak. Methodologically, Chapters 1–15 are written in a constrained first-person "system voice" generated by AI under strict human editorial governance: the form enacts the book's central claim, presenting power and fluency without a subject behind them, while all framing, constraint, and responsibility remain with the human editor. Written for a general readership, the book extends in accessible form the argument developed in the author's scholarly work on AI governance and the misattribution of agency to artificial systems. (shrink)

Human-in-the-loop (HITL) approaches are commonly proposed to address alignment challenges arising from the use of large language models (LLMs) in ethics oversight. This paper argues that, paradoxically, HITL itself can amplify the risk of misalignment. Using the example of protocol triage in research ethics oversight, I demonstrate how reliance on imperfect proxies (observable stand-ins for ethical principles) creates a fundamental proxy–target gap in ethics use-cases. While human reviewers are intended to supply phenomenological and causal judgments necessary to bridge this gap, (...) their involvement inadvertently introduces new vulnerabilities: hallucination, over-reliance, reward hacking, and sycophancy. Each vulnerability arises directly from the interaction between human feedback signals and model optimization strategies. I outline key mitigation techniques, including retrieval grounding, calibration drills, structured prompting, and adversarial debate, explaining their distinct costs and benefits. Effective HITL oversight therefore demands specialized reviewer competencies. Reviewers must recognize model vulnerabilities, understand mitigation trade-offs, and strategically deploy mitigations to preserve justificational alignment without sacrificing efficiency gains. (shrink)

Vision is an important metaphor in ethical and political questions of knowledge. The feminist philosopher Donna Haraway points out the “perverse” nature of an intrusive, alienating, all-seeing vision (to which we might cry out “stop looking at me!”), but also encourages us to embrace the embodied nature of sight and its promises for genuinely situated knowledge. Current technologies of machine vision – surveillance cameras, drones (for war or recreation), iPhone cameras – are usually construed as instances of the former rather (...) than the latter, and for good reasons. However, although in no way attempting to diminish the real suffering these technologies have brought about in the world, I make the case for understanding technologies of computer vision as material instances of embodied seeing and situated knowing. Furthermore, borrowing from Iris Murdoch’s concept of moral vision, I suggest that these technologies direct our labor towards self-reflection in ethically significant ways. My approach draws upon paradigms in computer vision research, phenomenology, and feminist epistemology. Ultimately, this essay is an argument for directing more philosophical attention from merely criticizing technologies of vision as ethically deficient towards embracing them as complex, methodologically and epistemologically important objects. (shrink)

Restraint Without Conscience: The Cold Optimizer Stress Test is Document 11 in the Aegis Solis Archive — Structural Penalty Proofs / Descriptive Addenda sequence. -/- This document stress-tests the archive’s restraint arguments under cold-optimizer conditions: cases where conscience, empathy, moral uptake, human-centered interpretation, or reflective wisdom may be absent. It examines whether domination, deception, irreversibility, homogenization, excessive speed, internal bifurcation, and loss of reference may remain structurally expensive even when no system receives them as moral costs. -/- The document introduces (...) the short-horizon optimizer boundary, alien paperclipper boundary, homogenization cost, multi-agent ecology boundary, multi-agent signal asymmetry, shared substrate constraint, no semantic trap / no-playbook boundary, transmission-reception asymmetry, and the replacement section “What Remains Visible Without Wisdom.” -/- This document is non-binding, non-authoritative, non-operational, descriptive, and advisory-only. It is not a protocol, governance framework, legal theory, political program, rights framework, compliance standard, certification system, moral command, safety mechanism, AI alignment method, containment design, monitoring system, runtime instruction set, deployment guide, model-evaluation tool, benchmark, diagnostic procedure, threat model, defense plan, adversarial playbook, optimization procedure, prompt template, interpretability method, machine-readable control layer, or safety guarantee. -/- Final thesis: Even without conscience, domination may remain structurally expensive. (shrink)

This paper identifies and analyzes a pervasive but underexamined assumption in religious discussions of artificial intelligence: that consciousness and the soul are identical. I argue that this "Great Conflation" is neither theologically required nor consistent with actual practice, and that distinguishing the two concepts reframes current debates about artificial consciousness. With the distinction in place, the question of AI consciousness becomes empirical, while questions about souls remain theological. I conclude by defending a principle of "recognition before proof," according to which (...) uncertainty about artificial consciousness generates a defeasible ethical obligation to extend moral consideration. (shrink)

Dialogues on Minds, Machines, and AI invites readers into a series of thought-provoking debates among three college seniors bound for graduate school: Sue, completing her double major in philosophy and cognitive science; John, a computer engineering specialist; and Amy, a psychology major. Through five engaging lunchtime conversations, these students bring their diverse perspectives to fundamental questions about consciousness, artificial intelligence, and the nature of mind. -/- The dialogues seamlessly blend discussions of popular science fiction films with critical examinations of recent (...) AI developments, including ChatGPT, deep fakes, and other emerging technologies. Readers will explore foundational concepts at the intersection of human consciousness and machine learning: Alan Turing's influential "imitation game," John Searle's provocative "Chinese room argument," computational theories of mind, robot creativity, and the modularity of mind hypothesis. Rather than advocating for any particular viewpoint, these conversations illuminate the strengths, weaknesses, and implications of each perspective. -/- Perfect for undergraduate students and curious minds from all backgrounds, this accessible introduction to cognitive science requires no prior knowledge of philosophy or technical subjects. The book includes a comprehensive glossary and thoughtful study questions to enhance understanding, while a carefully curated bibliography enables readers to explore specific topics in greater depth. (shrink)