The Principle of Analogy. ABSTRACT. Sceptics question whether ‘distinctively human’ predicates such as ‘just’, ‘loving’ and ‘powerful’ can intelligibly be attributed to a divine being. If not, then a vicious form of agnosticism seems to threaten orthodox theism. Especially if one assumes a broadly empiricist semantics the challenge, whether formulated in terms of a univocal or an equivocal understanding of predicates, seems to generate intractable philosophical problems. Aquinas’ theory of analogical predication, understood either in terms of ‘analogy duorum ad (...) tertium’ or in terms of ‘analogy unus ad alterum’, is an influential response to this sceptical challenge. Difficulties in each understanding are explored and it is suggested that a more fruitful framework for understanding theistic language is to be found in late 20th century nativism of Fodor and Quine. (shrink)

This essay undertakes a critical examination of Kevin Vallier’s Principle of Convergent Restraint (PCR) within the framework of public reason liberalism. The article begins by scrutinizing the PCR’s inaugural provision: intelligibility, advancing the argument that Vallier’s explication of intelligibility contradicts the requisites of public justification in liberal democracies. It argues that Vallier’s predilection for intelligibility over accessibility runs afoul of the fundamental principles underpinning public reason and pluralistic liberalism. It then provides an evaluation of the second (...) provision, narrow restraint, asserting that a proper comprehension of PRL allows for the accommodation of diverse justificatory reasons without compromising the emergence of overlapping, comprehensive doctrines. The final section addresses the PCR’s third provision, proposal restraint, rejecting Vallier’s advocacy for placing justificatory restraints solely on public officials. The essay contends that the demarcation between citizens and public officials is artificial and posits that effective restraints must be universally applicable, considering the dynamic interplay between public deliberation, public opinion, and legislative proposals. (shrink)

This is a defense of John Stuart Mill’s proof of the principle of utility in the fourth chapter of his Utilitarianism. The proof is notorious as a fallacious attempt by a prominent philosopher, who ought not to have made the elementary mistakes he is supposed to have made. This book shows that he did not. The aim is not to glorify utilitarianism, in a full sweep, as the best normative ethical theory, or even to vindicate, on a more specific (...) level, Mill’s universalistic ethical hedonism as the best form of utilitarianism. The book is concerned only with Mill’s utilitarianism, and primarily with his proof of the principle of utility. The purpose is to show that Mill proceeds intelligibly and systematically in pursuing a well-defined project in the fourth chapter of Utilitarianism, and that he successfully defends what he sets out to establish in his proof of the principle of utility. (shrink)

We present a theory of cooperative-competitive intelligence (CCI), its measures, research program, and applications that stem from it. Within the framework of this theory, satisficing sub-optimal behavior is any behavior that does not promote a decrease in the prospective control of the functional action diversity/unpredictability (D/U) potential of the agent or team. This potential is defined as the entropy measure in multiple, context-dependent dimensions. We define the satisficing interval of behaviors as CCI. In order to manifest itself at individual or (...) team level, this capacity harnesses properties such as degeneracy, pleiotropy (pluri-potentiality), synergies, and metastability. Intelligence is embodied because intelligent behavior is deeply dependent on body functionalities, defined as entropy measures. We base our theory on three principles: (a) relativity of functional entropy/ information in agent (team)-environment systems, (b) tendency toward the satisficing level of D/U potential, and (c) tendency toward the non-decreasing D/U potential. The conjunction of these three principles provides existence of sub-optimal behaviors associated with CCI. First, we deal with the problem of how to reduce multidimensional behavior to a concept that accounts for the vast set of scenarios in which CCI is manifested. Secondly, we define and discuss the three interacting principles that underpin CCI behavior as well as providing an outline for a future CCI research program supported by agent￾based modeling and empirical research. Finally, we provide some preliminary practical issues that stem from the theory. (shrink)

Some forms of defining PNC in Aristotle’s works are as follows: a) Everything must be either affirmed or denied (φάναι ἢ ἀποφάναι). (Met., B, 996b28-29) or: it will not be possible to assert and deny the same thing truly at the same time. (Met., Γ, 1008a36-b1) In other words, ‘contradictory statements (ἀντικειμένας φάσεις) are not at the same time true. (Met., Γ, 1011b13-14) Also, ‘It is impossible that contradictories (ἀντίφασιν) should be at the same time true of the same thing.’ (...) (Met., Γ, 1011b15-16) Also, ‘Opposite statements (ἀντικειμένας φάσεις) can never be true of the same subjects.’ (Met., K, 1062a33-34; 1063b15-17) Also, ‘Of all affirmation or negation one is impossible. (PsA., A, 11, 77a22) b) A thing cannot at the same time be and not be. (Met., B, 996b30-31; Γ, 1006a3-5) This can also be extended to many other similar pairs of opposites: ‘The same thing cannot at the same time be and not be, or admit any other similar pair of opposites.’ (Met., K, 1061b34-1062a2) Also, ‘It will be possible for the same thing to be and not to be, except in virtue of an ambiguity.’ (Met., Γ, 1006b18-19) This is also asserted in another similar way: it is impossible that it should be at the same time true to say the same thing is a thing and is not a thing.’ (Met., Γ, 1006b33-34) c) ‘The same attribute cannot at the same time belong (ὑπάρχειν) and not belong to the same object in the same respect.’ (Met., Γ, 1005b19-21) d) Those positive and negative propositions are said to be contradictory which have the same subject and predicate. (OI, I, 7, 17a33-35) The opposition between an affirmation and a denial makes contradictories (ἀντίφασεως). (PsA., A, 2, 72a11-14) Based on Aristotle’s definition, ‘An affirmation is opposed to a denial in the sense which I denote by the term ‘contradictory’ (ἀντίφατικως), when, while the subject remains the same, the affirmation is of universal character and the denial is not.’ (OI., I, 7, 17b16-19) 1) Characteristics of PNC a) It is the most certain (Met., Γ, 1005b22-23 and b11) and the most indisputable (Met., Γ, 1006a5-6) of all principles. b) It is impossible: to believe its contrary (Met., Γ, 1005b24-30); to be really in that position (Met., Γ, 1008b11-13); and to defend it. (OI, I, 9, 18b17-19) Nonetheless, Aristotle thinks that many of the writers about nature assert the contrary of PNC and use a language opposite to it. (Met., Γ, 1005b35-1006a3) c) It is the starting point of all the other axioms. (Met., Γ, 1005b32-34) d) It is not hypothetical. (Met., Γ, 1005b13-17) e) Contradictories are extremely opposed to each other. (Met., Γ, 1007a1-4) f) Believing in PNC saves substance and essence and not believing in it makes all attributes accidents and there will be nothing as being essentially something. The reason is that something which essentially is a being cannot avoid being that thing. (Met., Γ, 1007a20-29 and b16-18) g) PNC supports plurality of things because otherwise all things will be one: ‘If all contradictories are true of the same subject at the same time, evidently all things will be one. For the same thing will be a trireme, a wall, and a man, if it is equally possible to affirm and deny anything of anything.’ (Met., Γ, 1007b18-22) In fact, PNC supports difference: ‘For if contradictories can be predicated alike of each subject, one thing will in no wise differ from another; for if it differs, this difference will be something true and peculiar to it.’ (Met., Γ, 1008a25-27) h) To accept truth and falsity, whether in an absolute sense (e.g. A is more true than B; or C is less true than D) entails PNC. (Met., Γ, 1008b2-7 and b31-35; 1009a2-5) In fact, PNC is entailed by accepting true affirmation. (Met., K, 1062b7-11) i) Judging and choosing between at least two things entails PNC: you cannot choose one as better than another without a previous judging that one is A and the other not A. (Met., Γ, 1008b18-24) The same is true about avoiding. (Met., Γ, 1008b24-29) j) PNC guarantees speaking and saying anything intelligible because otherwise e.g. saying ‘yes’ means both yes and no. (Met., Γ, 1008b7-13) k) Contradictories do not accept intermediates that means we must either affirm or deny a predicate on a subject and there is no third option. (Met., Γ, 1011b23-24; Met., I, 1055b1-2; PsA., A, 2, 72a11-14; Met., I, 1057a33-36) l) PNC is applicable also to the future time. (OI., I, 9, 19a28-29) m) PNC is presupposed by the least semantic of words. If we accept that each word has a meaning and, thus, signifies something definite, we cannot accept that it has the contradictory meaning and signies contradictory things and this approves PNC. Thus, Aristotle asks the opponent of PNC to say just one word, a significant word and takes this as the demonstration of PNC because by saying the word e.g. ‘man’ you have already signified man and not-man. (Met., Γ, 1005a11-13 and a18-22; 1006a28-31 and b13-15) Therefore, signification entails PNC: ‘He, then, who says this is and is not denies what he affirms, so that what the word signifies, he says it does not signify; and this is impossible. Therefore, if ‘This is’ signifies something, one cannot truly assert the contradictory.’ (Met., K, 1062a16-20) He says again: ‘If the word signifies something and this can be truly asserted of it, it necessarily is this; and it is not possible that that which is necessary should ever not be: it is not possible therefore to make the opposed assertions truly of the same subject.’ (Met., K, 1062a20-23; cf. Met., K, 1062a24-31) n) At Met., 4, 3, 1005b9-10 (check???) PNC is called as principle of things (ἀρχὰς τοῦ πράγματος). (quoted from B215, 517) . (shrink)

This paper addresses the cultural sustainability of artificial intelligence use through one of its most widely discussed instances: autonomous driving. The introduction of self-driving cars places us in a radically novel moral situation, requiring advance, reflectively endorsed, forced, and iterable choices, with yet uncharted forms of risk imposition. The argument is meant to explore the necessity and possibility of maintaining one of our most fundamental moral-cultural principles in this new context, that of the equal treatment of persons. It is claimed (...) that the implementation of this principle requires central and uniform regulation in autonomous mobility. (shrink)

A lean hylomorphism stands as a metaphysical holy grail. An embarrassing feature of traditional hylomorphic ontologies is prime matter. Prime matter is both so basic that it cannot be examined (in principle) and its engagement with the other hylomorphic elements is far from clear. One particular problem posed by prime matter is how it is to be understood both as a principle of individuation for material substances and as pure potency. I present Thomas Aquinas’s way of squeezing some (...) intelligibility out of prime matter by modeling it on the idea of logical genus. Such a modeling provides insight into understanding prime matter as substratum, as maximally indeterminate, and as ontologically vague. One of the unusual but exciting things that fall out from this analysis of prime matter is the Entirety Thesis: “For any substance x, if x has prime matter then the prime matter of x is the same* as x,” where ‘same*’ is understood as “indeterminately identical.”. (shrink)

The objective of this essay is to provide the beginning of a principled classification of some of the ways space is intelligently used. Studies of planning have typically focused on the temporal ordering of action, leaving as unaddressed questions of where to lay down instruments, ingredients, work-in-progress, and the like. But, in having a body, we are spatially located creatures: we must always be facing some direction, have only certain objects in view, be within reach of certain others. How we (...) manage the spatial arrangement of items around us is not an afterthought: it is an integral part of the way we think, plan, and behave. The proposed classification has three main categories: spatial arrangements that simplify choice; spatial arrangements that simplify perception; and spatial dynamics that simplify internal computation. The data for such a classification is drawn from videos of cooking, assembly and packing, everyday observations in supermarkets, workshops and playrooms, and experimental studies of subjects playing Tetris, the computer game. This study, therefore, focuses on interactive processes in the medium and short term: on how agents set up their workplace for particular tasks, and how they continuously manage that workplace. (shrink)

Legg and Hutter, as well as subsequent authors, considered intelligent agents through the lens of interaction with reward-giving environments, attempting to assign numeric intelligence measures to such agents, with the guiding principle that a more intelligent agent should gain higher rewards from environments in some aggregate sense. In this paper, we consider a related question: rather than measure numeric intelligence of one Legg- Hutter agent, how can we compare the relative intelligence of two Legg-Hutter agents? We propose an elegant (...) answer based on the following insight: we can view Legg-Hutter agents as candidates in an election, whose voters are environments, letting each environment vote (via its rewards) which agent (if either) is more intelligent. This leads to an abstract family of comparators simple enough that we can prove some structural theorems about them. It is an open question whether these structural theorems apply to more practical intelligence measures. (shrink)

The physicist Richard Gott defends the Copernican principle, which claims that when we have no information about our position along a given dimension among a group of observers, we should consider ourselves to be randomly located among those observers in respect to that dimension. First, I apply Copernican reasoning to the distribution of evil in the universe. I then contend that evidence for intelligent extraterrestrial life strengthens four important versions of the argument from evil. I remain neutral regarding whether (...) this result is a reductio of these arguments from evil or the statement of a genuine evidential relationship. (shrink)

Modern digital technologies—from web-based services to Artificial Intelligence (AI) solutions—increasingly affect the daily lives of billions of people. Such innovation brings huge opportunities, but also concerns about design, development, and deployment of digital technologies. This article identifies and discusses five clusters of risk in the international debate about digital ethics: ethics shopping; ethics bluewashing; ethics lobbying; ethics dumping; and ethics shirking.

Artificial Intelligence (AI) is already having a major impact on society. As a result, many organizations have launched a wide range of initiatives to establish ethical principles for the adoption of socially beneficial AI. Unfortunately, the sheer volume of proposed principles threatens to overwhelm and confuse. How might this problem of ‘principle proliferation’ be solved? In this paper, we report the results of a fine-grained analysis of several of the highest-profile sets of ethical principles for AI. We assess whether (...) these principles converge upon a set of agreed-upon principles, or diverge, with significant disagreement over what constitutes ‘ethical AI.’ Our analysis finds a high degree of overlap among the sets of principles we analyze. We then identify an overarching framework consisting of five core principles for ethical AI. Four of them are core principles commonly used in bioethics: beneficence, non-maleficence, autonomy, and justice. On the basis of our comparative analysis, we argue that a new principle is needed in addition: explicability, understood as incorporating both the epistemological sense of intelligibility (as an answer to the question ‘how does it work?’) and in the ethical sense of accountability (as an answer to the question: ‘who is responsible for the way it works?’). In the ensuing discussion, we note the limitations and assess the implications of this ethical framework for future efforts to create laws, rules, technical standards, and best practices for ethical AI in a wide range of contexts. (shrink)

I argue that Leibniz's rejection of the hypothesis of thinking matter on grounds of unintelligibility conflicts with his position on sensible qualities such as color. In the former case, he argues that thought must be a modification of something immaterial because we cannot explain thought in mechanical terms. In the latter case, however, he (rightly) grants that we cannot explain sensible qualities in mechanical terms, that is, cannot explain why a certain complex mechanical quality gives rise to the appearance of (...) a certain sensible quality, even while insisting that sensible qualities are modifications of bodies. I argue that the two cases are analogous in the relevant respects, and that Leibniz's (plausible) position on sensible qualities should have thrown his Principle of Intelligibility into doubt. (shrink)

This paper argues that the Value Sensitive Design (VSD) methodology provides a principled approach to embedding common values in to AI systems both early and throughout the design process. To do so, it draws on an important case study: the evidence and final report of the UK Select Committee on Artificial Intelligence. This empirical investigation shows that the different and often disparate stakeholder groups that are implicated in AI design and use share some common values that can be used to (...) further strengthen design coordination efforts. VSD is shown to be both able to distill these common values as well as provide a framework for stakeholder coordination. (shrink)

Biomarker-based predictive tests for subjectively asymptomatic Alzheimer’s disease (AD) are utilized in research today. Novel applications of artificial intelligence (AI) promise to predict the onset of AD several years in advance without determining biomarker thresholds. Until now, little attention has been paid to the new ethical challenges that AI brings to the early diagnosis in asymptomatic individuals, beyond contributing to research purposes, when we still lack adequate treatment. The aim of this paper is to explore the ethical arguments put forward (...) for AI aided AD prediction in subjectively asymptomatic individuals and their ethical implications. The ethical assessment is based on a systematic literature search. Thematic analysis was conducted inductively of 18 included publications. The ethical framework includes the principles of autonomy, beneficence, non-maleficence, and justice. Reasons for offering predictive tests to asymptomatic individuals are the right to know, a positive balance of the risk-benefit assessment, and the opportunity for future planning. Reasons against are the lack of disease modifying treatment, the accuracy and explicability of AI aided prediction, the right not to know, and threats to social rights. We conclude that there are serious ethical concerns in offering early diagnosis to asymptomatic individuals and the issues raised by the application of AI add to the already known issues. Nevertheless, pre-symptomatic testing should only be offered on request to avoid inflicted harm. We recommend developing training for physicians in communicating AI aided prediction. (shrink)

Abstract: As the integration of Artificial Intelligence (AI) continues to permeate various sectors, the legal domain stands on the cusp of a transformative era. This research paper delves into the multifaceted relationship between AI and the law, scrutinizing the profound implications and innovative applications that emerge at the intersection of these two realms. The study commences with an examination of the current landscape, assessing the challenges and opportunities that AI presents within legal frameworks. With an emphasis on efficiency, accuracy, and (...) accessibility, AI technologies are reshaping traditional legal processes, ranging from document analysis and contract review to predictive legal analytics. Furthermore, the paper scrutinizes the ethical considerations and potential biases inherent in AI algorithms, exploring the delicate balance between technological advancements and the preservation of legal principles such as fairness, accountability, and transparency. The research also delves into the evolving role of legal professionals in navigating and overseeing AI applications, emphasizing the importance of responsible AI deployment. Drawing on case studies and real-world examples, this paper showcases instances where AI has already demonstrated its efficacy in legal contexts, highlighting successful implementations and identifying areas for improvement. The discussion extends to the evolving regulatory landscape, as legal systems grapple with the need to adapt and establish frameworks that ensure the responsible and ethical use of AI technologies. In conclusion, this research contributes to the growing discourse on the dynamic interplay between AI and the legal domain. By illuminating the potential benefits, ethical considerations, and regulatory challenges, it provides a comprehensive overview for legal practitioners, policymakers, and technologists alike, fostering a nuanced understanding of the evolving landscape where artificial intelligence intersects with the law. (shrink)

Modern life sciences research is increasingly relying on artificial intelligence (AI) approaches to model biological systems, primarily centered around the use of machine learning (ML) models. Although ML is undeniably useful for identifying patterns in large, complex data sets, its widespread application in biological sciences represents a significant deviation from traditional methods of scientific inquiry. As such, the interplay between these models and scientific understanding in biology is a topic with important implications for the future of scientific research, yet it (...) is a subject that has received little attention. Here, we draw from an epistemological toolkit to contextualize recent applications of ML in biological sciences under modern philosophical theories of understanding, identifying general principles that can guide the design and application of ML systems to model biological phenomena and advance scientific knowledge. We propose that conceptions of scientific understanding as information compression, qualitative intelligibility, and dependency relation modelling provide a useful framework for interpreting ML-mediated understanding of biological systems. Through a detailed analysis of two key application areas of ML in modern biological research – protein structure prediction and single cell RNA-sequencing – we explore how these features have thus far enabled ML systems to advance scientific understanding of their target phenomena, how they may guide the development of future ML models, and the key obstacles that remain in preventing ML from achieving its potential as a tool for biological discovery. Consideration of the epistemological features of ML applications in biology will improve the prospects of these methods to solve important problems and advance scientific understanding of living systems. (shrink)

Artificial intelligence (AI) profoundly influences a number of societal structures today, including religious dynamics. Using Bernard Lonergan’s critical realism as a lens, this article investigates the intersections of AI and religious traditions in their shared pursuit of the common good. Beginning with Lonergan’s principle that humans construct their understanding through cognitive processes, we examine how AI-mediated realities align with or challenge traditional religious tenets. By delving into specific cases, we spotlight AI’s role in reshaping religious symbols, rituals, and even (...) creating novel spiritual meanings. Using Lonergan’s insights on the balance between subjectivity and objectivity, I analyze AI’s potential to both create new sacred spaces and challenge religious orthodoxy. The crux of the discussion centers on the negotiation between religious values and technological innovation, assessing how AI can bolster religious life while maintaining its core essence. Ultimately, this article underscores the importance of the common good in the age of AI-driven religious evolution. (shrink)

From artistic performances in the visual arts and in music to motor control in gymnastics, from tool use to chess and language, humans excel in a variety of skills. On the plausible assumption that skillful behavior is a visible manifestation of intelligence, a theory of intelligence—whether human or not—should be informed by a theory of skills. More controversial is the question as to whether, in order to theorize about intelligence, we should study certain skills in particular. My target is the (...) view that only a particular class/kind of skill (i.e., ‘theoretical’, or ‘intellectual’ skills, versus ‘practical’, or ‘embodied’ skills) manifests intelligence, or especially does so. I call this view ‘Intelligence Elitism’. Intelligence Elitism is pervasive in popular culture, in academic culture, as well as in psychometrics. It has, arguably, a long pedigree in philosophy (though explicit arguments for it are rare). But it is a substantive view which, if false, can promote unfairness. In this article, I defend Intelligence Socialism—the claim that intelligent behavior is everywhere skillful behavior is. I go on to isolate the best case for the further Elitist claim that, even if all skillful behavior is intelligent in some modest sense of ‘intelligence’, there is a principled difference in intelligence between theoretical, or intellectual, skills, on one side, and practical, or embodied skills, on the other, and I show it wanting. (shrink)

While practical efforts in the field of artificial intelligence grow exponentially, the truly scientific and mathematically exact understanding of the underlying phenomena of intelligence and consciousness is still missing in the conventional science framework. The inevitably dominating empirical, trial-and-error approach has vanishing efficiency for those extremely complicated phenomena, ending up in fundamentally limited imitations of intelligent behaviour. We provide the first-principle analysis of unreduced many-body interaction process in the brain revealing its qualitatively new features, which give rise to rigorously (...) defined chaotic, noncomputable, intelligent and conscious behaviour. Based on the obtained universal concepts of unreduced dynamic complexity, intelligence and consciousness, we derive the universal laws of intelligence applicable to any kind of intelligent system interacting with the environment. We finally show why and how these fundamentally substantiated and therefore practically efficient laws of intelligent system dynamics are indispensable for correct AI design and training, which is urgently needed in this time of critical global change towards the truly sustainable development. (shrink)

Defining Artificial Intelligence and Artificial General Intelligence remain controversial and disputed. They stem from a longer-standing controversy of what is the definition of consciousness, which if solved could possibly offer a solution to defining AI and AGI. Central to these problems is the paradox that appraising AI and Consciousness requires epistemological objectivity of domains that are ontologically subjective. I propose that applying the philosophy of art, which also aims to define art through a lens of epistemological objectivity where the domains (...) are ontologically subjective, can further elucidate this unsolved question. In this sense, Art and AI and ultimately consciousness are multifaceted domains where conventional complexity theory and current philosophical approaches may be augmented by aesthetic principles ranging from classical Aristotelian essentialism to Wittgensteinian anti-essentialism. This approach of AI as art may offer novel solutions to characterising and elucidating the ciphers of consciousness and AI. (shrink)

The recent explosion in the discovery of exoplanets and our incipient ability to detect atmospheric biomarkers recommend reflection on the conceptual implications of discovering – or not discovering – extrasolar life. I contend that evidence for intelligent extraterrestrial life is evidence against the existence of God, because if there are intelligent extraterrestrials, there are likely to be evils in the universe even greater than those found on Earth. My reasoning is based on Richard Gott's Copernican Principle, which holds that (...) in the absence of information to the contrary, we should take ourselves to be typical observers. (shrink)

This paper investigates how the simulation of intelligence, an activity that has been considered the notional task of Artificial Intelligence, does not comprise its duplication. Briefly touching on the distinction between conceivability and possibility, and commenting on Ryan’s approach to fiction in terms of the interplay between possible worlds and her principle of minimal departure, we specify verisimilitude in Artificial Intelligence as the accurate resemblance of intelligence by its simulation and, from this characterization, claim the metaphysical impossibility of duplicating (...) intelligence, as neither verisimilarly nor convincingly simulating intelligence involves its duplication. To this end, we argue by a representative case of simulation that, albeit conceivable, Turing’s test for machine intelligence wrongly equates the occurrence of indistinguishable intelligence performance to intelligence duplication, which is grounded in a prima facie conceivable but metaphysically impossible view that separates intelligence from its origin. Finally, we establish the following criterion for evaluating simulation in Artificial Intelligence: simulations succeed in AI if and only if they are able to epistemically persuade human beings that intelligence has been duplicated, that is, if and only if verisimilar simulations can convincingly minimally depart from actual intelligence. (shrink)

This article is an attempt to highlights the importance of Beijing Principle of Artificial Intelligence for Children for preventing the Juvenile Delinquency. The article argues that the artificial intelligence products should protect children's privacy, promote children's physical and mental health, and control potential risks.

This article centers on Hume’s position on the intelligibility of natural philosophy. To that end, the controversy surrounding universal gravitation shall be scrutinized. It is very well-known that Hume sides with the Newtonian experimentalist approach rather than with the Leibnizian demand for intelligibility. However, what is not clear is Hume’s overall position on the intelligibility of natural philosophy. It shall be argued that Hume declines Leibniz’s principle of intelligibility. However, Hume does not eschew intelligibility (...) altogether; his concept of causation itself stipulates mechanical intelligibility. (shrink)

This paper addresses a question about the moral status of Artificial Intelligence (AI): will AIs ever become moral patients? I argue that, while it is in principle possible for an intelligent machine to be a moral patient, there is no good reason to believe this will in fact happen. I start from the plausible assumption that traditional artifacts do not meet a minimal necessary condition of moral patiency: having a good of one's own. I then argue that intelligent machines (...) are no different from traditional artifacts in this respect. To make this argument, I examine the feature of AIs that enables them to improve their intelligence, i.e., machine learning. I argue that there is no reason to believe that future advances in machine learning will take AIs closer to having a good of their own. I thus argue that concerns about the moral status of future AIs are unwarranted. Nothing about the nature of intelligent machines makes them a better candidate for acquiring moral patiency than the traditional artifacts whose moral status does not concern us. (shrink)

The article presents the grounds for defining the fetish of artificial intelligence (AI). The fundamental differences of AI from all previous technological innovations are highlighted, as primarily related to the introduction into the human cognitive sphere and fundamentally new uncontrolled consequences for society. Convincing arguments are presented that the leaders of the globalist project are the main beneficiaries of the AI fetish. This is clearly manifested in the works of philosophers close to big technology corporations and their mega-projects. It is (...) proposed to consider the problem of how to use the capabilities of AI to overcome the growing international conflicts and the global crisis in general. The focus is on the problem of subjectness, the solution of which from the standpoint of an anthropomorphic approach to AI is fraught with serious negative consequences. When endowing AI with subjectness, responsibility is implicitly removed from the person who uses this technology, and the established legislative practice is also destroyed. The presentation of AI as an agent endowed with a set of invariant simplified qualities that natural subjects have is proposed. These qualities include: the ability to purposefulness, a kind of reflexivity, communication and simplified elements of sociality. Such a representation of AI as an agent (pseudo-subject) is consistent with the principle of distributed control in biology and psychology, which was called the principle of a dual subject. In combination with the systems of principles and ontologies specified in the concept of post-nonclassical cybernetics of self-developing environments, this will allow the use of AI as a means of social innovation, while maintaining control over AI technologies. And also to pose and solve the problem of integrating the formations of artificial and natural intelligence while maintaining the basic qualities of carriers of natural intelligence. (shrink)

Technological progress has brought about the emergence of machines that have the capacity to take human lives without human control. These represent an unprecedented threat to humankind. This paper starts from the example of chemical weapons, now banned worldwide by the Geneva protocol, to illustrate how technological development initially aimed at the benefit of humankind has, ultimately, produced what is now called the “Weaponization of Artificial Intelligence (AI)”. Autonomous Weapon Systems (AWS) fail the so-called discrimination principle, yet, the wider (...) public is largely unaware of this problem. Given that ongoing scientific research on AWS, performed in the military sector, is generally not made available to the public domain, many of the viewpoints on this subject, expressed across different media, invoke common sense rather than scientific evidence. Yet, the implications of a potential weaponization of our work as scientists, especially in the field of AI, are reaching further than some may think. The potential consequences of a deployment of AWS for citizen stakeholders are incommensurable, and it is time to raise awareness in the public domain of the kind of potential threats identified, and to encourage legal policies ensuring that these threats will not materialize. (shrink)

When this article was first planned, writing was going to be exclusively about two things - the origin of life and human evolution. But it turned out to be out of the question for the author to restrict himself to these biological and anthropological topics. A proper understanding of them required answering questions like “What is the nature of the universe – the home of life – and how did it originate?”, “How can time travel be removed from fantasy and (...) science fiction, to be made scientific and practical?”, and “How can the proposed young age of genus Homo be made to actually be reasonable – when simply stating it would be solid ground for instant rejection and dismissal?” The result is that the article also talks about subjects like Artificial Intelligence, General Relativity, and cosmology. -/- From where did life originate? God? Evolution? Panspermia? If the tendency of humans and scientists to regard undiscovered science as pseudoscience can be overcome, Einstein gave another alternative to consider when he introduced General Relativity. Time isn’t linear – progressing in a straight line from past to present to future. That assumption ignores Relativity which states that space AND TIME are curved. Where did life and the genetic code come from? Can the answer build AI? -/- The first question can be answered by the section of this article titled SETI, Evolution, and Time which says life (possibly multicellular and intelligent) and the genetic code came from humans acquiring knowledge of these things over the centuries, then applying that knowledge – via terraforming, accumulation of raw materials like amino acids and nucleic acids, genetic engineering - to a time in the past when life didn’t exist. From that origin, life evolved through innumerable mutations and adaptations, with humans once again acquiring knowledge of it in cyclic (nonlinear) time. -/- The second question is answered by saying artificial intelligence (AI) as the product of life is only half of the equation. The other half refers to Relativity’s curved space-time and violation of the notion that time always travels from past to future. We have always lived in an artificially intelligent, non-probabilistic universe where everything in time and space is connected into one thing by quantum entanglement – making the brain and genes products of binary-digit activity or artificial intelligence (life is not merely dependent on biology’s “lock and key” mechanisms but also possesses AI). -/- The earliest documented representative of the genus Homo is Homo habilis, which evolved around 2.8 million years ago. Scientists used to believe there was a straight line from H. habilis to us, Homo sapiens. This article will use the “advanced” waves loved by Physics Nobel laureate Richard Feynman, view the history of science through the lens of Conic Sections applied to Relativity’s curved space-time, and incorporate the necessity of so-called imaginary time * – popularized by Prof. Stephen Hawking. While the evolutionary proposals are more in agreement with this early straight line than with modern theories, Albert Einstein’s General Relativity is used to transform the straight line into a curved line, ultimately concluding that Homo habilis (H. habilis) originated only (and unbelievably, as far as today’s science and technology is concerned) ~250,000 years ago. Other branches and dead ends of Homo – e.g. Neanderthals – are the result of mutations and adaptations, with the resultant modifications to anatomy and physiology. The surprisingly young age of H. habilis allows nearly 200,000 years for habilis, or one of its descendants, to reach Australia … if this country’s indigenous Aboriginal population did, as claimed, reach this “island continent” 60,000 years ago. -/- * The ultraviolet catastrophe, also called the Rayleigh–Jeans catastrophe, is a failure of classical physics to predict observed phenomena: it can be shown that a blackbody - a hypothetical perfect absorber and radiator of energy - would release an infinite amount of energy, contradicting the principles of conservation of energy and indicating that a new model for the behaviour of blackbodies was needed. At the start of the 20th century, physicist Max Planck derived the correct solution by making some strange (for the time) assumptions. In particular, Planck assumed that electromagnetic radiation can only be emitted or absorbed in discrete packets, called quanta. Albert Einstein postulated that Planck's quanta were real physical particles (what we now call photons), not just a mathematical fiction. From there, Einstein developed his explanation of the photoelectric effect (when quanta or photons of light shine on certain metals, electrons are released and can form an electric current). So it appears entirely possible that another supposed mathematical trickery (imaginary time and the y-axis of Wick rotation) will find practical application in the future. -/- The article includes mathematical references to cosmology (spoiler alert – you’ll read about things like Vector-Tensor-Scalar Geometry, topology, the “eternal present”, Einstein’s Unified Field, the inverse-square law, and there being no Big Bang and no multiverse - but there will also be no equations). -/- The other subheadings in this essay are – -/- NONLINEAR TIME AND ELECTRICAL ENGINEERING (about a 2009 electrical engineering experiment at America’s Yale University, and cosmic wormholes) -/- BITS AND TOPOLOGY (base-2 maths aka Binary digiTS, Mobius strips, and figure-8 Klein bottles) -/- WICK ROTATION, CAUSALITY, AND UNITING TIME (do past, present and future co-exist in an “eternal present”?) -/- DIGITAL BRAIN, DIGITAL UNIVERSE (if the brain and the universe are ultimately composed of binary digits, we'll someday be able to do the same things with the brain and universe that we now do with computers) -/- PROPOSAL: HUMAN AND ANIMAL INSTINCTS ARE THE RESULT OF THE UNIVERSE BEING UNIFIED BY BINARY DIGITS (AND TOPOLOGY) (If everything in the universe is ultimately composed of electronic BITS, then the universe must possess Artificial Intelligence - some prefer the term Cosmic Consciousness) -/- INFORMATION THEORY CONQUERS A RED GIANT (preserving Earth by keeping the Sun near today’s level of activity forever). 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One of the main issues that dominates Neoplatonism in late antique philosophy of the 3rd–6th centuries A.D. is the nature of the first principle, called the ‘One’. From Plotinus onward, the principle is characterized as the cause of all things, since it produces the plurality of intelligible Forms, which in turn constitute the world’s rational and material structure. Given this, the tension that faces Neoplatonists is that the One, as the first cause, must transcend all things that are (...) characterized by plurality—yet because it causes plurality, the One must anticipate plurality within itself. This becomes the main mo- tivation for this study’s focus on two late Neoplatonists, Proclus (5th cent. A.D.) and Damascius (late 5th–early 6th cent. A.D.): both attempt to address this tension in two rather different ways. Proclus’ attempted solution is to posit intermediate principles (the ‘henads’) that mirror the One’s nature, as ‘one’, but directly cause plurality. This makes the One only a cause of unity, while its production of plurality is mediated by the henads that it produces. Damascius, while appropriating Proclus’ framework, thinks that this is not enough: if the One is posed as a cause of all things, it must be directly related to plurality, even if its causality is mediated through the henads. Damascius then splits Proclus’ One into two entities: (1) the Ineffable as the first ‘principle’, which is absolutely transcendent and has no causal relation; and (2) the One as the first ‘cause’ of all things, which is only relatively transcendent under the Ineffable. -/- Previous studies that compare Proclus and Damascius tend to focus either on the Ineffable or a skeptical shift in epistemology, but little work has been done on the causal framework which underlies both figures’ positions. Thus, this study proposes to focus on the causal frameworks behind each figure: why and how does Proclus propose to assert that the One is a cause, at the same time that it transcends its final effect? And what leads Damascius to propose a notion of the One’s causality that no longer makes it transcendent in the way that a higher principle, like the Ineffable, is? The present work will answer these questions in two parts. In the first, Proclus’ and Damascius’ notions of causality will be examined, insofar as they apply to all levels of being. In the second part, the One’s causality will be examined for both figures: for Proclus, the One’s causality in itself and the causality of its intermediate principles; for Damascius, the One’s causality, and how the Ineffable is needed to explain the One. The outcome of this study will show that Proclus’ framework results in an inner tension that Damascius is responding to with his notion of the One. While Damascius’ own solution implies its own tension, he at least solves a difficulty in Proclus—and in so doing, partially returns to a notion of the One much like Iamblichus’ and Plotinus’ One. (shrink)

Abstract. Intelligent Tutoring System Builder (ITSB) is an authoring tool designed and developed to aid teachers in constructing intelligent tutoring systems in a multidisciplinary fields. The teacher is needed to create a set of pedagogical fundamentals, which, in line, are inured to automatically build up a broad tutor framework and construct an intelligent tutoring system. In this paper an explanation of the theory and the architecture of the tool is outlined. A presentation of several system components, the requirements of the (...) different components, integration of these components in ITSB tool are shown. Furthermore, implanting of requirements, cognitive principle, and common design fundamentals in the tool to ease the use of teachers. A variety of design matters, an example of building an intelligent tutoring system for teaching Java language using ITSB tool and an evaluation are presented. (shrink)

This article offers an overview of the main first-order ethical questions raised by robots and Artificial Intelligence (RAIs) under five broad rubrics: functionality, inherent significance, rights and responsibilities, side-effects, and threats. The first letter of each rubric taken together conveniently generates the acronym FIRST. Special attention is given to the rubrics of functionality and inherent significance given the centrality of the former and the tendency to neglect the latter in virtue of its somewhat nebulous and contested character. In addition to (...) exploring some illustrative issues arising under each rubric, the article also emphasizes a number of more general themes. These include: the multiplicity of interacting levels on which ethical questions about RAIs arise, the need to recognise that RAIs potentially implicate the full gamut of human values (rather than exclusively or primarily some readily identifiable sub-set of ethical or legal principles), and the need for practically salient ethical reflection on RAIs to be informed by a realistic appreciation of their existing and foreseeable capacities. -/- . (shrink)

The debate about the ethical implications of Artificial Intelligence dates from the 1960s :741–742, 1960; Wiener in Cybernetics: or control and communication in the animal and the machine, MIT Press, New York, 1961). However, in recent years symbolic AI has been complemented and sometimes replaced by Neural Networks and Machine Learning techniques. This has vastly increased its potential utility and impact on society, with the consequence that the ethical debate has gone mainstream. Such a debate has primarily focused on principles—the (...) ‘what’ of AI ethics —rather than on practices, the ‘how.’ Awareness of the potential issues is increasing at a fast rate, but the AI community’s ability to take action to mitigate the associated risks is still at its infancy. Our intention in presenting this research is to contribute to closing the gap between principles and practices by constructing a typology that may help practically-minded developers apply ethics at each stage of the Machine Learning development pipeline, and to signal to researchers where further work is needed. The focus is exclusively on Machine Learning, but it is hoped that the results of this research may be easily applicable to other branches of AI. The article outlines the research method for creating this typology, the initial findings, and provides a summary of future research needs. (shrink)

Copernican reasoning involves considering ourselves, in the absence of other information, to be randomly selected members of a reference class. Consider the reference class intelligent observers. If there are extraterrestrial intelligences (ETIs), taking ourselves to be randomly selected intelligent observers leads to the conclusion that it is likely the Earth has a larger population size than the typical planet inhabited by intelligent life, for the same reason that a randomly selected human is likely to come from a more populous country. (...) The astrophysicist Fergus Simpson contends that this reasoning supports the claims that the typical planet inhabited by ETIs is smaller than Earth (radius about 5,000km; cf. Earth's radius = 6,371km) and that the typical ETI is significantly larger than us about 314kg, the size of an adult male grizzly bear). Simpson's applications of Copernican reasoning are novel and exciting. They should be of interest to philosophers concerned with Richard Gott's delta t argument, the N=1 problem in astrobiology, limited principles of indifference, and probabilistic epistemology in general. While we agree with Simpson about the qualitative direction of his conclusions, we take issue with his presentation of precise quantitative results because his methods (1) display bias, (2) ignore other variables contributing to population size, (3) commit an equivocation, and (4) conceal their dependence on arbitrary assumptions. (shrink)

Over recent decades, several global tech giants have gained enormous power while at the same time generating various disputes with their end-users, local governments, and regulators. We propose that the Jewish concept of covenant can help the above parties, legal scholars, and wider society, in addressing this complex legal reality. We present the challenge of disequilibrium between the above four parties against the main points of conflict: the requirement of customer consent; clear contractual provisions upon entry; options for reasonable customer (...) exit; limitations on the platform’s ability to exercise unilateral termination; profile-based discrimination; and liability for mere intermediation. We introduce the biblical concept of covenant, and we review its unfolding in Jewish tradition. Further, we conceptualize three main covenantal principles: (1) responsibility—God and humans are both conceived as moral agents; (2) reciprocity—God as a caring law giver, open to human appeals; and (3) reasonability—divine instruction as initially intelligible. We demonstrate how the latter principle of explainability is exercised in the biblical law narratives and how the story of Balaam stresses the significance of moral agency that cannot hide behind “mere intermediary” claims. In light of this analysis, we revisit the relationship between tech giants and tech users to demonstrate how covenantality offers novel ways to conceptualize the noted conflicts between the parties. (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)

One of the objections against the thesis of underdetermination of theories by observations is that it is unintelligible. Any two empirically equivalent theories — so the argument goes—are in principle intertranslatable, hence cannot count as rivals in any non-trivial sense. Against that objection, this paper shows that empirically equivalent theories may contain theoretical sentences that are not intertranslatable. Examples are drawn from a related discussion about incommensurability that shows that theoretical non-intertranslatability is possible.

This work stresses the importance of AI accountability to citizens and explores how a fourth independent government branch/institutions could be endowed to ensure that algorithms in today´s democracies convene to the principles of Constitutions. The purpose of this fourth branch of government in modern democracies could be to enshrine accountability of artificial intelligence development, including software-enabled technologies, and the implementation of policies based on big data within a wider democratic regime context. The work draws on Philosophy of Science, Political Theory (...) (Ethics and Ideas), as well as concepts derived from the study of democracy (responsibility and accountability) to make a theoretical analysis of what artificial intelligence (AI) means for the governance of society and what are the limitations of such type of AI governance. The discussion shows that human ideas, as cement of societies, make it problematic to enshrine governance of artificial intelligence into the world of devices. In ethical grounds, the work stresses an existing trade off between greater and faster advancement of technology, or innovation on the one hand, and human well being on the oher, where the later is not automatically guaranteed by default. This trade off is yet unresolved. The work contends that features of AI offer an opportunity to revise government priorities from a multilevel perspective, from the local to the upper levels. artificial intelligence, accountability, democracy, regulation, philosophy of science, ethics, political theory . (shrink)

The application of artificial intelligence (AI) to judicial decision-making has already begun in many jurisdictions around the world. While AI seems to promise greater fairness, access to justice, and legal certainty, issues of discrimination and transparency have emerged and put liberal democratic principles under pressure, most notably in the context of bail decisions. Despite this, there has been no systematic analysis of the risks to liberal democratic values from implementing AI into judicial decision-making. This article sets out to fill this (...) void by identifying and engaging with challenges arising from artificial judicial decision-making, focusing on three pillars of liberal democracy, namely equal treatment of citizens, transparency, and judicial independence. Methodologically, the work takes a comparative perspective between human and artificial decision-making, using the former as a normative benchmark to evaluate the latter. -/- The chapter first argues that AI that would improve on equal treatment of citizens has already been developed, but not yet adopted. Second, while the lack of transparency in AI decision-making poses severe risks which ought to be addressed, AI can also increase the transparency of options and trade-offs that policy makers face when considering the consequences of artificial judicial decision-making. Such transparency of options offers tremendous benefits from a democratic perspective. Third, the overall shift of power from human intuition to advanced AI may threaten judicial independence, and with it the separation of powers. While improvements regarding discrimination and transparency are available or on the horizon, it remains unclear how judicial independence can be protected, especially with the potential development of advanced artificial judicial intelligence (AAJI). Working out the political and legal infrastructure to reap the fruits of artificial judicial intelligence in a safe and stable manner should become a priority of future research in this area. (shrink)

The paper outlines an analysis of two types of information - ordinary and subjective, consideration is given to the difference between the concepts of intelligence and perceiving mind. It also provides description of some logical functional features of consciousness. A technical approach is proposed to technical obtaining of subjective information by changing the signal’s time degree of freedom to the spatial one in order to obtain the "observer" function in the system and information signals appearing in relation to it, that (...) serve as subjective sensations. The solution to this problem may give a new approach to designing a strong artificial intelligence and shed light on the difficult problem of the mind. (shrink)

Computers can mimic human intelligence, sometimes quite impressively. This has led some to claim that, a.) computers can actually acquire intelligence, and/or, b.) the human mind may be thought of as a very sophisticated computer. In this paper I argue that neither of these inferences are sound. The human mind and computers, I argue, operate on radically different principles.

The principle of self-organization has acquired a fundamental significance in the newly emerging field of computational philosophy. Self-organizing systems have been described in various domains in science and philosophy including physics, neuroscience, biology and medicine, ecology, and sociology. While system architecture and their general purpose may depend on domain-specific concepts and definitions, there are (at least) seven key properties of self-organization clearly identified in brain systems: 1) modular connectivity, 2) unsupervised learning, 3) adaptive ability, 4) functional resiliency, 5) functional (...) plasticity, 6) from-local-to-global functional organization, and 7) dynamic system growth. These are defined here in the light of insight from neurobiology, cognitive neuroscience and Adaptive Resonance Theory (ART), and physics to show that self-organization achieves stability and functional plasticity while minimizing structural system complexity. A specific example informed by empirical research is discussed to illustrate how modularity, adaptive learning, and dynamic network growth enable stable yet plastic somatosensory representation for human grip force control. Implications for the design of “strong” artificial intelligence in robotics are brought forward. (shrink)

In the case of AI, automated systems are making increasingly complex decisions with significant ethical implications, raising questions about who is responsible for decisions made by AI and how to ensure that these decisions align with society's ethical and moral values, both in India and the West. Jonathan Haidt has conducted research on moral and ethical decision-making. Today, solving problems like decision-making in autonomous vehicles can draw on the literature of the trolley dilemma in that it illustrates the complexity of (...) ethical decisions faced in emergency situations, as well as the moral implications of the decisions made. However, a series of moral principles must be understood and cited to avoid insufficient mechanistic explanations. Here we present a compilation of ethical positions both in India and the West. (shrink)

Science deals with the physical aspect of reality; its subject matter is data that, in principle, can be collected solely by physical devices. If physical devices cannot measure something, then that something is not the subject matter of science. Of course, the whole of reality encompasses more than the physical.

Whether causing flash crashes in financial markets, purchasing illegal drugs, or running over pedestrians, AI is increasingly engaging in activity that would be criminal for a natural person, or even an artificial person like a corporation. We argue that criminal law falls short in cases where an AI causes certain types of harm and there are no practically or legally identifiable upstream criminal actors. This Article explores potential solutions to this problem, focusing on holding AI directly criminally liable where it (...) is acting autonomously and irreducibly. Conventional wisdom holds that punishing AI is incongruous with basic criminal law principles such as the capacity for culpability and the requirement of a guilty mind. -/- Drawing on analogies to corporate and strict criminal liability, as well as familiar imputation principles, we show how a coherent theoretical case can be constructed for AI punishment. AI punishment could result in general deterrence and expressive benefits, and it need not run afoul of negative limitations such as punishing in excess of culpability. Ultimately, however, punishing AI is not justified, because it might entail significant costs and it would certainly require radical legal changes. Modest changes to existing criminal laws that target persons, together with potentially expanded civil liability, are a better solution to AI crime. (shrink)

This essay hypothesizes that the Universe contains a self-reproducing neural network of Black Holes with computational abilities—i.e., the Universe can “think”! It then rephrases the Final Anthropic Principle to state: “Intelligent information-processing must come into existence in each new Universe to assure the birth of intelligent successor universes”. Continued research into the theory of Early Universe and Black Hole information storage, processing and retrieval is recommended, as are observational searches for time-correlated electromagnetic and gravitational wave emission patterns from widely (...) separated Black Hole transient events indicative of the existence of a universal inter-Black Hole faster-than-light communications network. (shrink)

Machine intelligence already helps medical staff with a number of tasks. Ethical decision-making, however, has not been handed over to computers. In this proof-of-concept study, we show how an algorithm based on Beauchamp and Childress’ prima-facie principles could be employed to advise on a range of moral dilemma situations that occur in medical institutions. We explain why we chose fuzzy cognitive maps to set up the advisory system and how we utilized machine learning to train it. We report on the (...) difficult task of operationalizing the principles of beneficence, non-maleficence and patient autonomy, and describe how we selected suitable input parameters that we extracted from a training dataset of clinical cases. The first performance results are promising, but an algorithmic approach to ethics also comes with several weaknesses and limitations. Should one really entrust the sensitive domain of clinical ethics to machine intelligence? (shrink)

Technological developments involving robotics and artificial intelligence devices are being employed evermore in elderly care and the healthcare sector more generally, raising ethical issues and practical questions warranting closer considerations of what we mean by “care” and, subsequently, how to design such software coherently with the chosen definition. This paper starts by critically examining the existing approaches to the ethical design of care robots provided by Aimee van Wynsberghe, who relies on the work on the ethics of care by Joan (...) Tronto. In doing so, it suggests an alternative to their non-principled approach, an alternative suited to tackling some of the issues raised by Tronto and van Wynsberghe, while allowing for the inclusion of two orientative principles. Our proposal centres on the principles of autonomy and vulnerability, whose joint adoption we deem able to constitute an original revision of a bottom-up approach in care ethics. Conclusively, the ethical framework introduced here integrates more traditional approaches in care ethics in view of enhancing the debate regarding the ethical design of care robots under a new lens. (shrink)