We comment on the collection of papers inspired by our book Why Machines Will Never Rule the World published in volume 12 (5+6) of the journal Cosmos+Taxis. We summarize the arguments made by the contributors about what we say in the book, and then show where we disagree.

Introduction: bearing politics -- Abortion, sin, and the state -- A history of the abortion debate -- Conceiving the nation: representations of abortion in Thailand -- Corrupt girls, victims of men, desperate women: representations of women who abort -- 'A small sin': everyday acts -- 'The truth of our day by day lives': situational ethics -- Global debates, local dilemmas.

Artificial intelligence (AI) research enjoyed an initial period of enthusiasm in the 1970s and 80s. But this enthusiasm was tempered by a long interlude of frustration when genuinely useful AI applications failed to be forthcoming. Today, we are experiencing once again a period of enthusiasm, fired above all by the successes of the technology of deep neural networks or deep machine learning. In this paper we draw attention to what we take to be serious problems underlying current views of artificial (...) intelligence encouraged by these successes, especially in the domain of language processing. We then show an alternative approach to language-centric AI, in which we identify a role for philosophy. (shrink)

In his “Bridging mainstream and formal ontology”, Augusto (2021) gives an excellent analysis of Dietrich von Freiberg’s idea of using causality as a partitioning principle for upper ontologies. For this Dietrich’s notion of extrinsic principles is crucial. The question whether causation can and indeed should be used as a partitioning principle for ontologies is discussed using mathematics and physics as examples.

The book’s core argument is that an artificial intelligence that could equal or exceed human intelligence—sometimes called artificial general intelligence (AGI)—is for mathematical reasons impossible. It offers two specific reasons for this claim: Human intelligence is a capability of a complex dynamic system—the human brain and central nervous system. Systems of this sort cannot be modelled mathematically in a way that allows them to operate inside a computer. In supporting their claim, the authors, Jobst Landgrebe and Barry Smith, marshal (...) evidence from mathematics, physics, computer science, philosophy, linguistics, and biology, setting up their book around three central questions: What are the essential marks of human intelligence? What is it that researchers try to do when they attempt to achieve "artificial intelligence" (AI)? And why, after more than 50 years, are our most common interactions with AI, for example with our bank’s computers, still so unsatisfactory? Landgrebe and Smith show how a widespread fear about AI’s potential to bring about radical changes in the nature of human beings and in the human social order is founded on an error. There is still, as they demonstrate in a final chapter, a great deal that AI can achieve which will benefit humanity. But these benefits will be achieved without the aid of systems that are more powerful than humans, which are as impossible as AI systems that are intrinsically "evil" or able to "will" a takeover of human society. (shrink)

Originally presented as the author's thesis (doctoral--Gregorian University).

The term ‘intelligence’ as used in this paper refers to items of knowledge collected for the sake of assessing and maintaining national security. The intelligence community (IC) of the United States (US) is a community of organizations that collaborate in collecting and processing intelligence for the US. The IC relies on human-machine-based analytic strategies that 1) access and integrate vast amounts of information from disparate sources, 2) continuously process this information, so that, 3) a maximally comprehensive understanding of world actors (...) and their behaviors can be developed and updated. Herein we describe an approach to utilizing outcomes-based learning (OBL) to support these efforts that is based on an ontology of the cognitive processes performed by intelligence analysts. Of particular importance to the Cognitive Process Ontology is the class Representation that is Warranted. Such a representation is descriptive in nature and deserving of trust in its veridicality. The latter is because a Representation that is Warranted is always produced by a process that was vetted (or successfully designed) to reliably produce veridical representations. As such, Representations that are Warranted are what in other contexts we might refer to as ‘items of knowledge’. (shrink)

Implicit stochastic models, including both ‘deep neural networks’ (dNNs) and the more recent unsupervised foundational models, cannot be explained. That is, it cannot be determined how they work, because the interactions of the millions or billions of terms that are contained in their equations cannot be captured in the form of a causal model. Because users of stochastic AI systems would like to understand how they operate in order to be able to use them safely and reliably, there has emerged (...) a new field called ‘explainable AI’ (XAI). When we examine the XAI literature, however, it becomes apparent that its protagonists have redefined the term ‘explanation’ to mean something else, namely: ‘interpretation’. Interpretations are indeed sometimes possible, but we show that they give at best only a subjective understanding of how a model works. We propose an alternative to XAI, namely certified AI (CAI), and describe how an AI can be specified, realized, and tested in order to become certified. The resulting approach combines ontologies and formal logic with statistical learning to obtain reliable AI systems which can be safely used in technical applications. (shrink)

The view of nature we adopt in the natural attitude is determined by common sense, without which we could not survive. Classical physics is modelled on this common-sense view of nature, and uses mathematics to formalise our natural understanding of the causes and effects we observe in time and space when we select subsystems of nature for modelling. But in modern physics, we do not go beyond the realm of common sense by augmenting our knowledge of what is going on (...) in nature. Rather, we have measurements that we do not understand, so we know nothing about the ontology of what we measure. We help ourselves by using entities from mathematics, which we fully understand ontologically. But we have no ontology of the reality of modern physics; we have only what we can assert mathematically. In this paper, we describe the ontology of classical and modern physics against this background and show how it relates to the ontology of common sense and of mathematics. (shrink)

Barry Smith recently discussed the diagraphs of book eight of Jacob Lorhard’s Ogdoas scholastica under the heading “birth of ontology” (Smith, 2022; this issue). Here, I highlight the commonalities between the original usage of diagraphs in the tradition of Ramus for didactic purposes and the the usage of their present-day successors–modern ontologies–for computational purposes. The modern ideas of ontology and of the universal computer were born just two generations apart in the breakthrough century of instrumental reason.

Since the noun phrase `artificial intelligence' (AI) was coined, it has been debated whether humans are able to create intelligence using technology. We shed new light on this question from the point of view of themodynamics and mathematics. First, we define what it is to be an agent (device) that could be the bearer of AI. Then we show that the mainstream definitions of `intelligence' proposed by Hutter and others and still accepted by the AI community are too weak even (...) to capture what is involved when we ascribe intelligence to an insect. We then summarise the highly useful definition of basic (arthropod) intelligence proposed by Rodney Brooks, and we identify the properties that an AI agent would need to possess in order to be the bearer of intelligence by this definition. Finally, we show that, from the perspective of the disciplines needed to create such an agent, namely mathematics and physics, these properties are realisable by neither implicit nor explicit mathematical design nor by setting up an environment in which an AI could evolve spontaneously. (shrink)

Some defenders of so-called `artificial intelligence' believe that machines can understand language. In particular, Søgaard has argued in his "Understanding models understanding language" (2022) for a thesis of this sort. His idea is that (1) where there is semantics there is also understanding and (2) machines are not only capable of what he calls `inferential semantics', but even that they can (with the help of inputs from sensors) `learn' referential semantics. We show that he goes wrong because he pays insufficient (...) attention to the difference between language as used by humans and the sequences of inert symbols which arise when language is stored on hard drives or in books in libraries. (shrink)

Sam Harris is a contemporary illustration of the difficulties standing in the way of coherent interdisciplinary thinking in an age where science and the humanities have drifted so far apart. We are here with Harris’s views on AI, and specifically with his view according to which, with the advance of AI, there will evolve a machine superintelligence with powers that far exceed those of the human mind. This he sees as something that is not merely possible, but rather a matter (...) of inevitability. If, however, we look carefully at what intelligence is, and at how computers really work on the basis of mathematical models, then we can see that it is forever impossible to emulate inside a computer even the intelligence of crows or rabbits, let alone that of human beings. (shrink)

Transcript of an Interview on the podcast: Irreverend: Faith and Current Affairs.

Health Level 7 (HL7) is an international standards development organisation in the domain of healthcare information technology. Initially the mission of HL7 was to enable data exchange via the creation of syntactic standards which supported point-to-point messaging. Currently HL7 sees its mission as one of creating standards for semantic interoperability in healthcare IT on the basis of its flagship “version 3” (v3). Unfortunately, v3 has been plagued by quality and consistency issues, and it has not been able to keep pace (...) with recent developments either in semantics and ontology or in computer science and engineering. HL7’s response has been to develop its “Services-Aware Interoperability Framework” (SAIF), which is intended to provide a foundation for work on all aspects of standardization in HL7 henceforth. We here summarise the major design principles that must be satisfied by a semantic interoperability framework – principles relating both to static semantics and to computational behaviour. We then assess the SAIF in light of these principles. We conclude that the SAIF is not in a position to support the needed reform of the HL7 v3 family of standards. (shrink)

Accompanying DVD is a filmed segment of the conversation.

Das in diesem Aufsatz vorgebrachte Argumentationsmuster hat folgende Schritte: 1. Der menschliche Geist ist vom Körper nicht trennbar, sie bilden ein Kontinuum. 2. Unser Bewusstsein und alle darauf aufbauenden geistigen Phänomene sind die Emanation eines materiellen Prozesses, den ein komplexes System verursacht. 3. Komplexe Systeme lassen sich mathematisch nicht modellieren und nicht kausal verstehen. 4. Computer sind Turing-Maschinen. Sie können nur mathematische Modelle berechnen. Es wird niemals Hyper-Turing Maschinen geben, und wenn es sie gäbe, könnten sie auch nur mathematische Modelle (...) berechnen. 5. Es ist nicht möglich, den Körper als Substrat des Geistes durch einen Computer zu ersetzen. Die digitale Unsterblichkeit ist demzufolge ein Ding der Unmöglichkeit. (shrink)

The goal of creating Artificial General Intelligence (AGI) – or in other words of creating Turing machines (modern computers) that can behave in a way that mimics human intelligence – has occupied AI researchers ever since the idea of AI was first proposed. One common theme in these discussions is the thesis that the ability of a machine to conduct convincing dialogues with human beings can serve as at least a sufficient criterion of AGI. We argue that this very ability (...) should be accepted also as a necessary condition of AGI, and we provide a description of the nature of human dialogue in particular and of human language in general against this background. We then argue that it is for mathematical reasons impossible to program a machine in such a way that it could master human dialogue behaviour in its full generality. This is (1) because there are no traditional explicitly designed mathematical models that could be used as a starting point for creating such programs; and (2) because even the sorts of automated models generated by using machine learning, which have been used successfully in areas such as machine translation, cannot be extended to cope with human dialogue. If this is so, then we can conclude that a Turing machine also cannot possess AGI, because it fails to fulfil a necessary condition thereof. At the same time, however, we acknowledge the potential of Turing machines to master dialogue behaviour in highly restricted contexts, where what is called “narrow” AI can still be of considerable utility. (shrink)

Several attempts have been made to apply the choice-sensitive theory of distributive justice, luck egalitarianism, in the context of health and healthcare. This article presents a framework for this discussion by highlighting different normative decisions to be made in such an application, some of the objections to which luck egalitarians must provide answers and some of the practical implications associated with applying such an approach in the real world. It is argued that luck egalitarians should address distributions of health rather (...) than healthcare, endorse an integrationist theory that combines health concerns with general distributive concerns and be pluralist in their approach. It further suggests that choice-sensitive policies need not be the result of applying luck egalitarianism in this context. (shrink)

Call it the Skynet hypothesis, Artificial General Intelligence, or the advent of the Singularity — for years, AI experts and non-experts alike have fretted (and, for a small group, celebrated) the idea that artificial intelligence may one day become smarter than humans. -/- According to the theory, advances in AI — specifically of the machine learning type that’s able to take on new information and rewrite its code accordingly — will eventually catch up with the wetware of the biological brain. (...) In this interpretation of events, every AI advance from Jeopardy-winning IBM machines to the massive AI language model GPT-3 is taking humanity one step closer to an existential threat. We’re literally building our soon-to-be-sentient successors. -/- Except that it will never happen. At least, according to the authors of the new book Why Machines Will Never Rule the World: Artificial Intelligence without Fear. (shrink)

Friedrich Nietzsche in seinen Werken ist ein unveränderter, hochwertiger Nachdruck der Originalausgabe aus dem Jahr 1894. Hansebooks ist Herausgeber von Literatur zu unterschiedlichen Themengebieten wie Forschung und Wissenschaft, Reisen und Expeditionen, Kochen und Ernährung, Medizin und weiteren Genres. Der Schwerpunkt des Verlages liegt auf dem Erhalt historischer Literatur. Viele Werke historischer Schriftsteller und Wissenschaftler sind heute nur noch als Antiquitäten erhältlich. Hansebooks verlegt diese Bücher neu und trägt damit zum Erhalt selten gewordener Literatur und historischem Wissen auch für die Zukunft (...) bei. (shrink)

El presente artículo intentará mostrar el punto de transición que se da en el pensamiento merleau-pontyano entre un primado de la percepción y una rehabilitación ontológica de lo sensible. Dicho punto se refiere a una prioridad ontológica del mundo percibido, el cual pone de manifiesto el paso hacia una ontología de lo percibido, hacia la descripción del ser de lo percibido. Con ello podremos dar cuenta de la exposición del propio autor del modo en cómo la percepción puede ser entendida (...) como un verdadero acceso al ser: el primado de la percepción abarcaría una prioridad propiamente ontológica. El objetivo principal de esta investigación se situará en la exposición de una red conceptual que nos permita dar cuenta del fenómeno perceptivo que no sólo nos proporciona el mundo, tal y como se le aparece al sujeto, sino que intenta ir más allá del aspecto visible, intentará dar cuenta del ser de lo percibido. Expresar, en definitiva, este circuito de incorporación donde se hallan inseridos tanto el ser como el sujeto, donde hay una co-pertenencia entre ambos. (shrink)

In der vorliegenden Arbeit geht es um Entscheidungsspielräume und Entscheidungsprozesse von hauptamtlichen Hospizmitarbeiterinnen und -mitarbeitern in ethisch relevanten Situationen. Wie sich diese Prozesse und Spielräume konkret in der Praxis gestalten, erforschten wir mittels einer qualitativen Studie, die wir in drei Hospizen in Nordrhein-Westfalen durchführten. Als ethische Haupthandlungsfelder nannten die befragten Pflegekräfte die Medikation in der präfinalen Phase, den Umgang mit terminaler Sedierung und mit der Flüssigkeitszufuhr und Ernährung am Lebensende. Entscheidungen innerhalb dieser Felder werden i. d. R. kollektiv getroffen. Die (...) individuellen Entscheidungsspielräume der Mitarbeiterinnen und Mitarbeiter betreffen hauptsächlich den Pflegestil und das auf den Gast bezogene Zeitmanagement. Die Gestaltung dieser Entscheidungsspielräume hängt dabei häufig weniger von einem Rahmenkonzept ab, wie es Leitbilder oder Ethikkodizes nahelegen könnten, als vielmehr von einer Anspruchsanpassung der Pflegenden in der Praxis, wie es Modelle eingeschränkter Rationalität nahelegen. Damit übernehmen die Pflegekräfte in einem Hospiz eine sich selbst beratende wie korrigierende Funktion in ethischen Fragen, die angesichts des individuellen Sterbens eines Gastes immer wieder von Neuem ausgehandelt werden. (shrink)

Research on the ethics of algorithms has grown substantially over the past decade. Alongside the exponential development and application of machine learning algorithms, new ethical problems and solutions relating to their ubiquitous use in society have been proposed. This article builds on a review of the ethics of algorithms published in 2016, 2016). The goals are to contribute to the debate on the identification and analysis of the ethical implications of algorithms, to provide an updated analysis of epistemic and normative (...) concerns, and to offer actionable guidance for the governance of the design, development and deployment of algorithms. (shrink)

Research on the ethics of algorithms has grown substantially over the past decade. Alongside the exponential development and application of machine learning algorithms, new ethical problems and solutions relating to their ubiquitous use in society have been proposed. This article builds on a review of the ethics of algorithms published in 2016, 2016). The goals are to contribute to the debate on the identification and analysis of the ethical implications of algorithms, to provide an updated analysis of epistemic and normative (...) concerns, and to offer actionable guidance for the governance of the design, development and deployment of algorithms. (shrink)

Die Reihe Beihefte zur Zeitschrift für die neutestamentliche Wissenschaft (BZNW) ist eine der ältesten undrenommiertesten internationalen Buchreihen zur neutestamentlichen Wissenschaft. Seit 1923 publiziert sie wegweisende Forschungsarbeiten zum frühen Christentum und angrenzenden Themengebieten. Die Reihe ist historisch-kritisch verankert und steht neuen methodischen Ansätzen, die unser Verständnis des Neuen Testaments befördern, gleichfalls offen gegenüber.

Because of its practical advantages, machine learning (ML) is increasingly used for decision-making in numerous sectors. This paper demonstrates that the integral characteristics of ML, such as semi-autonomy, complexity, and non-deterministic modeling have important ethical implications. In particular, these characteristics lead to a lack of insight and lack of comprehensibility, and ultimately to the loss of human control over decision-making. Errors, which are bound to occur in any decision-making process, may lead to great harm and human rights violations. It is (...) important to have a principled way of assigning responsibility for such errors. The integral characteristics of ML, however, pose serious difficulties in defining responsibility and regulating ML decision-making. First, we elaborate on these characteristics and their epistemic and ethical implications. We then analyze possible general strategies for resolving the assignment of moral responsibility and show that, due to the specific way in which ML functions, each potential solution is problematic, whether we assign responsibility to humans, machines, or using hybrid models. Then, we shift focus on an alternative approach that bypasses moral responsibility and attempts to define legal liability independently through solutions such as informed consent and the no-fault compensation system. Both of these solutions prove unsatisfactory because they leave too much room for potential abuses of ML decision-making. We conclude that both ethical and legal solutions are fraught with serious difficulties. These difficulties prompt us to re-weigh the costs and benefits of using ML for high-stake decisions. (shrink)

Not all homo sapiens are human subjects. This paper explores the lived experience of homo sapiens but not human that I call “lived flesh.” A lived experience/distinction that shouldn’t be possible on Merleau-Ponty’s account of human subjectivity in Phenomenology of Perception and “The Intertwining – The Chiasm.” The use of flesh is deliberate and emerges from my engagement with Merleau-Ponty’s Phenomenology of Perception and “The Intertwining – The Chiasm” through Toni Morrison’s Beloved, Hortense Spillers’ “Interstices: A Small Drama of Words” (...) and “Mama’s Baby, Papa’s Maybe: An American Grammar Book,” Amber Musser’s Sensual Excess: Queer Femininity and Brown Jouissance, and Audre Lorde’s Zami: A New Spelling of My Name. The affective, experiential, and ethical practices of american Blackwomxn in these texts problematize Merleau-Ponty’s account of human subjectivity and his account of the generality of Being (“The Intertwining – The Chiasm”). Merleau-Ponty’s effacement of raced, sexed, and gendered difference results in a construct of the human subject that cannot include all homo sapiens. (shrink)

The intention of this paper is to point to the dilemma humanity may face in light of AI advancements. The dilemma is whether to create a world with less evil or maintain the human status of moral agents. This dilemma may arise as a consequence of using automated decision-making systems for high-stakes decisions. The use of automated decision-making bears the risk of eliminating human moral agency and autonomy and reducing humans to mere moral patients. On the other hand, it also (...) has the potential to bring tremendous benefits to humanity by decreasing human-induced harm in the world. After presenting how this dilemma may arise, I explore general avenues for addressing it. I will argue that we do not have to solve this dilemma in an all-or-nothing fashion and that a more nuanced approach may be suitable. However, the main point I want to highlight is that we need to have a principled way of addressing this dilemma, which is currently missing. (shrink)

L'ingegneria concettuale è una branca della filosofia caratterizzata da un approccio normativo nei confronti della rappresentazione. Assunzione fondamentale è che i nostri dispositivi rappresentazionali possano essere difettosi. Si configura dunque come l'attività che consiste nell'identificare i difetti in tali dispositivi e mettere in atto strategie di miglioramento. Verranno illustrate le questioni fondamentali a cui una teoria di ingegneria concettuale deve rispondere: in cosa consiste esattamente questa attività? Come possiamo attuarla? Quali meccanismi regolano la formazione dei dispositivi rappresentazionali? Possiamo influire su (...) tali meccanismi? Verrà inoltre presentata un'obiezione all'ingegneria concettuale e varie risposte. -/- Conceptual engineering is a branch of philosophy characterised by a normative approach towards representation. The fundamental assumption of it is that our representational devices can be defective. Conceptual engineering is then the activity consisting of identifying the defects of such devices and putting in place ameliorative strategies. This paper illustrates the fundamental issues for a theory of conceptual engineering: what does this activity consist of? How can we implement it? What mechanisms regulate the formation of representational devices? Can we have an influence over those mechanisms? Moreover, it will be presented an objection to conceptual engineering and various responses to it. (shrink)