Recently, the United Kingdom Supreme Court decided that only natural persons can be considered inventors. A year before, the United States Court of Appeals for the Federal Circuit issued a similar decision. In fact, so have many the courts all over the world. This Article analyses these decisions, argues that the courts got it right, and finds that artificial inventorship is at odds with patent law doctrine, theory, and philosophy. The Article challenges the intellectual property (IP) post-humanists, exposing the (...) analytical and normative perils of their argumentation, and recommends against getting rid of the nominally central place of humans in the law. This response to IP post-humanism rests in equal measure on patent doctrine, legal causation, and the mythology which creates and justifies the law. (shrink)

Concept Progress is a fusion of science fiction and philosophy. It is a thesis on metaphysics that stretches beyond the scope of modern science and scratches many of our curious itches. The thesis is complemented by short and loosely tied sci-fi stories that make its conceptualizations come to life. ​ The central theme throughout is that progress is a driving force in human evolution. This recurring viewpoint has previously stirred much debate. However, as we escalate through the twenty-first century, the (...) evidence is plentiful. Concept Progress offers a fresh perspective into the topic, citing humanity's ongoing accomplishments as a convincing piece of that evidence. In the book, we celebrate ourselves for our achievements, challenge our perceived limits, and conclude that progress will eventually produce the most evolved life form. In so doing, we look back to the beginning of time and circle forward to a time that is farther away than the current age of the universe. ​ While the tone of the book's body resembles that of a philosophical prose, with each chapter, the reader realizes more and more that the narrative is actually one of science fiction. The intent of the book's structure and approach is manifold. ​ First, it is safe to say that any literature that points to the future is already, by definition, a work of fiction—no matter how serious it tries to sound. Imagining future technologies, foreseeing the next stages of human evolution, and exploring the realm of the highest dimension surely makes it a science fiction. ​ Second, the book is a collection of concepts—abstract notions of the mind that reflect our grasp on certain aspects of reality. It is also a play on those concepts, exposing how our progressive understanding of these notions can gradually be transcended. Each chapter starts with a sketch of a particular concept whose humanistic yet quantum mechanical context lets us identify with it and be mystified by it. From the concepts of sound and light to the concepts of consciousness and coexistence, each concept tale depicts a personal expression of our mutual worldview. ​ Third, each one of the ten chapters concludes with a science fiction story. These stories project the theme further and subtly point to each other. As we connect the dots from one story to another, the outline reveals a world that makes us wonder whether we are headed toward its future or whether we will bypass it as an alternate universe. In one story, we meet the inventor of mind-reading technology while in another story, we meet an artificial life form that will be made possible by this technology. Yet another story is about the time-traveling mind of an astrophysicist whose life's work has impacts on whole timelines, as revealed by a different story. In the end, it all comes together with the final piece of the puzzle completing not only the short story series, but also the novel as a whole. ​ Each three-part chapter is a triad with a distinct purpose in mind. We begin the journey with our own curiosity. This basic emotion allows us to open the door to that which we are so curiously seeking. Essentially, that covers everything. In questioning the entirety of existence, we commence with the premise that it is the element of life that sends us on a quest for meaning. So we review the trend of life's evolution on Earth from its roots to the present day and follow this trend into the distant future. The process of evolutionary development leads us to a recipe for one's own personal progress, which is comprised of physical, mental, and spiritual ingredients. It soon becomes clear that a species can change only insofar as its individual members embrace this change. And we realize that our choice in the matter has impacts not only on our own future, but also on the future of everyone who shares our timeline. ​ In some ways, Concept Progress is a modern reflection of Charles Darwin's revolutionary theory of evolution. In other ways, it is an encouraging observation of our humble human existence. As we widen the time scale and follow this evolutionary trend from biological, social, and cosmic angles, the concepts of evolution and progress slowly but surely become synonymous. (shrink)

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

Artificial Intelligence is at a turning point, with a substantial increase in projects aiming to implement sophisticated forms of human intelligence in machines. This research attempts to model specific forms of intelligence through brute-force search heuristics and also reproduce features of human perception and cognition, including emotions. Such goals have implications for artificial consciousness, with some arguing that it will be achievable once we overcome short-term engineering challenges. We believe, however, that phenomenal consciousness cannot be implemented in machines. (...) This becomes clear when considering emotions and examining the dissociation between consciousness and attention in humans. While we may be able to program ethical behavior based on rules and machine learning, we will never be able to reproduce emotions or empathy by programming such control systems—these will be merely simulations. Arguments in favor of this claim include considerations about evolution, the neuropsychological aspects of emotions, and the dissociation between attention and consciousness found in humans. Ultimately, we are far from achieving artificial consciousness. (shrink)

In the field of machine consciousness, it has been argued that in order to build human-like conscious machines, we must first have a computational model of qualia. To this end, some have proposed a framework that supports qualia in machines by implementing a model with three computational areas (i.e., the subconceptual, conceptual, and linguistic areas). These abstract mechanisms purportedly enable the assessment of artificial qualia. However, several critics of the machine consciousness project dispute this possibility. For instance, Searle, (...) in his Chinese room objection, argues that however sophisticated a computational system is, it can never exhibit intentionality; thus, would also fail to exhibit consciousness or any of its varieties. This paper argues that the proposed architecture mentioned above answers the problem posed by Searle, at least in part. Specifically, it argues that we could reformulate Searle’s worries in the Chinese room in terms of the three-stage artificial qualia model. And by doing so, we could see that the person doing all the translations in the room could realize the three areas in the proposed framework. Consequently, this demonstrates the actualization of self-consciousness in machines. (shrink)

Conventional methods of genetic engineering and more recent genome editing techniques focus on identifying genetic target sequences for manipulation. This is a result of historical concept of the gene which was also the main assumption of the ENCODE project designed to identify all functional elements in the human genome sequence. However, the theoretical core concept changed dramatically. The old concept of genetic sequences which can be assembled and manipulated like molecular bricks has problems in explaining the natural genome-editing competences (...) of viruses and RNA consortia that are able to insert or delete, combine and recombine genetic sequences more precisely than random-like into cellular host organisms according to adaptational needs or even generate sequences de novo. Increasing knowledge about natural genome editing questions the traditional narrative of mutations (error replications) as essential for generating genetic diversity and genetic content arrangements in biological systems. This may have far-reaching consequences for our understanding of artificial genome editing. (shrink)

This paper investigates the concept of behavioral autonomy in Artificial Life by drawing a parallel to the use of teleological notions in the study of biological life. Contrary to one of the leading assumptions in Artificial Life research, I argue that there is a significant difference in how autonomous behavior is understood in artificial and biological life forms: the former is underlain by human goals in a way that the latter is not. While behavioral traits can be (...) explained in relation to evolutionary history in biological organisms, in synthetic life forms behavior depends on a design driven by a research agenda, further shaped by broader human goals. This point will be illustrated with a case study on a synthetic life form. Consequently, the putative epistemic benefit of reaching a better understanding of behavioral autonomy in biological organisms by synthesizing artificial life forms is subject to doubt: the autonomy observed in such artificial organisms may be a mere projection of human agency. Further questions arise in relation to the need to spell out the relevant human aims when addressing potential social or ethical implications of synthesizing artificial life forms. (shrink)

Book Description (Blurb): Cognitive Design for Artificial Minds explains the crucial role that human cognition research plays in the design and realization of artificial intelligence systems, illustrating the steps necessary for the design of artificial models of cognition. It bridges the gap between the theoretical, experimental and technological issues addressed in the context of AI of cognitive inspiration and computational cognitive science. -/- Beginning with an overview of the historical, methodological and technical issues in the field of (...) Cognitively-Inspired Artificial Intelligence, Lieto illustrates how the cognitive design approach has an important role to play in the development of intelligent AI technologies and plausible computational models of cognition. Introducing a unique perspective that draws upon Cybernetics and early AI principles, Lieto emphasizes the need for an equivalence between cognitive processes and implemented AI procedures, in order to realise biologically and cognitively inspired artificial minds. He also introduces the Minimal Cognitive Grid, a pragmatic method to rank the different degrees of biologically and cognitive accuracy of artificial systems in order project and predict their explanatory power with respect to the natural systems taken as source of inspiration. -/- Providing a comprehensive overview of cognitive design principles in constructing artificial minds, this text will be essential reading for students and researchers of artificial intelligence and cognitive science. (shrink)

This project has been supported by the Australian Government through the Australian Research Council (project number CS170100008); the Department of Industry, Innovation and Science; and the Department of Prime Minister and Cabinet. ACOLA collaborates with the Australian Academy of Health and Medical Sciences and the New Zealand Royal Society Te Apārangi to deliver the interdisciplinary Horizon Scanning reports to government. The aims of the project which produced this report are: 1. Examine the transformative role that artificial (...) intelligence may play in different sectors of the economy, including the opportunities, risks and challenges that advancement presents. 2. Examine the ethical, legal and social considerations and frameworks required to enable and support broad development and uptake of artificial intelligence. 3. Assess the future education, skills and infrastructure requirements to manage workforce transition and support thriving and internationally competitive artificial intelligence industries. (shrink)

The declared goal of this paper is to fill this gap: “... cognitive systems research needs questions or challenges that define progress. The challenges are not (yet more) predictions of the future, but a guideline to what are the aims and what would constitute progress.” – the quotation being from the project description of EUCogII, the project for the European Network for Cognitive Systems within which this formulation of the ‘challenges’ was originally developed (http://www.eucognition.org). So, we stick out (...) our neck and formulate the challenges for artificial cognitive systems. These challenges are articulated in terms of a definition of what a cognitive system is: a system that learns from experience and uses its acquired knowledge (both declarative and practical) in a flexible manner to achieve its own goals. (shrink)

Since the second half of the XXth century, researchers in cybernetics and AI, neural nets and connectionism, Artificial Life and new robotics have endeavoured to build different machines that could simulate functions of living organisms, such as adaptation and development, problem solving and learning. In this book these research programs are discussed, particularly as regard the epistemological issues of the behaviour modelling. One of the main novelty of this book consists of the fact that certain projects involving the building (...) of simulative machine models before the advent of cybernetics are been investigated for the first time, on the basis of little known, and sometimes completely forgotten or unpublished, texts and figures. These pre-cybernetics projects can be considered as steps toward the “discovery” of a modelling methodology that has been fully developed by those more recent research programs, and that shares some of their central goals and key methodological proposals. -/- More info in Springer link: http://www.springer.com/new+%26+forthcoming+titles+%28default%29/book/978-1-4020-0606-7 -/- This book is the English translation of La scoperta dell'artificiale, Dunod/Masson, Milan, 1998. (shrink)

What is the essential ingredient of creativity that only humans – and not machines – possess? Can artificial intelligence help refine the notion of creativity by reference to that essential ingredient? How / do we need to redefine our conceptual and legal frameworks for rewarding creativity because of this new qualifying – actually creatively significant – factor? -/- Those are the questions tackled in this essay. The author’s conclusion is that consciousness, experiential states (such as a raw feel of (...) what is like to be creating) and propositional attitudes (such as intention to instigate change by creating) appear pivotal to qualifying an exploratory effort as creativity. Artificial intelligence systems would supposedly be capable of creativity if they could exhibit such states, which philosophers and computer scientists posit as conceptually admissible and practically possible. -/- The existing legal framework rewards creative endeavours by reference to the novelty or originality of the end result. But this bar is not insurmountable for artificial intelligence. Technically speaking, artificial intelligence systems can create works that are novel and/or original. Are we then prepared to grant to those systems the legal status of “creators” in their own right? Whom should the associated benefits and rewards be assigned to? How does the position change (or not) based on the qualifying factors set out above? Should – and if, how – the general public benefit from inventions / creative works of artificial intelligence systems if troves of personal data are the key component that fueled and informed creative choices? (shrink)

Whether the hands-on experience of creating inventions can promote Students’ interest in pursuing a science, technology, engineering, and mathematics (STEM) career has not been extensively studied. In a quantitative study, we drew on the attitude-behavior-outcome framework to explore the correlates between hands-on making attitude, epistemic curiosities, and career interest. This study targeted students who joined the selection competition for participating in the International Exhibition of Young Inventors (IEYI) in Taiwan. The objective of the invention exhibition is to encourage young students (...) to make innovative projects by applying STEM knowledge and collaborative design. We collected 220 valid data from participants in the 2021 Taiwan IEYI selection competition and conducted a confirmatory factor analysis and structural equation modeling to test the hypotheses. Results indicated that: (1) hands-on making attitude was positively related to two types of epistemic curiosity; (2) interest-type epistemic curiosity (IEC) and deprivation-type epistemic curiosity (DEC) were positively associated with STEM career interest; additionally, DEC had a higher coefficient on STEM career interest than IEC; (3) both types of EC had a mediating role between hands-on making attitude and STEM career interest. It is expected that encouraging students to participate in invention exhibition competitions can raise both types of EC and increase their interest in pursuing STEM careers. (shrink)

In this paper, we focus on the most efficacious AI applications for life extension and anti-aging at three expected stages of AI development: narrow AI, AGI and superintelligence. First, we overview the existing research and commercial work performed by a select number of startups and academic projects. We find that at the current stage of “narrow” AI, the most promising areas for life extension are geroprotector-combination discovery, detection of aging biomarkers, and personalized anti-aging therapy. These advances could help currently living (...) people reach longevity escape velocity and survive until more advanced AI appears. When AI comes close to human level, the main contribution to life extension will come from AI integration with humans through brain-computer interfaces, integrated AI assistants capable of autonomously diagnosing and treating health issues, and cyber systems embedded into human bodies. Lastly, we speculate about the more remote future, when AI reaches the level of superintelligence and such life-extension methods as uploading human minds and creating nanotechnological bodies may become possible, thus lowering the probability of human death close to zero. We suggest that medical AI based superintelligence could be safer than, say, military AI, as it may help humans to evolve into part of the future superintelligence via brain augmentation, uploading, and a network of self-improving humans. Medical AI’s value system is focused on human benefit. (shrink)

Because of advanced automation, data exchange, and cyber-physical systems, traditional project risk management strategies are losing their effectiveness in the era of Industry 4.0. This study investigates how integrating Industry 4.0 technology into project risk management frameworks can have real-world implications. Using technologies like artificial intelligence (AI), big data analytics, and the Internet of Things (IoT), it proposes a new framework that enhances risk identification, assessment, and mitigation methods. In order to demonstrate how Industry 4.0 is transforming (...) risk management practices, this article examines real-world case studies and industry implementations. The framework addresses significant opportunities and challenges to provide practitioners with useful insights for adapting to the evolving technological context. The findings suggest that incorporating Industry 4.0 technologies can significantly improve risk management efficiency and project outcomes, offering a pathway for organizations to navigate the complexities of modern project environments. (shrink)

In this paper I argue that the search for explainable models and interpretable decisions in AI must be reformulated in terms of the broader project of offering a pragmatic and naturalistic account of understanding in AI. Intuitively, the purpose of providing an explanation of a model or a decision is to make it understandable to its stakeholders. But without a previous grasp of what it means to say that an agent understands a model or a decision, the explanatory strategies (...) will lack a well-defined goal. Aside from providing a clearer objective for XAI, focusing on understanding also allows us to relax the factivity condition on explanation, which is impossible to fulfill in many machine learning models, and to focus instead on the pragmatic conditions that determine the best fit between a model and the methods and devices deployed to understand it. After an examination of the different types of understanding discussed in the philosophical and psychological literature, I conclude that interpretative or approximation models not only provide the best way to achieve the objectual understanding of a machine learning model, but are also a necessary condition to achieve post hoc interpretability. This conclusion is partly based on the shortcomings of the purely functionalist approach to post hoc interpretability that seems to be predominant in most recent literature. (shrink)

The aim of this thesis is to advance a philosophically justifiable account of Artificial Moral Agency (AMA). Concerns about the moral status of Artificial Intelligence (AI) traditionally turn on questions of whether these systems are deserving of moral concern (i.e. if they are moral patients) or whether they can be sources of moral action (i.e. if they are moral agents). On the Organic View of Ethical Status, being a moral patient is a necessary condition for an entity to (...) qualify as a moral agent. This view claims that because artificial agents (AAs) lack sentience, they cannot be proper subjects of moral concern and hence cannot be considered to be moral agents. I raise conceptual and epistemic issues with regards to the sense of sentience employed on this view, and I argue that the Organic View does not succeed in showing that machines cannot be moral patients. Nevertheless, irrespective of this failure, I also argue that the entire project is misdirected in that moral patiency need not be a necessary condition for moral agency. Moreover, I claim that whereas machines may conceivably be moral patients in the future, there is a strong case to be made that they are (or will very soon be) moral agents. Whereas it is often argued that machines cannot be agents simpliciter, let alone moral agents, I claim that this argument is predicated on a conception of agency that makes unwarranted metaphysical assumptions even in the case of human agents. Once I have established the shortcomings of this “standard account”, I move to elaborate on other, more plausible, conceptions of agency, on which some machines clearly qualify as agents. Nevertheless, the argument is still often made that while some machines may be agents, they cannot be moral agents, given their ostensible lack of the requisite phenomenal states. Against this thesis, I argue that the requirement of internal states for moral agency is philosophically unsound, as it runs up against the problem of other minds. In place of such intentional accounts of moral agency, I provide a functionalist alternative, which makes conceptual room for the existence of AMAs. The implications of this thesis are that at some point in the future we may be faced with situations for which no human being is morally responsible, but a machine may be. Moreover, this responsibility holds, I claim, independently of whether the agent in question is “punishable” or not. (shrink)

Traditional project risk management techniques are becoming less and less effective in the age of Industry 4.0, which is defined by sophisticated automation, data interchange, and cyber-physical systems. It suggests a new framework that improves risk detection, assessment, and mitigation techniques by utilising technology like artificial intelligence (AI), big data analytics, and the Internet of Things (IoT). This paper illustrates how Industry 4.0 is revolutionising risk management procedures by looking at actual case studies and industry implementations. The framework (...) offers practical insights for practitioners looking to adjust to the changing technological landscape by addressing important possibilities and obstacles. According to the research, implementing Industry 4.0 technologies can greatly enhance project results and risk management effectiveness, providing a means for businesses to handle the challenges of contemporary project environments. (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)

This article analyzes emerging artificial intelligence (AI)-enhanced lie detection systems from ethical and human resource (HR) management perspectives. I show how these AI enhancements transform lie detection, followed with analyses as to how the changes can lead to moral problems. Specifically, I examine how these applications of AI introduce human rights issues of fairness, mental privacy, and bias and outline the implications of these changes for HR management. The changes that AI is making to lie detection are altering the (...) roles of human test administrators and human subjects, adding machine learning-based AI agents to the situation and establishing invasive data collection processes as well as introducing certain biases in results. I project that the potentials for pervasive and continuous lie detection initiatives (“truth machines”) are substantial, displacing human-centered efforts to establish trust and foster integrity in organizations. I argue that if it is possible for HR managers to do so, they should cease using technologically-based lie detection systems entirely and work to foster trust and accountability on a human scale. However, if these AI-enhanced technologies are put into place by organizations by law, agency mandate, or other compulsory measures, care should be taken that the impacts of the technologies on human rights and wellbeing are considered. The article explores how AI can displace the human agent in some aspects of lie detection and credibility assessment scenarios, expanding the prospects for inscrutable, “black box” processes and novel physiological constructs (such as “biomarkers of deceit”) that may increase the potential for such human rights concerns as fairness, mental privacy, and bias. Employee interactions with autonomous lie detection systems rather with than human beings who administer specific tests can reframe organizational processes and rules concerning the assessment of personal honesty and integrity. The dystopian projection of organizational life in which analyses and judgments of the honesty of one’s utterances are made automatically and in conjunction with one’s personal profile provides unsettling prospects for the autonomy of self-representation. (shrink)

As autonomous mobile robots (AMRs) begin living in the home, performing service tasks and assisting with daily activities, their actions will have profound ethical implications. Consequently, AMRs need to be outfitted with the ability to act morally with regard to human life and safety. Yet, in the area of robotics where morality is a relevant field of endeavor (i.e. human-robot interaction) the sub-discipline of morality does not exist. In response, the Utilibot project seeks to provide a point of initiation (...) for the implementation of ethics in an AMR. The Utilibot is a decision-theoretic AMR guided by the utilitarian notion of the maximization of human well-being. The core ethical decision-making capacity of the Utilibot consists of two dynamic Bayesian networks that model human and environmental health, a dynamic decision network that accounts for decisions and utilities, and a Markov decision process (MDP) that decomposes the planning problem to solve for the optimal course of action to maximize human safety and well-being. (shrink)

The papers in the following volume are the outcome of a three-year long interdisciplinary research project. The project began with an in-person meeting hosted and funded by the Daimler und Benz Stiftung in Germany in March 2020 (the world was shutting down one nation at a time as we met). During the pandemic we continued to meet monthly online with support from Memorial University of Newfoundland. From the beginning it was the goal of the Working Group on Intelligence (...) (WGI), as we called ourselves, to broaden and deepen the AI debate with a more nuanced understanding of intelligence than is common in cognitive and computer science discussions of AI. We wished to draw on the history of philosophy, ecology, and the philosophy of mind to establish that intelligence is meant in many senses, to use an Aristotelian expression. The clarification of these various meanings is essential to the discussion around the ethics of AI, especially the question concerning the possibility of strong AI or Artificial General Intelligence. (shrink)

Since the early 1990's the value sensitive design (VSD) approach has been a continually burgeoning design methodology for technological innovation. VSD is commonly described as a "principled approach" to technology design, given that it is explicitly orientated towards designing technologies for human values, rather than sidelining them to ad hoc and/or ex post facto design. However, in much of its near three-decades-long development, the VSD approach has mostly been adopted as a conceptual framework to assess existing technologies and to explore (...) how the consequences of the technology's development could have been influenced positively if VSD was adopted early on and throughout the design process (Friedman et al. 2002). Similarly, VSD has been adopted as a conceptual framework for analysing how future speculative technologies like molecular manufacturing (Umbrello 2019) and advanced artificial intelligence systems can be directed towards positive futures (Umbrello and van de Poel 2021). Yet, despite the benefits of these endeavours and VSD being an approach that can be adapted to any given design domain, it has yet to be widely appropriated in existing design spaces as a primary design approach. In this short paper, we aim to fill this lacuna by framing VSD as a toolkit that can be adopted by existing design teams rather than a wholesale approach. In particular, we describe how VSD maps seamlessly onto agile workflows, an approach to project management that is widely adopted globally. By doing so, we hope that the VSD approach will likewise be more attractive and thus adopted more broadly. As a consequence, a more explicit orientation towards designing technologies for human values will follow. (shrink)

In its two parts, this study intends to reconstruct with some detail the fiasco of the Artificial Intelligence research project and the devastating critique carried out against it by Hubert Dreyfus in his magnum opus What Computers Still Can’t Do (1972, 1979, 1992). Part of these consequences is the emergence within this specialized field of a group of scholars who have called themselves ‘Heideggerian’. This definition shall be dealt with and criticized in the second part of this study. (...) In this first part, we go on to analize (i) the bizarre dreams and false expectations of AI researchers, and (ii) Dreyfus’ own criticism and its definitive thrust of phenomenological nature. (shrink)

Recent research into the nature of self in artificial and biological systems raises interest in a uniquely determining immutable sense of self, a “metaphysical ‘I’” associated with inviolable personal values and moral convictions that remain constant in the face of environmental change, distinguished from an object “me” that changes with its environment. Complementary research portrays processes associated with self as multimodal routines selectively enacted on the basis of contextual cues informing predictive self or world models, with the notion of (...) the constant, per-vasive and invariant sense of self associated with a multistable attractor set aiming to ensure personal integrity against threat of disintegrative change. This paper proposes that an immutable sense of self emerges as a global attractor which can be described as a project ideal self-situation embodied in frontal medial processes during more or less normal adolescent development, and that thereafter serves to orient agency in the more or less free development of embodied potentials over the life course in effort to realize project conditions, phenomenally identified with the felt pull towards this end as purpose of and source of meaning in life. So oriented, life-long self-development aims to embody solutions to problems at different timescales depending on this embodied purpose, ultimately in the service of evolutionary processes securing organism populations against threats of disintegrative change over timespans far beyond that of the individual. After characterizing the target sense of self, research circling this target is briefly surveyed. Self as global project and developmental neural correlates are proposed. Then, the paper discusses some implications for research in biological and artificial systems. Building from earlier work in cognitive neurorobotics, discussion affirms the value of reinforcement rituals including prayer in metaphysical self-development, considers implications for value alignment and rights associated with free will in the context of artificial intelligence and robot religion, and concludes by emphasizing the importance of self-development toward project ideals as source of meaning in life in the current social-political environment. (shrink)

Lilly was one of the greatest scientists and pioneers on the limits of human possibility but after his death a collective amnesia has descended and he is now almost forgotten. His Wiki is good but inevitably incomplete so here are a few missing details and viewpoints. Lilly was a generation (or more) ahead of his time. He is almost single-handedly responsible for the great interest in dolphins (which led to the Marine Mammal Protection Act in the USA and helped to (...) found the animal rights movement). In 1958 he noted that the brains of elephants and cetaceans were larger than ours, that we should not abuse them and that it was one our most important projects to communicate with them. He invented sensory isolation tanks (at NIMH in 1954) and used them extensively with and without powerful psychoactive drugs at a time when it was thought that either the brain would shut down or one would go insane if external stimuli were eliminated. He created methods for implanting electrodes in mammal brains and was planning to do it to himself. He was one of the first to make serious use of computers in bioscience research and created the hardware and software to make the first attempts to communicate with dolphins. He self experimented with dangerous physiological investigations in high altitude medicine for the military during WW2, took LSD with dolphins and movie stars, submitted himself to the rigors of various forms of yoga and of Arica training, and taught classes at Esalen. He was a computer pioneer who forsaw the rapid advances in A.I. and it's inevitable clash with humans. He was the first one to investigate the bizarre psychedelic ketamine (" vitamin K "), and his results (published in the two last chapters of his book `The Scientist`) are still the best data on the dose/effect relation of any psychedelic on one person. It cured his lifelong daily migraine headaches (see http://www.conspiracyarchive.com/UFOs/Gorightly.htm). And all this happened before most of us were born! He had courage, honesty and integrity that is rare anywhere and almost nonexistent in science. His goal was to find the ultimate truth about everything and he went about as far as anyone ever has. He had little patience with the stupid and hypocritical games one has to play to fit into monkey society. Of course the reaction of the establishment was predictable. He left the NIMH and was never given any government or academic support for the last 35 years of his life. His paper and comments at a conference on sensory deprivation were removed from the published version. He was not invited to government sponsored symposia on dolphins (he had refused to help develop them as weapons), though he clearly knew more about them than anyone in the world. He liked to live and work on the edge and few could keep up with him, as his books make clear. If you have read some of his other books it will be much easier going. He was a pioneer in consciousness research and pushed the boundaries of our understanding of who we are and what we might become. Among other things he catalogs the various states reached by drugs, meditation, and isolation, tries to determine their significance, and suggests how to use them. I very briefly review and comment on his life and work. -/- Those interested in all my writings in their most recent versions may download from this site my e-book ‘Philosophy, Human Nature and the Collapse of Civilization Michael Starks (2016)- Articles and Reviews 2006-2016’ by Michael Starks First Ed. 662p (2016). -/- All of my papers and books have now been published in revised versions both in ebooks and in printed books. -/- Talking Monkeys: Philosophy, Psychology, Science, Religion and Politics on a Doomed Planet - Articles and Reviews 2006-2017 (2017) https://www.amazon.com/dp/B071HVC7YP. -/- The Logical Structure of Philosophy, Psychology, Mind and Language in Ludwig Wittgenstein and John Searle--Articles and Reviews 2006-2016 (2017) https://www.amazon.com/dp/B071P1RP1B. -/- Suicidal Utopian Delusions in the 21st century: Philosophy, Human Nature and the Collapse of Civilization - Articles and Reviews 2006-2017 (2017) https://www.amazon.com/dp/B0711R5LGX -/- . (shrink)

Thanks to mounting discussion about projected technologies’ possibly altering the species mentally and physically, philosophical investigation of what human beings are proceeds robustly. Many thinkers contend that whatever we are has little to do with how we should behave. Yet, tampering with what the human being is may tread upon human rights to be whatever one is. Rights given in widely recognized documents such as the U.N. Declaration of the Rights of Indigenous Peoples assume what humans are and need depends (...) upon ontological assumptions about human existence. Godman turns to human ontology—just what kind of beings humans are (from an angle distinct from the other two books) and how these play into rights. She is concerned with how well the social sciences accord with what we are. Gunkel homes in on a more specific moral topic than Godman's general concern with identity’s role in rights: automata moral status and rights. He enjoins us to inquire into what human rights are before we take on the new technologies’ challenge to it. Schneider’s Artificial You, while not explicitly about rights, poses a rights quandary. Certain individuals with reputable resources and practical backing explicitly seek to evolve the species as they see fit. The urgency among these works concerns how we need a sharper idea of what we are, how we should act and be treated, and how our rights fare among potential human improvements. (shrink)

This project aims to develop a robust system capable of predicting the prices of used cars based on various factors such as make, model, year, mileage, location, and condition. The rising demand for second-hand vehicles has led to the need for accurate pricing models, and this project utilizes machine learning techniques, particularly Artificial Neural Networks (ANNs), to address this challenge. The system is trained on a comprehensive dataset of used car listings, incorporating key features that impact car (...) prices. Various machine learning algorithms, including linear regression, decision trees, and random forest, are tested and compared to assess their predictive accuracy. However, the core model relies on ANNs for its ability to capture complex, non-linear relationships in the data. By utilizing deep learning, the model can learn intricate patterns and make more accurate predictions, especially in cases where traditional models might struggle. The evaluation of the system is performed using standard regression metrics such as Mean Squared Error (MSE) and R-squared to ensure its reliability and performance. This predictive model not only provides a valuable tool for both buyers and sellers in the used car market but also demonstrates the potential of artificial intelligence in making data-driven decisions in the automotive industry. (shrink)

In recent years, a trend in AI research has started to pursue human-level, general artificial intelli-gence (AGI). Although the AGI framework is characterised by different viewpoints on what intelligence is and how to implement it in artificial systems, it conceptualises intelligence as flexible, general-purposed, and capable of self-adapting to different contexts and tasks. Two important ques-tions remain open: a) should AGI projects simu-late the biological, neural, and cognitive mecha-nisms realising the human intelligent behaviour? and b) what is the (...) relationship, if any, between the concept of general intelligence adopted by AGI and that adopted by psychometricians, i.e., the g factor? In this paper, we address these ques-tions and invite researchers in AI to open a dis-cussion on the theoretical conceptions and practi-cal purposes of the AGI approach. (shrink)

A ansiedade gerada pela possível criação de inteligência artificial geral, algo profetizado desde a fundação do campo de pesquisa (i.e., Dartmouth's Summer Research Project on Artificial Intelligence) (MCCARTHY et al., 1955), é algo comumente investigado dentro dos círculos transhumanistas e singularistas (KURZWEIL, 2005; CHALMERS, 2010; TEGMARK, 2016; 2017; CORRÊA; DE OLIVEIRA, 2021). Por exemplo, em seu livro “Superintelligence: Paths, Dangers, Strategies”, Nick Bostrom (2014) apresenta uma série de argumentos para justificar a ideia de que precisamos ser cautelosos (...) em relação a criação de inteligência artificial avançada ou inteligência artificial geral. Contudo, muito dos argumentos levantados, em suas versões originais (i.e., convergência instrumental e ortogonalidade (OMOHUNDRO, 2008), são baseados em noções “vagas” de conceitos complexos (i.e., “inteligência”, “racionalidade”, “agência”). O objetivo deste resumo (apresentação) será introduzir o leitor/ouvinte ao campo de Segurança da Inteligência Artificial. Nesse campo, questões como o “Problema de controle” (i.e., evitar construir inadvertidamente uma inteligência artificial geral que prejudicará seus criadores) e o “Problema de Alinhamento” (i.e., criar sistemas de inteligência artificial que permaneçam seguros mesmo quando atuando de forma autônoma no ambiente real), que são questões muitas vezes debatidas apenas dentro da Filosofia ou Ficção Científica, ganham um aspecto muito mais real e formal (AMODEI et al., 2016, HUBINGER et al., 2019). A criação de alguns dos modelos de inteligência artificial mais avançados já criados (e.g., AlphaGo, GPT-3) (SILVER el al., 2016; BROWN et al., 2020), está ligado a utilização de dois paradigmas da área de Aprendizagem de Máquina, i.e., Aprendizagem Profunda e Aprendizagem por Reforço. Dentro deste contexto, podemos definir “um sistema autônomo inteligente” como “um sistema que implementa uma política ótima (tecnicamente "ϵ-greedy optimal") para alguma função de recompensa” (ORSEAU et al., 2018). Podemos também definir tais sistemas como “maximizadores de utilidade esperada” (VON NEUMANN; MORGENSTERN, 1944). Um sistema de IA maximizando uma função de recompensa (i.e., objetivo) especificada erroneamente pode vir a causar danos reais quando interagindo no ambiente real, seja por erros de especificação (i.e., Efeitos Colaterais Negativos, Hackeamento de Recompensa, Interrupção Segura), ou quando o domínio de treinamento é diferente do domínio de implantação (i.e., Exploração Segura e Mudança de Domínio). Ao mesmo tempo, especificar objetivos complexos (e.g., preferências e valores humanos) é uma tarefa extremamente complexa, e quando visamos a possibilidade de inteligência artificial avançada agindo no mundo real, é imperativo que tais sistemas estejam: (1) alinhados com nossos objetivos; e (2) desenvolvidos com um design que evite os problemas citados acima. Contudo, tais problemas permanecem em aberto. Por fim, gostaria de ressaltar que no cerne desta problemática, não temos apenas problemas técnicos de aprendizagem de máquina, mas uma importante questão de cunho “Moral”: “O que é a coisa ‘certa” a fazer”? “Qual o objetivo correto a ser perseguido”? “Como podemos especificar isso”? Perguntas como essas prometem um fértil campo para pesquisas interdisciplinares envolvendo inteligência artificial, aprendizagem de máquina, ciências da computação e filosofia moral. (shrink)

The Tannhäuser Gate. Architecture in science fiction films of the second half of the 20th and the beginning of the 21st century as a component of utopian and dystopian projections of the future. -/- The films of science fiction genre from the second half of the 20th and early 21st century contained many visions of the future, which were at the same time a reflection on the achievements and deficiencies of modern times. In 1960s, cinematographic works were dominated by optimism (...) and faith in the possibility of never-ending progress. The disappearance of political divisions between the blocs of states and the joint exploration of the cosmos was foreseen. The designers undertook cooperation with scientists, which manifested itself in showing cosmic constructions far exceeding the real technical capabilities. Starting from the 1970s, pessimism and the belief that the future will bring, above all, the intensification of negative phenomena of the present began to grow in films. Fears of the future were connected with indicating various possible defects and insoluble contradictions between them. When, therefore, some dystopian visions illustrated the threat of increase in crime, others depicted the future as saturated with state control mechanisms and the prevalence of surveillance. The fears shown on the screens were also aroused by the growth of large corporations, especially by their gaining political influence or staying outside the system of democracy. The authors of the films also presented their suspicions related to the creation of new types of weapons by corporations, the use of which might breach the current legal norms. Particular objections concerned research on biological weapons and the possible spread of lethal viruses. The development of robotics and research into artificial intelligence, which must have resulted in the appearance of androids and inevitable tensions in their relations with humans, also triggered fear. Another problem for film-makers has become hybrids that are a combination of people and electronic parts. Scriptwriters and directors likewise considered the development of genetic engineering, which led to the creation of mutant human beings. A number of film dystopias contemplated the possibility of the collapse of democratic systems and the development of authoritarian regimes in their place, often based on broad public support. This kind of dystopia also includes films presenting the consequences of contemporary hedonism and consumerism. The problem is, however, that works critical of these phenomena were themselves advertisements for attractive products. (shrink)

The deep crisis in modern fundamental science development is ever more evident and openly recognised now even by mainstream, official science professionals and leaders. By no coincidence, it occurs in parallel to the world civilisation crisis and related global change processes, where the true power of unreduced scientific knowledge is just badly missing as the indispensable and unique tool for the emerging greater problem solution and further progress at a superior level of complex world dynamics. Here we reveal the mathematically (...) exact reason for the crisis in conventional science, containing also the natural and unified problem solution in the form of well-specified extension of usual, artificially restricted paradigm. We show how that extended, now causally complete science content provides various "unsolvable" problem solutions and opens new development possibilities for both science and society, where the former plays the role of the main, direct driver for the latter. We outline the related qualitative changes in science organisation, practice and purposes, giving rise to the sustainability transition in the entire civilisation dynamics towards the well-specified superior level of its unreduced, now well understood and universally defined complexity. (shrink)

The idea of artificial intelligence for social good is gaining traction within information societies in general and the AI community in particular. It has the potential to tackle social problems through the development of AI-based solutions. Yet, to date, there is only limited understanding of what makes AI socially good in theory, what counts as AI4SG in practice, and how to reproduce its initial successes in terms of policies. This article addresses this gap by identifying seven ethical factors that (...) are essential for future AI4SG initiatives. The analysis is supported by 27 case examples of AI4SG projects. Some of these factors are almost entirely novel to AI, while the significance of other factors is heightened by the use of AI. From each of these factors, corresponding best practices are formulated which, subject to context and balance, may serve as preliminary guidelines to ensure that well-designed AI is more likely to serve the social good. (shrink)

The project of growing meat artificially represents for some the next best thing to humanity. If successful, it could be the solution to several problems, such as feed- ing a growing global population while reducing the environmental impact of raising animals for food and, of course, reducing the amount and degree of animal cruelty and suffering that is involved in animal farming. In this paper, I argue that the issue of the morality of such a project has been (...) framed only in terms of the best conse- quences for the environment, animals, and humans, or in terms of deontic princi- ples. I argue that to appreciate how deep and difficult this issue is, it is necessary to consider it in terms of a virtue-oriented approach. Such an approach will reveal aspects that are not apparent, not contemplated by typical approaches, but are essen- tial to our understanding of the morality of lab-grown meat. As I argue, evaluating the issue from a virtue-oriented perspective suggests that the project of in vitro meat should not be supported because it stems from unvirtuous motivations. (shrink)

The project of a 'naive physics' has been the subject of attention in recent years above all in the artificial intelligence field, in connection with work on common-sense reasoning, perceptual representation and robotics. The idea of a theory of the common-sense world is however much older than this, having its roots not least in the work of phenomenologists and Gestalt psychologists such as K hler, Husserl, Schapp and Gibson. This paper seeks to show how contemporary naive physicists can (...) profit from a knowledge of these historical roots of their discipline, which are shown to imply above alla critique of the set-theory-based models of reality typically presupposed by contemporary work in common-sense ontology [1]. (shrink)

The project of a naive physics has been the subject of attention in recent years above all in the artificial intelligence field, in connection with work on common-sense reasoning, perceptual representation and robotics. The idea of a theory of the common-sense world is however much older than this, having its roots not least in the work of phenomenologists and Gestalt psychologists such as Kohler, Husserl, Schapp and Gibson. This paper seeks to show how contemporary naive physicists can profit (...) from a knowledge of these historical roots of their discipline, which are shown to imply above all a critique of the set-theory-based models of reality typically presupposed by contemporary work in common-sense ontology. (shrink)

The fact that real-world decisions made by artificial intelligences (AI) are often ethically loaded has led a number of authorities to advocate the development of “moral machines”. I argue that the project of building “ethics” “into” machines presupposes a flawed understanding of the nature of ethics. Drawing on the work of the Australian philosopher, Raimond Gaita, I argue that ethical dilemmas are problems for particular people and not (just) problems for everyone who faces a similar situation. Moreover, the (...) force of an ethical claim depends in part on the life history of the person who is making it. For both these reasons, machines could at best be engineered to provide a shallow simulacrum of ethics, which would have limited utility in confronting the ethical and policy dilemmas associated with AI. (shrink)

Jonathan Y. Tsou examines and defends positions on central issues in philosophy of psychiatry. The positions defended assume a naturalistic and realist perspective and are framed against skeptical perspectives on biological psychiatry. Issues addressed include the reality of mental disorders; mechanistic and disease explanations of abnormal behavior; definitions of mental disorder; natural and artificial kinds in psychiatry; biological essentialism and the projectability of psychiatric categories; looping effects and the stability of mental disorders; psychiatric classification; and the validity of the (...) DSM's diagnostic categories. The main argument defended by Tsou is that genuine mental disorders are biological kinds with harmful effects. This argument opposes the dogma that mental disorders are necessarily diseases that result from biological dysfunction. Tsou contends that the broader ideal of biological kinds offers a more promising and empirically ascertainable naturalistic standard for assessing the reality of mental disorders and the validity of psychiatric categories. (shrink)

In the article, the author analyzes the problems of human-computer communication in the context of artificial intelligence, augmented reality and a Turing methodology for comparing the capabilities of artificial and natural intelligence in a dialogue. It is argued that the tool with which the computer and humans communicate is of no less importance than the computer program with which the dialogue is conducted. As an example of the implementation of such visualization, the project “E.LENA” of a digital (...) television anchor created at the Sberbank Robotics Laboratory was considered. The author gives his own version of Turing's specific test to study the features of non- verbal communication interfaces between a person and a computer. The key idea formulated by the author for further discussion is to provide artificial intelligence with visual avatar in order to avoid the alienation of man and computer and the loss of semantic information during its transmission from computer to person. (shrink)

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

The rapid advancement of artificial intelligence (AI) technologies has revolutionized various industries, including the realm of education and career guidance. This project endeavors to harness the power of AI to develop a sophisticated career guidance application that offers personalized and effective recommendations to students and job seekers. The primary objective of this project is to address the limitations of traditional career guidance methods, which often lack customization and fail to adapt to individual preferences, skills, and aspirations. Through (...) the integration of AI algorithms, NLP techniques, and ML models, our application aims to provide accurate interest assessments, skill matching, and tailored educational pathways. The scope of the project encompasses the design, development, and implementation of AI-driven functionalities such as interest assessment, skill analysis, resume building, and personalized recommendations. The methodology involves data collection through user inputs, preprocessing of data for analysis, and the creation of a robust system architecture comprising frontend interfaces, backend servers, and database management. (shrink)

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

Initiatives relying on artificial intelligence (AI) to deliver socially beneficial outcomes—AI for social good (AI4SG)—are on the rise. However, existing attempts to understand and foster AI4SG initiatives have so far been limited by the lack of normative analyses and a shortage of empirical evidence. In this Perspective, we address these limitations by providing a definition of AI4SG and by advocating the use of the United Nations’ Sustainable Development Goals (SDGs) as a benchmark for tracing the scope and spread of (...) AI4SG. We introduce a database of AI4SG projects gathered using this benchmark, and discuss several key insights, including the extent to which different SDGs are being addressed. This analysis makes possible the identification of pressing problems that, if left unaddressed, risk hampering the effectiveness of AI4SG initiatives. (shrink)

Connectionism seems to avoid many of the problems of classical artificial intelligence, but has it avoided all of them? In this thesis I examine the problem that Intentionality, the directedness of thought to an object, raises for connectionism. As a preliminary approach, I consider the role of Intentionality in classical artificial intelligence from the programmer’s point of view. In this investigation, one problem I identify with classical artificial intelligence is that the Intentionality of the programmer seems to (...) be projected onto the system, rather than the programmer creating a system whereby Intentionality arises intrinsically within the system. -/- In considering the current practice of connectionism, the same problem with Intentionality reappears. The assignment of Intentional content to input or output nodes in a neural network likewise projects the Intentionality of the programmer onto the system, and that projection is often reinforced by the training process of the neural network. However, connectionism seems to have an advantage over classical artificial intelligence in this respect, in that there is a form of neural network in which the network itself organizes the output nodes. The challenge is to utilize these self-organizing networks without having the programmer project Intentionality onto the system in an act of interpretation. -/- I suggest that the way to overcome these problems in connectionism is to embody the neural network within a world, whether physical or virtual, and to allow the system to develop concepts purely empirically. In this manner, connectionism can make scientific observations concerning the nature of cognition without the risk of contamination from the programmer’s own Intentionality. (shrink)

This chapter uncovers the complex negotiations for authority in various representations about futures of life which have been advanced by different branches of the sciences, and have culminated in the emerging concept of life as algorithm. It charts the historical shifts in expertise and representations of life, from naturalists, to mathematical modellers, and specialists in computation, and argues that physicists, game theorists, and economists now take a leading role in explaining and projecting futures of life. The chapter identifies Richard Dawkins (...) and Max Tegmark at the forefront of the concept of life as algorithm: the first inspired by game theory as a means to study evolution; the second proposing that a materialist basis of life could place humans and artificial intelligence on an equal footing. Through close reading of their respective texts, the chapter demonstrates that both thinkers consider life as an algorithm programmed to achieve success in survival and reproduction. (shrink)

Summary We offer a novel historical-philosophical framework for discussing experimental practice which we call ‘Generating Experimental Knowledge’. It combines three different perspectives: experimental systems, concept formation, and the pivotal role of error. We then present an historical account of the invention of the Scanning Tunnelling Microscope (STM), or Raster-Tunnelmikroskop, and interpret it within the proposed framework. We show that at the outset of the STM project, Binnig and Rohrer—the inventors of the machine—filed two patent disclosures; the first is dated (...) 22 December 1978 (Switzerland), and the second, two years later, 12 September 1980 (US). By studying closely these patent disclosures, the attempts to realize them, and the subsequent development of the machine, we present, within the framework of generating experimental knowledge, a new account of the invention of the STM. While the realization of the STM was still a long way off, the patent disclosures served as blueprints, marking the changes that had to be introduced on the way from the initial idea to its realization. (shrink)

Whole Brain Emulation has been championed as the most promising, well-defined route to achieving both human-level artificial intelligence and superintelligence. It has even been touted as a viable route to achieving immortality through brain uploading. WBE is not a fringe theory: the doctrine of Computationalism in philosophy of mind lends credence to the in-principle feasibility of the idea, and the standing of the Human Connectome Project makes it appear to be feasible in practice. Computationalism is a popular, independently (...) plausible theory, and Connectomics a well-funded empirical research program, so optimism about WBE is understandable. However, this optimism may be misplaced. This article argues that WBE is, at best, no more compelling than any of the other far-flung routes to achieving superintelligence. Similarly skeptical conclusions are found regarding immortality. The essay concludes with some positive considerations in favor of the Biological Theory of consciousness, as well as morals about the limits of Computationalism in both artificial intelligence and the philosophy of mind more generally. (shrink)

As large language models (LLMs) continue to demonstrate remarkable abilities across various domains, computer scientists are developing methods to understand their cognitive processes, particularly concerning how (and if) LLMs internally represent their beliefs about the world. However, this field currently lacks a unified theoretical foundation to underpin the study of belief in LLMs. This article begins filling this gap by proposing adequacy conditions for a representation in an LLM to count as belief-like. We argue that, while the project of (...) belief measurement in LLMs shares striking features with belief measurement as carried out in decision theory and formal epistemology, it also differs in ways that should change how we measure belief. Thus, drawing from insights in philosophy and contemporary practices of machine learning, we establish four criteria that balance theoretical considerations with practical constraints. Our proposed criteria include accuracy, coherence, uniformity, and use, which together help lay the groundwork for a comprehensive understanding of belief representation in LLMs. We draw on empirical work showing the limitations of using various criteria in isolation to identify belief representations. (shrink)

I argue that current projects in ‘naturalized metaphysics’ fail to be properly naturalistic, and thereby fail in their stated aim to take one’s metaphysics from science. I argue that naturalism must involve the idea of taking science seriously, and that this can only be spelled out in terms of taking not only the theories of science seriously, but also its practice and its socio-linguistic situatedness seriously as well. This accords with naturalism because not doing so draws an artificial (non-natural) (...) distinction between the epistemic products of science as essence, and its socio-linguistic and practical features as accidents. The picture of naturalism which falls out of this is a form of pragmatism. Once this is spelled out, the question becomes, what is the appropriate attitude for the pragmatist/naturalist to have toward ontology? It is not the same as that of traditional metaphysics, since such an attitude (that metaphysical theorizing can make positive epistemic contributions) requires a priori commitments which themselves are (1) not subject to empirical review, and (2) are anthropocentric and so potentially distorted. But the pragmatist/naturalist will not go the opposite way, and say that metaphysics is meaningless either, since (true to their pragmatic commitments) ontology does things for the scientist and the layperson. It is a mistake to reject it wholesale, since the task of asserting what there is, exposing such an ontology to criticism, both empirical and logical, and revising it, has both small-scale and large-scale consequences. On the small-scale, ontologies are a guide for thinking—scientists, engineers, and lay people can and do use models of existence to navigate occurent problems in their day-to-day lives. Whether this is posing research hypotheses, developing protocols for generating new materials, or cooling off a cup of coffee, ontology plays a role. Large-scale consequences are more weighty, and more difficult to see. These large-scale consequences have to do with the aims and values which individuals and societies possess, and their interrelation with ontology. This certainly was at the forefront of the earliest ontologies—the Epicureans and Stoics built their moral philosophy on the basis of what ontology they thought was correct. This sort of practice goes on, unabated, today, though with virtually no overt acknowledgement of this important interdependency. How, for the pragmatist, do we make sense of ontological talk, if we are to eschew traditional metaphysics? Ontology—the naturalist/pragmatist declares—is a tool. Ontology helps us do things, whether it be predict behavior, understand phenomena, blame or forgive someone, and hope or despair about a life after this one (for example). Building an ontology is about building our own concepts, and this, in turn is a negotiation between our beliefs, experiences, and commitments, and the beliefs, experiences, and commitments of with whom we’re discursively engaged. (shrink)

Look! Up in the bookshelf! Is it science? Is it science-fiction? No, it's Super Science: strange visitor from the future who can be everywhere in the universe and everywhen in time, can change the world in a single bound and who - disguised as a mild mannered author - fights for truth, justice and the super-scientific way. -/- Though I put a lot of hard work into this book, I can't take all the credit. I believe that the whole universe (...) - everything on Earth and in space plus everything in the past, present, and future - is entangled and unified. Everybody is part of this unity, so anybody could have written the ideas in this book. It turned out to be me simply because I've got intense curiosity about the book's contents, enough persistence and imagination to combine science with topics like religion and philosophy, and enough spare time to assemble all the pre-existing pieces in space and time (my contribution to the book is like putting together the pieces of a big jigsaw puzzle). -/- This book, with its vast collection of scientific fact and study results, presents some fascinating theories and is an expansive journey through my research. The topic will appeal to the science-minded reader who is open to speculating on how conditions may evolve in the future, perhaps questioning the very foundations of our place in the universe. This book is not written as a single story but is a collection of 9 articles written in the first half of 2022. Each chapter of this book is presented as a research paper. There's the abstract, the introduction, the keywords, the body of the work divided into sections, and a reference section. Though this might turn some readers off, I'm a member of ResearchGate, a community of researchers. So it isn't surprising that I've presented this book this way. Each article is meant to be self-contained and well explained in plain English. As a result, some explanations appear in several of the articles. -/- Please be patient when you encounter jargon and mathematics - I've tried to keep these to a minimum but they're bound to put in an appearance in a book that's largely about science (and I have compiled an enormous amount of intricate research for this project, hopefully impressing with the organization). Quotes from a range of scientists and icons in the industry should add further fascination to the descriptions, inspiring the reader into more of an openness to speculating on the distant future. There's a lot to absorb here but understanding the future . . . It Don't Come Easy (just ask Ringo Starr who once dreamed he was an alien living on another planet in the future. -/- Contents -/- Special Relativity's Consequences For General Relativity, Quantum Mechanics And Quantum Gravity (Can Science And The Paranormal Coexist?) -/- Intergalactic Travel and Riemann Hypothesis - featuring Dark Matter, Dark Energy, Higgs Boson, Higgs Field, Electroweak Interaction, No Big Bang, Other Dimensions, Plus Other Physics and Mathematics -/- New Perspectives On Life, Death, Cancer and Covid-19 Arising From An Artificially Intelligent, Non-probabilistic Universe -/- Unipositional Interpretation Of Quantum Mechanics Means Entanglement Occurring Simultaneously With Gravitational Slingshots Reduces Problems Associated With Spaceflight -/- Unipositional Interpretation Of Quantum Mechanics Explains Time Dilation, Updates Cosmology -/- WHERE DID EVERYTHING COME FROM – Combining Science, Mathematics, Computers, Religion, Philosophy, Relativity, Quantum Physics, Darwinism, and a Podcast to Reach One Person’s Plausible Ideas -/- Thoughts on Artificial Intelligence and the Origin of Life Resulting from General Relativity, with Neo-Darwinist Reference to Human Evolution and Mathematical Reference to Cosmology -/- Planet 9 and Black Hole Versus Relativity’s Precession and Dark Matter -/- THE WORLD’S REAL-LIFE EXPERIMENTS WITH COVID-19 AND PHYSICS ALTER SOCIETY AND GLOBAL ECONOMICS . (shrink)