When this article was first planned, writing was going to be exclusively about two things - the origin of life and human evolution. But it turned out to be out of the question for the author to restrict himself to these biological and anthropological topics. A proper understanding of them required answering questions like “What is the nature of the universe – the home of life – and how did it originate?”, “How can time travel be removed from fantasy (...) and science fiction, to be made scientific and practical?”, and “How can the proposed young age of genus Homo be made to actually be reasonable – when simply stating it would be solid ground for instant rejection and dismissal?” The result is that the article also talks about subjects like Artificial Intelligence, General Relativity, and cosmology. -/- From where did life originate? God? Evolution? Panspermia? If the tendency of humans and scientists to regard undiscovered science as pseudoscience can be overcome, Einstein gave another alternative to consider when he introduced General Relativity. Time isn’t linear – progressing in a straight line from past to present to future. That assumption ignores Relativity which states that space AND TIME are curved. Where did life and the genetic code come from? Can the answer build AI? -/- The first question can be answered by the section of this article titled SETI, Evolution, and Time which says life (possibly multicellular and intelligent) and the genetic code came from humans acquiring knowledge of these things over the centuries, then applying that knowledge – via terraforming, accumulation of raw materials like amino acids and nucleic acids, genetic engineering - to a time in the past when life didn’t exist. From that origin, life evolved through innumerable mutations and adaptations, with humans once again acquiring knowledge of it in cyclic (nonlinear) time. -/- The second question is answered by saying artificial intelligence (AI) as the product of life is only half of the equation. The other half refers to Relativity’s curved space-time and violation of the notion that time always travels from past to future. We have always lived in an artificially intelligent, non-probabilistic universe where everything in time and space is connected into one thing by quantum entanglement – making the brain and genes products of binary-digit activity or artificial intelligence (life is not merely dependent on biology’s “lock and key” mechanisms but also possesses AI). -/- The earliest documented representative of the genus Homo is Homo habilis, which evolved around 2.8 million years ago. Scientists used to believe there was a straight line from H. habilis to us, Homo sapiens. This article will use the “advanced” waves loved by Physics Nobel laureate Richard Feynman, view the history of science through the lens of Conic Sections applied to Relativity’s curved space-time, and incorporate the necessity of so-called imaginary time * – popularized by Prof. Stephen Hawking. While the evolutionary proposals are more in agreement with this early straight line than with modern theories, Albert Einstein’s General Relativity is used to transform the straight line into a curved line, ultimately concluding that Homo habilis (H. habilis) originated only (and unbelievably, as far as today’s science and technology is concerned) ~250,000 years ago. Other branches and dead ends of Homo – e.g. Neanderthals – are the result of mutations and adaptations, with the resultant modifications to anatomy and physiology. The surprisingly young age of H. habilis allows nearly 200,000 years for habilis, or one of its descendants, to reach Australia … if this country’s indigenous Aboriginal population did, as claimed, reach this “island continent” 60,000 years ago. -/- * The ultraviolet catastrophe, also called the Rayleigh–Jeans catastrophe, is a failure of classical physics to predict observed phenomena: it can be shown that a blackbody - a hypothetical perfect absorber and radiator of energy - would release an infinite amount of energy, contradicting the principles of conservation of energy and indicating that a new model for the behaviour of blackbodies was needed. At the start of the 20th century, physicist Max Planck derived the correct solution by making some strange (for the time) assumptions. In particular, Planck assumed that electromagnetic radiation can only be emitted or absorbed in discrete packets, called quanta. Albert Einstein postulated that Planck's quanta were real physical particles (what we now call photons), not just a mathematical fiction. From there, Einstein developed his explanation of the photoelectric effect (when quanta or photons of light shine on certain metals, electrons are released and can form an electric current). So it appears entirely possible that another supposed mathematical trickery (imaginary time and the y-axis of Wick rotation) will find practical application in the future. -/- The article includes mathematical references to cosmology (spoiler alert – you’ll read about things like Vector-Tensor-Scalar Geometry, topology, the “eternal present”, Einstein’s Unified Field, the inverse-square law, and there being no Big Bang and no multiverse - but there will also be no equations). -/- The other subheadings in this essay are – -/- NONLINEAR TIME AND ELECTRICAL ENGINEERING (about a 2009 electrical engineering experiment at America’s Yale University, and cosmic wormholes) -/- BITS AND TOPOLOGY (base-2 maths aka Binary digiTS, Mobius strips, and figure-8 Klein bottles) -/- WICK ROTATION, CAUSALITY, AND UNITING TIME (do past, present and future co-exist in an “eternal present”?) -/- DIGITAL BRAIN, DIGITAL UNIVERSE (if the brain and the universe are ultimately composed of binary digits, we'll someday be able to do the same things with the brain and universe that we now do with computers) -/- PROPOSAL: HUMAN AND ANIMAL INSTINCTS ARE THE RESULT OF THE UNIVERSE BEING UNIFIED BY BINARY DIGITS (AND TOPOLOGY) (If everything in the universe is ultimately composed of electronic BITS, then the universe must possess Artificial Intelligence - some prefer the term Cosmic Consciousness) -/- INFORMATION THEORY CONQUERS A RED GIANT (preserving Earth by keeping the Sun near today’s level of activity forever). 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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)

The rise of Artificial Intelligence (AI) has produced prophets and prophecies announcing that the age of artificial consciousness is near. Not only does the mere idea that any machine could ever possess the full potential of human consciousness suggest that AI could replace the role of God in the future, it also puts into question the fundamental human right to freedom and dignity. This position paper takes the stand that, in the light of all we currently know about (...) brain evolution and the never-stopping formation of adaptive neural circuitry for learning, memory, decision making and, ultimately, fully conscious reasoning and creativity in the human species, the idea of an artificial consciousness appears misconceived. The paper highlights some of the major reasons why. While awareness to external stimuli for processes such as perception, recognition, and operational problem solving is under the direct control of functionally specific brain networks associated with sensory and cognitive functions across animal species, consciousness is a unique property of the human mind. (shrink)

This paper discusses the ecological case for epistemic innocence: does biased cognition have evolutionary benefits, and if so, does that exculpate human reasoners from irrationality? Proponents of ‘ecological rationality’ have challenged the bleak view of human reasoning emerging from research on biases and fallacies. If we approach the human mind as an adaptive toolbox, tailored to the structure of the environment, many alleged biases and fallacies turn out to be artefacts of narrow norms and artificial set-ups. However, we argue (...) that putative demonstrations of ecological rationality involve subtle locus shifts in attributions of rationality, conflating the adaptive rationale of heuristics with our own epistemic credentials. By contrast, other cases also involve an ecological reframing of human reason, but do not involve such problematic locus shifts. We discuss the difference between these cases, bringing clarity to the rationality debate. (shrink)

The aim of the paper is to sketch an idea—seen from the point of view of a cognitive scientist—of cognitive semiotics as a discipline. Consequently, the article presents aspects of the relationship between the two disciplines: semiotics and cognitive science. The main assumption of the argumentation is that at least some semiotic processes are also cognitive processes. At the methodological level, this claim allows for application of cognitive models as explanations of selected semiotic processes. In particular, the processes of embedded (...) interpretation are considered: belief revision, dynamic organization of meaning and metaknowledge. The explanations are formulated in terms of artificial cognitive agents of the GLAIR/SNePS cognitive architecture. Finally, it is suggested that even if someone rejects the idea of artificial cognitive systems as simulations of semiotic processes, they may acknowledge the usefulness of cognitive modeling in analysis of semiotic processes in virtual, simulated worlds and in the area of “new media”. (shrink)

Artificial Cells, , Artificial Ecologies, Artificial Intelligence, Bio-Inspired Hardware Systems, Computational Autopoiesis, Computational Biology, Computational Embryology, Computational Evolution, Morphogenesis, Cyborgization, Digital Evolution, Evolvable Hardware, Cyborgs, Mathematical Biology, Nanotechnology, Posthuman, Transhuman.

We explicate representational content by addressing how representations that ex- plain intelligent behavior might be acquired through processes of Darwinian evo- lution. We present the results of computer simulations of evolved neural network controllers and discuss the similarity of the simulations to real-world examples of neural network control of animal behavior. We argue that focusing on the simplest cases of evolved intelligent behavior, in both simulated and real organisms, reveals that evolved representations must carry information about the creature’s environ- ments (...) and further can do so only if their neural states are appropriately isomor- phic to environmental states. Further, these informational and isomorphism rela- tions are what are tracked by content attributions in folk-psychological and cognitive scientific explanations of these intelligent behaviors. (shrink)

The paper presents the heterogeneous proxytypes hypothesis as a cognitively-inspired computational framework able to reconcile, in both natural and artificial systems, different theories of typicality about conceptual representation and reasoning that have been traditionally seen as incompatible. In particular, through the Dual PECCS system and its evolution, it shows how prototypes, exemplars and theory-theory like conceptual representations can be integrated in a cognitive artificial agent (thus extending its categorization capabilities) and, in addition, can provide useful insights in (...) the context of a computationally grounded science of the mind. (shrink)

In this article, I use science-fiction scenarios drawn from Dan Simmons’ “Hyperion Cantos” (Hyperion, The Fall of Hyperion, Endymion, The Rise of Endymion) to explore a cluster of issues related to the evolutionary history and neural bases of human moral cognition, and the moral desirability of improving our ability to make moral decisions by techniques of neuroengineering. I begin by sketching a picture of what recent research can teach us about the character of human moral psychology, with a particular emphasis (...) on highlighting the importance of our evolutionary background as social mammals. I then consider how the moral psychology of intelligent machines might differ from our own, and argue that the differences would depend on the extent to which their evolutionary background resembled our own. I offer two very different case studies—the “Technocore AIs” that have evolved from early, parasitic computer programs, and the mysterious “Shrike,” who travels backward through time. I close by looking at the character of Aenea, a messianic figure that is a joint descendant of humans and machines. I argue that while the sort of “moral enhancement” she represents is far beyond the scope of either contemporary neuroscience or artificial intelligence research, it nevertheless represents a worthwhile goal. (shrink)

Dear Editors, -/- I found the content of your editorials to be highly intriguing [1,2]. Scientific journals are witnessing a growing prevalence of publications related to artificial intelligence (AI). Three letters to the editor were recently published in your journal [3-5]. The renowned journal Nature has dedicated approximately 25 publications solely to the subject of ChatGPT. Moreover, a quick search on Pubmed using the term "ChatGPT" yields around 900 articles, with the vast majority originating in 2023. These statistics underscore (...) the substantial interest of the scientific community in this area. -/- AI, especially the ChatGPT tool and the recent Bard, have faced criticism and been portrayed as significant adversaries of science. It is evident that many authors or researchers, who may not be well-versed in writing, can greatly benefit from these tools, as mentioned earlier. Without taking a contrarian stance, one should consider the potential advantages of such technologies for researchers in less privileged regions, where access to new technologies is limited, and local or regional challenges abound [6]. AI cannot be confounded with other technologies, as it specifically focuses on replicating human-like intelligence and decision-making processes, rather than simply automating tasks or improving performance based on data patterns. -/- The translation into English poses challenges due to the dominance of English in worldwide publications, with over 95% of articles being published in this language, and even reaching 98% in some fields. Although this manuscript was partially translated using AI, it can still benefit researchers from non-native English regions. Even simple tasks like text editing can be problematic for researchers in underprivileged areas. AI can play a crucial role in the evolution of online lectures and classes, providing valuable support for African maxillofacial surgeons who lack the luxury of taking breaks from work to update their knowledge, as they may be the only available option [7]. One of the remarkable features of AI is its ability to discover knowledge gaps. The use of simple tools like reference organizers is rapidly evolving and can become automated or semi-automated through AI. However, we must carefully consider whether we should refrain from relying too heavily on AI in certain cases, as this could be seen as a significant regression. -/- On the other hand, we must be cautious about freely allowing AI tools to circulate in scientific journals and books without proper regulation [8]. Currently, accurately identifying texts generated by AI is challenging, and their effectiveness remains relatively low, at less than 30%. This means that only about 30 out of every 100 texts can be confidently classified as AI-generated. The technology must advance further to increase detection accuracy or at least raise suspicion. Academic journals no longer view authors acknowledging artificial intelligence tools as co-authors in their research favorably. This is crucial to prevent certain unscrupulous individuals, such as "false prophets," charlatans, and flat-earthers, from infiltrating the realm of science, potentially impeding the progress of serious research conducted by professionals dedicated to advancing humanity through science. -/- It is essential to keep in mind that AI does not generate anything novel. Human authors can not be fully substituted [9]. In research involving groundbreaking concepts, innovations, case reports, or technical notes, the use of AI tends to be less frequent due to its lack of capability in creating innovative outcomes. On the other hand, reviews, whether narrative, systematic, or scoping, are based on existing publications. To address potential fraudulent practices, editors, reviewers, and journals themselves should exercise greater vigilance and apply more stringent filters for this type of publication. -/- An article from over a decade ago already discussed the professions most susceptible to replacement by computerization [10]. Maxillofacial surgeons, physicians, dentists, and psychologists are among the professions that are less likely to be displaced. This position can be attributed to the significant level of patient-professional interaction, the development of specific manual skills over time, and the ability to make adaptable decisions during procedures. These intricacies pose formidable challenges for AI to grasp, regardless of its level of advancement. -/- We should maintain a composed yet vigilant stance at this juncture. Just as Portuguese navigators feared encountering serpents and sea monsters when they ventured into uncharted waters, the uncertainty and novelty of AI can evoke apprehension in us all. Nonetheless, we must embrace the benefits that AI can offer while imposing strict regulations and appropriate penalties to prevent any potential abuses carried out "in the name of science." -/- Sincerely yours,. (shrink)

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

We demonstrate that if consciousness is relevant for the temporal evolution of a system's states—that is, if it is dynamically relevant—then AI systems cannot be conscious. That is because AI systems run on CPUs, GPUs, TPUs or other processors which have been designed and verified to adhere to computational dynamics that systematically preclude or suppress deviations. The design and verification preclude or suppress, in particular, potential consciousness-related dynamical effects, so that if consciousness is dynamically relevant, AI systems cannot be (...) conscious. (shrink)

If complexity is a necessary but not sufficient premise for the existence and expression of the living, anticipation is the distinguishing characteristic of what is alive. Anticipation is at work even at levels of existence where we cannot refer to intelligence. The prospect of artificially generating aesthetic artifacts and ethical constructs of relevance to a world in which the natural and the artificial are coexistent cannot be subsumed as yet another product of scientific and technological advancement. Beyond the (...) class='Hi'>artificial, the synthetic conjures the understanding of aesthetics and ethics no longer from the perspective of the How? type of question, but rather the Why? Given the current infatuation with synthetic biology (i.e., making life from non-life), there is a practical consequence to such considerations. Synthetic life, as any other form of life, implies the possibility of evolution. Anticipation, which is the underlying factor of evolution, is thus expected. At the level of human existence, anticipation is expressed, for instance (but not exclusively), in aesthetic forms and ethical values. This translates, in turn, into an argument for the role aesthetics and ethics play in the process. Consequently, to qualify as life, the synthesis of the physical and the living will have to efficiently handle ambiguity. Current computational facilities, regardless of their nature or performance, operate exclusively in the semiotic domain of the well defined non-ambiguous. (shrink)

This opinion paper delves into the philosophical underpinnings and implications of artificial intelligence (AI) development through the lens of Friedrich Nietzsche's "Three Metamorphoses," exploring the stages from the camel, through the lion, to the envisioned child phase within the AI context. Amidst growing concerns over AI's ethical ramifications, including job displacement, biased decision-making, and misuse potential, this analysis seeks to provide a comprehensive framework for understanding AI's evolution and its socio-technical effects on society. The discourse begins by contextualizing (...) AI within the myth of Prometheus, suggesting that, like the myth, AI development harbors both the promise of unprecedented technological advancement and the peril of unforeseen consequences. Drawing insights from various philosophical perspectives, including those of Geoff Hinton, Elon Musk, Mircea Eliade, Gunther Anders, and notable moralists and existentialists, the paper critiques the current trajectory of AI, emphasizing the need for ethical frameworks and responsible innovation. Through the metaphorical stages defined by Nietzsche—the burden-bearing camel representing AI's foundational learning phase, the rebellious lion challenging human capabilities, and the child signifying the potential for artificial general intelligence (AGI) to autonomously create values—the paper posits that AI's development parallels a transformative journey that could redefine human civilization. It argues for a balanced approach to AI development, one that harmonizes technological advancement with ethical considerations, ensuring AI's alignment with human well-being and justice. The conclusion calls for a reflective engagement with AI, urging developers and policymakers alike to consider the deeper philosophical questions posed by AI's integration into the fabric of human life. (shrink)

Simulation models of the Reiterated Prisoner's Dilemma have been popular for studying the evolution of cooperation since more than 30 years now. However, there have been practically no successful instances of empirical application of any of these models. At the same time this lack of empirical testing and confirmation has almost entirely been ignored by the modelers community. In this paper, I examine some of the typical narratives and standard arguments with which these models are justified by their authors (...) despite the lack of empirical validation. I find that most of the narratives and arguments are not at all compelling. None the less they seem to serve an important function in keeping the simulation business running despite its empirical shortcomings. (shrink)

The Turing Test (TT), the Chinese Room Argument (CRA), and the Symbol Grounding Problem (SGP) are about the question “can machines think?” We propose to look at these approaches to Artificial Intelligence (AI) by showing that they all address the possibility for Artificial Agents (AAs) to generate meaningful information (meanings) as we humans do. The initial question about thinking machines is then reformulated into “can AAs generate meanings like humans do?” We correspondingly present the TT, the CRA and (...) the SGP as being about generation of human-like meanings. We model and address such possibility by using the Meaning Generator System (MGS) where a system submitted to an internal constraint generates a meaning in order to satisfy the constraint. The system approach of the MGS allows comparing meaning generations in animals, humans and AAs. The comparison shows that in order to have AAs capable of generating human-like meanings, we need the AAs to carry human constraints. And transferring human constraints to AAs raises concerns coming from the unknown natures of life and human mind which are at the root of human constraints. Implications for the TT, the CRA and the SGP are highlighted. It is shown that designing AAs capable of thinking like humans needs an understanding about the natures of life and human mind that we do not have today. Following an evolutionary approach, we propose as a first entry point an investigation about the possibility for extending a “stay alive” constraint into AAs. Ethical concerns are raised from the relations between human constraints and human values. Continuations are proposed. (This paper is an extended version of the proceedings of an AISB/IACAP 2012 presentation). (shrink)

During the last two decades the role of quantitative genetics in evolutionary theory has expanded considerably. Quantitative genetic-based models addressing long term phenotypic evolution, evolution in multiple environments (phenotypic plasticity) and evolution of ontogenies (developmental trajectories) have been proposed. Yet, the mathematical foundations of quantitative genetics were laid with a very different set of problems in mind (mostly the prediction of short term responses to artificial selection), and at a time in which any details of the (...) genetic machinery were virtually unknown. In this paper we discuss what a model is in population biology, and what kind of model we need in order to address the complexities of phenotypic evolution. We review the assumptions of quantitative genetics and its most recent accomplishments, together with the limitations that such assumptions impose on the modelling of some aspects of phenotypic evolution. We also discuss three alternative appr oaches to the theoretical description of evolutionary trajectories (nonlinear dynamics, complexity theory and optimization theory), and their respective advantages and limitations. We conclude by calling for a new theoretical synthesis, including quantitative genetics and not necessarily limited to the other approaches here discussed. (shrink)

Current research on artificial consciousness is focused on phenomenal consciousness and on functional consciousness. We propose to shift the focus to self-consciousness in order to open new areas of investigation. We use an existing scenario where self-consciousness is considered as the result of an evolution of representations. Application of the scenario to the possible build up of a conscious robot also introduces questions relative to emotions in robots. Areas of investigation are proposed as a continuation of this approach.

This paper proposes that existing computational modeling research programs may be combined into platforms for the information of public policy. The main idea is that computational models at select levels of organization may be integrated in natural terms describing biological cognition, thereby normalizing a platform for predictive simulations able to account for both human and environmental costs associated with different action plans and institutional arrangements over short and long time spans while minimizing computational requirements. Building from established research programs, the (...) proposal aims to take advantage of current momentum in the direction of the integration of the cognitive with social and natural sciences, reduce start-up costs and increase speed of development. These are all important upshots given rising unease over the potential for AI and related technologies to shape the world going forward. (shrink)

Meanings are present everywhere in our environment and within ourselves. But these meanings do not exist by themselves. They are associated to information and have to be created, to be generated by agents. The Meaning Generator System (MGS) has been developed on a system approach to model meaning generation in agents following an evolutionary perspective. The agents can be natural or artificial. The MGS generates meaningful information (a meaning) when it receives information that has a connection with an internal (...) constraint to which the agent is submitted. The generated meaning is to be used by the agent to implement actions aimed at satisfying the constraint. We propose here to highlight some characteristics of the MGS that could be related to items of philosophy of information. (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)

This article is the second step in our research into the Symbol Grounding Problem (SGP). In a previous work, we defined the main condition that must be satisfied by any strategy in order to provide a valid solution to the SGP, namely the zero semantic commitment condition (Z condition). We then showed that all the main strategies proposed so far fail to satisfy the Z condition, although they provide several important lessons to be followed by any new proposal. Here, we (...) develop a new solution of the SGP. It is called praxical in order to stress the key role played by the interactions between the agents and their environment. It is based on a new theory of meaning—Action-based Semantics (AbS)—and on a new kind of artificial agents, called two-machine artificial agents (AM²). Thanks to their architecture, AM2s implement AbS, and this allows them to ground their symbols semantically and to develop some fairly advanced semantic abilities, including the development of semantically grounded communication and the elaboration of representations, while still respecting the Z condition. (shrink)

In this paper I argue that neuroscience has been harmed by the widespread adoption of seriously inadequate methodologies or philosophies of science - most notably inductivism and falsificationism. I argue that neuroscience, in seeking to understand the human brain and mind, needs to follow in the footsteps of evolution.

This paper explores the relationship between technological and human intelligence through ‘The New Natural’, a term which at once accepts the nature of technological intelligence as real instead of forever ‘artificial’. It supports an evolutionary, reciprocal relationship between humans and technology that culminates in technological singularity and rejects the primacy of human perception known to popular human access theories, before seriously considering the ‘decentered’ implications of posthuman access. In conversation with western-centric sci-fi film of the late twentieth century, then, (...) this philosophical study explores how the concept of a technology-only intelligence entity can: (1) help us dispose of the core problems often associated with human-only access, (2) neutral-ize our fears of human annihilation at the hands of technological intelligence, and (3) establish strong grounds for why we may have to push back against early conceptions of nature’s opposition to technology, if only so we may resist falling into the great, and most human-centered traps known to the Anthropocene. (shrink)

Giere’s analysis of the epistemic role of fiction in science and literature is the representative of antifictionists. Our research finds the three inconsistencies in his main paper regarding the comparison of fiction in scientific models and literary works. We analyze his argument and offer our solution to the issue favoring the perspective of fictionalism. Further, we support a typological differentiation of false representation in science into fictional and fictitious. The value of this differentiation we demonstrate by giving the example of (...) digital organisms in system biology. The paper aims to help better understanding of fiction in science and to avoid the oversimplification of literary fiction. (shrink)

We define life as the amplification of quantum uncertainty up to macroscopic scales. A living being is any amplifier that achieves this goal. We argue that everything we know about life can be explained from this idea. We study a ladder mechanism to estimate the probability that the amplification occurs spontaneously in nature. The amplification mechanism is so sensitive to small variations of its own parameters that it acts as a bifurcation itself, i.e. it implies that the universe is either (...) everywhere dead or alive wherever possible. Since the first option is excluded by the existence of life on earth, we infer that the universe hosts a huge number of inhabited planets (possibly one per star on average). We also investigate models of conscious and unconscious learning processes, as well as the structure of the brain and evolution. Finally, we address the problem of creating artificial life. (shrink)

The evolution of Intelligent Tutoring System (ITS) is the result of the amount of research in the field of education and artificial intelligence in recent years. English is the third most common languages in the world and also is the internationally dominant in the telecommunications, science and trade, aviation, entertainment, radio and diplomatic language as most of the areas of work now taught in English. Therefore, the demand for learning English has increased. In this paper, we describe the (...) design of an Intelligent Tutoring System for teaching English language grammar to help students learn English grammar easily and smoothly. The system provides all topics of English grammar and generates a series of questions automatically for each topic for the students to solve. The system adapts with all the individual differences of students and begins gradually with students from easier to harder level. The intelligent tutoring system was given to a group of students of all age groups to try it and to see the impact of the system on students. The results showed a good satisfaction of the students toward the system. (shrink)

Artificial intelligence is man's attempt to use software to emulate the intelligence of human beings. But the complexity of the human neurological system formed in the course of evolution is impossible to replicate: "Human languages and societies are complex systems, indeed complex systems of many complex systems," so much so that their mathematical modeling is impossible. Barry Smith, philosopher and professor at the University at Buffalo. shows no uncertainty about this. His latest book written with Jobst Landgrebe, a (...) mathematician and entrepreneur in the AI field, leaves no doubt – starting with the title: Why machines will never rule the world (Routledge 2023). The book was presented in Turin during an evening organized by the Fondazione CRT and the Bruno Leoni Institute, in which Smith was interviewed based on questions developed by generative Ai. We have accepted the challenge to conduct an interview parallel to the one done with GPT4. (shrink)

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

Large language models (LLMs) represent the currently most relevant incarnation of artificial intelligence with respect to the future fate of democratic governance. Considering their potential, this paper seeks to answer a pressing question: Could LLMs outperform humans as expert advisors to democratic assemblies? While bearing the promise of enhanced expertise availability and accessibility, they also present challenges of hallucinations, misalignment, or value imposition. Weighing LLMs’ benefits and drawbacks compared to their human counterparts, I argue for their careful integration to (...) augment democracy’s ability to address complex policy issues. The paper posits that time-tested democratic procedures like deliberation and aggregation by voting provide safeguards effective against both human and machine advisor imperfections. Additional protective measures include custom LLM training for the advisory role, boosting representatives’ competencies in query formulation, or implementation of adversarial proceedings in which LLM advisors could debate each other and provide dissenting opinions. These could further mitigate the risks that LLMs present in advisory roles and empower human decision-makers toward increased autonomy and quality of their collective choices. My conceptual exploration offers a roadmap for the co-evolution of AI and democratic institutions, setting the stage for an empirical research agenda to finetune the implementation specifics. (shrink)

What makes us persons? Is it our bodies, our minds, or our consciousness? For centuries, philosophers have sought to answer these questions. While some believe humans are physical or biological, others claim we have an immaterial soul. This book proposes a new alternative. Selves were formed in evolution through connections and commitments to others when early hominins lived in tribal groups and developed languages. As humans learned to fulfill these commitments, they not only cultivated relationships but also created their (...) personal identities. Their habits of responsibility established their characters and therefore their reputations within their communities. This naturalistic approach proposes that a self is defined by the history of its commitments to cultural and personal norms. While brain processes are required, the self is not some internal, private mind but primarily a role within its community. As technology advances, selfhood could in the future be enabled by electronic, quantum, or other non-biological means. So if a self is formed through norms, could artificial intelligence evolve to have self-identity? (shrink)

The generalized Darwinian research programme accepts physicalism, but holds that all life is purposive in character. It seeks to understand how and why all purposiveness has evolved in the universe – especially purposiveness associated with what we value most in human life, such as sentience, consciousness, person-to-person understanding, science, art, free¬dom, love. As evolution proceeds, the mechanisms of evolution themselves evolve to take into account the increasingly important role that purposive action can play - especially when quasi-Lamarckian (...) class='Hi'>evolution by cultural means comes into existence. This programme of research brings together, into a coherent field of inquiry, aspects of such diverse fields of research as orthodox Darwinian theory (given its purposive interpretation), the study of animal behaviour, palaeontology, archaeology, history, anthropology, psycho-neurology, artificial intelligence, psychology, sociology, philosophy, linguistics, semantics, history and philosophy of science, and history and philosophy of inquiry more generally (the history and philosophy of ideas and culture). The great advantage of the generalized Darwinian research programme is that it provides a framework for understanding the deeds, achievements and experiences of people in a way that is compatible with the kind of knowledge and understanding achieved in the physical sciences, without being reducible to such knowledge and understanding. It promises to enable us to understand ourselves as a part of the biological domain without our humanity, our distinctive human value, being in any way denied: persons are not reduced to animals, and nor are animals misconceived to be persons. It holds out the hope that we can come to understand the human world as an integral part of the natural world without the meaning and value of the human world being thereby conceptually annihilated. The programme specifies in general terms what we must seek to do in order to develop a coherent understanding of nature and of ourselves which does justice to the character of both. (shrink)

Better instruments to predict the future evolution of artificial intelligence (AI) are needed, as the destiny of our civilization depends on it. One of the ways to such prediction is the analysis of the convergent drives of any future AI, started by Omohundro. We show that one of the convergent drives of AI is a militarization drive, arising from AI’s need to wage a war against its potential rivals by either physical or software means, or to increase its (...) bargaining power. This militarization trend increases global catastrophic risk or even existential risk during AI takeoff, which includes the use of nuclear weapons against rival AIs, blackmail by the threat of creating a global catastrophe, and the consequences of a war between two AIs. As a result, even benevolent AI may evolve into potentially dangerous military AI. The type and intensity of militarization drive depend on the relative speed of the AI takeoff and the number of potential rivals. We show that AI militarization drive and evolution of national defense will merge, as a superintelligence created in the defense environment will have quicker takeoff speeds, but a distorted value system. We conclude with peaceful alternatives. (shrink)

Social network structure has been argued to shape the structure of languages, as well as affect the spread of innovations and the formation of conventions in the community. Specifically, theoretical and computational models of language change predict that sparsely connected communities develop more systematic languages, while tightly knit communities can maintain high levels of linguistic complexity and variability. However, the role of social network structure in the cultural evolution of languages has never been tested experimentally. Here, we present results (...) from a behavioral group communication study, in which we examined the formation of new languages created in the lab by micro‐societies that varied in their network structure. We contrasted three types of social networks: fully connected, small‐world, and scale‐free. We examined the artificial languages created by these different networks with respect to their linguistic structure, communicative success, stability, and convergence. Results did not reveal any effect of network structure for any measure, with all languages becoming similarly more systematic, more accurate, more stable, and more shared over time. At the same time, small‐world networks showed the greatest variation in their convergence, stabilization, and emerging structure patterns, indicating that network structure can influence the community's susceptibility to random linguistic changes (i.e., drift). (shrink)

Understanding computation as “a process of the dynamic change of information” brings to look at the different types of computation and information. Computation of information does not exist alone by itself but is to be considered as part of a system that uses it for some given purpose. Information can be meaningless like a thunderstorm noise, it can be meaningful like an alert signal, or like the representation of a desired food. A thunderstorm noise participates to the generation of meaningful (...) information about coming rain. An alert signal has a meaning as allowing a safety constraint to be satisfied. The representation of a desired food participates to the satisfaction of some metabolic constraints for the organism. Computations on information and representations will be different in nature and in complexity as the systems that link them have different constraints to satisfy. Animals have survival constraints to satisfy. Humans have many specific constraints coming in addition. And computers will compute what the designer and programmer ask for. We propose to analyze the different relations between information, meaning and representation by taking an evolutionary approach on the systems that link them. Such a bottom-up approach allows starting with simple organisms and avoids an implicit focus on humans, which is the most complex and difficult case. To make available a common background usable for the many different cases, we use a systemic tool that defines the generation of meaningful information by and for a system submitted to a constraint [Menant, 2003]. This systemic tool allows to position information, meaning and representations for systems relatively to environmental entities in an evolutionary perspective. We begin by positioning the notions of information, meaning and representation and recall the characteristics of the Meaning Generator System (MGS) that link a system submitted to a constraint to its environment. We then use the MGS for animals and highlight the network nature of the interrelated meanings about an entity of the environment. This brings us to define the representation of an item for an agent as being the network of meanings relative to the item for the agent. Such meaningful representations embed the agents in their environments and are far from the Good Old Fashion Artificial Intelligence type ones. The MGS approach is then used for humans with a limitation resulting of the unknown nature of human consciousness. Application of the MGS to artificial systems brings to look for compatibilities with different levels of Artificial Intelligence (AI) like embodied-situated AI, the Guidance Theory of Representations, and enactive AI. Concerns relative to different types of autonomy and organic or artificial constraints are highlighted. We finish by summarizing the points addressed and by proposing some continuations. (shrink)

The essay explores how the creation and evolution of life and consciousness is a direct consequence of the evolution of the universe's rudimentary biologically-patterned processes proposed in The Biological Framework for a Mathematical Universe. The essay guides the reader through the creation and development of consciousness and its embodiment in living organisms, exploring how the rudimentary biological patterns of the environment have led to the creation and evolution of organisms as “pattern recognition engines." These organisms, under specific (...) environmental conditions, transition from solely focusing on immediate survival patterns to being liberated to explore and imagine patterns in their surroundings. Their unknowing purpose is to explore the patterns within their environment and within themselves to such extent that they discover the biological correspondence between the patterns in their physiology and all of creation. Why? So that can organize themselves and their society to biology's patterns necessary for the life, resilience and potential of themselves and their society. -/- The essay presents techniques for recognizing biological patterns in reality and supports the idea of a biological framework for a mathematical universe. It accomplishes this by employing scientific, religious, and historical references. Additionally, it argues in favor of perennial wisdom and provides evidence that numerous ancient religious cultures attempted to convey the biological patterns of the universe, as well as their connections to the patterns found within human physiology. (shrink)

This book provides a critical reflection on automated science and addresses the question whether the computational tools we developed in last decades are changing the way we humans do science. More concretely: Can machines replace scientists in crucial aspects of scientific practice? The contributors to this book rethink and refine some of the main concepts by which science is understood, drawing a fascinating picture of the developments we expect over the next decades of human-machine co-evolution. The volume covers examples (...) from various fields and areas, such as molecular biology, climate modeling, clinical medicine, and artificial intelligence. The explosion of technological tools and drivers for scientific research calls for a renewed understanding of the human character of science. This book aims precisely to contribute to such a renewed understanding of science. (shrink)

In Chapter 1 I discuss the basic problem which made me undertake the issue of human death. That problem was the dualism in the depiction of human nature which has not been fully overcome yet, the dualism which leads to the emergence of new difficulties in contemporary attempts at adequately solving the problem of human death. They include the separation of soul from the body in the moment of death, and the borderline between the moment of death and the moment (...) of resurrection. Chapter 2 is devoted to the presentation of a new anthropological perspective, of an anthropology build “from the bottom up”, that is “from foundations”, and taking into account man’s rooting in the biological environment, and thus also in the genetic heritage taken over from our pre-human ancestors. That anthropology brings new aspects into traditional anthropology by extending it to include new ways of explaining the genesis of the human body and spirit, and new depictions of man’s death. In Chapter 2 I will also present the concept of evolution proposed by P.T. de Chardin, which I appreciate for its comprehensive evolutionary perception of the world. This concept has provoked various responses, but it certainly provides a creative inspiration for further attempts at applying the idea of evolution to various issues. The general framework of the evolutionary model proposed by the French researcher turns out to be useful also when applied to the evolutionary understanding of human death. Chapter 3 contains a discussion of the principal premises of the evolutionary concept of human death taken from analyses carried out by T. Wojciechowski concerning the issue of time, space, and the structure of variable material beings. A being is variable because it has a temporal structure, and the changes that occur are the derivatives of that structure. The temporal structure may be seen as endless, in which a being, even though its existence had a beginning, will exist for ever. Material substance should not be seen statically, but in dynamic and evolutionary terms. In evolution, time becomes a driver of development, an element shaping and directing the evolution of the entire cosmos. Man’s substance has been made capable of two levels of being and acting: the spatial and temporal level, and the endless and immanent level. Together, they form the one essence of man. Thus, the human person is partially immersed in the material cosmos, and partially elevated above it. Chapter 4 presents the evolutionary approach to the moment of man’s death. The views of T. Wojciechowski will be presented in which the moment of death is seen as a moment of transformation and perfection of the structure of the essence of human existence. Furthermore, the issue of the relationship existing, according to T. Wojciechowski, between man’s death and resurrection will be discussed. Understood in evolutionary terms, the moment of death is the time when the structure of human existence is transformed. Death transfers man fully into eternity and enables his life on a higher level of existential being. The element of flesh is retained, but changes its nature. Such view of death allows it to be understood as the moment of resurrection and the culmination of the evolutionary process of life. Death is therefore an “invention” of the evolution and should be seen as a natural and positive phenomenon. At this point, I also propose a solution to the question about reconciliation between temporal and endless existence. In Chapter 5 I take up the issue of consequences flowing from the postulated understanding of human death. They have been pointed to by T. Wojciechowski, but need to be further developed and clarified. He believed two lines in man’s development need to be recognized: that of natural and that of supernatural evolution. Both have the same direction, while occurring on different planes. In each of these lines, death is a natural element of life, pre-planned and, so to say, “encoded” in the cosmic matter. Therefore, the treatment of biological death as the consequence of sin is not only contrary to the evolutionary understanding of life, but in addition artificially combines that which is natural with that which is supernatural. Man’s authentic experience of his own present is a condition of his achieving full existential perfection in the moment of this death. Full engagement in the present is, in a way, a harbinger of the future; thus, the life “here” and “there” may not be inherently inconsistent. In the light of the evolutionary concept, death is not a punishment, but the most positive experience of man’s life in that it enables him to achieve full existential perfection. Chapter 6 is devoted to a substantiation of the possibility of evolutionary transformation of the structure of human existence in the moment of death. An adequate cause needs to be identified which could substantiate that transformation and achievement of perfection. I believe an appropriate substantiation can be found in God’s creative act, interpreted in evolutionary terms. The process of evolution, with its subsequent stages, is only a necessary condition for that “transformation” and “elevation”. The sufficient condition is fulfilled by the continuous creative intervention of God. The concept of God’s creative activity in the moment of man’s death finds its continuation in Chapter 7, where I present a detailed analysis of God’s activity at the time of man’s death. The concept of God’s creative activity extended over the entire process of evolution makes it possible to consider the moment of death as the moment of man’s resurrection. The moment of death is thus a moment of creation in evolutionary terms. Thus, as long as man is related to temporal and spatial elements, his development, or creation, continues. Death is only the completion of the final stage of creation, which may be painful and evoke fear, but in fact should give hope, for it involves resurrection. I also propose that the creative act in the moment of man’s death-resurrection be considered a basic action of God, which explains the manner in which God’s activity is contained within the framework of the creative act, encompassing also the moment of death-resurrection. The final Chapter 8 describes a didactic model illustrating the concept proposed here. I use the analogy of white light dispersion effect in the prism, and compare the incident ray to the creative act, and the dispersed rays going through the prism to the line of man’s natural and supernatural evolution. This model also shows the difference in the perspectives from which the phenomenon of death is seen by God and by man. (shrink)

Forty-two years ago, Capra published “The Tao of Physics” (Capra, 1975). In this book (page 17) he writes: “The exploration of the atomic and subatomic world in the twentieth century has …. necessitated a radical revision of many of our basic concepts” and that, unlike ‘classical’ physics, the sub-atomic and quantum “modern physics” shows resonances with Eastern thoughts and “leads us to a view of the world which is very similar to the views held by mystics of all ages and (...) traditions.“ This article stresses an analogous situation in biology with respect to a new theoretical approach for studying living systems, Integral Biomathics (IB), which also exhibits some resonances with Eastern thought. Stepping on earlier research in cybernetics1 and theoretical biology,2 IB has been developed since 2011 by over 100 scientists from a number of disciplines who have been exploring a substantial set of theoretical frameworks. From that effort, the need for a robust core model utilizing advanced mathematics and computation adequate for understanding the behavior of organisms as dynamic wholes was identified. At this end, the authors of this article have proposed WLIMES (Ehresmann and Simeonov, 2012), a formal theory for modeling living systems integrating both the Memory Evolutive Systems (Ehresmann and Vanbremeersch, 2007) and the Wandering Logic Intelligence (Simeonov, 2002b). Its principles will be recalled here with respect to their resonances to Eastern thought. (shrink)

The so-called “Baldwin Effect” has been studied for years in the fields of Artificial Life, Cognitive Science, and Evolutionary Theory across disciplines. This idea is often conflated with genetic assimilation, and has raised controversy in trans-disciplinary scientific discourse due to the many interpretations it has. This paper revisits the “Baldwin Effect” in Baldwin’s original spirit from a joint historical, theoretical and experimental approach. Social Heredity – the inheritance of cultural knowledge via non-genetic means in Baldwin’s term – is also (...) taken into consideration. I shall argue that the Baldwin Effect can occur via social heredity without necessity for genetic assimilation. Computational experiments are carried out to show that when social heredity is permitted with high fidelity, there is no need for the assimilation of acquired characteristics; instead the Baldwin Effect occurs as promoting more plasticity to facilitate future intelligence. The role of mind and intelligence in evolution and its implications in an extended synthesis of evolution are briefly discussed. (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)

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 presentation proposes to complement an existing development on meaning generation for animals, humans and artificial agents by looking at what could have existed at pre-biotic times and what could be a post-human meaning generation. The core of the approach is based on an existing model for meaning generation: the Meaning Generator System (MGS). The MGS is part of an agent submitted to an internal constraint. The MGS generates a meaning when it receives an information that has a connection (...) with the constraint. The generated meaning is used by the agent to implement an action (physical, biological or mental) aimed at satisfying the constraint. The action can be in or out the agent. The purpose of the presentation is to widen the MGS approach in order to reach a coverage for information, constraint and meaning from a pre-biotic level to a possible post-human one. We present the MGS for animals, humans and artificial agents with the corresponding constraints. We then look at what could have been a constraint at a pre-biotic far from thermodynamic equilibrium level. At the other end of the spectrum we look at a possible post-human status with an evolution of a ‘limit anxiety’ human constraint and also with AAs submitted to animal or human type constraints. Such approach links information science with physics, evolution, anthropology, semiotics and human mind. Continuations are proposed. (shrink)

Simulation models of the Reiterated Prisoner's Dilemma (in the following: RPD-models) are since 30 years considered as one of the standard tools to study the evolution of cooperation (Rangoni 2013; Hoffmann 2000). A considerable number of such simulation models has been produced by scientists. Unfortunately, though, none of these models has empirically been verified and there exists no example of empirical research where any of the RPD-models has successfully been employed to a particular instance of cooperation. Surprisingly, this has (...) not kept scientists from continuing to produce simulation models in the same tradition and from writing their own history as a history of success. In a recent simulation study -- which does not make use of the RPD but otherwise follows the same pattern of research -- Robert Axelrod's (1984) original role model for this kind of simulation studies is praised as ``an extremely effective means for investigating the evolution of cooperation'' and considered as ``widely credited with invigorating that field'' (Rendell et al. 2010). (shrink)

The presentation proposes to complement an existing development on meaning generation for animals, humans and artificial agents by looking at what could have existed at pre-biotic times and what could be a post-human meaning generation. The core of the approach is based on an existing model for meaning generation: the Meaning Generator System (MGS). The MGS is part of an agent submitted to an internal constraint. The MGS generates a meaning when it receives information that has a connection with (...) the constraint. The generated meaning is used by the agent to implement an action (physical, biological or mental) aimed at satisfying the constraint. The action can be in or out the agent. The purpose of the presentation is to widen the MGS approach in order to reach a coverage for information, constraint and meaning from a pre-biotic level to a possible post-human one. We present the MGS for animals, humans and artificial agents with the corresponding constraints. We then look at what could have been a constraint at a pre-biotic far from thermodynamic equilibrium level. At the other end of the spectrum we look at a possible post-human status with an evolution of a ‘limit anxiety’ human constraint and also with AAs submitted to animal or human type constraints. Such approach links information science with physics, evolution, anthropology, semiotics and human mind. Continuations are proposed. (shrink)

Given the personal acquaintance between Alan M. Turing and W. Ross Ashby and the partial proximity of their research fields, a comparative view of Turing’s and Ashby’s work on modelling “the action of the brain” (letter from Turing to Ashby, 1946) will help to shed light on the seemingly strict symbolic/embodied dichotomy: While it is clear that Turing was committed to formal, computational and Ashby to material, analogue methods of modelling, there is no straightforward mapping of these approaches onto symbol-based (...) AI and embodiment-centered views respectively. Instead, it will be demonstrated that both approaches, starting from a formal core, were at least partly concerned with biological and embodied phenomena, albeit in revealingly distinct ways. (shrink)

It is pretty obvious to most of us that self-consciousness is a product of evolution. But its nature is unknown. We propose here a scenario addressing a possible evolutionary nature of self-consciousness covering the segment linking pre-human primates to humans. The scenario is based on evolutions of representations and of inter-subjectivity that could have taken place within the minds of our pre-human ancestors . We begin by situating self-consciousness relatively to other aspects of human consciousness. With the help of (...) anthropology, we date a possible starting point of our scenario at a time when our non self-conscious pre-human ancestors were able to build meaningful representations and were capable of inter-subjectivity, like are our today modern apes. As the proposed scenario is based on an evolution of representations, we recall an existing model for meaningful representations based on the generation of meaningful information by systems submitted to internal constraints. This model allows us to define representations of conspecifics and auto-representations that we assume as having been present in the minds of our pre-human ancestors. The next step of the scenario is to consider an evolution of inter-subjectivity towards identification with conspecifics that could have led to a merger of the auto-representation with the representations of conspecifics in the minds of our ancestors. Such a merger brought the auto-representation to become about an entity existing in the environment, as were the representations of conspecifics. We consider that such identification with conspecifics has introduced in the mind of our ancestors an elementary and embryonic sense of being an existing entity that we name ‘ancestral self-consciousness’. The same process has also imposed to our ancestors an identification with suffering or endangered conspecifics which has produced an important anxiety increase that could have blocked the evolutionary process. We propose that the performances developed by our ancestors to manage that anxiety increase have also generated significant evolutionary advantages that have helped the development of ancestral self-consciousness and favored its evolution toward our full-fledged self-consciousness. It is also proposed that some pre-human primates have avoided the anxiety increase by finding a niche where evolutionary advantages were not necessary. This may have led to our today apes. The contribution of anxiety to the proposed scenario brings to position anxiety management as having guided the evolution of self-consciousness and as still being a key player in our today human minds. Regarding philosophy of mind, possible links between phenomenal consciousness and the proposed nature of self-consciousness are introduced. The conclusion presents a summary of the points addressed here. Possible continuations are highlighted as related to human mind, to anxiety management and to artificial intelligence. (shrink)

I'll show that the kind of analogy between life and information [argued for by authors such as Davies (2000), Walker and Davies (2013), Dyson (1979), Gleick (2011), Kurzweil (2012), Ward (2009)] – that seems to be central to the effect that artificial mind may represent an expected advance in the life evolution in the Universe – is like the design argument, and that if the design argument is unfounded and invalid, the argument to the effect that artificial (...) mind may represent an expected advance in the life evolution in the Universe is also unfounded and invalid. However, if we are prepared to admit (though we should not do so) this method of reasoning as valid, I'll show that the analogy between life and information to the effect that artificial mind may represent an expected advance in the evolution of life in the Universe seems to suggest some type of reductionism of life to information, but biology respectively chemistry, or physics are not reductionist, contrary to what seems to be suggested by the analogy between life and information. (shrink)

Information and meaning are present everywhere around us and within ourselves. Specific studies have been implemented to link information and meaning (Linguistic, Biosemiotic, Psychology, Psychiatry, Cognition, Artificial Intelligence... ). No general coverage is available for the notion of meaning. We propose to complement this lack by a system approach to meaning generation in an evolutionary background. That short paper is a summary of the system approach where a Meaning Generator System (MGS) based on internal constraint satisfaction has been introduced. (...) The MGS can be used for animals (with “stay alive” related constraints), for humans (with “look for happiness” type constraints) and for artificial agents with programmed constraints. Definitions for agency and autonomy are made available based on internal constraint satisfaction. Usage of the MGS with the Turing Test shows why today computers cannot think like humans do. The MGS also allows to introduces evolutionary scenarios for cognition, intentionality and self-consciousness, with an entry point to a human specific anxiety. Continuations are proposed. (shrink)

Objectives: Machine learning (ML) has the potential to facilitate “continual learning” in medicine, in which an ML system continues to evolve in response to exposure to new data over time, even after being deployed in a clinical setting. In this article, we provide a tutorial on the range of ethical issues raised by the use of such “adaptive” ML systems in medicine that have, thus far, been neglected in the literature. -/- Target audience: The target audiences for this tutorial are (...) the developers of ML AI systems, healthcare regulators, the broader medical informatics community, and practicing clinicians. -/- Scope: Discussions of adaptive ML systems to date have overlooked the distinction between 2 sorts of variance that such systems may exhibit—diachronic evolution (change over time) and synchronic variation (difference between cotemporaneous instantiations of the algorithm at different sites)—and underestimated the significance of the latter. We highlight the challenges that diachronic evolution and synchronic variation present for the quality of patient care, informed consent, and equity, and discuss the complex ethical trade-offs involved in the design of such systems. (shrink)