This research aims to determine the effectiveness of the self-directed learning model and the discovery learning model assisted by focusky media on the historical analysis abilities and learning outcomes of students in history subjects. This type of research is a quasi-experiment with a sample size of 65 students at SMA Negeri 1 Bangorejo. The results of the t-test of historical analysis ability and learning outcomes, it shows that there is a significant difference with the difference (...) in the average posttest score for historical analysis ability 2.733 and the difference in the average posttest score for learning outcomes 3.059. Then, the historical analysis effectiveness test, it shows a medium category of 0.050, while the learning outcomes show a medium category of 0.053. This shows that experiment class 1 is better than experiment class 2 and the self-directed learning model has proven to be effective in improving historical analysis skills and learning outcomes. (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are been investigated for the first time, on the basis of little known, and sometimes completely forgotten or unpublished, texts and figures.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)

When philosophers discuss the possibility of machines making scientific discoveries, they typically focus on discoveries in physics, biology, chemistry and mathematics. Observing the rapid increase of computer-use in science, however, it becomes natural to ask whether there are any scientific domains out of reach for machine discovery. For example, could machines also make discoveries in qualitative social science? Is there something about humans that makes us uniquely suited to studying humans? Is there something about machines that would bar them (...) from such activity? A close look at the methodology of interpretive social science reveals several abilities necessary to make a social scientific discovery, and one capacity necessary to possess any of them is imagination. For machines to make discoveries in social science, therefore, they must possess imagination algorithms. (shrink)

Deep learning may transform health care, but model development has largely been dependent on availability of advanced technical expertise. The aim of this study is to develop a deep learning model to predict the gender from retinal fundus images. The proposed model was based on the Xception pre-trained model. The proposed model was trained on 20,000 retinal fundus images from Kaggle depository. The dataset was preprocessed them split into three datasets (training, validation, Testing). After training and cross-validating the (...) proposed model, it was evaluated using the testing dataset. The result of testing, the area under receiver operating characteristic curve (AUROC) of the model was 0.99, precision, recall, f1-score and accuracy were 99%, precision, recall, f1-score and accuracy were 96.83%, 96.83%, 96.82% and 96.83% respectively.. Clinicians are presently unaware of dissimilar retinal feature variants between females and males, stressing the importance of model explain ability for the prediction of gender from retinal fundus images. The proposed deep learning may enable clinician-driven automated discovery of novel visions and disease biomarkers. (shrink)

Much of my working life has been devoted to trying to get across the point that we urgently need to bring about a revolution in the aims and methods of academic inquiry, so that the basic aim becomes to seek and promote wisdom rather than just acquire knowledge.

In this essay I argue that theorists such as Kohn and Mitra have been too hasty in pronouncing the superiority of problem-based learning over direct instruction.

This thesis examines the prospects for mechanical procedures that can identify true, complete, universal, first-order logical theories on the basis of a complete enumeration of true atomic sentences. A sense of identification is defined that is more general than those which are usually studied in the learning theoretic and inductive inference literature. Some identification algorithms based on confirmation relations familiar in the philosophy of science are presented. Each of these algorithms is shown to identify all purely universal theories without (...) function symbols. It is demonstrated that no procedure can solve this universal theory inference problem in the more usual senses of identification. The question of efficiency for theory inference systems is addressed, and some definitions of limiting complexity are examined. It is shown that several aspects of obvious strategies for solving the universal theory inference problem are NP-hard. Finally, some non-worst case heuristic search strategies are examined in light of these NP-completeness results. These strategies are based upon an isomorphism between clausal entailments of a certain class and partition lattices, and are applicable to the improvement of earlier work on language acquisition and logical inductive inference. (shrink)

This chapter explores the personal and professional obstacles faced by Humanities and Social Science scholars contemplating pre-publication of their scholarly work in an on-line network. Borrowing a theoretical framework from the radical educational theorist Ivan Illich, it also develops the idea that pre-publication networks offer higher education a bottom-up, decentralized alternative to business-modeled e-learning. If learners would only embrace this more anarchical medium, appreciating writing for pre-publication as a process of open-ended discovery rather than product delivery, then the (...) prospect of deinstitutionalizing e-learning could become an exciting new reality. The chapter’s methodology is a combination of normative-theoretical analysis and small sample (n=2) case study based on the author’s personal and professional experiences. While the generalizability (or external validity) of the conclusions is limited, the author hopes to motivate further inquiry into the connection between on-line pre-publication and e-learning. (shrink)

Aim: This study attempted to assess the organizational resiliency in the implementation of Basic Education School Learning Continuity Plan and to design a resilient basic education school learning continuity plan. -/- Methodology: The study used mixed method which is quantitative and qualitative. The data for the quantitative part of the study were gathered through a survey with the 19 school heads and 345 teacher- respondents while the qualitative method was conducted through focus group discussion interview with 19 key (...) informants who were composed of the teachers, school heads and stakeholders. The research instrument that was used for the perceived organizational resiliency was a survey questionnaire that was validated by the experts and which the reliability was tested through Cronbach’s alpha with excellent level of internal consistency. The statistical treatment for quantitative results used mean and standard deviation to determine the perception of the respondents with regards to the organizational resiliency on the implementation of the BE-SLCP and Pearson Product Moment Correlation Coefficient, testing its significance at the 0.05 level was used in finding out the relationship between the evaluation of the basic education school learning continuity plan and school performance indicators and organizational resiliency. While content analysis was employed for the qualitative results. -/- Results: The salient findings of the study were as follows: The result showed that the rate of enrollment during pandemic is low while the drop-out rate fostered a positive rate. The school heads and teacher respondents perceived the schools’ organizational resiliency as high. Based on the feedback of the key informants the lessons learned from the implementation of Basic Education School Learning Continuity Plan are strong collaboration, consistent communication, and enhanced ICT Skills. The best practices that were observed are sustained partnership and continuous implementation of programs, projects, and activities. The challenges encountered include authenticity of assessment and low capability of learning facilitators at home. The respondent assessed the developed learning continuity plan as very highly satisfactory. -/- Conclusion: The organizational resiliency of schools is high in its performance of continuing education during pandemic. The study suggests that the schools may developed creative strategies on increasing enrolment; the school may strengthen its school-based management level to ensure that the plans and goals for continuity of education will be achieved; the school may also consider strengthening the stakeholders’ involvement and the school may consider the strategy of close coordination and constant monitoring and follow-ups with parents/guardians on the implementation of learning delivery. (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)

How should a machine intelligence perform unsupervised structure discovery over streams of sensory input? One approach to this problem is to cast it as an apperception task [1]. Here, the task is to construct an explicit interpretable theory that both explains the sensory sequence and also satisfies a set of unity conditions, designed to ensure that the constituents of the theory are connected in a relational structure. However, the original formulation of the apperception task had one fundamental limitation: it (...) assumed the raw sensory input had already been parsed using a set of discrete categories, so that all the system had to do was receive this already-digested symbolic input, and make sense of it. But what if we don't have access to pre-parsed input? What if our sensory sequence is raw unprocessed information? The central contribution of this paper is a neuro-symbolic framework for distilling interpretable theories out of streams of raw, unprocessed sensory experience. First, we extend the definition of the apperception task to include ambiguous (but still symbolic) input: sequences of sets of disjunctions. Next, we use a neural network to map raw sensory input to disjunctive input. Our binary neural network is encoded as a logic program, so the weights of the network and the rules of the theory can be solved jointly as a single SAT problem. This way, we are able to jointly learn how to perceive (mapping raw sensory information to concepts) and apperceive (combining concepts into declarative rules). (shrink)

Humankind is currently confronted with a critical challenge that determines its very existence, not only on an individual, racial, or national level but as a whole species: the fight against climate change and environmental degradation. To win this battle, humanity needs innovations and non-linear thinking. Nature has long been a substantial information source for unthinkable discoveries that save human lives. The paper suggests that by understanding the nature, emergence, and mechanism of serendipity, the survival skill of humans, humanity can capitalize (...) on it to learn from nature and generate nature-based innovations that can address the climate and environmental degradation crises. In the era of Artificial Intelligence (AI) proliferation, AI will be a vital tool providing navigational and useful information to leverage the power of serendipity in climate and sustainability science. However, an eco-surplus culture that incorporates core values pertaining to nature and sees environmental sustainability as the conscience of the times needs to be built to direct and control the immense power of AI-leveraged serendipity. Insights applied in this paper are drawn from the book titled “A New Theory of Serendipity: Nature, Emergence and Mechanism”. (shrink)

This paper comprehensively examines Antoine Henri Becquerel’s discovery of radioactivity in 1896, a groundbreaking scientific advancement often viewed through serendipity. This case study explores the typologies of serendipity and investigates the conditions that foster its occurrence. A detailed study of Becquerel’s investigations reveals that his discovery aligns with a Walpolian type of serendipity, characterized by true serendipity heavily influenced by unforeseen experimental results. This paper emphasizes the role of bisociation, a cognitive process associating previously disconnected concepts, in Becquerel’s (...) discovery, challenging the view that his discovery was merely a chance event. Instead, it argues that Becquerel’s discovery represents an intricate interplay of logic and chance, exemplifying the Walpolian type of serendipity. Moreover, by examining Becquerel’s experimental design, results, and innovative approach, this paper illustrates that his discovery adheres to the fundamental aspects of the scientific method, albeit executed in a non-linear and iterative manner. The process and context of Becquerel’s discovery provide valuable insights into scientific knowledge inception, progression, and definition, underscoring the intertwined roles of serendipity and scientific inquiry in advancing science. (shrink)

This paper attempts to answer a central question in unsupervised learning: what does it mean to “make sense” of a sensory sequence? In our formalization, making sense involves constructing a symbolic causal theory that both explains the sensory sequence and also satisfies a set of unity conditions. The unity conditions insist that the constituents of the causal theory – objects, properties, and laws – must be integrated into a coherent whole. On our account, making sense of sensory input is (...) a type of program synthesis, but it is unsupervised program synthesis. Our second contribution is a computer implementation, the Apperception Engine, that was designed to satisfy the above requirements. Our system is able to produce interpretable human-readable causal theories from very small amounts of data, because of the strong inductive bias provided by the unity conditions. A causal theory produced by our system is able to predict future sensor readings, as well as retrodict earlier readings, and impute (fill in the blanks of) missing sensory readings, in any combination. In fact, it is able to do all three tasks simultaneously. We tested the engine in a diverse variety of domains, including cellular automata, rhythms and simple nursery tunes, multi-modal binding problems, occlusion tasks, and sequence induction intelligence tests. In each domain, we test our engine's ability to predict future sensor values, retrodict earlier sensor values, and impute missing sensory data. The Apperception Engine performs well in all these domains, significantly out-performing neural net baselines. We note in particular that in the sequence induction intelligence tests, our system achieved human-level performance. This is notable because our system is not a bespoke system designed specifically to solve intelligence tests, but a general-purpose system that was designed to make sense of any sensory sequence. (shrink)

This article examines two questions about scientists’ search for knowledge. First, which search strategies generate discoveries effectively? Second, is it advantageous to diversify search strategies? We argue pace Weisberg and Muldoon, “Epistemic Landscapes and the Division of Cognitive Labor”, that, on the first question, a search strategy that deliberately seeks novel research approaches need not be optimal. On the second question, we argue they have not shown epistemic reasons exist for the division of cognitive labor, identifying the errors that led (...) to their conclusions. Furthermore, we generalize the epistemic landscape model, showing that one should be skeptical about the benefits of social learning in epistemically complex environments. (shrink)

The central thesis of this book is that we need to reform philosophy and join it to science to recreate a modern version of natural philosophy; we need to do this in the interests of rigour, intellectual honesty, and so that science may serve the best interests of humanity. Modern science began as natural philosophy. In the time of Newton, what we call science and philosophy today – the disparate endeavours – formed one mutually interacting, integrated endeavour of natural philosophy: (...) to improve our knowledge and understanding of the universe, and to improve our understanding of ourselves as a part of it. Profound discoveries were made, indeed one should say unprecedented discoveries. It was a time of quite astonishing intellectual excitement and achievement. And then natural philosophy died. It split into science on the one hand, and philosophy on the other. This happened during the 18th and 19th centuries, and the split is now built into our intellectual landscape. But the two fragments, science and philosophy, are defective shadows of the glorious unified endeavour of natural philosophy. Rigour, sheer intellectual good sense and decisive argument demand that we put the two together again, and rediscover the immense merits of the integrated enterprise of natural philosophy. This requires an intellectual revolution, with dramatic implications for how we understand our world, how we understand and do science, and how we understand and do philosophy. There are dramatic implications, too, for education. And it does not stop there. For, as I show in the final chapter, resurrected natural philosophy has dramatic, indeed revolutionary methodological implications for social science and the humanities, indeed for the whole academic enterprise. It means academic inquiry needs to be reorganized so that it comes to take, as its basic task, to seek and promote wisdom by rational means, wisdom being the capacity to realize what is of value in life, for oneself and others, thus including knowledge, technological know-how and understanding, but much else besides. The outcome is institutions of learning rationally designed and devoted to helping us tackle our immense global problems in increasingly cooperatively rational ways, thus helping us make progress towards a good world – or at least as good a world as possible. (shrink)

In his recent article "Advent of Google means we must rethink our approach to education", Sugata Mitra argues that our education system needs to change. He suggests that the existence of modern technologies such as Google make the skills of the past obsolete. For Mitra, the only reason we continue to teach skills such as longhand multiplication is because we have some sort of romantic attachment to the past. In this short article I respond to his central claim that we (...) should replace the Intellectual Traditionalist form of education with a new system. I argue that Mitra description of the Intellectual Traditionalist system is a strawman. Further, I argue that it would be a mistake to replace Intellectual Traditionalism with a constructivist pedagogy. (shrink)

Two fundamentally distinct approaches to the teaching of philosophy are contrasted: On the one hand, there is the “information-oriented” approach which has dominated classrooms and which emphasizes the understanding of historically important philosophical works. On the other hand, there is the “cognitive skills” approach. The two approaches may be distinguished under the headings of ‘knowing that’ as opposed to ‘knowing how’. This paper describes and discusses four perspectives relating to the teaching of cognitive skills: (i) the discovery-oriented approach, (ii) (...) Piagetian learning cycles, (iii) protocol analysis, and (iv) conceptual therapy. The latter approach reflects the author’s interest in helping students to develop “therapeutic” skills that enable them to identify and eliminate concepts which they employ in their thinking and which are incompatible with their own presuppositional bases and are therefore self-refuting. ●●●●● -/- 2022 UPDATE: The approach of this paper has been updated and developed further in Appendix II, "Epistemological Intelligence," of the author’s 2021 book _Critique of Impure Reason: Horizons of Possibility and Meaning_. The book is available both in a printed edition (under ISBN 978-0-578-88646-6 from Barnes & Noble, Amazon, and other booksellers) and an Open Access eBook edition (available through Philpapers under the book’s title and other philosophy online archives). (shrink)

We need urgently to bring about a revolution in universities around the world, wherever possible, so that they take their fundamental task to be, not to acquire and apply knowledge, but rather to help humanity learn how to resolve conflicts and problems of living in increasingly cooperatively rational ways, so that we may make progress towards a good, genuinely civilized, wise world. The pursuit of knowledge would be a vital but subsidiary task. I have argued for the urgent need for (...) such an academic revolution for nearly 50 years, ever since the publication of two books: What’s Wrong With Science? Towards a People’s Rational Science of Delight and Compassion, 1976, and From Knowledge to Wisdom: A Revolution for Science and the Humanities, 1984, both available free online. This article, written in preparation for a talk given to Pittsburgh University on the 15th September 2023, gives an outline of my baffled struggles with problems of philosophy, science, literature and life that led up to the discovery of the urgent need for an intellectual and institutional revolution in universities around the world, needed in order to galvanize the social revolution required to enable us to make progress to a world in which peace, justice, democracy, individual freedom, sustainable prosperity, the possibility of a good life, are available to all, insofar as that is attainable. (shrink)

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

This paper reports on an ongoing ARC Discovery Project that is conducting design research into learning in collaborative virtual worlds (CVW).The paper will describe three design components of the project: (a) pedagogical design, (b)technical and graphics design, and (c) learning research design. The perspectives of each design team will be discussed and how the three teams worked together to produce the CVW. The development of productive failure learning activities for the CVW will be discussed and there (...) will be an interactive demonstration of the project's CVW. (shrink)

Humankind is currently confronted with a critical challenge that determines its very existence, not only on an individual, racial, or national level but as a whole species: the fight against climate change and environmental degradation. To win this battle, humanity needs innovations and non-linear thinking. Nature has long been a substantial information source for unthinkable discoveries that save human lives. The paper suggests that by understanding the nature, emergence, and mechanism of serendipity, the survival skill of humans, humanity can capitalize (...) on it to learn from nature and generate nature-based innovations that can address the climate and environmental degradation crises. In the era of Artificial Intelligence (AI) proliferation, AI will be a vital tool providing navigational and useful information to leverage the power of serendipity in climate and sustainability science. However, an eco-surplus culture that incorporates core values pertaining to nature and sees environmental sustainability as the conscience of the times needs to be built to direct and control the immense power of AI-leveraged serendipity. Insights applied in this paper are drawn from the book titled “A New Theory of Serendipity: Nature, Emergence and Mechanism”. (shrink)

In adversarial machine learning, attackers add carefully crafted perturbations to input, where the perturbations are almost imperceptible to humans, but can cause models to make wrong predictions. In this paper, we did comprehensive review of some of the most recent research, advancement and discoveries on adversarial attack, adversarial sampling generation, the potency or effectiveness of each of the existing attack methods, we also did comprehensive review on some of the most recent research, advancement and discoveries on adversarial defense strategies, (...) the effectiveness of each defense methods, and finally we did comparison on effectiveness and potency of different adversarial attack and defense methods. We came to conclusion that adversarial attack will mainly be blackbox for the foreseeable future since attacker has limited or no knowledge of gradient use for NN model, we also concluded that as dataset becomes more complex, so will be increase in demand for scalable adversarial defense strategy to mitigate or combat attack, and we strongly recommended that any neural network model with or without defense strategy should regularly be revisited, with the source code continuously updated at regular interval to check for any vulnerability against newer attack. (shrink)

Difficulties in learning Ohm’s Law suggest a need to refocus it from the law for a part of the circuit to the law for the whole circuit. Such a revision may improve understanding of Ohm’s Law and its practical applications. This suggestion comes from analysis of the history of the law’s discovery and its teaching. The historical materials this paper provides can also help teacher to improve students’ insights into the nature of science.

The main aim of Samuel Hartlib was to provide an advancement of learning finalized to the amelioration of the material conditions of men and the pursuit of a religious peace, i.e., the unification of the Protestants. To this aim, inspired by Comenius, he devoted his efforts or gathering knowledge by the creation of a society or office of learned men (in technical fields, philosophy, and theology), and by the establishment of a network of correspondents (the Hartlib Circle). The method (...) of discovery underlying his program of advancement of learning was inspired by Bacon’s Novum Organum and by Jacopo Aconcio’s method of analysis, while the categorization and transmission of knowledge had to be based on commonplace books and artificial languages. His plan of economic improvement, to be fulfilled mainly through the amelioration of husbandry, was motivated by the Puritan Millenarianism to which he adhered. (shrink)

It is well-established that algorithms can be instruments of injustice. It is less frequently discussed, however, how current modes of AI deployment often make the very discovery of injustice difficult, if not impossible. In this article, we focus on the effects of algorithmic profiling on epistemic agency. We show how algorithmic profiling can give rise to epistemic injustice through the depletion of epistemic resources that are needed to interpret and evaluate certain experiences. By doing so, we not only demonstrate (...) how the philosophical conceptual framework of epistemic injustice can help pinpoint potential, systematic harms from algorithmic profiling, but we also identify a novel source of hermeneutical injustice that to date has received little attention in the relevant literature: epistemic fragmentation. Epistemic fragmentation is a structural characteristic of algorithmically-mediated environments that isolate individuals, making it more difficult to develop, uptake and apply new epistemic resources. This, in turn, can impede the identification and conceptualisation of emerging harms in these environments. We trace the occurrence of hermeneutical injustice back to the fragmentation of the epistemic experiences of individuals, who are left more vulnerable by the inability to share, compare, and learn from shared experiences. (shrink)

Analysis of grip force signals tailored to hand and finger movement evolution and changes in grip force control during task execution provide unprecedented functional insight into somatosensory cognition. Somatosensory cognition is a basis of our ability to manipulate, move, and transform objects of the physical world around us, to recognize them on the basis of touch alone, and to grasp them with the right amount of force for lifting and manipulating them. Recent technology has permitted the wireless monitoring of grip (...) force signals recorded from biosensors in the palm of the human hand to track and trace human grip forces deployed in cognitive tasks executed under conditions of variable sensory (visual, auditory) input. Non-invasive multi-finger grip force sensor technology can be exploited to explore functional interactions between somatosensory brain mechanisms and motor control, in particular during learning a cognitive task where the planning and strategic execution of hand movements is essential. Sensorial and cognitive processes underlying manual skills and/or hand-specific (dominant versus non-dominant hand) behaviors can be studied in a variety of contexts by probing selected measurement loci in the fingers and palm of the human hand. Thousands of sensor data recorded from multiple spatial locations can be approached statistically to breathe functional sense into the forces measured under specific task constraints. Grip force patterns in individual performance profiling may reveal the evolution of grip force control as a direct result of cognitive changes during task learning. Grip forces can be functionally mapped to from-global-to-local coding principles in brain networks governing somatosensory processes for motor control in cognitive tasks leading to a specific task expertise or skill. Under the light of a comprehensive overview of recent discoveries into the functional significance of human grip force variations, perspectives for future studies in cognition, in particular the cognitive control of strategic and task relevant hand movements in complex real-world precision task, are pointed out. (shrink)

The paper identifies defining characteristics of the principal models of problem-solving behavior which are useful in developing a general theory of problem-solving. An attempt is made both to make explicit those disagreements between theorists of different persuasions which have served as obstacles to an integrated approach, and to show that these disagreements have arisen from a number of conceptual confusions: The conflict between information processors and behavioral analysts has resulted from a common failure to understand theoretical sufficiency, and hence these (...) theorists have been at a loss to understand one another. Two directions of research in problem-solving, mechanical algorithmic problem-solving and the psychology of invention, have been thought to be divergent, but in fact complement one another once it is clear that problem-solving involves neither discovery nor invention, but rather is a matter of perceptual encoding and processing. Successful problem-solving behavior can be described as adaptive, learning behavior in which organization skills are effectively associated with situationally determined perceptual encoding processes of the individual mechanical or biological problem-solver. (shrink)

Artificial intelligence (AI) is expected to revolutionise the practice of medicine. Recent advancements in the field of deep learning have demonstrated success in variety of clinical tasks: detecting diabetic retinopathy from images, predicting hospital readmissions, aiding in the discovery of new drugs, etc. AI’s progress in medicine, however, has led to concerns regarding the potential effects of this technology on relationships of trust in clinical practice. In this paper, I will argue that there is merit to these concerns, (...) since AI systems can be relied on, and are capable of reliability, but cannot be trusted, and are not capable of trustworthiness. Insofar as patients are required to rely on AI systems for their medical decision-making, there is potential for this to produce a deficit of trust in relationships in clinical practice. (shrink)

Causal models of agents have been used to analyse the safety aspects of machine learning systems. But identifying agents is non-trivial -- often the causal model is just assumed by the modeler without much justification -- and modelling failures can lead to mistakes in the safety analysis. This paper proposes the first formal causal definition of agents -- roughly that agents are systems that would adapt their policy if their actions influenced the world in a different way. From this (...) we derive the first causal discovery algorithm for discovering agents from empirical data, and give algorithms for translating between causal models and game-theoretic influence diagrams. We demonstrate our approach by resolving some previous confusions caused by incorrect causal modelling of agents. (shrink)

If you start taking courses in contemporary cognitive science, you will soon encounter a particular picture of the human mind. This picture says that the mind is a lot like a computer. Specifically, the mind is made up of certain states and certain processes. These states and processes interact, in accordance with certain general rules, to generate specific behaviors. If you want to know how those states and processes got there in the first place, the only answer is that they (...) arose through the interaction of other states and processes, which arose from others... until, ultimately, the chain goes back to factors in our genes and our environment. Hence, one can explain human behavior just by positing a collection of mental states and psychological processes and discussing the ways in which these states and processes interact. This picture of the mind sometimes leaves people feeling deeply uncomfortable. They find themselves thinking something like: 'If the mind actually does work like that, it seems like we could never truly be morally responsible for anything we did. After all, we would never be free to choose any behavior other than the one we actually performed. Our behaviors would just follow inevitably from certain facts about the configuration of the states and processes within us.' Many philosophers think that this sort of discomfort is fundamentally confused or wrongheaded. They think that the confusion here can be cleared up just by saying something like: 'Wait! It doesn't make any sense to say that the interaction of these states and processes is preventing you from controlling your own life. The thing you are forgetting is that the interaction of these states and processes – this whole complex system described by cognitive science – is simply you. So when you learn that these states and processes control your behavior, all you are learning is that you are controlling your behavior. There is no reason at all to see these discoveries as a threat to your freedom or responsibility.'2 Philosophers may regard this argument as a powerful one, perhaps even irrefutable.. (shrink)

Healthcare systems across the globe are struggling with increasing costs and worsening outcomes. This presents those responsible for overseeing healthcare with a challenge. Increasingly, policymakers, politicians, clinical entrepreneurs and computer and data scientists argue that a key part of the solution will be ‘Artificial Intelligence’ (AI) – particularly Machine Learning (ML). This argument stems not from the belief that all healthcare needs will soon be taken care of by “robot doctors.” Instead, it is an argument that rests on the (...) classic counterfactual definition of AI as an umbrella term for a range of techniques that can be used to make machines complete tasks in a way that would be considered intelligent were they to be completed by a human. Automation of this nature could offer great opportunities for the improvement of healthcare services and ultimately patients’ health by significantly improving human clinical capabilities in diagnosis, drug discovery, epidemiology, personalised medicine, and operational efficiency. However, if these AI solutions are to be embedded in clinical practice, then at least three issues need to be considered: the technical possibilities and limitations; the ethical, regulatory and legal framework; and the governance framework. In this article, we report on the results of a systematic analysis designed to provide a clear overview of the second of these elements: the ethical, regulatory and legal framework. We find that ethical issues arise at six levels of abstraction (individual, interpersonal, group, institutional, sectoral, and societal) and can be categorised as epistemic, normative, or overarching. We conclude by stressing how important it is that the ethical challenges raised by implementing AI in healthcare settings are tackled proactively rather than reactively and map the key considerations for policymakers to each of the ethical concerns highlighted. (shrink)

The change in the organization of science education over the past fifty years is quickly recalled. Being its cultural bound the lack of a conception of the foundation of science, the multiple innovations have resulted as temporary improvements without a clear direction, apart from the technocratic goal of an automation of learning processes. The discovery of two dichotomies as the foundations of science suggests a pluralist conception of science, and hence the need to entirely renew science education, in (...) particular by introducing the notions of incommensurability and radical variations in meaning of the basic notions. This change was already anticipated by several proposals within each subject-matter. (shrink)

Visual analytics (VA) combines the strengths of human and machine intelligence to enable the discovery of interesting patterns in challenging datasets. Historically, most attention has been given to developing the machine component—for example, machine learning or the human-computer interface. However, it is also essential to develop the abilities of the analysts themselves, especially at the beginning of their careers. -/- For the past several years, we at the University of British Columbia (UBC)—with the support of The Boeing Company—have (...) experimented with various ways of preparing undergraduate students for VA. Although inspired by the need to prepare students to become visual analysts, the result turned out to be fairly general in scope, applicable to other analytical approaches, as well as more general research. In hindsight, this makes considerable sense. Although the visual component of VA is necessary, it is insufficient; many analytical activities at the human end involve nonvisual skills, such as effective decision-making and the ability to quickly focus on the relevant parts of a problem. -/- The result of this experimentation is a third-year undergraduate course titled Cognitive Systems 303 (COGS 303) that focuses on “VA unplugged”—that is, on developing investigative abilities prior to training on the VA systems themselves. It was felt that if students focused on developing basic analytical habits of thought prior to learning VA systems, these habits would be reinforced by subsequent practice on “live” systems. (shrink)

Science urges philosophy to be more empirical and philosophy urges science to be more reflective. This markedly occurred along the “discovery of the artificial” (CORDESCHI 2002): in the early days of Cybernetics and Artificial Intelligence (AI) researchers aimed at making machines more cognizant while setting up a framework to better understand human intelligence. By and large, those genuine goals still hold today, whereas AI has become more concerned with specific aspects of intelligence, such as (machine) learning, reasoning, vision, (...) and action. As a matter of fact, the field suffers from a chasm between two formerly integrated aspects. One is the engineering endeavour involving the development of tools, e.g., autonomous systems for driving cars as well as software for semantic information retrieval. The other is the philosophical debate that tries to answer questions concerning the nature of intelligence. Bridging these two levels can indeed be crucial in developing a deeper understanding of minds. An opportunity might be offered by the cogent theme of emotions. Traditionally, computer science, psychological and philosophical research have been compelled to investigate mental processes that do not involve mood, emotions and feelings, in spite of Simon’s early caveat (SIMON 1967) that a general theory of cognition must incorporate the influences of emotion. Given recent neurobiological findings and technological advances, the time is ripe to seriously weigh this promising, albeit controversial, opportunity. (shrink)

What are the implications for human society, and for our institutions of higher learning, of the discovery of a sophisticated extraterrestrial intelligence (ETI) operating on and around Earth? This book explores this timely question from a multidisciplinary perspective. It considers scientific, philosophical, theological, and interdisciplinary ways of thinking about the question, and it represents all viewpoints on how likely it is that an ETI is already operating here on Earth. The book’s contributors represent a wide range of academic (...) disciplines in their formal training and later vocations, and, upon reflection on the book’s topic, they articulate a diverse range of insights into how ETI will impact humankind. It is safe to say that any contact or communication with ETI will not be merely a game changer for human society, but it also will be a paradigm changer. It makes sense for human beings to prepare themselves now for this important transition. (shrink)

The biological Brain createst the mental Mind. Today our collective Mind becomes so fascinated by its source, the Brain, that all sciences incorporate neuro models in their concepts to increase global brainpower with technology. The most significant discovery is probably technology. We learn how the Brain creates consciousness and how the Brain generates momentaneous Time. Discover how at each moment in Time, our body runs the whole program of Evolution. What we know about the Brain is phantasy from the (...) Mind. (shrink)

Schools, colleges, and universities have become homogenizing systems that are almost exclusively focused on imposing a pre-ordered curricula through exams and grades or tight research lines. In the process, they are killing passion, creativity, and individuals’ potential and skills. Ultimately, schools and academia make up a system that serves a collective machinery but suffocates individual growth. This state of affairs is not a necessary evil. Learning, discovering and teaching can be a natural, spontaneous and luminous expressions of a free (...) and progressive growth if they are allowed to be practiced in an appropriate environment. This is a ‘manifesto’ for a Free-Progress-Education (FPE) paradigm according to which the best way of learning, acquiring knowledge, and doing research comes through a process of free self-directed learning, and a progress of self-unfoldment and self-discovery, that must be guided from within. In schools, colleges, universities and beyond. A FPE learning centre would be expected to foster curiosity, intuition, self-directed-learning in diversity, and, especially, wholesome respect for the practice of complete and responsible freedom of individual expression.FPE goes beyond the standard paradigm of unschooling or the pedagogical approach of democratic schools since it includes self-directed-education that can also work in high schools, colleges, universities, and research centres. It iAfter a brief introductory presentation, a personal preamble of the author describes his experiences with institutionalized learning from childhood to the doctoral dissertation and in a high school as a teacher. Then, the roots of the stagnant state of education will be investigated which is still based on an industrial and mechanistic mindset, and is perceived with increasing dissatisfaction. While analysing the detrimental effects that a managerial and industrial mentality has had on the education and intellectual growth of several generations, we will take as an example the deficiencies of the so-called big science, i.e. of the modern, large-scale scientific initiatives. Surveying past and present learning approaches such as the interesting renaissance of homeschooling and welcoming new trends such as unschooling or democratic education, the second part of this book looks beyond these paradigms searching for a wider spirit of education. It is emphasized that no reform is possible inside the current school and university paradigm, because it is in its essence an authoritarian system that won't allow itself to be dismantled from within. The last part of this book focuses upon a brief set of alternative proposals, which aim at overcoming the centuries-old shortcomings of the present educational system, by favouring intrinsic over extrinsic motivation. Preliminary practical ideas are put forward on what a free-progress learning community might look like, and what the first steps for its realization might be. It is explained there why it is only through a change from the ground up that the certificate-oriented educational system can transform itself into a project-oriented, self-organized, competence-portfolio based one, with no exams, grades, degrees, or other administrative trammels. At the same time, it must be made clear that the ultimate aim of doing away with the present system of assessment criteria would be to install a much deeper and articulated paradigm shift than some superficial reform and even beyond the actually undeveloped democratic education concept which still falls short beyond high-school level. What is visualized is an evolutionary pedagogical perspective, compared to the conventional one, and presented as the necessary condition for a 'Copernican approach' to education. Only after that perspective has been realized can new competences, curiosity, intuition, and real forms of creative learning return to flourish in schools and academia. (shrink)

Popper first developed his theory of scientific method – falsificationism – in his The Logic of Scientific Discovery, then generalized it to form critical rationalism, which he subsequently applied to social and political problems in The Open Society and Its Enemies. All this can be regarded as constituting a major development of the 18th century Enlightenment programme of learning from scientific progress how to achieve social progress towards a better world. Falsificationism is, however, defective. It misrepresents the real, (...) problematic aims of science. We need a new conception of scientific method, a meta-methodology which provides a framework for the improvement of the aims and methods of science as scientific knowledge improves. This aim-oriented empiricist idea can be generalized to form a conception of rationality – aim-oriented rationality – which helps us improve problematic aims and methods whatever we may be doing. In this way, Popper’s version of the Enlightenment programme can be much improved, indeed transformed. (shrink)

In this essay, I argue that an immortal existence could be desirable. Taking the accounts of Williams and Smuts under careful consideration, I agree with Fischer that an immortal existence could be gratifying. When Fischer argues that it is unfair for Williams to posit that an immortal life must have self-exhausting pleasures and, overall, a better experience than mortal life, he gets to the crux of the argument for immortality: as long as there are positive categorical desires for the individual, (...) then such life-affirming desires will provide an impetus to carry on. In moving past the Teiresias model of a phenomenon that retains memories while changing characters, I argue that a life of intellectual inquiry – which essentially alters the character of the individual while maintaining memories – offers an outward looking existence which provides internal pleasures. Accordingly, with the use of technology, computer simulations have the potential to provide pleasures and experiences that escape reality. In this sense, technology has the potential to supplement an immortal life. We cannot say whether there will be a pinnacle of such learning and pleasure which leads to decreasing returns, but it seems plausible that an immortal being who incorporates learning and pleasure that could potentially lead to innovation and discovery would seek to continue such intellectual inquiry and varied experiences until all learning potentials were exhausted. (shrink)

“ A man orders a whole pizza pie for himself and is asked whether he would like it cut into eight or four slices. He responds, ‘Four, I’m on a diet ”’ (Noël Carroll) -/- While not hilarious --so funny that it induces chortling punctuated with outrageous vomiting--this little gem is amusing. We recognize that something has gone wrong. On a first reading it might not compute, something doesn’t quite make sense. Then, aha! , we understand the hapless dieter has (...) misapplied general rules of thumb, mental short-cuts, or heuristics, that we were also initially committed to and that would usually be good enough to rely upon— fewer slices equals fewer calories; diets require fewer calories, etc—but in this particular case they fail, and the feeling of mirth is our reward for making this discovery. We don’t say all of that after a punchline, of course, but that’s what is happening according to the Humor as Error-Detection Theory : our sense of humor can sense our errors. This chapter will focus on the overlap and benefits of a humorous and philosophical attitude toward the world and our place in it. The historian of philosophy Will Durant tells us that genuine philosophy begins when one learns to doubt; we can say something similar with humor--trust me. (shrink)

The most exciting and important new philosophical idea of the past decade, in my view, is the discovery that we urgently need to bring about a revolution in science, and in academic inquiry more generally, so that the basic intellectual aim becomes to seek and promote wisdom. We urgently need to transform our schools and universities so that they become rationally devoted to helping humanity learn how to tackle our grave global problems, and thus make progress towards as good (...) a world as possible. (shrink)

Evolutionary economics often focuses on the comparison between economic competition and the process of natural selection to select the fitter members of a given population. But that neglects the other "half" of an evolutionary process, the mechanism for the generation of new possibilities that is key to dynamic efficiency. My topic is the process of parallel experimentation which I take to be a process of multiple experiments running concurrently with some form of common goal, with some semi-isolation between the experiments, (...) with benchmarking comparisons made between the experiments, and with the "migration" of discoveries between experiments wherever possible to ratchet up the performance of the group. The thesis is that parallel experimentation is a fundamental dynamic efficiency scheme to enhance and accelerate variation, innovation, and learning in contexts of genuine uncertainty or known ignorance. Within evolutionary biology, this type of parallel experimentation scheme was developed in Sewall Wright's shifting balance theory of evolution. It addressed the rather neglected topic of how a population on a low fitness peak might eventually be able to go "downhill" against selective pressures, traverse a valley of low fitness, and then ascend a higher fitness peak. The theme of parallel experimentation is used to recast and pull together dynamic and pluralistic theories in economics, political theory, philosophy of science, and social learning. (shrink)

The most exciting and important new philosophical idea of the past decade, in my view, is the discovery that we urgently need to bring about a revolution in science, and in academic inquiry more generally, so that the basic intellectual aim becomes to seek and promote wisdom. We urgently need to transform our schools and universities so that they become rationally devoted to helping humanity learn how to tackle our grave global problems, and thus make progress towards as good (...) a world as possible. (shrink)

As is clear from the multiple references to knowledge in the proemium of fragment B1, Parmenides presented himself to his audiences as one who had achieved a profound insight into the nature of ‘what-is’. In support of this claim he conducted an elenchos or ‘testing’ of the ways of inquiry available for thinking, in the process revealing a set of sêmata or ‘signs’ indicating that what-is an eternal, indivisible, and unchanging plenum. In each of these respects, Parmenides was speaking the (...) language of discovery heard elsewhere in early Greek poetry. Similarly, his claim that we can neither learn nor know about what-is-not (hence must not say or think ‘it is not’) was justified by the ordinary meaning of the ancient Greek verbs for learning and knowing. Strikingly, Parmenides’ revisionary metaphysics rested in large measure on a widely shared view of what can be learned, known, and made known to others. -/- . (shrink)

Well elucidated and defined education policy is the most essential criteria for comprehensive progress of all human beings. From the time immemorial it is known that progress can be ushered only through education. A futuristic education policy both at the school and university level is extremely imperative. Countries at the global level have been adopting effective education policies to meet the changing needs of education and society at large. There is a need to shift educational approach from rote learning (...) to understanding, from exhaustive learning techniques to excitement of discovery and towards the joyful exploration. True education must encompass a synchronized working of body, mind and spirit. The ultimate aim of education must be to help the growing soul draw out the best and make it perfect for a noble use. The aim of education is not only to prepare an individual to succeed in life and society, but to reach the optimum. With this background, the paper is attempting at the theoretical level, to study the Integral philosophy, in the light of NEP 2020. It also tries to inquire into the modalities of Integral thinking, propose the application of the same in education and pedagogies to characterize its practice and goals in Integral Education. (shrink)

1.Summary The key terms. 1. Key term: ‘Sunyata’. Nagarjuna is known in the history of Buddhism mainly by his keyword ‘sunyata’. This word is translated into English by the word ‘emptiness’. The translation and the traditional interpretations create the impression that Nagarjuna declares the objects as empty or illusionary or not real or not existing. What is the assertion and concrete statement made by this interpretation? That nothing can be found, that there is nothing, that nothing exists? Was Nagarjuna denying (...) the external world? Did he wish to refute that which evidently is? Did he want to call into question the world in which we live? Did he wish to deny the presence of things that somehow arise? My first point is the refutation of this traditional translation and interpretation. 2. Key terms: ‘Dependence’ or ‘relational view’. My second point consists in a transcription of the keyword of ‘sunyata’ by the word ‘dependence’. This is something that Nagarjuna himself has done. Now Nagarjuna’s central view can be named ‘dependence of things’. Nagarjuna is not looking for a material or immaterial object which can be declared as a fundamental reality of this world. His fundamental reality is not an object. It is a relation between objects. This is a relational view of reality. This is the heart of Nagarjuna’s ideas. In the 19th century a more or less unknown Italian philosopher, Vincenzo Goberti, spoke about relations as the mean and as bonds between things. Later, in quantum physics and in the philosophy of Alfred North Whitehead we are talking about interactions and entanglements. These ideas of relatedness or connections or entanglements in Eastern and Western modes of thought are the main idea of this essay. Not all entanglements are known. Just two examples: the nature of quantum entanglements is not known. Quantum entanglements should be faster than light. That's why Albert Einstein had some doubts. A second example: the completely unknown connections between the mind and the brain. Other examples are mysterious like the connections between birds in a flock. Some are a little known like gravitational forces. 3. Key terms: ‘Arm in arm’. But Nagarjuna did not stop there. He was not content to repeat this discovery of relational reality. He went on one step further indicating that what is happening between two things. He gave indications to the space between two things. He realized that not the behaviour of bodies, but the behaviour of something between them may be essential for understanding the reality. This open space is not at all empty. It is full of energy. The open space is the middle between things. Things are going arm in arm. The middle might be considered as a force that bounds men to the world and it might be seen as well as a force of liberation. It might be seen as a bondage to the infinite space. 4. Key term: Philosophy. Nagarjuna, we are told, was a Buddhist philosopher. This statement is not wrong when we take the notion ‘philosophy’ in a deep sense as a love to wisdom, not as wisdom itself. Philosophy is a way to wisdom. Where this way has an end wisdom begins and philosophy is no more necessary. A.N. Whitehead gives philosophy the commission of descriptive generalization. We do not need necessarily a philosophical building of universal dimensions. Some steps of descriptive generalization might be enough in order to see and understand reality. There is another criterion of Nagarjuna’s philosophy. Not his keywords ‘sunyata’ and ‘pratityasamutpada’ but his 25 philosophical examples are the heart of his philosophy. His examples are images. They do not speak to rational and conceptual understanding. They speak to our eyes. Images, metaphors, allegories or symbolic examples have a freshness which rational ideas do not possess. Buddhist dharma and philosophy is a philosophy of allegories. This kind of philosophy is not completely new and unknown to European philosophy. Since Plato’s allegory of the cave it is already a little known. (Plato 424 – 348 Befor Current Era) The German philosopher Hans Blumenberg has underlined the importance of metaphors in European philosophy. 5. Key terms: Quantum Physics. Why quantum physics? European modes of thought had no idea of the space between two this. They were bound to the ideas of substance or subject, two main metaphysical traditions of European philosophical history, two main principles. These substances and these subjects are two immaterial bodies which were considered by traditional European metaphysics as lying, as a sort of core, inside the objects or underlying the empirical reality of our world. The first European scientist who saw with his inner eye the forces between two things had been Michael Faraday (1791-1867). Faraday was an English scientist who contributed to the fields of electromagnetism. Later physicists like Albert Einstein, Niels Bohr, Erwin Schrödinger, Werner Heisenberg and others followed his view in modern physics. This is a fifth point of my work. I compare Nagarjuna with European scientific modes of thought for a better understanding of Asia. I do not compare Nagarjuna with European philosophers like Hegel, Heidegger, Wittgenstein. The principles and metaphysical foundations of physical sciences are more representative for European modes of thought than the ideas of Hegel, Heidegger and Wittgenstein and they are more precise. And slowly we are beginning to understand these principles. Let me take as an example the interpretation of quantum entanglement by the British mathematician Roger Penrose. Penrose discusses in the year of 2000 the experiences of quantum entanglement where light is separated over a distance of 100 kilometers and still remains connected in an unknown way. These are well known experiments in the last 30 years. Very strange for European modes of thought. The light should be either separated or connected. That is the expectation most European modes of thought tell us. Aristotle had been the first. Aristotle (384 - 322 Before Current Era) was a Greek philosopher, a student of Plato and a teacher of Alexander the Great. He told us the following principle as a metaphysical foundation: Either a situation exists or not. There is not a third possibility. Now listen to Roger Penrose: “Quantum entanglement is a very strange type of thing. It is somewhere between objects being separate and being in communication with each other” (Roger Penrose, The Large, the Small and the Human Mind, Cambridge University Press. 2000 page 66). This sentence of Roger Penrose is a first step of a philosophical generalization in a Whiteheadian sense. 6. Key terms: ‘The metaphysical foundations of modern science’ had been examined particularly by three European and American philosophers: E. A. Burtt, A.N. Whitehead and Hans-Georg Gadamer, by Gadamer eminently in his late writings on Heraclitus and Parmenides. I try to follow the approaches of these philosophers of relational views and of anti-substantialism. By ‘metaphysical foundations’ Edwin Arthur Burtt does not understand transcendental ideas but simply the principles that are underlying sciences. -/- 7. Key terms: ‘Complementarity’, ‘interactions’, ‘entanglements’. Since 1927 quantum physics has three key terms which give an indication to the fundamental physical reality: Complementarity, interactions and entanglement. These three notions are akin to Nagarjuna’s relational view of reality. They are akin and they are very precise, so that Buddhism might learn something from these descriptions and quantum physicists might learn from Nagarjuna’s examples and views of reality. They might learn to do a first step in a philosophical generalisation of quantum physical experiments. All of us we might learn how objects are entangled or going arm in arm. [The end of the summary.] -/- « Wenn du gerade das, wodurch auch immer du gefesselt bist, erkennst, wirst du zur Freiheit gelangen. Wenn du diesen speziellen Pfad verwirklichst, gelangst du in einem Leben zur Buddhaschaft. Deswegen verhält es sich folgendermaßen : Wenn plötzlich die Geistesregung « Begierde » enststeht, dann betrachte, ohne ihr zu folgen, direkt ihre Essenz und verweile in dieser Betrachtung, ohne Ablenkungen zuzulassen. Auf diese Weise reinigt Begierde sich selbst, ohne aufgegeben zu werden, da sie ohne Grundlage und Ursprung entsteht. Das wird « Befreiung in sich selbst », « unterscheidende ursprüngliche Weisheit » oder Buddha Amitabha » genannt ». Jigden Sumgön, Licht, das die Dunkelheit durchbricht, Otter Verlag, München 2006, Seite 47, 48 . (shrink)

Thought (νοῦς) for Aristotle is ‘that whereby the soul thinks and judges.’ This identity, however, ‘is not actually any real thing before thinking’ (ἐνεργείᾳ τῶν ὄντων πρὶν νοεῖν) and, thus, cannot reasonably be regarded as blended with the body and cannot acquire any quality or have any organ. (So., Γ, 4, 429a22-27) In fact, Aristotle defines thought more with a capability: ‘That which is capable of receiving the object of thought, i.e. the substance, is thought.’ (Met., Λ, 1072b22-23) Thought is (...) not blended with and, thus, is separable from body. (So., Γ, 4, 429b4-5) This separability, however, belongs only to the active thought. (So., Γ, 5, 430a17-19) A. Nature of thought ‘Since everything is a possible object of thought,’ Aristotle believes, as Anaxagoras believed before him, in order to know things, mind ‘must be pure from all admixtures.’ The reason for this being that ‘the co-presence of what is alien to its nature is a hindrance and a block.’ Therefore, thought ‘can have no nature of its own other than that of having a certain capacity.’ (So., Γ, 4, 429a18-22) B. Thought elements A thought element, i.e. an element/object in thought or a concept (νόημα) has the following features: 1. Every thought element or concept (νόημα) is single (ἓν). This singularity is not restricted to substances because the concept of any other thing is single as well. (Met., A, 990b22-27) 2. Concepts (νόηματα) of thought are either simple or complex. Simple concepts do not involve truth or falsity but complex ones do. Aristotle speaks of ‘thoughts without co-positing and positing away’ (ἄνευ συνθέσεως καὶ διαίρέσεως νοήματι) to which nouns and verbs are similar. (OI., I, 1, 16a13-14) In OI., I, 1, 16a9-11 Aristotle does not use the words simple or complex but his assertion implies them: ‘As there are in the mind thoughts (νόημα) which do not involve truth or falsity, and also those which must be either true or false, so it is in speech.’ 3. The copula-is has no corresponding concept in thought: ‘For neither are ‘to be’ and ‘not to be’ the participle ‘being’ significant of any fact, unless something is added; for they do not themselves indicate anything, but imply a copulation, of which we cannot form a conception apart from the things coupled.’ (OI., I, 3, 16b22-25) C. Thought and its objects To understand Aristotle’s theory of thought, we have two differentiations, one between objects of thought and one in thought itself. Everything that might be posited in front of our thought and be thought as a possible object of thought we call object I (to distinguish it from what we call object II). Therefore, everything in the world is an object I of thought. These objects are in the sensible forms, viz. both the abstract objects and all the states and affections of sensible things. (So., Γ, 8, 432a3-6) These objects might be either composite, containing matter and form, or simple and matterless. When they are thought, we will have them in thought but not necessarily as they are in the world, i.e. as object I, but as something else, which we call object II. This is supposed to make the difference between object I and object II clear: object I is in the world and object II is its corresponding object in our thought. These two kinds of objects are neither necessarily the same nor necessarily different. Objects I are of two kinds: matterful and matterless. Whereas a matterful object I is necessarily different from its corresponding object II (So., Γ, 4, 430a6-9), a matterless object I is not different from its corresponding object II. (So., Γ, 4, 430a2-5; Met., Λ, 1075a3-4) Object II must thus be understood as the form of object I: ‘The thinking part of the soul must therefore be, while impassible, capable of receiving the form of an object; that is, must be potentially identical in character with its object without being the object.’ (So., Γ, 4, 429a13-16) Thought has no nature by its own and is all potentiality before thinking. (cf. So., Γ, 4, 429b6-10) Let’s call this the first potentiality of thought. This potentiality is the potentiality of a tabula rasa: ‘Thought is in a sense potentially whatever is thinkable, though actually it is nothing until it has thought? What it thinks must be in it just as characters may be said to be on a writing-table on which as yet nothing actually stands written: this is exactly what happens with thought.’ (So., Γ, 4, 429b29-430a2) Thought is then all dependent on its objects. By thinking on objects I, objects II are formed in thought. Now thought is nothing but its objects II which are necessarily matterless objects (Met., Λ, 1075a5-7): ‘In every case the thought which is actively thinking is the objects which it thinks.’ (So., Γ, 7, 431b16-17) Thought is the same as its objects II and in the case of matterless objects I, it is the same as its objects I. (Met., Λ, 1075a3-5) This thought is actual compared to its first potentiality: while it was all potentiality in its first potentiality, it now contains some objects II and is then actual. It seems we must interpret Aristotle based on this sense of actuality when he calls a thought possessing object as active: ‘For that which is capable of receiving the objects of thought, i.e. the substance, is thought. And it is active when it possesses this object.’ (Met., Λ, 1072b22-23) This thought, however, is called passive thought due to a second potentiality: ‘When thought has become each thing in the way in which a man who actually knows is said to do so (this happens when he is now able to exercise the power on his own initiatives). Its condition is still one of potentiality, but in a different sense from the potentiality which preceded the acquisition of knowledge by learning or discovery; and thought is then able to think of itself.’ (So., Γ, 4, 429b6-10) It is this thought in its second potentiality that Aristotle calls passive thought distinguishing it from active thought: ‘And in fact thought … is what it is by virtue of becoming all things, while there is another which what it is by virtue of making all things: this is a sort of positive state like light; for in a sense light makes potential colors into actual colors.’ (So., Γ, 5, 530a14-17) These two thoughts have a relationship like the relationship between matter and productive cause: ‘Since in every class of things, as in nature as a whole, we find two factors involved, a matter which is potentially all the particulars included in the class, a cause which is productive in the sense that it makes them all (the latter standing to the former, as e.g. an art to its material), these elements must likewise be found within the soul.’ (So., Γ, 5, 430a10-14) To understand Aristotle’s sense of active thought we must consider his theory of thinking. (shrink)

Popular culture continues fuelling public imagination with things, human and non-human, that we might beco-me or confront. Besides robots, other significant tropes in popular fiction that generated images include non-human humans and cyborgs, wired into his-torically varying sociocultural realities. Robots and artificial intelligence are re-defining the natural order and its hierar-chical structure. This is not surprising, as natural order is always in flux, shaped by new scientific discoveries, especially the reading of the genetic code, that reveal and redefine relationships between (...) life forms. However, for the first time, a new, artificial, species is being introduced into the existing diagrams, and, for the first time, it appears to hybridise the anthro-pocentric natural world order. (shrink)

1.Summary The key terms. 1. Key term: ‘Sunyata’. Nagarjuna (Kumarajiva) is known in the history of Buddhism mainly by his keyword ‘sunyata’. This word is translated into English by the word ‘emptiness’. The translation and the traditional interpretations create the impression that Nagarjuna (Kumarajiva) declares the objects as empty or illusionary or not real or not existing. What is the assertion and concrete statement made by this interpretation? That nothing can be found, that there is nothing, that nothing exists? Was (...) Nagarjuna (Kumarajiva) denying the external world? Did he wish to refute that which evidently is? Did he want to call into question the world in which we live? Did he wish to deny the presence of things that somehow arise? My first point is the refutation of this traditional translation and interpretation. 2. Key terms: ‘Dependence’ or ‘relational view’. My second point consists in a transcription of the keyword of ‘sunyata’ by the word ‘dependence’. This is something that Nagarjuna (Kumarajiva) himself has done. Now Nagarjuna’s (Kumarajiva’s) central view can be named ‘dependence of things’. Nagarjuna (Kumarajiva) is not looking for a material or immaterial object which can be declared as a fundamental reality of this world. His fundamental reality is not an object. It is a relation between objects. This is a relational view of reality. This is the heart of Nagarjuna’s (Kumarajiva’s) ideas. In the 19th century a more or less unknown Italian philosopher, Vincenzo Goberti, spoke about relations as the mean and as bonds between things. Later, in quantum physics and in the philosophy of Alfred North Whitehead we are talking about interactions and entanglements. These ideas of relatedness or connections or entanglements in Eastern and Western modes of thought are the main idea of this essay. Not all entanglements are known. Just two examples: the nature of quantum entanglements is not known. Quantum entanglements should be faster than light. That's why Albert Einstein had some doubts. A second example: the completely unknown connections between the mind and the brain. Other examples are mysterious like the connections between birds in a flock. Some are a little known like gravitational forces. 3. Key terms: ‘Arm in arm’. But Nagarjuna (Kumarajiva) did not stop there. He was not content to repeat this discovery of relational reality. He went on one step further indicating that what is happening between two things. He gave indications to the space between two things. He realized that not the behaviour of bodies, but the behaviour of something between them may be essential for understanding the reality. This open space is not at all empty. It is full of energy. The open space is the middle between things. Things are going arm in arm. The middle might be considered as a force that bounds men to the world and it might be seen as well as a force of liberation. It might be seen as a bondage to the infinite space. 4. Key term: Philosophy. Nagarjuna (Kumarajiva), we are told, was a Buddhist philosopher. This statement is not wrong when we take the notion ‘philosophy’ in a deep sense as a love to wisdom, not as wisdom itself. Philosophy is a way to wisdom. Where this way has an end wisdom begins and philosophy is no more necessary. A.N. Whitehead gives philosophy the commission of descriptive generalization. We do not need necessarily a philosophical building of universal dimensions. Some steps of descriptive generalization might be enough in order to see and understand reality. There is another criterion of Nagarjuna’s (Kumarajiva’s) philosophy. Not his keywords ‘sunyata’ and ‘pratityasamutpada’ but his 25 philosophical examples are the heart of his philosophy. His examples are images. They do not speak to rational and conceptual understanding. They speak to our eyes. Images, metaphors, allegories or symbolic examples have a freshness which rational ideas do not possess. Buddhist dharma and philosophy is a philosophy of allegories. This kind of philosophy is not completely new and unknown to European philosophy. Since Plato’s allegory of the cave it is already a little known. (Plato 424 – 348 Befor Current Era) The German philosopher Hans Blumenberg has underlined the importance of metaphors in European philosophy. 5. Key terms: Quantum Physics. Why quantum physics? European modes of thought had no idea of the space between two this. They were bound to the ideas of substance or subject, two main metaphysical traditions of European philosophical history, two main principles. These substances and these subjects are two immaterial bodies which were considered by traditional European metaphysics as lying, as a sort of core, inside the objects or underlying the empirical reality of our world. The first European scientist who saw with his inner eye the forces between two things had been Michael Faraday (1791-1867). Faraday was an English scientist who contributed to the fields of electromagnetism. Later physicists like Albert Einstein, Niels Bohr, Erwin Schrödinger, Werner Heisenberg and others followed his view in modern physics. This is a fifth point of my work. I compare Nagarjuna (Kumarajiva) with European scientific modes of thought for a better understanding of Asia. I do not compare Nagarjuna (kumarajiva) with European philosophers like Hegel, Heidegger, Wittgenstein. The principles and metaphysical foundations of physical sciences are more representative for European modes of thought than the ideas of Hegel, Heidegger and Wittgenstein and they are more precise. And slowly we are beginning to understand these principles. Let me take as an example the interpretation of quantum entanglement by the British mathematician Roger Penrose. Penrose discusses in the year of 2000 the experiences of quantum entanglement where light is separated over a distance of 100 kilometers and still remains connected in an unknown way. These are well known experiments in the last 30 years. Very strange for European modes of thought. The light should be either separated or connected. That is the expectation most European modes of thought tell us. Aristotle had been the first. Aristotle (384 - 322 Before Current Era) was a Greek philosopher, a student of Plato and a teacher of Alexander the Great. He told us the following principle as a metaphysical foundation: Either a situation exists or not. There is not a third possibility. Now listen to Roger Penrose: “Quantum entanglement is a very strange type of thing. It is somewhere between objects being separate and being in communication with each other” (Roger Penrose, The Large, the Small and the Human Mind, Cambridge University Press. 2000 page 66). This sentence of Roger Penrose is a first step of a philosophical generalization in a Whiteheadian sense. 6. Key terms: ‘The metaphysical foundations of modern science’ had been examined particularly by three European and American philosophers: E. A. Burtt, A.N. Whitehead and Hans-Georg Gadamer, by Gadamer eminently in his late writings on Heraclitus and Parmenides. I try to follow the approaches of these philosophers of relational views and of anti-substantialism. By ‘metaphysical foundations’ Edwin Arthur Burtt does not understand transcendental ideas but simply the principles that are underlying sciences. 7. Key terms: ‘Complementarity’, ‘interactions’, ‘entanglements’. Since 1927 quantum physics has three key terms which give an indication to the fundamental physical reality: Complementarity, interactions and entanglement. These three notions are akin to Nagarjuna’s (Kumarajiva’s) relational view of reality. They are akin and they are very precise, so that Buddhism might learn something from these descriptions and quantum physicists might learn from Nagarjuna’s (Kumarajiva’s) examples and views of reality. They might learn to do a first step in a philosophical generalisation of quantum physical experiments. All of us we might learn how objects are entangled or going arm in arm. [The end of the summary.]. (shrink)