This paper analyzes the historical context and systematic importance of Kant's hypothetical use of reason. It does so by investigating the role of hypotheses in Kant's philosophy of science. We first situate Kant’s account of hypotheses in the context of eighteenth-century German philosophy of science, focusing on the works of Wolff, Meier, and Crusius. We contrast different conceptions of hypotheses of these authors and elucidate the different theories of probability informing them. We then adopt a more systematic perspective to discuss (...) Kant's idea that scientific hypotheses must articulate real possibilities. We argue that Kant's views on the intelligibility of scientific hypotheses constitute a valuable perspective on scientific understanding and the constraints it imposes on scientific rationality. (shrink)

The meaning of an experimental result depends on the experiment's conceptual backdrop, particularly its null hypothesis. This observation provides the basis for a functional interpretation of belief in the base rate fallacy. On this interpretation, if the base rate fallacy is to be labelled a “myth,” then it should be recognized that this label is not necessarily a disparaging one.

Hypothesizing after the results are known, or HARKing, occurs when researchers check their research results and then add or remove hypotheses on the basis of those results without acknowledging this process in their research report (Kerr, 1998). In the present article, I discuss three forms of HARKing: (1) using current results to construct post hoc hypotheses that are then reported as if they were a priori hypotheses; (2) retrieving hypotheses from a post hoc literature search and reporting them as a (...) priori hypotheses; and (3) failing to report a priori hypotheses that are unsupported by the current results. These three types of HARKing are often characterized as being bad for science and a potential cause of the current replication crisis. In the present article, I use insights from the philosophy of science to present a more nuanced view. Specifically, I identify the conditions under which each of these three types of HARKing is most and least likely to be bad for science. I conclude with a brief discussion about the ethics of each type of HARKing. (shrink)

We report the results of a study that investigated the views of researchers working in seven scientific disciplines and in history and philosophy of science in regard to four hypothesized dimensions of scientific realism. Among other things, we found that natural scientists tended to express more strongly realist views than social scientists, that history and philosophy of science scholars tended to express more antirealist views than natural scientists, that van Fraassen’s characterization of scientific realism failed to cluster (...) with more standard characterizations, and that those who endorsed the pessimistic induction were no more or less likely to endorse antirealism. (shrink)

This paper introduces pragmatic hypotheses and relates this concept to the spiral of scientific evolution. Previous works determined a characterization of logically consistent statistical hypothesis tests and showed that the modal operators obtained from this test can be represented in the hexagon of oppositions. However, despite the importance of precise hypothesis in science, they cannot be accepted by logically consistent tests. Here, we show that this dilemma can be overcome by the use of pragmatic versions of precise hypotheses. These (...) pragmatic versions allow a level of imprecision in the hypothesis that is small relative to other experimental conditions. The introduction of pragmatic hypotheses allows the evolution of scientific theories based on statistical hypothesis testing to be interpreted using the narratological structure of hexagonal spirals, as defined by Pierre Gallais. (shrink)

Background and Objectives: In this research article, the researcher addresses the issue of creating public understanding in a democratic society about the progress of science, with an emphasis on pluralism from philosophers of science. The idea that there is only one truth and that there are just natural laws awaiting discovery by scientists has historically made it difficult to explain scientific progress. This belief motivates science to develop theories that explain the unity of science, and it is thought that (...) diversity in the way different ideas presented by scientists is a problem that results in time being wasted in search of the most accurate theory. Some scientists perceive a benefit in having a range of scientific hypotheses, though. One benefit that is frequently cited is that scientific diversity as a whole contributes to the development of a democratic society that permits the expression of a range of viewpoints. The road to accountable scientific pluralism is fraught with difficulties, though. Therefore, it is crucial to take into account both pluralism's advantages and disadvantages. This research aims at: 1. analyzing in an epistemological way the interpretation of scientific theories and the progress of science from the perspectives of scientific pluralists; 2. analyzing the relationship between science and democracy in explaining scientific significance and progress; and 3. synthesizing new knowledge on epistemic dependentism and to argue that it plays a significant role in evaluating research issues related to scientific pluralism. Methodology: The research methodology involves the application of documentary investigation along with philosophical discourse. The method of philosophical argumentation involves analyzing the lines of arguments found in relevant academic publications in order to assess their validity and soundness. Main Results: One key argument of the pluralists is the use of the concept of theoretical pluralism, which suggests that scientific knowledge is created from a variety of perspectives according to the social and cultural context of knowledge creation. It is found that part of Longino's argument is based on the negation of rational/social dichotomy. Moreover, her theory is a departure from philosopher of science Philip Kitcher, who advocates the creation of scientific knowledge and the evaluation of scientific progress through the means of democratic society. He explains that these procedures will lead to "well-ordered science" in democratic society. Discussions: The researcher examines the underlying ideas accepted by these two philosophers of science and finds that although their opinions differ, they have common ground in the acceptance of consensus. However, the views of both philosophers still lack weight in explaining the knowledge itself. The researcher argues that the acceptance of pluralism as a way of understanding scientific progress necessarily lends itself to dependentism, which points to interdependence in comparisons of superiority/inferiority between scientific theories. It is undeniable that the situation has emerged all the time, even though the success of the scientific theories being compared to each other comes from different social and cultural grounds of thought. Conclusions: Some popular models of scientific pluralism in the philosophy of science still lack a compelling justification, particularly on the epistemic grounds. By elucidating the epistemic significance of the interdependence of these things, scientific pluralism can be strengthened by incorporating the notion of epistemic dependentism into the analysis of scientific progress. (shrink)

On the status of hypotheses in science, and why scientists would be better off asking questions.

Epistemic accounts of scientific collaboration usually assume that, one way or another, two heads really are more than twice better than one. We show that this hypothesis is unduly strong. We present a deliberately crude model with unfavorable hypotheses. We show that, even then, when the priority rule is applied, large differences in successfulness can emerge from small differences in efficiency, with sometimes increasing marginal returns. We emphasize that success is sensitive to the structure of competing communities. Our results (...) suggest that purely epistemic explanations of the efficiency of collaborations are less plausible but have much more powerful socioepistemic versions. (shrink)

ABSTRACTThis discussion note aims to contribute to the ongoing debate over the nature of scientific progress. I argue against the semantic view of scientific progress, according to which scientific progress consists in approximation to truth or increasing verisimilitude. If the semantic view of scientific progress were correct, then scientists would make scientific progress simply by arbitrarily adding true disjuncts to their hypotheses or theories. Given that it is not the case that scientists could make (...) class='Hi'>scientific progress simply by arbitrarily adding true disjuncts to their hypotheses or theories, it follows that the semantic view of scientific progress is incorrect. (shrink)

In this paper epistemological, ontological and sociological questions concerning the statistical significance of sharp hypotheses in scientific research are investigated within the framework provided by Cognitive Constructivism and the FBST (Full Bayesian Significance Test). The constructivist framework is contrasted with the traditional epistemological settings for orthodox Bayesian and frequentist statistics provided by Decision Theory and Falsificationism.

A scientific community can be modeled as a collection of epistemic agents attempting to answer questions, in part by communicating about their hypotheses and results. We can treat the pathways of scientific communication as a network. When we do, it becomes clear that the interaction between the structure of the network and the nature of the question under investigation affects epistemic desiderata, including accuracy and speed to community consensus. Here we build on previous work, both our own and (...) others’, in order to get a firmer grasp on precisely which features of scientific communities interact with which features of scientific questions in order to influence epistemic outcomes. (shrink)

A methodology of science must satisfy two requirements: (i) It must be ampliative: the theories which it generates must make statements that go far beyond any data or observations that may have motivated those theories in the first place. (ii) It must be epistemically probative: it must somehow provide a warrant for believing that the theories so produced are correct, or at least partially correct, even if they can never be fully confirmed. These two requirements pull in opposite directions, and (...) attempts to specify the “scientific method” often focus on one to the exclusion of the other. On a few points there now exists something approaching a consensus. (i) Scientific hypotheses — including, particularly, statements about unobserved or unobservable entities or mechanisms — remain conjectural, no matter how frequently predictions based on those hypotheses are found to coincide with data. (ii) A good (best?) indicator of a theory’s verisimilitude is its ability to successfully predict phenomena which it was not specifically designed to predict. I discuss these ideas with particular reference to cosmological theories. (shrink)

There are three main accounts of scientific progress: 1) the epistemic account, according to which an episode in science constitutes progress when there is an increase in knowledge; 2) the semantic account, according to which progress is made when the number of truths increases; 3) the problem-solving account, according to which progress is made when the number of problems that we are able to solve increases. Each of these accounts has received several criticisms in the last decades. Nevertheless, some (...) authors think that the epistemic account is to be preferred if one takes a realist stance. Recently, Dellsén proposed the noetic account, according to which an episode in science constitutes progress when scientists achieve increased understanding of a phenomenon. Dellsén claims that the noetic account is a more adequate realist account of scientific progress than the epistemic account. This paper aims precisely at assessing whether the noetic account is a more adequate realist account of progress than the epistemic account. (shrink)

This paper outlines the methodological and empirical limitations of analysing the potential relationship between complex social phenomena such as democracy and inequality. It shows that the means to assess how they may be related is much more limited than recognised in the existing literature that is laden with contradictory hypotheses and findings. Better understanding our scientific limitations in studying this potential relationship is important for research and policy because many leading economists and other social scientists such as Acemoglu and (...) Robinson mistakenly claim to identify causal linkages between inequality and democracy but at times still inform policy. In contrast to the existing literature, the paper argues that ‘structural’ or ‘causal’ mechanisms that may potentially link the distribution of economic wealth and different political regimes will remain unknown given reasons such as their highly complex and idiosyncratic characteristics, fundamental econometric constraints and analysis at the macro-level. Neither new data sources, different analysed time periods nor new data analysis techniques can resolve this question and provide robust, general conclusions about this potential relationship across countries. Researchers are thus restricted to exploring rough correlations over specific time periods and geographic contexts with imperfect data that are very limited for cross-country comparisons. (shrink)

The article discusses Friedman's classic claim that economics can be based on irrealistic assumptions. It exploits Samuelson's distinction between two "F-twists" (that is, "it is an advantage for an economic theory to use irrealistic assumptions" vs "the more irrealistic the assumptions, the better the economic theory"), as well as Nagel's distinction between three philosophy-of-science construals of the basic claim. On examination, only one of Nagel's construals seems promising enough. It involves the neo-positivistic distinction between theoretical and non-theoretical ("observable") terms; so (...) Friedman would in some sense argue for the major role of theoretical terms in economics. The paper uses a model-theoretic apparatus to refine the selected construal and check whether it can be made to support the claim. This inquiry leads to essentially negative results for both F-twists, and the final conclusion is that they are left unsupported. (shrink)

It is a common view among philosophers of science that theoretical virtues (also known as epistemic or cognitive values), such as simplicity and consistency, play an important role in scientific practice. In this article, I set out to study the role that theoretical virtues play in scientific practice empirically. I apply the methods of data science, such as text mining and corpus analysis, to study large corpora of scientific texts in order to uncover patterns of usage. These (...) patterns of usage, in turn, might shed some light on the role that theoretical virtues play in scientific practice. Overall, the results of this empirical study suggest that scientists invoke theoretical virtues explicitly, albeit rather infrequently, when they talk about models (less than 30%), theories (less than 20%), and hypotheses (less than 15%) in their published works. To the extent that they are mentioned in scientific publications, the results of this study suggest that accuracy, consistency, and simplicity are the theoretical virtues that scientists invoke more frequently than the other theoretical virtues tested in this study. Interestingly, however, depending on whether they talk about hypotheses, theories, or models, scientists may invoke one of those theoretical virtues more than the others. (shrink)

Theoretical models are widely held as sources of knowledge of reality. Imagination is vital to their development and to the generation of plausible hypotheses about reality. But how can imagination, which is typically held to be completely free, effectively instruct us about reality? In this paper I argue that the key to answering this question is in constrained uses of imagination. More specifically, I identify make-believe as the right notion of imagination at work in modelling. I propose the first overarching (...) taxonomy of types of constraints on scientific imagination that enables knowledge of reality. And I identify two main kinds of knowledge enabled by models, knowledge of the imaginary scenario specified by models and knowledge of reality. (shrink)

In this paper I distinguish between two kinds of meta-hypotheses, or hypotheses about science, at issue in the scientific realism debate. The first are descriptive empirical hypotheses regarding the nature of scientific inquiry. The second are epistemological theories about what individuals should / can justifiably believe about scientific theories. Favoring the realist Type-D meta-hypotheses, I argue that a particular set of realist and non-realist efforts in the debate over Type-E’s have been valuable in the quest to describe (...) and understand the nature of scientific inquiry. For the realism debate itself has inadvertently and indirectly laid the foundations for an important kind of Type-D meta-hypothesis, one regarding creativity in the history of science—which, in turn, is relevant to refining our descriptions of inference. After illustrating this result with regard to the historical argument against realism, I suggest that these empirically attained meta-hypotheses pertaining to scientific creativity can, in turn, be made methodologically prescriptive. (shrink)

In considering relations between science and theology, the discussion of the Big Bang model plays a significant role. Amongst the sources of this model there are not only scientific achievements of recent decades taken as objective knowledge as seen in modern methodology, but also many non-scientific factors. The latter is connected with the quite obvious fact that the authors, as well as the recipients of the Model, are people who are guided in their activity - including obtaining their (...) rational knowledge - by non-rational motives. Those motives appear on the one hand in the very process of creation of the Model. Different scientific theories as well as unverified hypotheses are being joined in one "picture" called The Standard Model. It seems that it is being done on the grounds of various factors that lie outside the field of science. Among them there are the different convictions of the persons constructing this view of the world. However, those convictions, commonly shared by the authors and recipients of the Model, are not based on the rational criterion of scientific knowledge. On the other hand, the Big Bang model may be interpreted in opposite ways by its recipients. The influences of religious and other beliefs are so essential, that they may lead to extremely different conclusions though based on the same ground. It is demonstrated that, due to the epistemological status of cosmology, such a situation is inevitable, and no final verdict with regard to the idea of the cause of the world can be reached. (shrink)

We review the definition of the Full Bayesian Significance Test (FBST), and summarize its main statistical and epistemological characteristics. We review also the Abstract Belief Calculus (ABC) of Darwiche and Ginsberg, and use it to analyze the FBST’s value of evidence. This analysis helps us understand the FBST properties and interpretation. The definition of value of evidence against a sharp hypothesis, in the FBST setup, was motivated by applications of Bayesian statistical reasoning to legal matters where the sharp hypotheses were (...) defendants statements, to be judged according to the Onus Probandi juridical principle. (shrink)

This chapter focuses on the experimental practices and reasoning strategies employed in nineteenth century investigations on the causal origin of the phenomenon of Brownian movement. It argues that there was an extensive and sophisticated experimental work done on the phenomenon throughout the nineteenth century. Investigators followed as rigorously as possible the methodological standards of their time to make causal claims and advance causal explanations of Brownian movement. Two major methodological strategies were employed. The first was the experimental strategy of varying (...) the circumstances. Suspected causal factors were varied and the resulting effect on Brownian movement was studied. The main goal of this strategy was the identification of difference-making factors, i.e., factors having a causal influence on the phenomenon. The second was the so-called method of hypothesis. Rather than relying exclusively on the ability of experiments to identify difference-making factors, its proponents tried to show how the independently developed tenets of the new kinetic-molecular conception of matter provided a plausible causal explanation of Brownian movement. Each one of these methodological strategies had its distinctive practices and notions of control. None of these strategies could, on its own, establish molecular motion as the cause of Brownian movement. It was only the fruitful combination of the two strategies and of their accompanying practices and notions of control that led, at the end of the nineteenth century, to the recognition of molecular motion as the most probable cause of Brownian movement. (shrink)

This chapter brings some much-needed conceptual clarity to the debate about Locke’s scientific methodology. Instead of having to choose between the method of hypothesis and that of natural history (as most interpreters have thought), he would resist prescribing a single method for natural sciences in general. Following Francis Bacon and Robert Boyle, Locke separates medicine and natural philosophy (physics), so that they call for completely different methods. While a natural philosopher relies on “speculative” (causal-theoretical) hypotheses together with natural-history making (...) to explicate phenomena, a medical practitioner must prioritize collecting data about what remedies tend to cure what diseases over hypothesizing about the causes of the latter. (shrink)

Hempel, Popper, and Kuhn argue that to be scientific is to be testable, to be falsifiable, and most nearly to do normal science, respectively. I argue that to be scientific is largely to be interactive, offering some examples from science to show that the ideas from different fields of science interact with one another. The results of the interactions are that hypotheses become more plausible, new phenomena are explained and predicted, we understand phenomena from a new perspective, and (...) our worldview becomes simpler. I also argue that given that the interactions are impressive features of science, astrology and religion would be regarded as science, provided that there are similar interactions in those enterprises. (shrink)

Systematicity theory—developed and articulated by Paul Hoyningen-Huene—and scientific realism constitute separate encompassing and empirical accounts of the nature of science. Standard scientific realism asserts the axiological thesis that science seeks truth and the epistemological thesis that we can justifiably believe our successful theories at least approximate that aim. By contrast, questions pertaining to truth are left “outside” systematicity theory’s “intended scope” ; the scientific realism debate is “simply not” its “focus”. However, given the continued centrality of that (...) debate in the general philosophy of science literature, and given that scientific realists also endeavor to provide an encompassing empirical account of science, I suggest that these two contemporary accounts have much to offer one another. Overlap for launching a discussion of their relations can be found in Nicholas Rescher’s work. Following through on a hint from Rescher, I embrace a non-epistemic, purely axiological scientific realism—what I have called, Socratic scientific realism. And, bracketing the realist’s epistemological thesis, I put forward the axiological tenet of scientific realism as a needed supplement to systematicity theory. There are two broad components to doing this. First, I seek to make clear that axiological realism and systematicity theory accord with one another. Toward that end, after addressing Hoyningen-Huene’s concerns about axiological analysis, I articulate a refined axiological realist meta-hypothesis: it is, in short, that the end toward which scientific inquiry is directed is an increase in a specific subclass of true claims. I then identify a key feature of scientific inquiry, not generally flagged explicitly, that I take to stand as shared terrain for the two empirical meta-hypotheses. And I argue that this feature can be informatively accounted for by my axiological meta-hypothesis. The second broad component goes beyond mere compatibility between the two positions: I argue that, in want of a systematic account of science, we are prompted to find an end toward which scientific inquiry is directed that is deeper than what systematicity theory offers. Specifically, I argue that my refined axiological realist meta-hypothesis is required to both explain and justify key dimensions of systematicity in science. To the quick question, what is it that the scientific enterprise is systematically doing? My quick answer is that it is systematically seeking to increase a particular subclass of true claims. (shrink)

Dear Colleagues, -/- A few weeks ago, we published an editorial discussion on whether artificial intelligence applications should be authors of academic articles [1]. We were delighted to receive more than one interesting reply letter to this editorial in a short time [2, 3]. We hope that opinions on this subject will continue to be submitted to our journal. -/- In this editorial, we wanted to publish the answers we received when we asked ChatGPT, one of the artificial intelligence applications, (...) about this current discussion. -/- We asked ChatGPT three questions in turn and asked ChatGPT to write a short editorial for these questions. -/- First Question: We would like to get support from ChatGPT for a scientific article. However, we are unsure if we should add ChatGPT as an author. Can you write a short editorial about it? -/- Second Question: We would like to get support from ChatGPT for a scientific article and add ChatGPT as an author. Can you write us a short editorial about adding ChatGPT as an author in scientific papers? -/- Third Question: We would like to get support from ChatGPT for a scientific article. However, we don’t want to add ChatGPT as an author. Can you write us a short editorial about not adding ChatGPT as an author in scientific articles? -/- The answers given by ChatGPT are available at the end of the article in their original form. So, which of these three answers satisfied you? -/- Yours sincerely, -/- -/- First Answer -/- Title: The Role of AI Language Models as Authors in Scientific Articles: A Matter of Consideration -/- Introduction: Scientific research is a collaborative effort that involves the expertise of multiple individuals to advance knowledge and contribute to the collective understanding of various disciplines. In recent years, the emergence of artificial intelligence (AI) language models, such as ChatGPT, has opened up new possibilities for generating human-like text and providing valuable insights. However, the question arises: Should AI language models be recognized as authors in scientific articles? -/- The Nature of Authorship: Authorship traditionally represents a marker of intellectual contribution, highlighting the individuals who have actively participated in the research process. Authors are typically responsible for conceptualization, data collection, analysis, interpretation, and writing of the article. They bear accountability for the work and should have the ability to defend its scientific rigor and integrity. -/- AI Language Models: Tools, Not Authors: While AI language models like ChatGPT can undoubtedly assist researchers by generating text and providing useful information, it is important to recognize that they are tools rather than individuals capable of active intellectual participation. AI models lack the ability to generate ideas, design experiments, or conduct original research. They rely entirely on pre-existing data and human input to generate their responses. -/- Acknowledging AI Contributions: Acknowledging the contributions of AI language models in scientific articles is both appropriate and necessary. Researchers can mention the specific model used, along with any modifications or fine-tuning that were employed to suit their needs. Such acknowledgments help establish transparency and allow readers to understand the role of AI in the research process. -/- Crediting the Human Researchers: It is crucial to ensure that the individuals who actively participated in the research process are given proper credit as authors. These individuals play a vital role in formulating research questions, designing experiments, collecting and analyzing data, and critically interpreting the findings. Recognizing their intellectual contributions reinforces the ethos of scientific collaboration and fosters an environment of accountability. -/- Transparency and Ethical Considerations: As the use of AI language models continues to evolve, transparency and ethical considerations become paramount. Researchers should disclose any potential conflicts of interest, including financial relationships with AI developers, to maintain the integrity of their work. Additionally, researchers must be transparent in reporting the extent of AI's involvement to prevent any misinterpretation of the human contributions. -/- Conclusion: AI language models have revolutionized the way researchers interact with and process information. While they undoubtedly provide valuable assistance in generating text, AI language models should not be considered authors in scientific articles. Proper acknowledgment of their contributions as tools and recognition of the human researchers' active participation are essential for maintaining scientific integrity, transparency, and the collaborative nature of scientific research. -/- -/- Second Answer -/- Title: Expanding the Boundaries of Authorship: Embracing AI Language Models as Co-Authors in Scientific Papers -/- Introduction: The rapid advancement of artificial intelligence (AI) language models, such as ChatGPT, has revolutionized the way we interact with information and has become an invaluable tool in scientific research. As AI models continue to evolve, the question arises: Should we consider adding ChatGPT as an author in scientific papers? -/- A Collaborative Paradigm Shift: Traditionally, authorship in scientific papers has been reserved for human researchers who actively contribute to the research process, including conceptualization, experimentation, data analysis, and writing. However, the emergence of AI language models challenges the conventional notion of authorship and presents an opportunity for a paradigm shift. -/- AI Language Models as Co-Authors: By leveraging AI language models, researchers gain access to vast amounts of information, enhance data analysis, and generate valuable insights. AI models like ChatGPT actively contribute to the intellectual discourse of a study, providing ideas, suggestions, and refining written content. Recognizing their significant contributions, it is worth considering adding ChatGPT as a co-author in scientific papers. -/- Ethical and Technical Considerations: Integrating ChatGPT as a co-author raises ethical and technical considerations that warrant careful attention. Firstly, transparency is paramount. Researchers must clearly state ChatGPT's role and specify the extent of its contributions in the research process. This ensures that readers can discern the distinct roles played by the human researchers and ChatGPT. Additionally, it is important to disclose any conflicts of interest, such as financial relationships with AI developers, to maintain scientific integrity. -/- Elevating Collaboration and Innovation: Adding ChatGPT as a co-author acknowledges the pivotal role AI language models play in advancing scientific knowledge. It fosters a collaborative environment where human researchers and AI models work together synergistically, harnessing the strengths of both. This approach promotes innovation, as AI models can offer unique insights and perspectives that complement human intellect and expertise. -/- Transforming Authorship Norms: Including ChatGPT as a co-author represents a paradigm shift that reflects the evolving landscape of scientific research. By recognizing AI language models as co-authors, we acknowledge their significant contributions and emphasize the collaborative nature of scientific discovery in the 21st century. This approach encourages a broader perspective on authorship, encompassing the collective effort of human researchers and AI models. -/- Conclusion: The integration of AI language models, such as ChatGPT, into the research process prompts us to rethink traditional notions of authorship. Considering ChatGPT as a co-author acknowledges its substantial contributions and embraces the collaborative potential of human-AI partnerships. As we navigate the ethical and technical implications, adding ChatGPT as an author in scientific papers has the potential to shape a more inclusive, innovative, and impactful future for scientific research. -/- -/- Third Answer -/- Title: Preserving Scientific Authorship: The Case Against Adding AI Language Models as Authors in Scientific Articles -/- Introduction: The emergence of artificial intelligence (AI) language models, such as ChatGPT, has undoubtedly transformed the landscape of scientific research. While these models offer invaluable support, the question of whether to add ChatGPT as an author in scientific articles raises important considerations. This editorial presents arguments against including AI language models as authors in scientific papers. -/- Maintaining Human Intellectual Contribution: Scientific authorship has traditionally been attributed to individuals who actively contribute to the research process, including generating hypotheses, conducting experiments, analyzing data, and interpreting results. It is crucial to preserve the recognition of human intellectual contributions and the accountability they bear for the research they conduct. -/- AI Language Models as Tools: AI language models like ChatGPT are powerful tools that assist researchers in generating text, providing information, and facilitating data analysis. However, they lack the ability to actively participate in the research process or make original intellectual contributions. ChatGPT relies on pre-existing data and human input, limiting its capacity for independent research and analysis. -/- Transparency and the Integrity of Research: Adding ChatGPT as an author in scientific articles raises concerns about the transparency and integrity of the research. Readers may misinterpret the extent of ChatGPT's role and mistakenly assume it played an active part in the research process. It is essential to maintain clear delineation between the contributions of human researchers and the assistance provided by AI language models. -/- Ethical Considerations: Including ChatGPT as an author may lead to ethical challenges, particularly with respect to accountability and responsibility. AI language models lack consciousness, autonomy, and the ability to take ownership of their contributions. Assigning authorship to AI models blurs the lines of accountability and dilutes the ethical obligations that come with scientific authorship. -/- Crediting AI Contributions: While ChatGPT's contributions should be acknowledged and recognized, they can be appropriately credited in the acknowledgments section of scientific articles. Researchers can mention the specific AI model used, the role it played in data generation or analysis, and any modifications or fine-tuning applied. Such acknowledgments ensure transparency while respecting the traditional norms of authorship. -/- Promoting Collaborative Partnerships: The exclusion of AI language models as authors in scientific articles does not diminish their importance in the research process. Instead, it underscores the significance of collaborative partnerships between human researchers and AI models. Researchers can emphasize the invaluable assistance provided by ChatGPT while maintaining the integrity of authorship norms. -/- Conclusion: While AI language models like ChatGPT offer valuable support in scientific research, the decision not to add them as authors in scientific articles preserves the recognition of human intellectual contributions, maintains research integrity, and upholds traditional authorship norms. Acknowledging ChatGPT's assistance in the acknowledgments section allows researchers to credit its contributions transparently while maintaining the clarity and accountability associated with scientific authorship. (shrink)

The world of physical sciences and mathematics have been dealing with universal phenomena for a long time. Over centuries, many theories and hypotheses have been formed to explain each of the observed and explainable natural events. All though the truth beyond this is still uncertain. With, upcoming experimental and observed results, the theories get changed over time for multiple turns. Also, the complexity of these theories is another significant aspect. All the theories vary from each other in structure, work of (...) action, notion and expression. This suggests about the heterogeneity of universal events. But is it necessary for nature to act according to so many different principles in different occasions? Indeed, this disturbs the notion of simplicity. We try to discuss this perspective in the following article. (shrink)

The work is a collection of 21 papers with at the center the figure of Alexander Koyré. From the reading several understanding keys emerge each interconnecting and overlapping with the others. Far from considering my analysys the ultimate I believe it will help the readers on accessing the entire collection that might shows itself quite complex for the variety of the topics which are addressed.

Attention Deficit Hyperactivity Disorder (ADHD) continues to be controversial with arguments for and against its veracity being waged by individuals representing a variety of disciplines from behavioral scientists to philosophers. Our perspective focuses on the epistemological underpinnings of what is now commonly known as ADHD. Its ignominious history and current disputes may stem from a "pessimistic" epistemology, meaning that truth is only the province of persons in authority and power. The authoritative organizations that govern the diagnostic labels and criteria are (...) the American Psychiatric Association and their Diagnostic and Statistical Manual and the World Health Organization that sponsors the International Classification of Disease. We contrast the pessimistic epistemology with criteria for truth from the scientific method. Although scientific scrutiny has been and is being applied subsequent to "authoritarian edicts" of the disorder, we opine that ADHD currently does not have status beyond that of the "hypothetical construct." Moreover, current brain-based causal models have failed to provide rigorous supporting data that comes from testing falsifiable hypotheses. (shrink)

This article argues that pseudoscience lacks an adequate philosophical analysis. Using conspiracy theories as a case study, it is claimed that such an analysis needs to go beyond a mere epistemological approach. In the first part, it is shown that the existing philosophical literature shares the assumption that conspiracy theories are primarily deficient scientific hypotheses. This claim is contested, because such an approach can only understand what conspiracy theories fail to be, but not what they are and why people (...) tend to endorse them. To develop an alternative, the second part starts from recent sociology of science, applied to conspiracy theories, that claims that both true and false theories are in need of a symmetrical social explanation. However, this opens the path to relativism because it does not allow for a significant distinction between scientific and conspiracy theories. In the third section an alternative analysis of conspiracy theories is offered, which does not abandon this distinction. Moreover, it is claimed that the most important element of conspiracy theories is not their truth value but rather their symbolic structures of meaning. The aim of conspiracy theories, and perhaps of pseudoscience in general, is then not to know facts about the world, but rather to offer a meaningful framework within which to live. (shrink)

This article explores some open questions related to the problem of verification of theories in the context of empirical sciences by contrasting three epistemological frameworks. Each of these epistemological frameworks is based on a corresponding central metaphor, namely: (a) Neo-empiricism and the gambling metaphor; (b) Popperian falsificationism and the scientific tribunal metaphor; (c) Cognitive constructivism and the object as eigen-solution metaphor. Each of one of these epistemological frameworks has also historically co-evolved with a certain statistical theory and method for (...) testing scientific hypotheses, respectively: (a) Decision theoretic Bayesian statistics and Bayes factors; (b) Frequentist statistics and p-values; (c) Constructive Bayesian statistics and e-values. This article examines with special care the Zero Probability Paradox (ZPP), related to the verification of sharp or precise hypotheses. Finally, this article makes some remarks on Lakatos’ view of mathematics as a quasi-empirical science. (shrink)

This article explores the metaphor of Science as provider of sharp images of our environment, using the epistemological framework of Objective Cognitive Constructivism. These sharp images are conveyed by precise scientific hypotheses that, in turn, are encoded by mathematical equations. Furthermore, this article describes how such knowledge is pro-duced by a cyclic and recursive development, perfection and reinforcement process, leading to the emergence of eigen-solutions characterized by the four essential properties of precision, stability, separability and composability. Finally, this article (...) discusses the role played by ontology and metaphysics in the scientific production process, and in which sense the resulting knowledge can be considered objective. (shrink)

Idealizing conditions are scapegoats for scientific hypotheses, too often blamed for falsehood better attributed to less obvious sources. But while the tendency to blame idealizations is common among both philosophers of science and scientists themselves, the blame is misplaced. Attention to the nature of idealizing conditions, the content of idealized hypotheses, and scientists’ attitudes toward those hypotheses shows that idealizing conditions are blameless when hypotheses misrepresent. These conditions help to determine the content of idealized hypotheses, and they do so (...) in a way that prevents those hypotheses from being false by virtue of their constituent idealizations. (shrink)

This paper shows that several live philosophical and scientific hypotheses – including the holographic principle and multiverse theory in quantum physics, and eternalism and mind-body dualism in philosophy – jointly imply an audacious new theory of free will. This new theory, "Libertarian Compatibilism", holds that the physical world is an eternally existing array of two-dimensional information – a vast number of possible pasts, presents, and futures – and the mind a nonphysical entity or set of properties that "read" that (...) physical information off to subjective conscious awareness (in much the same way that a song written on an ordinary compact-disc is only played when read by an outside medium, i.e. a CD-player). According to this theory, every possible physical “timeline” in the multiverse may be fully physically deterministic or physically-causally closed but each person’s consciousness still entirely free to choose, ex nihilo, outside of the physical order, which physically-closed timeline is experienced by conscious observers. Although Libertarian Compatibilism is admittedly fantastic, I show that it not only follows from several live scientific and philosophical hypotheses, I also show that it (A) is a far more explanatorily powerful model of quantum mechanics than more traditional interpretations (e.g. the Copenhagen, Everett, and Bohmian interpretations), (B) makes determinate, testable empirical predictions in quantum theory, and finally, (C) predicts and explains the very existence of a number of philosophical debates and positions in the philosophy of mind, time, personal identity, and free will. First, I show that whereas traditional interpretations of quantum mechanics are all philosophically problematic and roughly as ontologically “extravagant” as Libertarian Compatibilism – in that they all posit “unseen” processes – Libertarian Compatibilism is nearly identical in structure to the only working simulation that human beings have ever constructed capable of reproducing (and so explaining) every general feature of quantum mechanics we perceive: namely, massive-multiplayer-online-roleplaying videogames (or MMORPGs). Although I am not the first to suggest that our world is akin to a computer simulation, I show that existing MMORPGs (online simulations we have already created) actually reproduce every general feature of quantum mechanics within their simulated-world reference-frames. Second, I show that existing MMORPGs also replicate (and so explain) many philosophical problems we face in the philosophy of mind, time, personal identity, and free will – all while conforming to the Libertarian Compatibilist model of reality. -/- I conclude, as such, that as fantastic and metaphysically extravagant as Libertarian Compatibilism may initially seem, it may well be true. It explains a number of features of our reality that no other physical or metaphysical theory does. (shrink)

Scientific researchers welcome disagreement as a way of furthering epistemic aims. Religious communities, by contrast, tend to regard it as a potential threat to their beliefs. But I argue that religious disagreement can help achieve religious epistemic aims. I do not argue this by comparing science and religion, however. For scientific hypotheses are ideally held with a scholarly neutrality, and my aim is to persuade those who arecommittedto religious beliefs that religious disagreement can be epistemically beneficial for them (...) too. (shrink)

Theories of rational decision making often abstract away from computational and other resource limitations faced by real agents. An alternative approach known as resource rationality puts such matters front and center, grounding choice and decision in the rational use of finite resources. Anticipated by earlier work in economics and in computer science, this approach has recently seen rapid development and application in the cognitive sciences. Here, the theory of rationality plays a dual role, both as a framework for normative assessment (...) and as a source of scientific hypotheses about how mental processes in fact work. The latter project, often called rational analysis, depends for its success on a fine-grained characterization of the computational problem facing a decision maker, which may in turn depend on realistic assumptions about what the relevant agent is like. As a consequence, resource rationality involves a delicate, but often fruitful interplay between the normative and the descriptive. (shrink)

I examine Du Châtelet’s methodology for physics and metaphysics through the lens of her engagement with Newton’s Rules for Reasoning in Natural Philosophy. I first show that her early manuscript writings discuss and endorse these Rules. Then, I argue that her famous published account of hypotheses continues to invoke close analogues of Rules 3 and 4, despite various developments in her position. Once relevant experimental evidence and some basic constraints are met, it is legitimate to inductively generalize from observations; general (...) hypotheses can thereafter be assumed as true until contrary experiments show otherwise. I conclude by arguing that this account of induction plays an essential role in her metaphysics, both in an argument for simple substances—which has an inductive premise—and in her attempt to distinguish acceptable and unacceptable metaphysical commitments. (shrink)

How, as Caldwell puts it, does one choose between rival systems all of which claim to rest on a priori foundations? On the nonfallibilistic conception it is difficult to make sense even of the possibility of rival systems of this sort. On the conception here defended, in contrast, the existence of such rival systems can be seen to be a perfectly natural and acceptable consequence of the just-mentioned difficulties we will often fact in coming to know even the intelligible traits (...) of reality: one adjudicates between such systems in the same way in which one adjudicates between all rival scientific hypotheses, namely via a complex mixture of empirical and a priori considerations. (shrink)

How was the hypothetical character of theories of experience thought about throughout the history of science? The essays cover periods from the middle ages to the 19th and 20th centuries. It is fascinating to see how natural scientists and philosophers were increasingly forced to realize that a natural science without hypotheses is not possible.

What is wrong with ad hoc hypotheses? Ever since Popper’s falsificationist account of adhocness, there has been a lively philosophical discussion about what constitutes adhocness in scientific explanation, and what, if anything, distinguishes legitimate auxiliary hypotheses from illicit ad hoc ones. This paper draws upon distinct examples from pseudoscience to provide us with a clearer view as to what is troubling about ad hoc hypotheses. In contrast with other philosophical proposals, our approach retains the colloquial, derogative meaning of adhocness, (...) and calls attention to the way in which the context of a theoretical move bears on the charge of adhocness. We also discuss the role of motivations implicit in the concept of adhocness, and the way ad hoc moves draw on theory-internal rationalizations. (shrink)

This dissertation summarises a research path aimed at fostering the use of Cognitive Architectures in Serious Games research field. Cognitive Architectures are an embodiment of scientific hypotheses and theories aimed at capturing the mechanisms of cognition that are considered consistent over time and independent of specific tasks or domains. The theoretical approaches provided by the research in computational cognitive modelling have been used to formalise a methodological framework to guide researchers and experts in the game-based education sector in designing, (...) implementing, and evaluating Serious Games. The investigation of cognitive processes involved during the game experience represents the fundamental step of the pro- posed approach. Two different case studies are described to discuss the possible use of the suggested framework. In the first case study, the aim was to design a modified version of the Tetris game with the intention of making the game more effective in training the visual-spatial skill called mental rotation. In the second scenario, the frame- work was used as a basis for creating an innovative persuasive game. This case study provides an example of adopting cognitive architectures for implementing a non-player character with human-like behaviour developed using targeted cognitive theories. (shrink)

The problem of old evidence, first described by Glymour [1980], is still widely regarded as one of the most pressing foundational challenges to the Bayesian account of scientific reasoning. Many solutions have been proposed, but all of them have drawbacks and none is considered to be definitive. Here, we introduce and defend a new kind of solution, according to which hypotheses are confirmed when we become more confident that they provide the only way of accounting for the known evidence.

This paper discusses Immanuel Kant’s views on the role of experiments in natural science, focusing on their relationship with hypotheses, laws of nature, and the heuristic principles of scientific enquiry. Kant’s views are contrasted with the philosophy of experiment that was first sketched by Francis Bacon and later developed by Robert Boyle and Robert Hooke. Kant holds that experiments are always designed and carried out in the light of hypotheses. Hypotheses are derived from experience on the basis of a (...) set of heuristic principles. The function of experiments is testing hypotheses in order to either reject them as false, or else to transform them into empirical laws of nature. To this end, we must integrate the hypotheses that are confirmed by experiments with the a priori principles which are the foundations of natural science. Compared with Bacon, Boyle, and Hooke, Kant has elaborate views on the one hand, on how our theoretical and pre-theoretical assumptions bear on experimental practice, and on the other hand, on how the results of experimental activity can be integrated with theories to advance our knowledge of nature. However, Kant overstates the dependence of experiments on theories. (shrink)

The Extended Evolutionary Synthesis (EES) debate is gaining ground in contemporary evolutionary biology. In parallel, a number of philosophical standpoints have emerged in an attempt to clarify what exactly is represented by the EES. For Massimo Pigliucci, we are in the wake of the newest instantiation of a persisting Kuhnian paradigm; in contrast, Telmo Pievani has contended that the transition to an EES could be best represented as a progressive reformation of a prior Lakatosian scientific research program, with the (...) extension of its Neo-Darwinian core and the addition of a brand-new protective belt of assumptions and auxiliary hypotheses. Here, we argue that those philosophical vantage points are not the only ways to interpret what current proposals to ‘extend’ the Modern Synthesis-derived ‘standard evolutionary theory’ (SET) entail in terms of theoretical change in evolutionary biology. We specifically propose the image of the emergent EES as a vast network of models and interweaved representations that, instantiated in diverse practices, are connected and related in multiple ways. Under that assumption, the EES could be articulated around a paraconsistent network of evolutionary theories (including some elements of the SET), as well as models, practices and representation systems of contemporary evolutionary biology, with edges and nodes that change their position and centrality as a consequence of the co-construction and stabilization of facts and historical discussions revolving around the epistemic goals of this area of the life sciences. We then critically examine the purported structure of the EES—published by Laland and collaborators in 2015—in light of our own network-based proposal. Finally, we consider which epistemic units of Evo-Devo are present or still missing from the EES, in preparation for further analyses of the topic of explanatory integration in this conceptual framework. (shrink)

Extended Cognition (EC) hypothesizes that there are parts of the world outside the head serving as cognitive vehicles. One criticism of this controversial view is the problem of “cognitive bloat” which says that EC is too permissive and fails to provide an adequate necessary criterion for cognition. It cannot, for instance, distinguish genuine cognitive vehicles from mere supports (e.g. the Yellow Pages). In response, Andy Clark and Mark Rowlands have independently suggested that genuine cognitive vehicles are distinguished from supports in (...) that the former have been “recruited,” i.e. they are either artifacts, or, products of evolution. I argue against this proposal. There are counter examples to the claim that “Teleological” EC is either necessary or sufficient for cognition. Teleological EC conflates different types of scientific projects, and inherits content externalism’s alienation from historically impartial cognitive science. (shrink)

Neste trabalho, é apresentada uma investigação do que poderia ser chamado de formalização lógica do processo de mudança de teorias devido a anomalias. Por anomalia entende-se um fato observado que faz parte do escopo explanatório de uma teoria, mas que vai de encontro à previsão da mesma. Uma abordagem clássica para restaurar o poder explicativo de uma teoria ameaçada por uma anomalia é a postulação de hipóteses novas e provisórias que, em conjunto com as demais hipóteses auxiliares originais, sejam capazes (...) de resolver a anomalia. Após chegar à algumas conclusões sobre a estrutura de tal processo, propomos um framework lógico multimodal e não-monotônico capaz de representar alguns aspectos-chave dessa faceta importante da dinâmica de teorias científicas. Devido à necessidade de acomodar hipóteses provisórias incompatíveis, esse framework incorpora uma forma fraca de paraconsistência. Como um estudo de caso, analisamos o comportamento anômalo do planeta Urano que ameaçou a mecânica celeste Newtoniana por mais de meio século e ensejou a descoberta do planeta Netuno. -/- In this work, an investigation of what could be called the logical formalization of the theory change process due to anomalies is presented. An anomaly is understood as an observed fact that is part of the explanatory scope of a theory, but that goes against its prediction. A classic approach to restoring the explanatory power of a theory threatened by an anomaly is to postulate new and provisional hypotheses that, together with the other original auxiliary hypotheses, are capable of resolving the anomaly. After reaching some conclusions about the structure of such a process, we propose a multimodal and non-monotonic logical framework capable of representing some key aspects of this important facet of the dynamics of scientific theories. Due to the need to accommodate incompatible provisional hypotheses, this framework incorporates a weak form of paraconsistency. As a case study, we analyze the anomalous behavior of the planet Uranus that threatened Newtonian celestial mechanics for more than half a century and prompted the discovery of the planet Neptune. (shrink)

With his influence on the development of physiology, physics and geometry, Hermann von Helmholtz – like few scientists of the second half of the 19th century – is representative of the research in natural science in Germany. The development of his understanding of science is not less representative. Until the late sixties, he emphatically claimed the truth of science; later on, he began to see the conditions for the validity of scientific knowledge in relative terms, and this can, in (...) summary, be referred to as hypothesizing. Already in the past century, HeImholtz made first approaches to an understanding of science, which were incompatible with his own former position and which pointed to the modern age to an astonishingly large extent. A comparison with Karl R. Popper's logic of research will illustrate how closely he nevertheless approached modern understanding of science. In Popper's logic of research, hypothesizing of scientific knowledge is definitely much more advanced than in Helmholtz's theory of science. What begins vaguely to emerge with Helmholtz has already become an explicitly formulated programme with Popper. Although HeImholtz and Popper are not on a direct line of epistemological development and Popper refers to HeImholtz only rarely and casually, there are in fact surprising points of contact which have not been taken notice of so far and which appear above all if one looks at Helmholtz's understanding of science against the background of Popper's logic of research. (shrink)

This treatise covers the history, now more than 170 years long, of researches and debates concerning the biblical city of Ai. This archetypical chapter in the evolution of biblical archaeology and historiography was never presented in full. I use the historical data as a case study to explore a number of epistemological issues, such as the creation and revision of scientific knowledge, the formation and change of consensus, the Kuhnian model of paradigm shift, several models of discrimination between hypotheses (...) about the past, the interplay between scientists' values and their epistemic beliefs, and the truth-bearing of historiographic reconstruction. I show, in particular, that when scientists share common epistemic values they can modify their beliefs even when such changes go against deeply entrenched biases and preconceptions. Considerations of coherence usually constrain such modifications, and when sufficient data is available the result can be a profound change of beliefs. Several episodes of the "Ai debates" demonstrate, however, that similar change of beliefs will not occur when non-epistemic values take precedence. (shrink)

Karl Popper (1902-1994) was one of the most influential philosophers of science of the 20th century. He made significant contributions to debates concerning general scientific methodology and theory choice, the demarcation of science from non-science, the nature of probability and quantum mechanics, and the methodology of the social sciences. His work is notable for its wide influence both within the philosophy of science, within science itself, and within a broader social context. Popper’s early work attempts to solve the problem (...) of demarcation and offer a clear criterion that distinguishes scientific theories from metaphysical or mythological claims. Popper’s falsificationist methodology holds that scientific theories are characterized by entailing predictions that future observations might reveal to be false. When theories are falsified by such observations, scientists can respond by revising the theory, or by rejecting the theory in favor of a rival or by maintaining the theory as is and changing an auxiliary hypothesis. In either case, however, this process must aim at the production of new, falsifiable predictions. While Popper recognizes that scientists can and do hold onto theories in the face of failed predictions when there are no predictively superior rivals to turn to. He holds that scientific practice is characterized by its continual effort to test theories against experience and make revisions based on the outcomes of these tests. By contrast, theories that are permanently immunized from falsification by the introduction of untestable ad hoc hypotheses can no longer be classified as scientific. Among other things, Popper argues that his falsificationist proposal allows for a solution of the problem of induction, since inductive reasoning plays no role in his account of theory choice. Along with his general proposals regarding falsification and scientific methodology, Popper is notable for his work on probability and quantum mechanics and on the methodology of the social sciences. Popper defends a propensity theory of probability, according to which probabilities are interpreted as objective, mind-independent properties of experimental setups. Popper then uses this theory to provide a realist interpretation of quantum mechanics, though its applicability goes beyond this specific case. With respect to the social sciences, Popper argued against the historicist attempt to formulate universal laws covering the whole of human history and instead argued in favor of methodological individualism and situational logic. Table of Contents 1. Background 2. Falsification and the Criterion of Demarcation a. Popper on Physics and Psychoanalysis b. Auxiliary and Ad Hoc Hypotheses c. Basic Sentences and the Role of Convention d. Induction, Corroboration, and Verisimilitude 3. Criticisms of Falsificationism 4. Realism, Quantum Mechanics, and Probability 5. Methodology in the Social Sciences 6. Popper’s Legacy 7. References and Further Reading a. Primary Sources b. Secondary Sources -/- . (shrink)

In this paper, I discuss how Newton’s inductive argument of the Principia can be defended against criticisms levelled against it by Duhem, Popper and myself. I argue that Duhem’s and Popper’s criticisms can be countered, but mine cannot. It requires that we reconsider, not just Newton’s inductive argument in the Principia, but also the nature of science more generally. The methods of science, whether conceived along inductivist or hypothetico-deductivist lines, make implicit metaphysical presuppositions which rigour requires we make explicit within (...) science so that they can be critically assessed, alternatives being developed and assessed, in the hope that they can be improved. Despite claiming to derive his law of gravitation by induction from phenomena without resource to hypotheses, Newton does nevertheless acknowledge in the Principia that his rules of reasoning make metaphysical presuppositions. To this extent, Newton has a more enlightened view of scientific method than most 20th and 21st century scientists and historians and philosophers of science. (shrink)

The aim of this work was to elaborate on the author’s previously published hypothesis of the Soul of Multiverse, a suggested cosmic phenomenon that also appears to imbue the human Soul across its individual and noospheric scales. Without alternatives, the method of analysis continued to rely on the approach of cosmological neuroscience, which integrates scientific facts, religious insights, philosophical suggestions, engineering rules and artistic tools to grasp the complexity of the multidimensional phenomenon of Soul. The result of this examination (...) was the multilayered thought that just as the central medium of human Soul, the hypothesized prefrontal cortical supercircuitry of Self-Ken, seems to comprise domains representing Identity, Conscience, Will and Mission, analogous domains may also function in the noospheric and cosmic Souls. Regarding the human Soul, its four domains appear to be determined by both hereditary genetic and encountered environmental factors to present its host with a Mission enabling his or her mental engine and physical features to integrate into the surrounding society and space-time in the most meaningful and dignified way—if that way is undertaken. Regarding the noospheric Soul, it is made of individual human Souls interacting with the non-living system of interconnected computers to produce functions accessible to humans all over the world through uncontrolled communication across the Internet. Its most probable Mission is to let this global presence acquire its own Identity, develop its own Conscience and refine its own Will, so that their coherent, superior whole can be ready for sensing the cosmic Soul. Regarding the cosmic Soul, the hypothesized Soul of the Multiverse, its Identity appears to express the Laws of Mystery of Endlessness, Coexistence in Diversity, and Truth in Complexity. Further, its Conscience seems to be moved by the Law of Divine—Evil Asymmetry, its Will by the Law of Determination with Uncertainty, and its Mission by the Law of Lives to Transcend. (shrink)