The central focus of this article is the epistemological assumption that knowledge could be generated based on human beings’ experiences and over their conceptions of the world. Logical characterisation of human inductive learning over their produced conceptions within terminological systems and providing a logical background for theorising over the Human Concept Learning Problem (HCLP) in terminological systems are the main contributions of this research. In order to make a linkage between ‘Logic’ and ‘Cognition’, Description (...) Logics (DLs) will be employed to provide a logical description and analysis of actual human inductive reasoning (and learning). This research connects with the topics ‘logic & learning’, ‘cognitive modelling’, and ‘terminological knowledge representation’. (shrink)

This research provides a contextual description concerning an existential and structural analysis of ‘Relations’ between human beings and machines. Subsequently, it will focus on the conceptual and epistemological analysis of (i) my own semantics-based framework [for human meaning construction] and of (ii) a well-structured machine concept learning framework. Accordingly, I will, semantically and epistemologically, focus on linking those two frameworks for logical analysis of concept learning in the context of human-machine interrelationships. It will (...) be demonstrated that the proposed framework provides a supportive structure over the described contextualisation of ‘relations’ between human beings and machines within concept learning processes. (shrink)

Linguistic and non-linguistic pattern learning have been studied separately, but we argue for a comparative approach. Analogous inductive problems arise in phonological and visual pattern learning. Evidence from three experiments shows that human learners can solve them in analogous ways, and that human performance in both cases can be captured by the same models. We test GMECCS, an implementation of the Configural Cue Model in a Maximum Entropy phonotactic-learning framework with a single free parameter, against (...) the alternative hypothesis that learners seek featurally simple algebraic rules. We study the full typology of patterns introduced by Shepard, Hovland, and Jenkins (), instantiated as both phonotactic patterns and visual analogs, using unsupervised training. Unlike SHJ, Experiments 1 and 2 found that both phonotactic and visual patterns that depended on fewer features could be more difficult than those that depended on more features, as predicted by GMECCS but not by rule-seeking. GMECCS also correctly predicted performance differences between stimulus subclasses within each pattern. A third experiment tried supervised training to elicit simple rule-seeking phonotactic learning, but cue-based behavior persisted. We conclude that similar cue-based cognitive processes are available for phonological and visual concept learning, and hence that studying either kind of learning can lead to significant insights about the other. (shrink)

Humans learn new concepts extremely fast. One or two examples of a new concept are often sufficient for us to grasp its meaning. Traditional theories of concept formation, such as symbolic or connectionist representations, have problems explaining the quick learning exhibited by humans. In contrast to these representations, I advocate a third form of representing categories, which employs geometric structures. I argue that this form is appropriate for modeling concept learning. By using the geometric structures (...) of what I call “conceptual spaces,” I define properties and concepts. A learning model that shows how properties and concepts can be learned in a simple but naturalistic way is then presented. This model accounts well for the role of similarity judgments in concept learning. Finally, as an application, the concept representations are used to give an analysis of nonmonotonic reasoning. (shrink)

This research works within the framework of constructivist learning (based on constructivist epistemology) and examines learning as an activity of construction, and it posits that knowledge acquisition (and learning) are transformative through self-involvement in some subject matter. Thus it leads, through this constructivism to a pedagogical theory of learning. I will mainly focus on conceptual and epistemological analysis of humans’ conceptualisations based on their own mental objects (schemata). Subsequently, I will propose an analytical specification of humans’ (...) conceptualisations and understandings over their mental structures in the framework of constructivism, and I will clarify my logical [and semantic] conceptions of humans’ concept understandings. This research focuses on the philosophy of education and on logics of human learning. It connects with the topics ‘Cognition in Education’ and ‘Mental Models’. (shrink)

This article attempts to make a conceptual and epistemological junction between human learning and machine learning. I will be concerned with specifying and analysing the structure of concepts in the common ground between a concept-based human learning theory and a concept-based machine learning paradigm. I will focus on (i) humans’ conceptual representations in the framework of constructivism (as an educational theory of learning and model of knowing) and constructionism (as a theory (...) for conceptualising learning) and (ii) concept representations in the framework of inductive concept learning (as an inductive machine learning paradigm). The results will support figuring out the most significant key points for constructing a conceptual linkage between a human learning theory and a machine learning paradigm. Accordingly, I will construct a conceptual ground for expressing and analysing concepts in the common ground of human and informatics sciences and in the context of human-machine interplays. (shrink)

Aesthetic non-cognitivists deny that aesthetic statements express genuinely aesthetic beliefs and instead hold that they work primarily to express something non-cognitive, such as attitudes of approval or disapproval, or desire. Non-cognitivists deny that aesthetic statements express aesthetic beliefs because they deny that there are aesthetic features in the world for aesthetic beliefs to represent. Their assumption, shared by scientists and theorists of mind alike, was that language-users possess cognitive mechanisms with which to objectively grasp abstract rules fixed independently of (...) class='Hi'>human responses, and that cognizers are thereby capable of grasping rules for the correct application of aesthetic concepts without relying on evaluation or enculturation. However, in this article I use Wittgenstein’s rule-following considerations to argue that psychological theories grounded upon this so-called objective model of rule-following fail to adequately account for concept acquisition and mastery. I argue that this is because linguistic enculturation, and the perceptual learning that’s often involved, influences and enables the mastery of aesthetic concepts. I argue that part of what’s involved in speaking aesthetically is to belong to a cultural practice of making sense of things aesthetically, and that it’s within a socio-linguistic community, and that community’s practices, that such aesthetic sense can be made intelligible. (shrink)

Providing more human-like concept learning in machines has always been one of the most significant goals of machine learning paradigms and of human-machine interaction techniques. This article attempts to provide a logical specification of conceptual mappings from humans’ minds into machines’ knowledge bases. We will focus on the representation of the mappings (transformations) relying on First-Order Predicate Logic. Additionally, the structure of concepts in the common ground between humans and machines will be analysed. It seems (...) quite necessary to pay attention to the philosophy of constructivism and constructivist models of knowing. This research constructs a conceptual ground for expressing and analysing concepts in the common ground between humanistic and informatics sciences and in the context of human-machine interplays. (shrink)

Learning general concepts in imperfect environments is difficult since training instances often include noisy data, inconclusive data, incomplete data, unknown attributes, unknown attribute values and other barriers to effective learning. It is well known that people can learn effectively in imperfect environments, and can manage to process very large amounts of data. Imitating human learning behavior therefore provides a useful model for machine learning in real-world applications. This paper proposes a new, more effective way to (...) represent imperfect training instances and rules, and based on the new representation, a Human-Like Learning (HULL) algorithm for incrementally learning concepts well in imperfect training environments. Several examples are given to make the algorithm clearer. Finally, experimental results are presented that show the proposed learning algorithm works well in imperfect learning environments. (shrink)

The paper adopts an inter-theoretical socio-cultural and -material perspective on the relationship between human + machine learning to propose a new way to investigate the human + machine assistive assemblages emerging in professional work (e.g. medicine, architecture, design and engineering). Its starting point is Hutchins’s (1995a) concept of ‘distributed cognition’ and his argument that his concept of ‘cultural ecosystems’ constitutes a unit of analysis to investigate collective human + machine working and learning (Hutchins, (...) Philos Psychol 27:39–49, 2013). It argues that: (i) the former offers a way to reveal the cultural constitution of and enactment of human + machine cognition and, in the process, the limitations of the computational and connectionist assumptions about learning that underpin, respectively, good old-fashioned AI and deep learning; and (2) the latter offers a way to identify, when amplified with insights from Socio-Materialism and Cultural-Historical Activity Theory, how ML is further rearranging and reorganising the distributed basis of cognition in assistive assemblages. The paper concludes by outlining a set of conjectures researchers that could use to guide their investigations into the ongoing design and deployment of HL + ML assemblages and challenges associated with the interaction between HL + ML. (shrink)

Machine learning has been proven useful for solving the bottlenecks in building expert systems. Noise in the training instances will, however, confuse a learning mechanism. Two main steps are adopted here to solve this problem. The first step is to appropriately arrange the training order of the instances. It is well known from Psychology that different orders of presentation of the same set of training instances to a human may cause different learning results. This idea is (...) used here for machine learning and an order arrangement scheme is proposed. The second step is to modify a conventional noise-free learning algorithm, thus making it suitable for noisy environment. The generalized version space learning algorithm is then adopted to process the training instances for deriving good concepts. Finally, experiments on the Iris Flower problem show that the new scheme can produce a good training order, allowing the generalized version space algorithm to have a satisfactory learning result. (shrink)

Critical consideration is given the empirical evidence for psychological models of religious development, its supposed relationship to other domains of psychological development, and especially, moral development. Significant problems with stage conceptions in these models augur a fundamental rethinking of religious development as a construct in developmental psychology. Model of Hierarchical Complexity has demonstrable promise for enabling greater precision in constructs and methods. This may resolve some central problems and advance research in the field.

Fodor argued that learning a concept by hypothesis testing would involve an impossible circularity. I show that Fodor's argument implicitly relies on the assumption that actually φ-ing entails an ability to φ. But this assumption is false in cases of φ-ing by luck, and just such luck is involved in testing hypotheses with the kinds of generative random sampling methods that many cognitive scientists take our minds to use. Concepts thus can be learned by hypothesis testing without circularity, (...) and it is plausible that this is how humans in fact acquire at least some of their concepts. (shrink)

Can we learn to create a better world? Yes, if we first create traditions and institutions of learning rationally devoted to that end. At present universities all over the world are dominated by the idea that the basic aim of academic inquiry is to acquire knowledge. Such a conception of inquiry, judged from the standpoint of helping us learn wisdom and civilization, is grotesquely and damagingly irrational. We need to change our approach to academic enterprise if we are to (...) create a kind of inquiry rationally devoted to helping us become more civilized. (shrink)

The purpose of this qualitative research is to conceptualize the factors that influence human flourishing. Data has been gathered through in-depth, semi-structured interviews with thirty global heads of Human Resources of manufacturing companies in India and South Asia. Data from these interviews are analyzed using grounded theory methodology to categorize concepts and create a conceptual model of the main themes which contribute to human flourishing. This study highlights three such themes: (1) opportunities for advancement; (2) personal capability; (...) and (3) leading people inclusively. This article provides implications for a more complete model for entrepreneurs, policy makers, and HR heads to understand the conditions necessary for human flourishing, filling a literature gap in the study of human flourishing from the perspective of an employer. (shrink)

Humanizing education in a democratic society requires an adequate conception of democratic life. Dewey's ideal of a society with free interaction among groups and extensive sharing of interests provides such a vision. His idea of purposing, as a key ingredient in meaningful learning, thought and action, also gives depth to the concept of education in democracy.

In his much-discussed Hitler’s Willing Executioners, Daniel Goldhagen claims to bring ‘the critical eye of the anthropologist’ to the task of understanding the motivational state of Holocaust perpetrators. This aspect of his methodology has not received much critical attention. In this article I seek to fill that gap. I do so through consideration of Peter Winch’s reflections on the concept of learning from anthropological study of an alien social and cultural world. Goldhagen tells us that perpetrators acted as (...) they did because they believed it was ‘necessary and just’ to do so. But he only tells us thatthey believed this. We need to know howthey could have believed such a thing. Drawing upon Winch’s reflections, and with recourse to a controversial analogy, I address the ‘phenomenological’ question that Goldhagen poses, but fails, to explore. (shrink)

American anthropology is distinguished by a four-fields approach in which biological, cultural, archaeological, and linguistic dimensions of behavior are examined in evolutionary and cross-cultural perspective. Nevertheless, assumptions of mind-body dualism pervade scholarly thinking in anthropology and have prevented the development of a truly integrated science of human experience. This dualism is most exemplified by the lack of consideration of the role of the brain in both “physical” and “mental” processes, including phenomena labeled as cultural. In this paper, I review (...) neural mechanisms of learning, communication, and emotion, and discuss the implications of these findings for culture theory. (shrink)

This guide accompanies the following article(s): ‘Full Disclosure of the “Raw Data” of Research on Humans: Citizens’ Rights, Product Manufacturer’s Obligations and the Quality of the Scientific Database.’Philosophy Compass 6/2 (2011): 90–99. doi: 10.1111/j.1747‐9991.2010.00376.x Author’s Introduction Securing consent (and informed consent) from patients and research study participants is a key concern in patient care and research on humans. Yet, the legal doctrines of consent and informed consent differ in their applications. In patient care, the judicial doctrines of consent and informed (...) consent are disclosure doctrines based on the obligation of physicians to inform their patients of the following types of information: the nature of the procedure the physician is recommending in the patent’s care (P), the alternatives to the physician‐recommendation (A), and the risks of procedure and its alternatives (R). In addition, the physician must provide truthful answers to the patient’s questions (Q) to the best of the physician’s abilities. In research on humans, the onus of disclosure by study sponsors and principal investigators is much greater than in patient care precisely because the purpose of research is not patient care. The purpose of research is the identification and development of new generalizable knowledge. Thus, participation in a research study or trial may not benefit the study volunteer at all. In addition, the participant may carry a heavy risk burden in relationship to any testing of a newly designed drug or device as part of their experiences in the research study. Presently, despite the risks borne by the research study participant, the raw data collected from volunteers in research trials are treated by courts as if they were the private property of the study sponsor rather than generally owed to the public as would be expected by an effort like research participation aimed at contributing to the development of generalizable knowledge. This paper reviews the obligations that study sponsors owe to their study participants based on the very definition of research as a systematic activity whose purpose is to develop generalizable knowledge to help all humans. Author Recommends Court cases Canterbury v. Spence, United States Court of Appeals, District of Columbia Circuit 464 F.2d 772 (1972). (Federal appellate decision heard in the District of Columbia, USA) Reibl v. Hughes, 2 S.C.R. 880 (1980). (Supreme Court of Canada) Rogers v. Whitaker, 175 C.L. R. 479 (1992). (High Court of Australia) Sidaway v. Board of Governors of the Bethlem Royal Hospital and the Maudsley Hospital and Others. 1 A.C. 871 (1985) (House of Lords) Canterbury v. Spence is the landmark Federal informed consent case in the United States heard in the District of Columbia. In this case, Judge Spottswood Robinson articulated the reasonable person standard of informed consent. This standard was subsequently adopted by the Supreme Court of Canada (Reibl v. Hughes, 2 S.C.R. 880 (1980)) and the High Court of Australia (Rogers v. Whitaker, 175 C.L. R. 479 (1992)). The House of Lords rejected the reasonable person standard in England in Sidaway v. Board of Governors of the Bethlem Royal Hospital and the Maudsley Hospital and Others. 1 A.C. 871 (1985). Book Mazur, Dennis J. The Science and Ethics of Research on Humans. Baltimore, MD: Johns Hopkins University Press, 2007. This book is a detailed guide for the review of scientific and ethical aspects of research on humans contained in the research study protocols and research informed consent forms which need to be submitted by study sponsors and principal investigators to institutional review boards (IRBs) for IRB review before a research study can receive approval to be conducted within a human study population in those institutions over which the IRB has authority. It also presents basic definitions in the area of research on humans and basic approaches to help conduct a deep review of the underlying scientific and ethical issues that are present within a research study protocol and its accompanying research informed consent form. Report National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research. The Belmont Report: Ethical Guidelines for the Protection of Human Subjects of Research. Washington, DC: DHEW Publications, 1978 (78‐0012). This U.S. National Commission in the Belmont Report argued for the necessity of a reasonable volunteer standard in research on humans in the United States. Arguing that the professional standard and the reasonable person standard of consent and informed consent were insufficient to base a disclosure standard in research on humans, this National Commission developed the reasonable volunteer standard where a study participant is to be approached in research informed consent with that information that a reasonable volunteer would want to know. Online Materials Belmont Report: Syllabus Topics for Lecture and Discussion Week I: Introduction and Overview Readings: Rogers v. Whitaker, 175 C.L.R. 479 (1992). (High Court of Australia) Sidaway v. Board of Governors of the Bethlem Royal Hospital and the Maudsley Hospital and Others. 1 A.C. 871 (1985) (House of Lords) Week II: The Different Standards of Consent and Informed Consent Readings: Canterbury v. Spence, 464 F.2d 772 (1972). (Federal appellate opinion heard in the District of Columbia) Sidaway v. Board of Governors of the Bethlem Royal Hospital and the Maudsley Hospital and Others. 1 A.C. 871 (1985) (House of Lords) Week III: Definition of Research Reading: Mazur, Dennis J. The Science and Ethics of Research on Humans. Baltimore, MD: Johns Hopkins University Press, 2007. (Especially Chapters 2 and 3) Week IV: How to Review a Research Study Protocol and Research Informed Consent Form Reading: Mazur, Dennis J. The Science and Ethics of Research on Humans. Baltimore, MD: Johns Hopkins University Press, 2007. (Especially Chapters 4–6, 10, and 12–14) Week V: Obligations in Research of Humans Versus Patient Care Reading: National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research. The Belmont Report: Ethical Guidelines for the Protection of Human Subjects of Research. Washington, DC: DHEW Publications, 1978 (78‐0012). Focus Questions • How do the judicial doctrines of consent in England and Australia compare to the judicial doctrines of informed consent in the United States and Canada? • How does a professional standard of disclosure differ from a reasonable person standard of disclosure? • What is the definition of research? • How is a research study (study proposal and research informed consent form) reviewed from scientific and ethical bases for considerations of approval by an IRB? • How do the obligations of a study sponsor, a principal investigator, and a research team conducting a research trial on human study participants differ from the obligations of a physician caring for a patient? • Should all raw data of research derived from humans be made available to the public for use in developing generalizable knowledge to help others, or should raw data be considered the private property of the study sponsors (for example, prescription drug manufacturers), who fund the research trials? Seminar/project Idea Draw a timeline of the development of the basic concepts of consent and informed consent in patient care and in patient research. On this timeline, first place the dates of the key court cases in England, the United States, Canada, and Australia on consent and informed consent. Then place the date of the development of the Belmont Report. Why do differences exist between these four countries in terms of the legal requirements of informedness of a patient (in medical care) and a study participant (in medical research)? What roles if any do the concepts of self‐determination and self‐decision have in consent and informed consent in patient care and in informed consent in research on humans among the four countries of interest? What are the realities of research on human participants that require a new standard of informed consent, the reasonable volunteer standard, to be developed beyond the two standards in patient care, the professional standard, and the reasonable person standard? Counterpoint Arguments The following are counterpoint arguments that need to be appreciated to more fully understand the concepts that impact the thesis that ‘raw data’ should be open to the public to allow the opportunity of checking of the results of its associated scientific paper and for further analysis. De‐Identified (Anonymized) Raw Data A current approach to identifying (anonymizinig) raw data is based on the Health Insurance Portability and Accountability Act (HIPAA) of 1996 (P.L.104‐191). HIPAA was enacted by the U.S. Congress in 1996 to keep a person’s medical information private. In a research study, a person’s private medical information can become research data. HIPAA’s Privacy Rule allows a covered entity to de‐identify data by removing all 18 elements that could be used to identify the individual or the individual’s relatives, employers, or household members; these elements are enumerated in the Privacy Rule. The covered entity must also have no actual knowledge that the remaining information could be used alone or in combination with other information to identify the individual who is the subject of the information. Under this method, the identifiers that must be removed are the following: 1 Names. 2 All geographic subdivisions smaller than a state, including street address, city, county, precinct, ZIP Code, and their equivalent geographical codes, except for the initial three digits of a ZIP Code if, according to the current publicly available data from the Bureau of the Census: 2a. The geographic unit formed by combining all ZIP Codes with the same three initial digits contains more than 20,000 people. 2b. The initial three digits of a ZIP Code for all such geographic units containing 20,000 or fewer people are changed to 000. 3 All elements of dates (except year) for dates directly related to an individual, including birth date, admission date, discharge date, and date of death, and all ages over 89 and all elements of dates (including year) indicative of such age, except that such ages and elements may be aggregated into a single category of age 90 or older. 4 Telephone numbers. 5 Facsimile numbers. 6 Electronic mail addresses. 7 Social security numbers. 8 Medical record numbers. 9 Health plan beneficiary numbers. 10 Account numbers. 11 Certificate/license numbers. 12 Vehicle identifiers and serial numbers, including license plate numbers. 13 Device identifiers and serial numbers. 14 Web universal resource locators (URLs). 15 Internet protocol (IP) address numbers. 16 Biometric identifiers, including fingerprints and voiceprints. 17 Full‐face photographic images and any comparable images. 18 Any other unique identifying number, characteristic, or code, unless otherwise permitted by the Privacy Rule for re‐identification. Even though ‘raw data’ can be de‐identified (anonymized) so that there is no way to trace back the data to the study participant from which it was drawn, there are still questions whether the ‘de‐identified raw data’ can be given to other researchers or made public without the original study participant’s approval. It may be the case that this approval could be done at the start of any research study where the individual considering study participation would be counseled on what the process of de‐identification consists of and would be asked whether the participant would allow use of the data by other researchers or made available to the public in a de‐identified state. However, there may be questions of the study participants as to whether the data are truly de‐identified and untraceable back to the study participant since the participant would not be able to see the process actually being carried out in detail in all relevant circumstances. Using Raw Data in Context Simply being in possession of raw data is never enough to build on that data from a research perspective. Researchers need to understand the context of the scientific research study in which the data were collected. This research context includes (but is not limited to): (i) the scientific hypothesis of the research study, (ii) the inclusion and exclusion criteria selected by the research designers of the study to determine which study participants were included and which were excluded from the study, (iii) the methods used to collect the data and possibilities of errors in the data collection processes, and (iv) answers to questions regarding whether any data were excluded from the study data and why these data were excluded. Ownership Rights Over Data There are ownership rights over data. Ownership rights include court decision making related to the question which parties are to be considered as the owners of the data. Possible owners here include (but are not limited to) (i) the study sponsor whose only role was to fund that study, (ii) the principal investigator(s) who developed the scientific hypothesis, and (iii) individual study participants through special contracts made by individual participants who negotiate such contracts with study sponsors and principal investigators to share in the ownership of data. Examples of such data are participant sources of unique gene lines or unique cell lines to be used in future research. Objections to Data Sharing Finally, individual researchers may simply object to sharing data. A researcher’s arguments here may be simply stating that he or she has a right to fully analyze the data since the collection of the data was the researchers’ idea in the first place. These researchers may argue that they have the right to mine the data as fully as they can before deciding to make the data open to the public for others to analyze. Works Cited 1 Kaiser, J. ‘Making Clinical Data Widely Available.’Science 322.5899 (10 Oct. 2008): 217–8. 2 de Lusignan, S., J.F. Metsemakers, P. Houwink, V. Gunnarsdottir, and J. van der Lei. ‘Routinely Collected General Practice Data: Goldmines for Research? A Report of the European Federation for Medical Informatics Primary Care Informatics Working Group (EFMI PCIWG) from MIE2006, Maastricht, The Netherlands.’Informatics in Primary Care 14.3 (2006): 203–9. 3 Sim, I. ‘Human Studies Database Project’, CTSA Data Repositories Symposium (17 Oct. 2008). 23 Nov. 2010. 4 Sim, I., C.G. Chute, H. Lehmann, R. Nagarajan, M. Nahm, and R.H. Scheuermann. ‘Keeping Raw Data in Context.’Science 323.5915 (6 Feb. 2009): 713. 5 U.S. Department of Health and Human Services, National Institutes of Health, HIPAA Privacy Rule, Information for Researchers. 13 Nov. 2010. 6 Wilczynski, N.L., R.B. Haynes, and Hedges Team. ‘EMBASE Search Strategies for Identifying Methodologically Sound Diagnostic Studies for Use by Clinicians and Researchers.’BMC Medicine 29.3 (March 2005): 7. (shrink)

Macmurray’s distinctive portrayal of personhood has much to contribute to more recent accounts of what it means to be human. Michael Fielding, for one, has devoted much of his career to promoting and advocating a Macmurrian-style of schooling both as a critique of and a corrective to the performance-driven form of state education that is prevalent in the UK. Further, while I agree with Fielding and others that Macmurray’s concept of the person is of importance for education, I (...) also hold that it contains significant social and political implications for a religiously plural era. In addition, Macmurray’s emphasis on our inherent relationality provides a philosophical grounding for what is coming to be known as ‘postliberalism’. (shrink)

Workplace spirituality deals with paradoxes. This concept has been taken on board since the late 1980s, but very few human resource managers have realised that workplace spirituality could make an essential contribution to a better understanding of workplace and corporate reality. Increasing numbers of academic papers are being published on this subject but mere remain many grey areas for researchers. The aim of this paper is to use Simone Weil’s philosophy as a reading grid to get an insight (...) into workplace spirituality as a new paradigm of management. Initial studies attempting to apply Weil’s philosophy to management highlight the necessity for all the actors within the organisation to define their job tasks and contents according to their own way of thinking. Our interpretation of Weil’s philosophy also sheds light on the impossibility of dissociating thinking and acting and reminds us that work is done to nourish both the body and the soul. By concentrating on the spirituality of work, we can establish new links between ethics and human resource management. (shrink)

The 3rd Report of the Special Representative of the Secretary-General of the United Nations appears to have generated significant consensus around its approach to business and human rights. This state of harmony relies mainly upon a narrow mandate limiting the endeavour largely to a mapping exercise. It also relies upon a process of 'operationalisation' that is yet to be undertaken despite the recent release of a 4th Report. After a brief presentation of the main parameters of the framework proposed (...) by the 3rd Report and of its precarious advantage over other similar initiatives, this article takes a close look at the main link that needs to be operationalised: i.e. the link between corporate responsibility for human rights and the concept of legal and criminal responsibility. The article then addresses the constitutive elements of the concept of responsibility to shed light upon the responsibility of business organisations in a human rights law context. It looks at the innovative ways in which the concept of corporate criminal responsibility has been dealt with in various domestic jurisdictions and at the new paradigms of corporate agency resulting in the process. Building on this inquiry, the analysis focusses on the way in which the legal discourse acquires new dimensions of corporate responsibility by moving away from an individualistic perspective. On the basis of this, the article suggests conceptual tools that can become instrumental in the process of the operationalisation of the 3rd Report, albeit at the likely cost of rendering the consensus around it more fragile. (shrink)

In my opinion, it is only in the framework of a research dealing with abductive cognition that we can analyze important cognitive aspects of human and machine capacities. From the point of view of human capacities the phenomenological concept of anticipation, which is related to the problem of the spontaneous generation of spatiality and its three-dimensionality, will be central. I will describe that anticipations can be seen as types of visual and manipulative abduction and also fruitful to (...) illustrate, in the case of human and machine capacities, the respective role of two kinds of strategic reasoning: locked and unlocked abductive strategies, which characterize the basic cognitive pro- cedure of “reading ahead”. The specificity of these contrasting inferential strategies is also related to their potentiality in producing different kinds of hypothetical outcomes, which in turn represent dissimilar levels of knowledge creativity. This diversity is also fundamental to depict the special character, the kind of creativity, and the limits of current computational deep learning AI systems, such as AlphaGo, which realize abductive cognitive processes. (shrink)

This target article presents a theory of human cultural learning. Cultural learning is identified with those instances of social learning in which intersubjectivity or perspective-taking plays a vital role, both in the original learning process and in the resulting cognitive product. Cultural learning manifests itself in three forms during human ontogeny: imitative learning, instructed learning, and collaborative learning – in that order. Evidence is provided that this progression arises from the (...) developmental ordering of the underlying social-cognitive concepts and processes involved. Imitative learning relies on a concept of intentional agent and involves simple perspective-taking. Instructed learning relies on a concept of mental agent and involves alternating/coordinated perspective-taking (intersubjectivity). Collaborative learning relies on a concept of reflective agent and involves integrated perspective-taking (reflective intersubjectivity). A comparison of normal children, autistic children and wild and enculturated chimpanzees provides further evidence for these correlations between social cognition and cultural learning. Cultural learning is a uniquely human form of social learning that allows for a fidelity of transmission of behaviors and information among conspecifics not possible in other forms of social learning, thereby providing the psychological basis for cultural evolution. (shrink)

This article illustrates the practical usefulness of transdisciplinary work for practical theology by showing how input from an occupational therapist informed my understanding and interpretation of the story of Hannetjie, who had been sexually abused as a child. This forms part of a narrative practical theological research project into the spirituality of female adult survivors of childhood sexual abuse. Transdisciplinary work is useful to practical theologians, as it opens possibilities for learning about matters pastors have to face, but may (...) not have knowledge about. A short retelling of Hannetjie’s story is given to provide information about the context of the research. Next, the transdisciplinary process that was followed is mentioned, and the questions that the transdisciplinary team had to respond to are discussed. Following that, I focus more specifically on the occupational therapist’s answers, and the knowledge gained from her contribution, as an example of how a co-researcher from a divergent discipline can inform a theological study. In this case, knowledge was shared about sensory integration and how the brain processes traumatic stimuli, such as sexual abuse. Lastly, the interrelationship between Hannetjie’s body stories, mind stories and spirit stories is discussed to show how the learning received from occupational therapy affected my thinking about Hannetjie’s stories and the relationships between them. Thus, it is concluded that transdisciplinary work has great value for practical theology, especially in the pastor’s daily work with people who are struggling with difficult stories, because we cannot listen to people’s spirit stories in isolation. They are inextricably intertwined with all our stories about ourselves. (shrink)

Through hypothetical scenarios, this paper analyses whether machine learning (ML) could resolve one of the main shortcomings present in Christopher Boorse’s Biostatistical Theory of health (BST). In doing so, it foregrounds the boundaries and challenges of employing ML in formulating a naturalist (i.e., prima facie value-free) definition of health. The paper argues that a sweeping dataist approach cannot fully make the BST truly naturalistic, as prior theories and values persist. It also points out that supervised learning introduces circularity, (...) rendering it incompatible with a naturalistic perspective. Additionally, it underscores the need for pre-existing auxiliary theories to assess results from unsupervised learning. It emphasizes the importance of understanding the epistemological entanglements between data and data processing methods to manage expectations about what data patterns can predict. In conclusion, the paper argues against delegating the final authority for defining complex concepts like health to AI systems, as it necessitates ethical judgment and capacities for deliberation that AI currently lacks. It also warns against granting creators and deployers of AI systems the discretionary authority to determine these definitions outside the wider social discussion, advocating for ongoing public engagement on normative notions. Failure to do so risks limiting individuals and collectives’ ability to shape a just digital future and diminishes their fundamental epistemic agency. (shrink)

Applying machine learning algorithms to automatically infer relationships between concepts from large-scale collections of documents presents a unique opportunity to investigate at scale how human semantic knowledge is organized, how people use it to make fundamental judgments (“How similar are cats and bears?”), and how these judgments depend on the features that describe concepts (e.g., size, furriness). However, efforts to date have exhibited a substantial discrepancy between algorithm predictions and human empirical judgments. Here, we introduce a novel (...) approach to generating embeddings for this purpose motivated by the idea that semantic context plays a critical role in human judgment. We leverage this idea by constraining the topic or domain from which documents used for generating embeddings are drawn (e.g., referring to the natural world vs. transportation apparatus). Specifically, we trained state-of-the-art machine learning algorithms using contextually-constrained text corpora (domain-specific subsets of Wikipedia articles, 50+ million words each) and showed that this procedure greatly improved predictions of empirical similarity judgments and feature ratings of contextually relevant concepts. Furthermore, we describe a novel, computationally tractable method for improving predictions of contextually-unconstrained embedding models based on dimensionality reduction of their internal representation to a small number of contextually relevant semantic features. By improving the correspondence between predictions derived automatically by machine learning methods using vast amounts of data and more limited, but direct empirical measurements of human judgments, our approach may help leverage the availability of online corpora to better understand the structure of human semantic representations and how people make judgments based on those. (shrink)

The new features of the business environment have expanded the concept of organizational learning capability. In today’s competitive business environment, OLC has been recognized as an essential means to gain a sustainable competitive advantage. However, the effective development of that capability has not been sufficiently analyzed in the organizational learning literature. Prompted by a recent paradigm shift in the organizational sciences, this research explores the link between altruism and OLC testing a wider picture that includes two intermediate (...) steps: Relationship Conflict and Organizational Trust. To check our hypotheses, we used structural equations to analyze data from a survey of Spanish firms with recognized excellence in human resource management. Results indicate that organizational trust mediates on the altruism—OLC relationship; however, such linkage is not mediated by relationship conflict. Findings suggest that altruism and trust should be promoted in organizations in order to boost OLC. (shrink)

Pioneering work in the 1940s and 1950s suggested that the concept of chunking might be important in many processes of perception, learning and cognition in humans and animals. We summarize here the major sources of evidence for chunking mechanisms, and consider how such mechanisms have been implemented in computational models of the learning process. We distinguish two forms of chunking: the first deliberate, under strategic control, and goal-oriented; the second automatic, continuous, and linked to perceptual processes. Recent (...) work with discrimination-network computational models of long- and short-term memory (EPAM/CHREST) has produced a diverse range of applications of perceptual chunking. We focus on recent successes in verbal learning, expert memory, language acquisition and learning multiple representations, to illustrate the implementation and use of chunking mechanisms within contemporary models of human learning. (shrink)

Maker education mainly involves “hands-on” as the core concept and combines various educational theories to redefine interactions between learners and teachers in a learning environment. Identification of meaningful “hands-on” behaviors is crucial to evaluate students’ learning performance, although an instructor’s observation of every student is not feasible. However, such observation is possible with the aid of the artificial intelligence image processing technique; the AI learning behavior recognition system can serve as the second eyes of teachers, thus (...) accounting for individual differences. However, in previous studies, learning behavior recognition was applied to the traditional or static classroom. A behavior recognition system for identifying “hands-on” actions in the learning context has still not been developed. Therefore, this study designed a human posture evaluation system, obtained human articulation node information from learning field images, and built a learning behavior recognition model suitable for maker education based on the AI convolutional neural network. A learning behavior model was defined, along with a number of student behavior indexes. Subsequently, the effectiveness of the model and behavior indexes was verified through practical learning activities. The model evaluation results indicated that the proposed model achieved a training accuracy of 0.99 and a model accuracy of 0.83. Thus, the model can be applied to dynamic maker activity learning environments. (shrink)

Key Gadamerian concepts that speak to the humanities classroom -- What is reading in the humanities classroom? : Gadamer responds -- Aristotle and Gadamer on imitation : reading and writing as transformative -- Tradition as a hermeneutic challenge, not a rigid standard -- Authority as liberating : Gadamer and the I-thou encounter in the humanities classroom -- A humanities pedagogy : a schema for investigating the humanities classroom -- A humanities pedagogy responds to the neoliberal educational program.

This is a philosophical study written by a group of scholars from India and some other countries. It was from a conference held at the Delhi University, Delhi, India in 2017. Authors in this study discussed such issues as Indian as well as Western understanding of justice and responsibility in relation to relearning to be human in contemporary times, global challenges to justice and responsibility; contemporary principles of Justice; responsibility and justice in the Eastern Christian societies; prefect justice and (...) injustice; concept of justice and obligation and morality; professional responsibility and commercialism; care Ethics; etc. (shrink)

Descriptions of body imagery and body parts are evident in expressions of Old Testament texts. Although there is no single term for ‘body’ in the Hebrew mind, the concept of ‘body’ functions in its different parts. As part of anthropomorphic descriptions of God and expressions attached to humankind, body parts have special significance, contributing to the theological dimension of texts. The poems in the Psalter are no exception. Several body parts are mentioned in Psalm 38, an individual lament song. (...) In addition to God’s hand (v. 3) and an allusion to his voice (v. 16), several body parts describe the psalmist’s condition. These include ‘flesh’ (bāšār, 3, 8), bones (‘ætsæm, 3), head (rôsh, 5), loins (kæsæl, 8), heart (lēb, 9, 11), eyes (‘yn, 11), mouth (pæh, 14, 15), and feet (rægæl, 17). In addition, allusions to the ear (14, 15) and injured body (wounds, 6) form part of the psalmist’s lamenting experience.Contribution: This presentation touches on the general meaning of these body imagery in the Old Testament and their specific function and meaning in the text of Psalm 38. A textual analysis will portray their theological significance. (shrink)

For all of recorded history prior to the second half of the twentieth century, there has been but one realm in which the cognitive processes of reasoning and problem solving, learning and discovery, language and mathematics took place. The realm of human intellect no longer has an exclusive claim on these cognitive processes--artificial intelligence represents a parallel claim. Wagman compares the two realms, focusing on each of the major components of cognition: logic, reasoning, problem-solving, language, memory, learning, (...) and discovery. He identifies consonant and disparate modes of cognition, and develops a general theory of human and artificial intelligence. (shrink)

Generalization is a fundamental problem solved by every cognitive system in essentially every domain. Although it is known that how people generalize varies in complex ways depending on the context or domain, it is an open question how people learn the appropriate way to generalize for a new context. To understand this capability, we cast the problem of learning how to generalize as a problem of learning the appropriate hypothesis space for generalization. We propose a normative mathematical framework (...) for learning how to generalize by learning inductive biases for which properties are relevant for generalization in a domain from the statistical structure of features and concepts observed in that domain. More formally, the framework predicts that an ideal learner should learn to generalize by either taking the weighted average of the results of generalizing according to each hypothesis space, with weights given by how well each hypothesis space fits the previously observed concepts, or by using the most likely hypothesis space. We compare the predictions of this framework to human generalization behavior with three experiments in one perceptual (rectangles) and two conceptual (animals and numbers) domains. Across all three studies we find support for the framework's predictions, including individual‐level support for averaging in the third study. (shrink)

We propose a new relational direction in higher education that acknowledges external and internal images as integrated in thinking and learning. We expand educational theory and practice that commonly rely on discrete conceptual developments that exclude images. Our argument epistemologically relies on certain semiotic views that consider the role of iconic signs and iconicity (meaning making by the virtue of similarity) as significant in relation to knowledge and learning. The analogical and imaginative work required to discover similarity between (...) external pictures and any educational concept is a form of iconic mind work that opens a space for transformational thinking and creative solutions. The novelty of our argument lies in the schematic philosophy of mind by C.S. Peirce, and specifically, an adaptation of Peirce’s triadic sign diagram for learning, exemplified via an ‘inquiry graphic’ sign and reflective method. This outlook seeks connections in diversity, arguing for an education that acknowledges and teaches intrinsic human relatedness to other humans, beings and things in the environment, thus challenging any notions of anthropocentrism and superiority. It calls for a reaction in international higher education to acknowledge the iconicity of concepts and thinking and embrace integrated image-concept signs for deep and critical teaching-learning, towards a modest educational contribution to counteracting social and environmental crises. (shrink)

We propose a new relational direction in higher education that acknowledges external and internal images as integrated in thinking and learning. We expand educational theory and practice that commonly rely on discrete conceptual developments that exclude images. Our argument epistemologically relies on certain semiotic views that consider the role of iconic signs and iconicity (meaning making by the virtue of similarity) as significant in relation to knowledge and learning. The analogical and imaginative work required to discover similarity between (...) external pictures and any educational concept is a form of iconic mind work that opens a space for transformational thinking and creative solutions. The novelty of our argument lies in the schematic philosophy of mind by C.S. Peirce, and specifically, an adaptation of Peirce’s triadic sign diagram for learning, exemplified via an ‘inquiry graphic’ sign and reflective method. This outlook seeks connections in diversity, arguing for an education that acknowledges and teaches intrinsic human relatedness to other humans, beings and things in the environment, thus challenging any notions of anthropocentrism and superiority. It calls for a reaction in international higher education to acknowledge the iconicity of concepts and thinking and embrace integrated image-concept signs for deep and critical teaching-learning, towards a modest educational contribution to counteracting social and environmental crises. (shrink)

Learning Love from a Tiger explores the vibrancy and variety of humans' sacred encounters with the natural world, gathering a range of stories culled from Christian, Muslim, Hindu, Mayan, Himalayan, Buddhist, and Chinese shamanic traditions. Readers will delight in tales of house cats who teach monks how to meditate, rivers that grant salvation, shamans who shape-shift into jaguars, crickets who perform Catholic mass, and many others. More than a collection of wonderful stories, this book introduces important concepts and approaches (...) that underlie much recent work in environmental ethics, religion, and ecology. Capper's light touch prompts readers to engage their own views of humanity's place in the natural world and in particular question longstanding assumptions of human superiority"--Provided by publisher. (shrink)

To explain social learning without invoking the cognitively complex concept of imitation, many learning mechanisms have been proposed. Borrowing an idea used routinely in cognitive psychology, we argue that most of these alternatives can be subsumed under a single process, priming, in which input increases the activation of stored internal representations. Imitation itself has generally been seen as a This has diverted much research towards the all-or-none question of whether an animal can imitate, with disappointingly inconclusive results. (...) In the great apes, however, voluntary, learned behaviour is organized hierarchically. This means that imitation can occur at various levels, of which we single out two clearly distinct ones: the a rather detailed and linear specification of sequential acts, and the a broader description of subroutine structure and the hierarchical layout of a behavioural Program level imitation is a high-level, constructive mechanism, adapted for the efficient learning of complex skills and thus not evident in the simple manipulations used to test for imitation in the laboratory. As examples, we describe the food-preparation techniques of wild mountain gorillas and the imitative behaviour of orangutans undergoing to the wild. Representing and manipulating relations between objects seems to be one basic building block in their hierarchical programs. There is evidence that great apes suffer from a stricter capacity limit than humans in the hierarchical depth of planning. We re-interpret some chimpanzee behaviour previously described as and suggest that all great apes may be able to imitate at the program level. Action level imitation is seldom observed in great ape skill learning, and may have a largely social role, even in humans. (shrink)

Only human beings have a rich conceptual repertoire with concepts like tort, entropy, Abelian group, mannerism, icon and deconstruction. How have humans constructed these concepts? And once they have been constructed by adults, how do children acquire them? While primarily focusing on the second question, in The Origin of Concepts , Susan Carey shows that the answers to both overlap substantially. Carey begins by characterizing the innate starting point for conceptual development, namely systems of core cognition. Representations of core (...) cognition are the output of dedicated input analyzers, as with perceptual representations, but these core representations differ from perceptual representations in having more abstract contents and richer functional roles. Carey argues that the key to understanding cognitive development lies in recognizing conceptual discontinuities in which new representational systems emerge that have more expressive power than core cognition and are also incommensurate with core cognition and other earlier representational systems. Finally, Carey fleshes out Quinian bootstrapping, a learning mechanism that has been repeatedly sketched in the literature on the history and philosophy of science. She demonstrates that Quinian bootstrapping is a major mechanism in the construction of new representational resources over the course of childrens cognitive development. Carey shows how developmental cognitive science resolves aspects of long-standing philosophical debates about the existence, nature, content, and format of innate knowledge. She also shows that understanding the processes of conceptual development in children illuminates the historical process by which concepts are constructed, and transforms the way we think about philosophical problems about the nature of concepts and the relations between language and thought. (shrink)

The extent to which concepts, memory, and planning are necessary to the simulation of intelligent behavior is a fundamental philosophical issue in Artificial Intelligence. An active and productive segement of the AI community has taken the position that multiple low-level agents, properly organized, can account for high-level behavior. Empirical research on these questions with fully operational systems has been restricted to mobile robots that do simple tasks. This paper recounts experiments with Hoyle, a system in a cerebral, rather than a (...) physical, domain. The program learns to perform well and quickly, often outpacing its human creators at two-person, perfect information board games. Hoyle demonstrates that a surprising amount of intelligent behavior can be treated as if it were situation-determined, that often planning is unnecessary, and that the memory required to support this learning is minimal. Concepts, however, are crucial to this reactive program's ability to learn and perform. (shrink)

A main goal of this paper is to complicate “learning loss” as the only, or even the main, thing schools should be concerned about as they respond to the Covid-19 pandemic. While schools have a responsibility to make sure students who are enrolled in school are learning, this cannot come at the cost of ignoring the other substantial losses students are also contending with. Following the work of Jonathan Lear, I make the case that schools should engage students (...) in a process of learning how to mourn for their individual and our collective losses, while also considering ways that school can move beyond narrow conceptions of the purposes of school and to a deeper appreciation for the ways that an education can promote human excellence. As this pandemic wears on, it becomes harder and harder to do anything but endure. One goal of this paper is to serve as a reminder that schools can do more than endure: they can envision new possibilities for schooling that promote conceptions of wellbeing that go beyond fear of learning loss. (shrink)