ABSTRACT I argue that this examination and appreciation for the shift to abductive reasoning should be extended to the intersection of neuroscience and novel brain-computer interfaces too. This paper highlights the implications of applying abductive reasoning to personalized implantable neurotechnologies. Then, it explores whether abductive reasoning is sufficient to justify insurance coverage for devices absent widespread clinical trials, which are better applied to one-size-fits-all treatments. INTRODUCTION In contrast to the classic model of randomized-control trials, often with a large number of (...) subjects enrolled, precision medicine attempts to optimize therapeutic outcomes by focusing on the individual.[i] A recent publication highlights the strengths and weakness of both traditional evidence-based medicine and precision medicine.[ii] Plus, it outlines a tension in the shift from evidence-based medicine’s inductive reasoning style (the collection of data to postulate general theories) to precision medicine’s abductive reasoning style (the generation of an idea from the limited data available).[iii] The paper’s main example is the application of precision medicine for the treatment of cancer.[iv] I argue that this examination and appreciation for the shift to abductive reasoning should be extended to the intersection of neuroscience and novel brain-computer interfaces too. As the name suggests, brain-computer interfaces are a significant advancement in neurotechnology that directly connects someone’s brain to external or implanted devices.[v] Among the various kinds of brain-computer interfaces, adaptive deep brain stimulation devices require numerous personalized adjustments to their settings during the implantation and computation stages in order to provide adequate relief to patients with treatment-resistant disorders. What makes these devices unique is how adaptive deep brain stimulation integrates a sensory component to initiate the stimulation. While not commonly at the level of sophistication as self-supervising or generative large language models,[vi] they currently allow for a semi-autonomous form of neuromodulation. This paper highlights the implications of applying abductive reasoning to personalized implantable neurotechnologies. Then, it explores whether abductive reasoning is sufficient to justify insurance coverage for devices absent widespread clinical trials, which are better applied to one-size-fits-all treatments.[vii] ANALYSIS I. The State of Precision Medicine in Oncology and the Epistemological Shift While a thorough overview of precision medicine for the treatment of cancer is beyond the scope of this article, its practice can be roughly summarized as identifying clinically significant characteristics a patient possesses (e.g., genetic traits) to land on a specialized treatment option that, theoretically, should benefit the patient the most.[viii] However, in such a practice of stratification patients fall into smaller and smaller populations and the quality of evidence that can be applied to anyone outside these decreases in turn.[ix] As inductive logic helps to articulate, the greater the number of patients that respond to a particular therapy the higher the probability of its efficacy. By straying from this logical framework, precision medicine opens the treatment of cancer to more uncertainty about the validity of these approaches to the resulting disease subcategories.[x] Thus, while contemporary medical practices explicitly describe some treatments as “personalized”, they ought not be viewed as inherently better founded than other therapies.[xi] A relevant contemporary case of precision medicine out of Norway focuses on the care of a patient with cancer between the ventricles of the heart and esophagus, which had failed to respond to the standard regimen of therapies over four years.[xii] In a last-ditch effort, the patient elected to pay out-of-pocket for an experimental immunotherapy (nivolumab) at a private hospital. He experienced marked improvements and a reduction in the size of the tumor. Understandably, the patient tried to pursue further rounds of nivolumab at a public hospital. However, the hospital initially declined to pay for it given the “lack of evidence from randomised clinical trials for this drug relating to this [patient’s] condition.”[xiii] In rebuttal to this claim, the patient countered that he was actually similar to a subpopulation of patients who responded in “open‐label, single arm, phase 2 studies on another immune therapy drug” (pembrolizumab).[xiv] Given this interpretation of the prior studies and the patient’s response, further rounds of nivolumab were approved. Had the patient not had improvements in the tumor’s size following a round of nivolumab, then pembrolizumab’s prior empirical evidence in isolation would have been insufficient, inductively speaking, to justify his continued use of nivolumab.[xv] The case demonstrates a shift in reasoning from the traditional induction to abduction. The phenomenon of ‘cancer improvement’ is considered causally linked to nivolumab and its underlying physiological mechanisms.[xvi] However, “the weakness of abductions is that there may always be some other better, unknown explanation for an effect. The patient may for example belong to a special subgroup that spontaneously improves, or the change may be a placebo effect. This does not mean, however, that abductive inferences cannot be strong or reasonable, in the sense that they can make a conclusion probable.”[xvii] To demonstrate the limitations of relying on the abductive standard in isolation, commentators have pointed out that side effects in precision medicine are hard to rule out as being related to the initial intervention itself unless trends from a group of patients are taken into consideration.[xviii] As artificial intelligence (AI) assists the development of precision medicine for oncology, this uncertainty ought to be taken into consideration. The implementation of AI has been crucial to the development of precision medicine by providing a way to combine large patient datasets or a single patient with a large number of unique variables with machine learning to recommend matches based on statistics and probability of success upon which practitioners can base medical recommendations.[xix] The AI is usually not establishing a causal relationship[xx] – it is predicting. So, as AI bleeds into medical devices, like brain-computer interfaces, the same cautions about using abductive reasoning alone should be carried over. II. Responsive Neurostimulation, AI, and Personalized Medicine Like precision medicine in cancer treatment, computer-brain interface technology similarly focuses on the individual patient through personalized settings. In order to properly expose the intersection of AI, precision medicine, abductive reasoning, and implantable neurotechnologies, the descriptions of adaptive deep brain stimulation systems need to deepen.[xxi] As a broad summary of adaptive deep brain stimulation, to provide a patient with the therapeutic stimulation, a neural signal, typically referred to as a local field potential,[xxii] must first be detected and then interpreted by the device. The main adaptive deep brain stimulation device with premarket approval, the NeuroPace Responsive Neurostimulation system, is used to treat epilepsy by detecting and storing “programmer-defined phenomena.”[xxiii] Providers can optimize the detection settings of the device to align with the patient’s unique electrographic seizures as well as personalize the reacting stimulation’s parameters.[xxiv] The provider adjusts the technology based on trial and error. One day machine learning algorithms will be able to regularly aid this process in myriad ways, such as by identifying the specific stimulation settings a patient may respond to ahead of time based on their electrophysiological signatures.[xxv] Either way, with AI or programmers, adaptive neurostimulation technologies are individualized and therefore operate in line with precision medicine rather than standard treatments based on large clinical trials. Contemporary neurostimulation devices are not usually sophisticated enough to be prominent in AI discussions where the topics of neural networks, deep learning, generative models, and self-attention dominate the conversation. However, implantable high-density electrocorticography arrays (a much more sensitive version than adaptive deep brain stimulation systems use) have been used in combination with neural networks to help patients with neurologic deficits from a prior stroke “speak” through a virtual avatar.[xxvi] In some experimental situations, algorithms are optimizing stimulation parameters with increasing levels of independence.[xxvii] An example of neurostimulation that is analogous to the use of nivolumab in Norway surrounds a patient in the United States who was experiencing both treatment-resistant OCD and temporal lobe epilepsy.[xxviii]Given the refractory nature of her epilepsy, implantation of an adaptive deep brain stimulation system was indicated. As a form of experimental therapy, her treatment-resistant OCD was also indicated for the off-label use of an adaptive deep brain stimulation set-up. Another deep brain stimulation lead, other than the one implanted for epilepsy, was placed in the patient’s right nucleus accumbens and ventral pallidum region given the correlation these nuclei had with OCD symptoms in prior research. Following this, the patient underwent “1) ambulatory, patient-initiated magnet-swipe storage of data during moments of obsessive thoughts; (2) lab-based, naturalistic provocation of OCD-related distress (naturalistic provocation task); and (3) lab-based, VR [virtual reality] provocation of OCD-related distress (VR provocation task).”[xxix] Such signals were used to identify when to deliver the therapeutic stimulation in order to counter the OCD symptoms. Thankfully, following the procedure and calibration the patient exhibited marked improvements in their OCD symptoms and recently shared her results publicly.[xxx] In both cases, there is a similar level of abductive justification for the efficacy of the delivered therapy. In the case study in which the patient was treated with adaptive deep brain stimulation, they at least had their neural activity tested in various settings to determine the optimum parameters for treatment to avoid them being based on guesswork. Additionally, the adaptive deep brain stimulation lead was already placed before the calibration trials were conducted, meaning that the patient had already taken on the bulk of the procedural risk before the efficacy could be determined. Such an efficacy test could have been replicated in the first patient’s cancer treatment, had it been biopsied and tested against the remaining immunotherapies in vitro. Yet, in the case of cancer with few options, one previous dose of a drug that appeared to work on the patient may justify further doses. However, as the Norwegian case presents, corroboration with known responses to a similar drug (from a clinical trial) could be helpful to validate the treatment strategy. (It should be noted that both patients were resigned to these last resort options regardless of the efficacy of treatment.) There are some elements of inductive logic seen with adaptive deep brain stimulation research in general. For example, abductively the focus could be that patient X’s stimulation parameters are different from patient Y’s and patient Z’s. In contrast, when grouped as subjects who obtained personalized stimulation, patients X, Y, and Z demonstrate an inductive aspect to this approach’s safety and/or efficacy. The OCD case holds plenty of abductive characteristics in line with precision medicine’s approach to treating cancer and as more individuals try the method, there will be additional data. With the gradual integration of AI into brain-computer interfaces in the name of efficacy, this reliance on abduction will continue, if not grow, over time. Moving forward, if a responsive deep brain stimulation treatment is novel and individualized (like the dose of nivolumab) and there is some other suggestion of efficacy (like clinical similarities to other patients in the literature), then it may justify insurance coverage for the investigative intervention, absent other unrelated reasons to deny it. III. Ethical Implications and Next Steps While AI’s use in oncology and neurology is not yet as prominent as its use in other fields (e.g., radiology), it appears to be on the horizon for both.[xxxi] AI can be found in both the functioning of the neurotechnologies as well as the implementation of precision medicine. The increasing use of AI may serve to further individualize both oncologic and neurological therapies. Given these implications and the handful of publications cited in this article, it is important to have a nuanced evaluation of how these treatments, which heavily rely on abductive justification, ought to be managed. The just use an abductive approach may be difficult as AI infused precision medicine is further pursued. At baseline, such technology relies on a level of advanced technology literacy among the general public and could exclude populations who lack access to basic technological infrastructure or know-how from participation.[xxxii] Even among nations with adequate infrastructure, as more patients seek out implantable neurotechnologies, which require robust healthcare resources, the market will favor patient populations that can afford this complex care.[xxxiii] If patients already have the means to pay for an initial dose/use of a precision medicine product out of pocket, should insurance providers be required to cover subsequent treatments?[xxxiv] That is, if a first dose of a cancer drug or a deep brain stimulator over its initial battery life is successful, patients may feel justified in having the costs of further treatments covered. The Norwegian patient’s experience implies there is a precedent for the idea that some public insurance companies ought to cover successful cancer therapies, however, insurance companies may not all see themselves as obligated to cover neurotechnologies that rely on personalized settings or that are based on precision/abductive research more than on clinical trials. CONCLUSION The fact that the cases outlined above rely on abductive style of reasoning implies that there may not be as strong a justification for coverage by insurance, as they are both experimental and individualized, when compared to the more traditional large clinical trials in which groups have the same or a standardized protocol (settings/doses). If a study is examining the efficacy of a treatment with a large cohort of patients or with different experimental groups/phases, insurance companies may conclude that the resulting symptom improvements are more likely to be coming from the devices themselves. A preference for inductive justification may take priority when ruling in favor of funding someone’s continued use of an implantable neurostimulator. There are further nuances to this discussion surrounding the classifications of these interventions as research versus clinical care that warrant future exploration, since such a distinction is more of a scale[xxxv] than binary and could have significant impacts on the “right-to-try” approach to experimental therapies in the United States.[xxxvi] Namely, given the inherent limitations of conducting large cohort trials for deep brain stimulation interventions on patients with neuropsychiatric disorders, surgically innovative frameworks that blend abductive and inductive methodologies, like with sham stimulation phases, have traditionally been used.[xxxvii] Similarly, for adaptive brain-computer interface systems, if there are no large clinical trials and instead only publications that demonstrate that something similar worked for someone else, then, in addition to the evidence that the first treatment/dose worked for the patient in question, the balance of reasoning would be valid and arguably justify insurance coverage. As precision approaches to neurotechnology become more common, frameworks for evaluating efficacy will be crucial both for insurance coverage and for clinical decision making. ACKNOWLEDGEMENT This article was originally written as an assignment for Dr. Francis Shen’s “Bioethics & AI” course at Harvard’s Center for Bioethics. I would like to thank Dr. Shen for his comments as well as my colleagues in the Lázaro-Muñoz Lab for their feedback. - [i] Jonathan Kimmelman and Ian Tannock, “The Paradox of Precision Medicine,” Nature Reviews. Clinical Oncology 15, no. 6 (June 2018): 341–42, https://doi.org/10.1038/s41571-018-0016-0. [ii] Henrik Vogt and Bjørn Hofmann, “How Precision Medicine Changes Medical Epistemology: A Formative Case from Norway,” Journal of Evaluation in Clinical Practice 28, no. 6 (December 2022): 1205–12, https://doi.org/10.1111/jep.13649. [iii] David Barrett and Ahtisham Younas, “Induction, Deduction and Abduction,” Evidence-Based Nursing 27, no. 1 (January 1, 2024): 6–7, https://doi.org/10.1136/ebnurs-2023-103873. [iv] Vogt and Hofmann, “How Precision Medicine Changes Medical Epistemology,” 1208. [v] Wireko Andrew Awuah et al., “Bridging Minds and Machines: The Recent Advances of Brain-Computer Interfaces in Neurological and Neurosurgical Applications,” World Neurosurgery, May 22, 2024, S1878-8750(24)00867-2, https://doi.org/10.1016/j.wneu.2024.05.104. [vi] Mark Riedl, “A Very Gentle Introduction to Large Language Models without the Hype,” Medium (blog), May 25, 2023, https://mark-riedl.medium.com/a-very-gentle-introduction-to-large-language-models-without-the-hype-5 f67941fa59e. [vii] David E. Burdette and Barbara E. Swartz, “Chapter 4 - Responsive Neurostimulation,” in Neurostimulation for Epilepsy, ed. Vikram R. Rao (Academic Press, 2023), 97–132, https://doi.org/10.1016/B978-0-323-91702-5.00002-5. [viii] Kimmelman and Tannock, 2018. [ix] Kimmelman and Tannock, 2018. [x] Simon Lohse, “Mapping Uncertainty in Precision Medicine: A Systematic Scoping Review,” Journal of Evaluation in Clinical Practice 29, no. 3 (April 2023): 554–64, https://doi.org/10.1111/jep.13789. [xi] Kimmelman and Tannock, “The Paradox of Precision Medicine.” [xii] Vogt and Hofmann, 1206. [xiii] Vogt and Hofmann, 1206. [xiv] Vogt and Hofmann, 1206. [xv] Vogt and Hofmann, 1207. [xvi] Vogt and Hofmann, 1207. [xvii] Vogt and Hofmann, 1207. [xviii] Vogt and Hofmann, 1210. [xix] Mehar Sahu et al., “Chapter Three - Artificial Intelligence and Machine Learning in Precision Medicine: A Paradigm Shift in Big Data Analysis,” in Progress in Molecular Biology and Translational Science, ed. David B. Teplow, vol. 190, 1 vols., Precision Medicine (Academic Press, 2022), 57–100, https://doi.org/10.1016/bs.pmbts.2022.03.002. [xx] Stefan Feuerriegel et al., “Causal Machine Learning for Predicting Treatment Outcomes,” Nature Medicine 30, no. 4 (April 2024): 958–68, https://doi.org/10.1038/s41591-024-02902-1. [xxi] Sunderland Baker et al., “Ethical Considerations in Closed Loop Deep Brain Stimulation,” Deep Brain Stimulation 3 (October 1, 2023): 8–15, https://doi.org/10.1016/j.jdbs.2023.11.001. [xxii] David Haslacher et al., “AI for Brain-Computer Interfaces,” 2024, 7, https://doi.org/10.1016/bs.dnb.2024.02.003. [xxiii] Burdette and Swartz, “Chapter 4 - Responsive Neurostimulation,” 103–4; “Premarket Approval (PMA),” https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpma/pma.cfm?id=P100026. [xxiv] Burdette and Swartz, “Chapter 4 - Responsive Neurostimulation,” 104. [xxv] Burdette and Swartz, 126. [xxvi] Sean L. Metzger et al., “A High-Performance Neuroprosthesis for Speech Decoding and Avatar Control,” Nature 620, no. 7976 (August 2023): 1037–46, https://doi.org/10.1038/s41586-023-06443-4. [xxvii] Hao Fang and Yuxiao Yang, “Predictive Neuromodulation of Cingulo-Frontal Neural Dynamics in Major Depressive Disorder Using a Brain-Computer Interface System: A Simulation Study,” Frontiers in Computational Neuroscience 17 (March 6, 2023), https://doi.org/10.3389/fncom.2023.1119685; Mahsa Malekmohammadi et al., “Kinematic Adaptive Deep Brain Stimulation for Resting Tremor in Parkinson’s Disease,” Movement Disorders 31, no. 3 (2016): 426–28, https://doi.org/10.1002/mds.26482. [xxviii] Young-Hoon Nho et al., “Responsive Deep Brain Stimulation Guided by Ventral Striatal Electrophysiology of Obsession Durably Ameliorates Compulsion,” Neuron 0, no. 0 (October 20, 2023), https://doi.org/10.1016/j.neuron.2023.09.034. [xxix] Nho et al. [xxx] Nho et al.; Erik Robinson, “Brain Implant at OHSU Successfully Controls Both Seizures and OCD,” OHSU News, accessed March 3, 2024, https://news.ohsu.edu/2023/10/25/brain-implant-at-ohsu-successfully-controls-both-seizures-and-ocd. [xxxi] Awuah et al., “Bridging Minds and Machines”; Haslacher et al., “AI for Brain-Computer Interfaces.” [xxxii] Awuah et al., “Bridging Minds and Machines.” [xxxiii] Sara Green, Barbara Prainsack, and Maya Sabatello, “The Roots of (in)Equity in Precision Medicine: Gaps in the Discourse,” Personalized Medicine 21, no. 1 (January 2024): 5–9, https://doi.org/10.2217/pme-2023-0097. [xxxiv] Green, Prainsack, and Sabatello, 7. [xxxv] Robyn Bluhm and Kirstin Borgerson, “An Epistemic Argument for Research-Practice Integration in Medicine,” The Journal of Medicine and Philosophy: A Forum for Bioethics and Philosophy of Medicine 43, no. 4 (July 9, 2018): 469–84, https://doi.org/10.1093/jmp/jhy009. [xxxvi] Vijay Mahant, “‘Right-to-Try’ Experimental Drugs: An Overview,” Journal of Translational Medicine 18 (June 23, 2020): 253, https://doi.org/10.1186/s12967-020-02427-4. [xxxvii] Michael S. Okun et al., “Deep Brain Stimulation in the Internal Capsule and Nucleus Accumbens Region: Responses Observed during Active and Sham Programming,” Journal of Neurology, Neurosurgery & Psychiatry 78, no. 3 (March 1, 2007): 310–14, https://doi.org/10.1136/jnnp.2006.095315. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:My Ability to FlourishPaulette KoehlerIn twenty years of convulsions, I’ve never heard a neurologist mention the word “epilepsy.” Over this time, the intensity of my original simple partial seizures, “simple” signifying retained consciousness and “partial” indicating disturbances restricted to a specific area of my brain, grew to the complex level on my left temporal lobe. I believe this development was influenced by my use of prescribed medications. Several (...) neurologists from Los Angeles to San Francisco directed various electroencephalograms (EEGs), including a week–long, prescription–free EEG in the hospital; magnetic resonance imaging tests (MRIs); computed tomography (CT) scans anywhere from forty–five minutes to four hours each; and blood profiles to help determine my situation. For legal reasons, one neurologist even had me sign a release stating that he was not able to diagnose my situation.Test results present limited information about my brain and without ever saying, “I don’t know,” these neurologists communicated my test results by utilizing technical terms and thus not always answering my questions. After explaining that my head turns to the left while my right hand shakes, symptoms that have been recognized and reported by several friends and family members, my doctor replied that a seizure on the left side of my brain should cause my head to turn to the right and then changed the subject. I felt like asking, “Am I doing it wrong?”The brain is different from other parts of our anatomy in that it can’t be replaced like a kidney, heart or other organ. It cannot be removed like tonsils, an appendix or even a limb. It can be physically studied or repaired while functioning but the resulting percentage of survival or proper operation of the body after surgery is minimal and the number of people requiring such attention is so low that the amount is scanty. A dead brain limits the analysis of its functions.My “disabilities” involve spontaneous uncontrolled loss of consciousness, exhaustion, mood swings, and the suspension of driving privileges. Activity interference, extra naps, losing friends and not being able to get around are definite disadvantages. However, everyone needs to manage personal problems. No one is perfect.Public transit schedules and directions don’t always offer me the transportation I need. Fortunately, the combination of a bus ride with walking or running can serve my needs while also helping me to keep physically healthy.Limited benefits include discounted transit and the option to ride instead of walking or running. A trip to Nana’s on the train is always a treat.I’d rather not be branded “disabled” even though those who understand my situation address me with compassionate, sympathetic attention, [End Page E4] always asking how I physically feel. I feel fine. A seizure is only a quick, conscious loss of time and an occasional scrape on the knee. I’m more annoyed when I notice strangers looking suspiciously at my public transport discount card as if I don’t really deserve it.Like the “disability” brand, the medications I’ve taken, Dilantin, Neurontin, Depakote, Keppra and Lamictal, among others, all of which produced serious side effects without reducing the frequency of my seizures have only been a cover–up, preventing a search for the true cause and effective treatment of my seizures. Being identified as disabled has only limited my daily schedule. I am not disabled, as society has unfortunately characterized me.My seizures began in 1993, the year our FDA started approving rBGH, recombinant bovine growth hormone, man–made for the use on dairy cows to enhance their milk production. As a result, milk on the market increased while keeping the price from rising, as demonstrated in Economics I. Can the use of rBGH act on my brain in any way?One neurologist, in order to avoid the responsibility of inappropriate recommendations, presented his thoughts in the form of questions, encouraging me to consider options.“You’ve tried all of these medications?”“Has your diet alteration made any difference in your seizures?”“Have you tried organic foods?”His inquiries persuaded me to contemplate whether drugs are an answer to my problem, pay attention to differences in my life and... (shrink)

In 1942 California corporate agribusiness seized upon racist hysteria and pseudo "national security" issues to manipulate social ideology so that it could unlawfully seize tens of thousands of acres of productive farm land from law-abiding American citizens. It was such seizures that then allowed already existing large-scale capital to further consolidate California's agricultural resources while at the same time restructuring and increasing its concentration of the state's agricultural production and food manufacturing capabilities. Meanwhile, in "the most striking mass (...) interference since slavery with the right of physical freedom," over 120,000 Japanese Americans were placed in concentration camps and illegally deprived of their property and human rights. (shrink)

Since the outbreak of the Coronavirus disease 2019 (Covid-19), tremendous efforts have been made by scientists, health professionals, business people, politicians, and laypeople around the world. Covid-19 vaccines are one of the most crucial innovations that help fight against the virus. This paper attempts to revisit the Covid-19 vaccines production process by employing the serendipity-mindsponge-3D creativity management theory. Vaccine production can be considered an information process and classified into three main stages. The first stage involved the processes of (...) absorbing information (e.g., digital data and open science) and rejecting unhelpful information (e.g., misinformation and fake news) for effectively acquiring useful insights. Useful insights were later employed by experts, enterprises, governments, and international organizations through interdisciplinary coordinated efforts for developing vaccines within a short period. Finally, the appearance of multiple types of vaccines enabled more strategic options for vaccine distribution and administration. Findings from this vaccine creativity management process could be used as critical lessons for further improvements of vaccination programs. (shrink)

As we approach the end of the twentieth century, the ways in which knowledge--scientific, social, and cultural--is produced are undergoing fundamental changes. In The New Production of Knowledge, a distinguished group of authors analyze these changes as marking the transition from established institutions, disciplines, practices, and policies to a new mode of knowledge production. Identifying such elements as reflexivity, transdisciplinarity, and heterogeneity within this new mode, the authors consider their impact and interplay with the role of knowledge in (...) social relations. While the knowledge produced by research and development in science and technology is accorded central focus, the authors also outline the changing dimensions of social scientific and humanities knowledge and the relations between the production of knowledge and its dissemination through education. Placing science policy and scientific knowledge within the broader context of contemporary society, this book will be essential reading for all those concerned with the changing nature of knowledge, with the social study of science, with educational systems, and with the correlation between research and development and social, economic, and technological development. "Thought-provoking in its identification of issues that are global in scope; for policy makers in higher education, government, or the commercial sector." --Choice "By their insightful identification of the recent social transformation of knowledge production, the authors have been able to assert new imperatives for policy institutions. The lessons of the book are deep." --Alexis Jacquemin, Universite Catholique de Louvain and Advisor, Foreign Studies Unit, European Commission "Should we celebrate the emergence of a 'post-academic' mode of postmodern knowledge production of the post-industrial society of the 21st Century? Or should we turn away from it with increasing fear and loathing as we also uncover its contradictions. A generation of enthusiasts and/or critics will be indebted to the team of authors for exposing so forcefully the intimate connections between all the cognitive, educational, organizational, and commercial changes that are together revolutionizing the sciences, the technologies, and the humanities. This book will surely spark off a vigorous and fruitful debate about the meaning and purpose of knowledge in our culture." --Professor John Ziman, (Wendy, Janey at Ltd. is going to provide affiliation. Contact if you don't hear from her.) "Jointly authored by a team of distinguished scholars spanning a number of disciplines, The New Production of Knowledge maps the changes in the mode of knowledge production and the global impact of such transformations. . . . The authors succeed . . . at sketching out, in very large strokes, the emerging trends in knowledge production and their implications for future society. The macro focus of the book is a welcome change from the micro obsession of most sociologists of science, who have pretty much deconstructed institutions and even scientific knowledge out of existence." --Contemporary Sociology "This book is a timely contribution to current discussion on the breakdown of and need to renegotiate the social contract between science and society that Vannevar Bush and likeminded architects of science policy constructed immediately after World War II. It goes far beyond the usual scattering of fragmentary insights into changing institutional landscapes, cognitive structures, or quality control mechanisms of present day science, and their linkages with society at large. Tapping a wide variety of sources, the authors provide a coherent picture of important new characteristics that, taken altogether, fundamentally challenge our traditional notions of what academic research is all about. This well-founded analysis of the social redistribution of knowledge and its associated power patterns helps articulate what otherwise tends to remain an--albeit widespread--intuition. Unless they adapt to the new situation, universities in the future will find the centers of gravity of knowledge production moving even further beyond their ken. Knowledge of the social and cognitive dynamics of science in research is much needed as a basis of science and technology policymaking. The New Production of Knowledge does a lot to fill this gap. Another unique feature is its discussion of the humanities, which are usually left out in works coming out of the social studies of science." --Aant Elzinga, University od Goteborg. (shrink)

By examining an exemplar sample of mental health nursing educational policies and related legislation, in this article, we trace the discursive production of madness as an “othered” identity category. We engage in a critical discourse analysis of mental health nursing education in Canada, drawing on provincial and federal policies and legislation as the main sources of data. Theoretically framed by critical posthumanism and mad studies, this article outlines how the mad subjectivity becomes decontextualized out of its identity‐based understanding and (...) recontextualized as an inferior category of “the human,” circulating within discourses of pedagogy, economics, law, and psychiatry. The article maps the intertextual nexus of the discourse of mental health nursing education, making visible the complex, the arbitrary, and the sometimes‐contradictory nature of the discipline's grappling with identity‐based mental health concepts. We close with several implications for nursing policy, education, and practice. (shrink)

During the last two decades, sociologist Pierre Bourdieu has become a dominant force in cultural activity ranging from taste in music and art to choices in food and lifestyles. _The Field of Cultural Production_ brings together Bourdieu's major essays on art and literature and provides the first introduction to Bourdieu's writings and theory of a cultural field that situates artistic works within the social conditions of their production, circulation, and consumption. Bourdieu develops a highly original approach to the study (...) of literary and artistic works, addressing many of the key issues that have preoccupied literary art and cultural criticism in the last twentieth century: aesthetic value and canonicity, intertextuality, the institutional frameworks of cultural practice, the social role of intellectuals and artists, and structures of literary and artistic authority. Bourdieu elaborates a theory of the cultural field which situates artistic works within the social conditions of their production, circulation, and consumption. He examines the individuals and institutions involved in making cultural products what they are: not only the writers and artists, but also the publishers, critics, dealers, galleries, and academies. He analyzes the structure of the cultural field itself as well as its position within the broader social structures of power. The essays in his volume examine such diverse topics as Flaubert's point of view, Manet's aesthetic revolution, the historical creation of the pure gaze, and the relationship between art and power. The Field of Cultural Porduction will be of interest to students and scholars from a wide range of disciplines: sociology and social theory, literature, art, and cultural studies. (shrink)

DCPS is a connectionist production system interpreter that uses distributed representations. As a connectionist model it consists of many simple, richly interconnected neuron‐like computing units that cooperate to solve problems in parallel. One motivation for constructing DCPS was to demonstrate that connectionist models are capable of representing and using explicit rules. A second motivation was to show how “coarse coding” or “distributed representations” can be used to construct a working memory that requires far fewer units than the number of (...) different facts that can potentially be stored. The simulation we present is intended as a detailed demonstration of the feasibility of certain ideas and should not be viewed as a full implementation of production systems. Our current model only has a few of the many interesting emergent properties that we eventually hope to demonstrate: It is damage‐resistant, it performs matching and variable binding by massively parallel constraint satisfaction, and the capacity of its working memory is dependent on the similarity of the items being stored. (shrink)

"What is at stake in this book is nothing less than a dramatically new way of approaching literature, one which in its unostentatious, low key way scandalously smashes a whole range of liberal humanist icons." --Terry Eagleton Who is more important: the reader, or the writer? Originally published in French in 1966, Pierre Macherey's first and most famous work, A Theory of Literary Production dared to challenge perceived wisdom, and quickly established him as a pivotal figure in literary theory. (...) In this provocative work, Macherey puts the focus as much on the reader as the writer, stating that the very act of reading is a form of production in its own right, generating interpretation and meanings which are beyond the control of the author. Part of the birth of a whole new branch of post-structuralist theory, Macherey's work also influenced a new generation of critics among them Jacques Derrida, his contemporary, and Terry Eagleton. His ideas have also led some observers to claim that he announced the death of the author fully two years before Roland Barthes' famous essay. The reissue of this work as a Routledge Classic brings some radical ideas to a new audience, and argues persuasively for a totally new way of reading. As such, it is an essential work for anyone interested in the development of literary theory. (shrink)

How is it that many schizophrenics identify certain instances of verbal imagery as hallucinatory? Most investigators have assumed that alterations in sensory features of imagery explain this. This approach, however, has not yielded a definitive picture of the nature of verbal hallucinations. An alternative perspective suggests itself if one allows the possibility that the nonself quality of hallucinations is inferred on the basis of the experience of unintendedness that accompanies imagery production. Information-processing models of “intentional” cognitive processes call for (...) abstract planning representations that are linked to goals and beliefs. Unintended actions - and imagery - can reflect planning disruptions whereby cognitive products do not cohere with concurrent goals. A model of schizophrenic speech disorganization is presented that postulates a disturbance of discourse planning. Insofar as verbal imagery can be viewed as inwardly directed speech, a consequence of such planning disturbances could be the production of unintended imagery. This link between the outward disorganization of schizophrenic speech and unintended verbal imagery is statistically supported by comparing the speech behavior of hallucinating and nonhallucinating schizophrenics. Studies of “borderline” hallucinations during normal, “goal-less” relaxation and drowsiness suggest that experiential unintendedness leads to a nonpathological variant of hallucinatory otherness that is correctable upon emerging from such passive cognitive states. This contrasts with the schizophrenic case, where nonconcordance with cognitive goals reinforces the unintendedness of verbal images and sustains the conviction of an external source. This model compares favorably with earlier models of verbal hallucinations and provides further evidence for a language production disorder in many schizophrenics.Short Abstract: How is it that many schizophrenics identify certain instances of verbal imagery as hallucinatory? This paper proposes that the critical feature identifying hallucinations is the experience of unintendedness. This experience is nonpathological during passive conscious states but pathological if occurring during goal-directed cognitive processing. A model of schizophrenic speech disorganization is presented that postulates a disturbance of discourse planning that specifies communicative intentions. These alterations could generate unintended verbal imagery as well. Statistical data are offered to support the model, and relevant empirical studies are reviewed. (shrink)

The article analyzes the technological shifts which took place in the second half of the 20th and early 21st centuries and forecasts the main shifts in the next half a century. On the basis of the analysis of the latest achievements in inno-vative technological directions and also on the basis of the opportunities pro-vided by the theory of production revolutions the authors present a detailed analysis of the latest production revolution which is denoted as ‘Сybernetic’. The authors give (...) some forecasts about its development in the nearest five decades and up to the end of the 21st century. It is shown that the development of various self-regulating systems will be the main trend of this revolution. The authors argue that at first the transition to the beginning of the final phase of the Cybernetic Revolution will start in the field of medicine (in its some innovative directions). In future we will deal with the start of convergence of innovative technologies which will form the system of MBNRIC-technologies (i.e. the technological paradigm based on medicine, bio- and nanotechnologies, robotics, IT and cognitive technologies). The article gives a detailed analysis of the future breakthroughs in medicine, bio- and nanotechnologies as well as some other technologies in terms of the development of self-regulating systems with their growing ability to select optimum modes of functioning as well as of other characteristics of the Cybernetic Revolution (resources and energy saving, miniaturization, individualization, etc.). (shrink)

Early practitioners of the social studies of science turned their attention away from questions of institutionalisation, which had tended to emphasize macrolevel explanations, and attended instead to microstudies of laboratory practice. The author is interested in re-investigating certain aspects of institution formation, notably the formation of scientific, medical, and engineering disciplines. He emphasises the manner in which science as cultural practice is imbricated with other forms of social, political, and even aesthetic practices. The author considers the following topics: the organic (...) physics of 1847; the innovative research program of Carl Ludwig as a model for institutionalising science-based medicine, optics, painting, and ideology in Germany, 1845-95; the Haber-Bosch synthesis of ammonia; and the introduction of nuclear magnetic resonance instrumentation into the practice of organic chemistry. (shrink)

This paper argues that the inappropriate framing and implementation of plagiarism detection systems in UK universities can unwittingly construct international students as ‘plagiarists’. It argues that these systems are often implemented with inappropriate assumptions about plagiarism and the way in which new members of a community of practice develop the skills to become full members of that community. Drawing on the literature and some primary data it shows how expectations, norms and practices become translated and negotiated in such a way (...) that legitimate attempts to conform with the expectations of the community of practice often become identified as plagiarism and illegitimate attempts at cheating often become obscured from view. It argues that this inappropriate framing and implementation of plagiarism detection systems may make academic integrity more illusive rather than less. It argues that in its current framing – as systems for ‘detection and discipline’ – plagiarism detection systems may become a new micro-politics of power with devastating consequences for those excluded. (shrink)