Matching Items (14)
Description
Emergentism offers a promising compromise in the philosophy of mind between Cartesian substance dualism and reductivistic physicalism. The ontological emergentist holds that conscious mental phenomena supervene on physical phenomena, but that they have a nature over and above the physical. However, emergentist views have been subjected to a variety of powerful objections: they are alleged to be self-contradictory, incompatible with mental causation, justified by unreliable intuitions, and in conflict with our contemporary scientific understanding of the world. I defend the emergentist position against these objections. I clarify the concepts of supervenience and of ontological novelty in a way that ensures the emergentist position is coherent, while remaining distinct from physicalism and traditional dualism. Making note of the equivocal way in which the concept of sufficiency is used in Jaegwon Kim's arguments against emergent mental causation, I argue that downward causation does not entail widespread overdetermination. I argue that considerations of ideal a priori deducibility from some physical base, or "Cosmic Hermeneutics", will not themselves provide answers to where the cuts in the structure of nature lie. Instead, I propose reconsidering the question of Cosmic Hermeneutics in terms of which cognitive resources would be required for the ideal reasoner to perform the deduction. Lastly, I respond to the objection that emergence in the philosophy of mind is in conflict with our contemporary scientific understanding of the world. I suggest that a kind of weak ontological emergence is a viable form of explanation in many fields, and discuss current applications of emergence in biology, sociology, and the study of complex systems.
ContributorsWatson, Jeffrey (Author) / Kobes, Bernard W (Thesis advisor) / Pinillos, Nestor (Committee member) / Horgan, Terence (Committee member) / Reynolds, Steven (Committee member) / Arizona State University (Publisher)
Created2013
Description
Critical care environments are complex in nature. Fluctuating team dynamics and the plethora of technology and equipment create unforeseen demands on clinicians. Such environments become chaotic very quickly due to the chronic exposure to unpredictable clusters of events. In order to cope with this complexity, clinicians tend to develop ad-hoc adaptations to function in an effective manner. It is these adaptations or "deviations" from expected behaviors that provide insight into the processes that shape the overall behavior of the complex system. The research described in this manuscript examines the cognitive basis of clinicians' adaptive mechanisms and presents a methodology for studying the same. Examining interactions in complex systems is difficult due to the disassociation between the nature of the environment and the tools available to analyze underlying processes. In this work, the use of a mixed methodology framework to study trauma critical care, a complex environment, is presented. The hybrid framework supplements existing methods of data collection (qualitative observations) with quantitative methods (use of electronic tags) to capture activities in the complex system. Quantitative models of activities (using Hidden Markov Modeling) and theoretical models of deviations were developed to support this mixed methodology framework. The quantitative activity models developed were tested with a set of fifteen simulated activities that represent workflow in trauma care. A mean recognition rate of 87.5% was obtained in automatically recognizing activities. Theoretical models, on the other hand, were developed using field observations of 30 trauma cases. The analysis of the classification schema (with substantial inter-rater reliability) and 161 deviations identified shows that expertise and role played by the clinician in the trauma team influences the nature of deviations made (p<0.01). The results shows that while expert clinicians deviate to innovate, deviations of novices often result in errors. Experts' flexibility and adaptiveness allow their deviations to generate innovative ideas, in particular when dynamic adjustments are required in complex situations. The findings suggest that while adherence to protocols and standards is important for novice practitioners to reduce medical errors and ensure patient safety, there is strong need for training novices in coping with complex situations as well.
ContributorsVankipuram, Mithra (Author) / Greenes, Robert A (Thesis advisor) / Patel, Vimla L. (Thesis advisor) / Petitti, Diana B. (Committee member) / Dinu, Valentin (Committee member) / Smith, Marshall L. (Committee member) / Arizona State University (Publisher)
Created2012
Description
What makes living systems different than non-living ones? Unfortunately this question is impossible to answer, at least currently. Instead, we must face computationally tangible questions based on our current understanding of physics, computation, information, and biology. Yet we have few insights into how living systems might quantifiably differ from their non-living counterparts, as in a mathematical foundation to explain away our observations of biological evolution, emergence, innovation, and organization. The development of a theory of living systems, if at all possible, demands a mathematical understanding of how data generated by complex biological systems changes over time. In addition, this theory ought to be broad enough as to not be constrained to an Earth-based biochemistry. In this dissertation, the philosophy of studying living systems from the perspective of traditional physics is first explored as a motivating discussion for subsequent research. Traditionally, we have often thought of the physical world from a bottom-up approach: things happening on a smaller scale aggregate into things happening on a larger scale. In addition, the laws of physics are generally considered static over time. Research suggests that biological evolution may follow dynamic laws that (at least in part) change as a function of the state of the system. Of the three featured research projects, cellular automata (CA) are used as a model to study certain aspects of living systems in two of them. These aspects include self-reference, open-ended evolution, local physical universality, subjectivity, and information processing. Open-ended evolution and local physical universality are attributed to the vast amount of innovation observed throughout biological evolution. Biological systems may distinguish themselves in terms of information processing and storage, not outside the theory of computation. The final research project concretely explores real-world phenomenon by means of mapping dominance hierarchies in the evolution of video game strategies. Though the main question of how life differs from non-life remains unanswered, the mechanisms behind open-ended evolution and physical universality are revealed.
ContributorsAdams, Alyssa M (Author) / Walker, Sara I (Thesis advisor) / Davies, Paul CW (Committee member) / Pavlic, Theodore P (Committee member) / Chamberlin, Ralph V (Committee member) / Arizona State University (Publisher)
Created2017
Description
The origin of Life on Earth is the greatest unsolved mystery in the history of science. In spite of progress in almost every scientific endeavor, we still have no clear theory, model, or framework to understand the processes that led to the emergence of life on Earth. Understanding such a processes would provide key insights into astrobiology, planetary science, geochemistry, evolutionary biology, physics, and philosophy. To date, most research on the origin of life has focused on characterizing and synthesizing the molecular building blocks of living systems. This bottom-up approach assumes that living systems are characterized by their component parts, however many of the essential features of life are system level properties which only manifest in the collective behavior of many components. In order to make progress towards solving the origin of life new modeling techniques are needed. In this dissertation I review historical approaches to modeling the origin of life. I proceed to elaborate on new approaches to understanding biology that are derived from statistical physics and prioritize the collective properties of living systems rather than the component parts. In order to study these collective properties of living systems, I develop computational models of chemical systems. Using these computational models I characterize several system level processes which have important implications for understanding the origin of life on Earth. First, I investigate a model of molecular replicators and demonstrate the existence of a phase transition which occurs dynamically in replicating systems. I characterize the properties of the phase transition and argue that living systems can be understood as a non-equilibrium state of matter with unique dynamical properties. Then I develop a model of molecular assembly based on a ribonucleic acid (RNA) system, which has been characterized in laboratory experiments. Using this model I demonstrate how the energetic properties of hydrogen bonding dictate the population level dynamics of that RNA system. Finally I return to a model of replication in which replicators are strongly coupled to their environment. I demonstrate that this dynamic coupling results in qualitatively different evolutionary dynamics than those expected in static environments. A key difference is that when environmental coupling is included, evolutionary processes do not select a single replicating species but rather a dynamically stable community which consists of many species. Finally, I conclude with a discussion of how these computational models can inform future research on the origins of life.
ContributorsMathis, Cole (Nicholas) (Author) / Walker, Sara I (Thesis advisor) / Davies, Paul CW (Committee member) / Chamberlin, Ralph V (Committee member) / Lachmann, Michael (Committee member) / Arizona State University (Publisher)
Created2018
Description
This work challenges the conventional perceptions surrounding the utility and use of the CMS Open Payments data. I suggest unconsidered methodologies for extracting meaningful information from these data following an exploratory analysis of the 2014 research dataset that, in turn, enhance its value as a public good. This dataset is favored for analysis over the general payments dataset as it is believed that generating transparency in the pharmaceutical and medical device R&D process would be of the greatest benefit to public health. The research dataset has been largely ignored by analysts and this may be one of the few works that have accomplished a comprehensive exploratory analysis of these data. If we are to extract valuable information from this dataset, we must alter both our approach as well as focus our attention towards re-conceptualizing the questions that we ask. Adopting the theoretical framework of complex systems serves as the foundation for our interpretation of the research dataset. This framework, in conjunction with a methodological toolkit for network analysis, may set a precedent for the development of alternative perspectives that allow for novel interpretations of the information that big data attempts to convey. By thus proposing a novel perspective in interpreting the information that this dataset contains, it is possible to gain insight into the emergent dynamics of the collaborative relationships that are established during the pharmaceutical and medical device R&D process.
ContributorsVelez-Cruz, Nayely Luz (Author) / Laubichler, Manfred (Thesis director) / Van Der Leeuw, Sander (Committee member) / School of Sustainability (Contributor) / Sanford School of Social and Family Dynamics (Contributor) / School of Human Evolution and Social Change (Contributor) / School of Historical, Philosophical and Religious Studies (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Liminal Space is a pen-and-paper roleplaying game designed to facilitate performative, personalized, and critical exploration of identity, value and truth dissensus; contemporary social, technological, political, and environmental issues; and modes of relating to socio-technical change, instability, and uncertainty. Pen-and-paper roleplaying games emerge from a 40-year history as an entertainment medium, but in recent decades have displayed the ability to personally speak to more "serious" issues. Mechanically, they combine elements of classroom or public-engagement, pedagogic, roleplaying exercises with benefits or participatory scenario construction, allowing players to immerse themselves in bespoke situations reflecting their personal interests, anxieties, and pedagogic aims and to reflexively and critically engage with contested truths or social disruptions in a safe space. Formal studies of roleplaying games are sparse, and I, the author, hope that Liminal Space can draw more study to a unique communication, entertainments, and performance medium and to the unique communities that surround it.
ContributorsNelson, John Paul (Author) / Bennett, Michael (Thesis director) / Keeler, Lauren (Committee member) / School for the Future of Innovation in Society (Contributor) / School of Historical, Philosophical and Religious Studies (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The majority of trust research has focused on the benefits trust can have for individual actors, institutions, and organizations. This “optimistic bias” is particularly evident in work focused on institutional trust, where concepts such as procedural justice, shared values, and moral responsibility have gained prominence. But trust in institutions may not be exclusively good. We reveal implications for the “dark side” of institutional trust by reviewing relevant theories and empirical research that can contribute to a more holistic understanding. We frame our discussion by suggesting there may be a “Goldilocks principle” of institutional trust, where trust that is too low (typically the focus) or too high (not usually considered by trust researchers) may be problematic. The chapter focuses on the issue of too-high trust and processes through which such too-high trust might emerge. Specifically, excessive trust might result from external, internal, and intersecting external-internal processes. External processes refer to the actions institutions take that affect public trust, while internal processes refer to intrapersonal factors affecting a trustor’s level of trust. We describe how the beneficial psychological and behavioral outcomes of trust can be mitigated or circumvented through these processes and highlight the implications of a “darkest” side of trust when they intersect. We draw upon research on organizations and legal, governmental, and political systems to demonstrate the dark side of trust in different contexts. The conclusion outlines directions for future research and encourages researchers to consider the ethical nuances of studying how to increase institutional trust.
ContributorsNeal, Tess M.S. (Author) / Shockley, Ellie (Author) / Schilke, Oliver (Author)
Created2016
Description
Integrating agent-based models (ABMs) has been a popular approach for teaching emergent science concepts. However, students continue to find it difficult to explain the emergent process of natural selection. This study adopted an ontological framework–the Pattern, Agents, Interactions, Relations, and Causality (PAIR-C)–to guide the design of learning modules. This pre-posttest experimental study examines the effects of the PAIR-C module versus the Regular module on fostering students’ deep understanding of natural selection. Results show that students in the PAIR-C intervention group performed better in answering deep questions assessing the understanding of inter-level causal relationships than those in the Regular control group. Although students in both groups did not show significantly improved abilities in explaining the natural selection process for other contexts or significant differences in their abilities to explain other emergent phenomena, students in the intervention group demonstrated system-thinking perspectives and fewer misconceptions in their expressions compared to the control group. A close analysis of student misconceptions consolidates that the intervention group demonstrated drastically fewer categories and numbers of misconceptions while those in the control group did not show such drastic changes before and after the study. To precisely address misconceptions and further improve students’ learning outcomes, Epistemic Network Analysis was adopted to capture students’ misconception characteristics by examining the co-occurrences of different misconception categories as well as the relationship between misconceptions and PAIR-C features. The results of student learning outcomes and misconception characteristics collectively provide directions for improving the instructional design of the PAIR-C module. Furthermore, findings on student engagement levels during learning can also inform future design efforts. Overall, this project sheds light on applying an innovative framework to designing effective learning modules to teach emergent science concepts.
ContributorsSu, Man (Author) / Chi, Michelene (Thesis advisor) / Nelson, Brian (Committee member) / Zheng, Yi (Committee member) / Arizona State University (Publisher)
Created2023
Description
The origin of life remains unknowable to current science. Scientists cannot see into the origin of life on Earth, and until humanity discovers life elsewhere in the universe and begin to compare this alien life to Earth, it is likely to be undiscoverable. However, alien life may be so different from life as it is currently known that it may not be recognizable when it is found. Therefore, astrobiology needs a universal theory for life to avoid detection methods being biased towards Earth-based life. This also extends to the instrumentation sent into space, which should be built to detect universal properties of life. Assembly theory, a novel measure of complexity and arguably the only testable agnostic biosignature in current science, is used here to provide precision requirements for mass spectrometry instrumentation on future spaceflight missions with the goal of finding life elsewhere. Universal properties are not only applicable to the origins of life, but also to technologically advanced societies. Predictable patterns are found in today’s industrially based society, such as energy usage as a function of population density. These patterns may serve as the basis for technosignatures that are evidence of advanced extraterrestrial civilizations. Patters found in patent chemistry are explored, as well as predictions of chemical complexity based on assembly theory, to determine how complex chemistry is built by human society and which statistical patterns may be found in extraterrestrial civilizations. Moving beyond astrobiology, science cannot be done in a vacuum but must be communicated and taught to others. Topics such as a universal definition of life, biosignatures, and increasing complexity mean nothing without interest and engagement from others, particularly students. To this end, transformative pedagogical tools are used, particularly sociotransformative constructivism (sTc), to build and teach an Earth Science and Astrobiology curriculum to a classroom of high school incarcerated students. The impact of this class on their science learning and how they personally identify as scientists is studied.
ContributorsMalloy, John (Author) / Walker, Sara (Thesis advisor) / Reano, Darryl (Committee member) / Hartnett, Hilairy (Committee member) / Trembath-Reichert, Elizabeth (Committee member) / Cronin, Leroy (Committee member) / Arizona State University (Publisher)
Created2023
Description
Recent findings in human interactions with complex objects, objects with unpredictable interaction dynamics, revealed predictability as an important factor when determining effective control strategies. The current study extended these findings by examining the role of predictability in the selection of control strategies in two scenarios: during initial interactions with a novel, complex object, and when intentional constraints are imposed. In Experiment 1, methods with which people can identify and improve their control strategy during initial interactions with a complex object were examined. Participants actively restricted their movements at first to simplify the object’s complex behavior, then gradually adjusted movements to improve the system’s predictability. In Experiment 2, predictability of participants’ control strategies was monitored when the intention to act was changed to prioritize speed over stability. Even when incentivized to seek alternative strategies, people still prioritized predictability, and would compensate for the loss of predictability. These experiments furthered understanding of the motor control processes as a whole and may reveal important implications when generalized to other domains that also interact with complex systems.
ContributorsNguyen, Tri Duc (Author) / Amazeen, Eric (Thesis advisor) / Glenberg, Arthur (Committee member) / Amazeen, Polemnia G (Committee member) / Brewer, Gene (Committee member) / Arizona State University (Publisher)
Created2022