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"Lissack, Michael"
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From LLMs to ethical research: beyond technological enframing
This paper develops a philosophical framework for understanding Large Language Model (LLM) integration in social science and professional research through the lens of ethical responsibility and existential engagement. We argue that contemporary research practice has fallen into what Heidegger identifies as technological “enframing,” where efficiency metrics override genuine inquiry into human experience. Drawing on Heidegger’s analysis of technological breakdown, Levinas’s ethics of responsibility to the Other, and Juarrero’s theory of enabling constraints, we examine how LLM-based tools make use of what we call “Requisite Experienced Cogency” (REC) for functioning as computational tools, but fundamentally lack the experiential cogency needed for understanding human awareness or producing substantive meaningful insights. Through an extended case study of healthcare research conducted by Thomas, a researcher with personal health challenges, we demonstrate how technological limitations can become enabling constraints when researchers maintain existential engagement with their subject matter while acknowledging what LLM-based tools cannot provide: theoretical depth, ethical sensitivity, and genuine understanding of human complexity. We engage critically with the substantial literature on LLM limitations while arguing that appropriate integration within clear boundaries can serve rather than undermine authentic inquiry.
Journal Article
Coherence in the midst of complexity : advances in social complexity theory
\"Complexity and emergence (the appearance and impact of the new) can be the bane of managers and their organizations. Both complexity and emergence threaten to upset adherence to predefined categories, which supposedly allows for efficiency. Indeed, traditional management thinking focuses on a retrospective coherence where ideas and events are assigned to categories, the categories are labeled, and outliers are treated as statistical deviants. The study of how such attributed (retrospective) sense-making breaks down in and around organizations is the focus of social complexity theory. Coherence in the Midst of Complexity discusses the social complexity approach, where dialogue and stories allow for the degrees of freedom needed for the opportunities of emergence to take root. The book focuses on the experience of coherence and how such experiential lessons differ from the establishment and maintenance of categories and labels. The authors offer a four-fold logic for discussing experiential coherence and the embrace of emergence in organizations of all sizes\"-- Provided by publisher.
Book
Second Order Science: Examining Hidden Presuppositions in the Practice of Science
The traditional sciences have always had trouble with ambiguity. To overcome this barrier, ‘science’ has imposed “enabling constraints”—hidden assumptions which are given the status of ceteris paribus. Such assumptions allow ambiguity to be bracketed away at the expense of transparency. These enabling constraints take the form of uncritically examined presuppositions, which we refer to throughout the article as “uceps.” The meanings of the various uceps are shown via their applicability to the science of climate change. Second order science examines variations in values assumed for these uceps and looks at the resulting impacts on related scientific claims. Second order science reveals hidden issues, problems and assumptions which all too often escape the attention of the practicing scientist (but which can also get in the way of the acceptance of a scientific claim). This article lays out initial foundations for second order science, its ontology, methodology, and implications.
Journal Article
Sloppy science, shortcuts, and COVID-19
Professor Michael Lissack, from the College of Design and Innovation at Tongji University in China, and Brenden Meagher from nonprofit Jhpiego study this worrying trend. The researchers explain the concept of slodderwetenschap and advise how good research design and rigorous interrogation can work together to prevent sloppy science. Expert in the field, Professor Michael Lissack at the College of Design and Innovation at Tongji University, Shanghai, China, succinctly defines slodderwetenschap: 'Sloppy science involves presenting ideas as conclusive facts without adequate scientific foundation.' The Stapel Affair was a case in the Netherlands where a prominent research psychologist, Diederik Stapel, forged fake data to produce near-perfect results for his students at Tilburg University.
Journal Article
What Second Order Science Reveals About Scientific Claims: Incommensurability, Doubt, and a Lack of Explication
The traditional sciences often bracket away ambiguity through the imposition of “enabling constraints”—making a set of assumptions and then declaring ceteris paribus. These enabling constraints take the form of uncritically examined presuppositions or “uceps.” Second order science reveals hidden issues, problems and assumptions which all too often escape the attention of the practicing scientist. These hidden values—precisely because they are hidden and not made explicit—can get in the way of the public’s acceptance of a scientific claim. A conflict in understood meaning—between the scientist’s restricted claims and the public’s broader understanding of those same claims can result in cognitive dissonance or the equivalent of the Mori Uncanny Valley. Scientists often react to these differences by claiming “incommensurability” between their restricted claim and the public’s understanding. Second order science, by explicating the effects of variations in values assumed for these uceps and associated impacts on related scientific claims, can often moot these assertions of incommensurability and thereby promote greater scientific understanding. This article explores how second order science can address issues of public doubt regarding the scientific enterprise using examples from medicine, diet and climate science.
Journal Article
Cues, Codes, Complexity, and Confusion Lessons from Complexity Regarding Productivity and Resilience
The very notion of productivity improvement involves measurement against a context. The success of computers and other quantitative approaches during the past half century has led to an ideational context wherein transmitters of information often assume that the content of their message is like code—ascertainable to the recipient by means of a look‐up table. Complexity science suggests that contexts themselves need to be continually examined lest a boundary or frame be inappropriately assumed. When, for example, efficiency improvements are the result of externality creation, a loss of resilience is often the price and a shift in frame would reveal the“improvement”to be either an increase in risk or a resetting of a boundary. Improvements are not al‐ways“code”for“better,”but may, in the light of a complex systems approach, be a cue for danger ahead.
Journal Article
Of chaos and complexity: managerial insights from a new science
As interest in the study of complex systems has grown, a new vocabulary is emerging to describe discoveries about wide-ranging and fundamental phenomena. A shared language based on the vocabulary of complexity can have an important role in a management context. Complexity metaphors - fitness landscapes, simulated annealing, local mxima, patches, generative relationships, increasing returns - when accepted within the vocabulary of an organization, can change both the way managers manage and the problems they choose to manage. Several case studies illustrating the role of complexity metaphors are presented.
Journal Article