Chemistry 597: A Joint Research Course for Science, Engineering, and Philosophy of Science Graduate Students: Addressing Ethics in the Natural Course of Research
Monday 1:50pm – 4:30 pm (Actually, arrive early for a class from 2-5pm)
Stuart Building, Room 212
IIT Main Campus
Dr. Vivian Weil
Office: Hermann Hall Room 204
Faculty: Jordi Cat, Indiana University, Nick Huggett, UIC, Eric Brey, IIT, Sandra Bishnoi, IIT by teleconference from Houston Texas, and Vivian Weil, IIT.
Graduate students acquire a view of science, engineering, and philosophy of science that makes the social and normative aspects of each essential and valuable as part of their understanding of their own respective disciplines and of research opportunities across disciplines..
Keywords: MULTIDISCIPLINARY, UNITY, DIVERSITY, DOMAINS, BOUNDARIES, LEVELS, COOPERATION, INTEGRATION, HYBRID, FUNDAMENTAL LEVEL, REDUCTIVE APPROACH
Description: One world and many disciplines: A philosophical and historical accident. The glory and misery of isolated disciplines: the myth, self-sustainability. Why unify scientific practices, and how? Is successful cooperation possible, even actual, without giving up autonomy? What are the hurdles? How surmount them to get the benefits of a different perspective? Critical distances, unique opportunities and enduring integrations: pure vs. hybrid products and processes. Science vs. philosophy?
Cat, Jordi., “The Unity of Science.” Stanford Encyclopedia of Philosophy. 18 Jun, 2010. http://plato.stanford.edu/entries/scientific-unity/ (Required, online).
Gorman , Michael E., “Levels of Expertise and Trading Zones: A Framework for Multidisciplinary Collaboration.” Social Studies of Science, 32 (2002), 933-938. (Required, Galvin Electronic Reserves) Galison, Peter, “Laboratory War: Radar Philosophy and the Los Alamos Man.” Image and Logic. The University of Chicago Press, 1997. 239-312. (Required, Galvin Electronic Reserves)
Longino, Helen E., “Science and the Common Good: Thoughts on Philip Kitcher’s Science, Truth, and Democracy.” Philosophy of Science, Vol. 69, No. 4 (Dec. 2002): 560-568. (Required, Galvin Electronic Reserves)
Keywords: SCIENTIFIC VALUES, METHODOLOGICAL VALUES, COGNITIVE VALUES, AESTHETIC VALUES, RESEARCH GOALS, STYLES, PROGRAMS AND TRADITIONS, STANDARDS, RULES, CONVENTIONS, PREDICTIVE POWER, EXPLANATORY VALUE, HEURISTIC VALUE, EVALUATION, OBJECTIVITY, RATIONALITY, NEUTRALITY, AUTHORITY
Description: Science is valuable because it is constructed with valuable tools and ingredients and practiced with values. What makes a scientific product or process, an idea, technique or communication, intelligible, relevant, promising, unbiased, acceptable or successful? Scientific practices are distinguished by a diversity of goals and values adopted by individuals and groups. Values make groups. Rationality and objectivity are social values in science. Values are means of both differentiation and cooperation between individuals and between groups.
Brown, John K., “Design Plans, Working Drawings, National Styles: Engineering Practice in Great Britain and the United States, 1775-1945.” Technology and Culture 41.2 (2000): 195-238. (Required, Galvin Electronic Reserves)
Gooday, Graeme, “Moralizing Measurement: (Dis)Trust In People, Instruments, and Techniques.” The Morals of Measurement, Cambridge University Press, 2004. 1-39. (Required, Galvin Electronic Reserves)
Quinn T. and Kovalevsky J., “The Development of Modern Metrology and its Role Today.” Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences 363.1834 (Sep 2005): 2307-2327. (Required, Galvin Electronic Reserves)
Ferguson, Eugene S., “The Nature of Engineering Design” and “The Mind’s Eye.” Engineering and the Mind's Eye, The MIT Press, 1994. 1-59. (Optional, Galvin Electronic Reserves)
Gooday, Graeme, “Meanings of Measurement and Accounts of Accuracy.” The Morals of Measurement, Cambridge University Press, 2004. 40-81. (Optional, Galvin Electronic Reserves)
Larkin, J. & Simon, H., “Why a diagram is (sometimes) worth ten thousand words.” Cognitive Science 11 (1987): 65-99. (Optional, Galvin Electronic Reserves)
Longino, Helen E., “Evidence and Hypothesis.” Science as Social Knowledge: Values and Objectivity in Scientific Inquiry. Princeton, NJ: Princeton University Press, 1990. 38-61. (Optional, Galvin Electronic Reserves)
O’Connell, Joseph, “Metrology: The Creation of Universality by the Circulation of Particulars.” Social Studies of Science, Vol. 23, No. 1 (1993): 129-173. (Optional, Galvin Electronic Reserves)
Keywords: SOCIAL VALUES, SCIENTIFIC COMMUNITIES, SCIENTIFIC SOCIETIES, SCIENCE IN SOCIETY, INDIVIDUAL ETHICS AND PROFESSIONAL ETHICS, SOCIAL BIASES AND SOCIAL RESOURCES, CONFLICTS OF INTEREST, SCIENCE AND IDEOLOGY, SCIENCE AND RELIGION, SCIENCE AND THE MARKET, SCIENCE AND REWARDS
Description: Science is not practiced by isolated individuals: the myth of self-sustainability of individual knowledge and of science without society. Scientific communities incorporate social values, for better or worse. Science and the larger society can shape and benefit each other.
Davis, Michael, Thinking Like an Engineer, Center for the Study of Ethics in the Professions at IIT, 18 Jun, 2010, http://ethics.iit.edu/publication/md_te.html. (Required, online)
Longino, Helen E., “Evidence and Hypothesis.” Science as Social Knowledge: Values and Objectivity in Scientific Inquiry. Princeton, NJ: Princeton University Press, 1990. 38-61. (Required, Galvin Electronic Reserves)
Weil, Vivian, “Is Engineering Ethics Just Business Ethics?” Engineering Ethics. Ed. Michael Davis. Ashgate Publishing, 2005. (Required, Galvin Electronic Reserves)
Weil, V. and Arzbaecher, R., “Ethics and Relationships in Laboratories and Research Communities.” Professional Ethics. 1995 Spring-Summer; 4(3-4): 83-125. (Required, Galvin Electronic Reserves)
Davis, Michael and Andrew Stark. Conflicts of Interest in the Professions. New York: Oxford University Press, 2001. (Optional, Galvin Circulation Reserves, CSEP BJ1725.C662001)
Keywords: DATA, PHENOMENA, INSTRUMENTS, EXPERIMENTS, TECHNOLOGY, LABORATORY, CONTROLS, SHIELDING, MECHANICAL OBJECTIVITY, INTERPRETATION, TACIT KNOWLEDGE, EMBODIED SKILLS, CALIBRATION, STANDARDIZATION, REPLICATION, VISUAL VS. STATISTICAL EVIDENCE, NATURAL VS. ARTIFICIAL
Description: Experiments differ interestingly from observations or measurements. What possibilities and challenges do they offer? What is the role of technology? Why do we trust instruments? What are the limitations of our technology/instrument? What is the difference between testing theories and testing technology? And the difference between knowing the world and constructing the world? What is the role of experimenters? Experimental settings and results are highly localized artificial systems and events; yet we expect results to be replicated in other settings, and to be relevant, even more broadly, to non-experimental environments.
Bogen, James and Woodward, James, “Saving the Phenomena.” The Philosophical Review, Vol. 97, No. 3 (Jul., 1988): 303-352. (Required, Galvin Electronic Reserves)
Chalmers, Alan, “The Theory-Dependence of the Use of Instruments in Science.” Philosophy of Science, Vol. 70, No. 3 (Jul., 2003), pp. 493-509. (Required, Galvin Electronic Reserves)
Radder, Hans, “Experimental Reproducibility and Experimenter’s Regress.” PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association, Vol. 1992, Volume One: Contributed Papers (1992), pp. 63-73. (Required, Galvin Electronic Reserves)
Rasmussen, Nicolas, “Introduction: Scientific Knowledge and Its Means of Production.” Picture Control: The Electron microscope and the Transformation of Biology in America, 1940-1960, Stanford University Press, 1999. 1-27. (Required, Galvin Electronic Reserves)
Longino, Helen, “Biological effects of Low Level Radiation: Values, Dose-Response Models, Risk Estimates”, Synthese, Vol. 81, No. 3, Applied Science (Dec., 1989), pp. 391-404. (Required, Galvin Electronic Reserves)
Keywords: MODELS, MODELS OF THEORIES, MODELS OF DATA, THEORIES, REPRESENTATIONS, IDEALIZATIONS, ABSTRACTIONS, APPROXIMATIONS, FICTIONS, SIMULATIONS
Description: Modeling is central to representing, exploring and engineering the world. Glory and misery of modeling as building idealized and abstract pictures: the myth of the whole truth and nothing but the truth. Our knowledge of the world is made up of models that are inexact and incomplete representations. What do they represent? What else can they do? How can inexactness and incompleteness be their strengths? How are they built? What are their strengths? What are the limits of their application? Models and experiments share key characteristics that enable one to test the other.
Cartwright, Nancy, “The Truth Doesn’t Explain Much.” American Philosophical Quarterly, Vol. 17, No. 2 (Apr., 1980), pp. 159-163. (Required, Galvin Electronic Reserves)
Giere, R. Chapter 5, Science without Laws. Chicago, IL: University of Chicago Press. 1999. 84-96. (Required, Galvin Electronic Reserves)
Morgan, Mary S., and Morrison, Margaret, “Models as Mediating Instruments.” Models as Mediators: Perspectives on Natural and Social Science, Cambridge, England: Cambridge University Press. 1999. 10-37. (Required, Galvin Electronic Reserves)
Wimsatt, William C., “False Models as Means to Truer Theories.” Re-Engineering Philosophy for Limited Beings: Piecewise Approximations to Reality. Harvard University Press, 2007. 94-132. (Required, Galvin Electronic Reserves)
Winsberg, Eric, “Simulated Experiments: Methodology for a Virtual World.” Philosophy of Science 70, 2003, 105-125. (Required, Galvin Electronic Reserves)
Jones, Martin R., “Idealization and Abstraction: A Framework.” Poznan Studies in the Philosophy of the Sciences and the Humanities, Idealization XII: Correcting the Model. Edited by Martin R. Jones and Nancy Cartwright, pp. 173-218(46). (Optional, Galvin Electronic Reserves)
Class 6 – 10/17 Causal Modeling and Mechanisms
Keywords: CAUSE, EFFECT, CAUSAL MODELS, CAUSAL MECHANISMS, CAUSAL EXPLANATIONS, CAUSAL KNOWLEDGE
Description: Causal information is the key to knowing and engineering the world, and to making effective decisions in it. But what is causal information? How do we learn what causation is? Is that science? How is causal knowledge useful? Causal constraints on the scope of validity of laws and models and the success of experiments and constructions.
Cartwright, Nancy, “Causal Laws and Effective Strategies”, Noûs, Vol. 13, No. 4, Special Issue on Counterfactuals and Laws (Nov., 1979), pp. 419-437. (Required, Galvin Electronic Reserves)
Craver, Carl F., “When Mechanistic Models Explain.” Synthese 153 (2006): 355-376. (Required, Galvin Electronic Reserves)
Glennan, Stuart S. "Mechanisms and the Nature of Causation." Erkenntnis: An International Journal of Analytic Philosophy 44:1 (January 1996) 49-71. (Required, Galvin Electronic Reserves)
Cartwright, Nancy, The Dappled World: A Study of the Boundaries of Science. New York: Cambridge University Press. 1999. (Optional, Galvin Circulation Reserves, CSEP Q175.C371999)
Keywords: THEORY CHOICE, EVIDENCE, DEGREES OF BELIEF, RELIABILITY, ERROR, PREFERENCE, BIAS, NEUTRALITY, OBJECTIVITY,
Description: Philosophers, historians, sociologists, psychologists of science as well as scientists and engineers have been concerned with evidence for scientific claims for centuries. What data and hypotheses are to be accepted? What's the difference between reliable evidence and bias? The scholarly and public debates have pointed to the crucial role of different criteria, standards, values within science and society more broadly. Different research communities often bring different values and standards of evidence.
Longino, Helen, ch 6, Science as Social Knowledge 1990, pp. 103-132. (Required, Galvin Electronic Reserves)
Sober, Elliott, “Evidence and Value Freedom”, in H. Kincaid, J. Dupre, A. Wylie, eds., Value-Free Science? Ideals and Illusions, New York: Oxford University Press. 2007, 109-119. (Required, Galvin Electronic Reserves)
Douglas, Heather, “Rejection the Idea of Value-Free Science”, in Kincaid, Dupre, and Wylie 2007, pp. 120-139. (Required, Galvin Electronic Reserves)
Mayo, Deborah G., “Experimental Practice and an Error statistical Account of Evidence.” Philosophy of Science, Vol. 67, Supplement. Proceedings of the 1998 Biennial Meetings of the Philosophy of Science Association. Part II: Symposia Papers (Sep., 2000), pp. S193-S207. (Required, Galvin Electronic Reserves)
Classes 8 through 11 (10/31, 11/7, 11/14, 11/21) deal with issues that arise specific to students’ ongoing research. No advance assigned readings; any readings to be assigned will relate to specific issues arising in the research.
Classes 12 through 13 features presentation of research reports and critiquing of reports and suggestions for turning them into publishable papers.
Class 14 (12/12) features presentation of completed, edited reports and discussion of prospects for publication. Wrap-up by instructors and students.