-------- Forwarded Message -------- Subject: [AISWorld] Forget Popper, Positivism, and Critical realism: What Every IS Scholar Should Learn from the Modern Philosophy of Science Date: Wed, 5 Oct 2022 12:42:06 +0000 From: Siponen, Mikko mikko.t.siponen@jyu.fi To: aisworld@lists.aisnet.org aisworld@lists.aisnet.org

SIG PHIL - Philosophy in IS Forget Popper, Positivism, and Critical realism: What Every IS Scholar Should Learn from the Modern Philosophy of Science Prof. Mikko Siponen D. Soc. Sc., Ph.D. Member of the Finnish Academy of Science and Letters SIG PHIL - Philosophy in IS workshop (ICIS Ancillary Meetings) Day: Sunday, December 11, 2022 Time: 9.30 – 14.30 Venue: ICIS2022, Bella Center (no online participation) You can register to this workshop through ICIS2022 registration Questions? Please email: mikko.t.siponen@jyu.fi Information systems (IS) philosophy is often understood through “-isms,” especially (logical) positivism, interpretivism, and critical realism. The modern philosophy of science is not committed to any of these “-isms.” The modern philosophy of science recognizes, for example, that virtually all theories and models idealize and that all these “-isms” were developed before idealizations were understood in the philosophy of science. Moreover, many influential theoretical accounts and concepts in IS are influenced by a received view (RV) of scientific theory that flourished in the philosophy of science around 1930–70. Modern philosophy of science has since widely rejected the RV tenets. The philosophy of science has progressed a lot in the last 30 years. Much of this development is missed in IS, and the recent developments, in many cases, reject the older views the IS community is using. It is, therefore, necessary to clear up some confusions on the fundamental philosophical concepts and introduce some updates from the modern philosophy of science. Participation in this workshop does not require a knowledge of philosophy. You will learn some basic philosophical concepts and what they mean in IS. You will also learn new modeling ideas (e.g., mechanism-based explanation and stage modeling). You also learn about the best candidates for theory in statistical and qualitative research and about the philosophical differences between laws, statistical explanations, process models, stage models, and mechanism-based explanations. Session 1: Basic philosophical concepts: common misunderstandings and the applicability of these concepts to IS Time: 9.30 – 10.30 You will learn why logical positivists (Carnap, Neurath) themselves rejected the famous ideas of logical positivism they had carefully developed earlier. You will learn why “most philosophers of science” think Popper’s philosophy of science is “fatally flawed” (Musgrave 2004, p. 19). You will learn why Popper’s (1959) falsifications do not apply in statistical and qualitative research in IS. You will learn how there is hardly ever “objective observation” and how IS research settings are generally theory-laden. You will learn what theory-ladenness is, what it means in IS, and how theory-ladenness is not the same as scientific theory. You will also learn what underdetermination is in IS and how it is different from theory-ladenness. Coffee break: 10.30 – 10.45 (coffee served) Session 2: What the IS community needs to learn from the modern views of scientific theory Time: 10.45-12.30 You learn why the standard definition of laws does not apply in IS. You learn the reasons why, for many philosophers and scientists, models are more important than theory in modern (philosophy of) science. You will learn that scientific theories/models hardly capture the truth but, in fact, typically deliberately mispresent assumed reality for strategic purposes. “All theories, even the best, make idealizations or other false assumptions that fail as correct descriptions of the world.” (Wimsatt 20007, p. 23) You will learn why idealizations (which are deliberate misrepresentations of assumed reality) are necessary in modern science (Cartwright, McMullin, Mäki, Wimsatt, etc.), and why idealizations as deliberate misrepresentations are actually a good thing. You will learn why some famous IS methods and philosophical positions cannot describe and do justice to idealizations and how they run the risk of inappropriate rejecting idealizations. You will learn how some IS models idealize and that the idealizations are not generally recognized, but they should be. Lunch break 12.30 – 13.00 (lunch served) Session 3: Mechanism-based explanations in IS Time: 13.00 – 14.00 “Mechanistic explanation has an impressive track record of advancing our understanding of complex… systems.” (Weiskopf 2011) “The philosophy of science, more generally, should be restructured around the fundamental idea that many scientists organize their work around the search for mechanisms.” (Craver & Tabery 2017) IS models are often divided into variance and process models (Rivard 2014). Mechanism models allow alternative ways of modeling to variance and process models. You will learn how the idea of mechanism-based explanations (from Salmon to what is known as “the now standard view”) has changed in response to criticism. You will learn how mechanism-based explanations are different from 1) laws, 2) statistical explanations, 3) variance models in IS, and 4) typical formulations of process models in IS. You will learn the principles of mechanism-based explanations in the modern philosophy of science (e.g., Bechtel, Craver, Darden). You will learn about the typical idealizations expected in mechanism-based models. Session 4 (if time). Either session 4A or Session 4b, based on voting. Time: 14.00 – 14.30 Session 4A: Principles of Stage Models You will learn what makes a theory a stage theory. You will learn how stage models/theories are different from 1) variance models in IS and 2) typical formulations of process models in IS. You will learn about the concept of stage as an idealization (e.g., Kohlberg, Weinstein, Schwarzer). Session 4B: Theory Development You will learn why the theory development in the so-called “scientific method” (the hypothetico-deductive method) was guessing and imagination. You will learn why a number of philosophers have vehemently denied the possibility of a stepwise method for developing theories. You will learn strategies for theory development from the modern philosophy of science. Bio Mikko Siponen is Professor of Information Systems at the University of Jyväskylä. In addition to a Ph.D. in IS, Professor Siponen has received an education in philosophy, including a doctoral degree majoring in Applied Philosophy.

Mikko Siponen D. Soc. Sc., Ph.D. Member of the Finnish Academy of Science and Letters Professor of Information Systems University of Jyväskylä Tel. +358 505588128

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