Lecture slides available here (to be updated weekly)
Part I — Classical Positions
Week 1 (21 Feb): Introduction
- Information on program, credit point requirements and reading groups
- Defining scientific prediction
- Basic concepts
In-session reading:
- Barrett, Jeff, and Kyle P. Stanford. 2005. “Prediction.” In The Philosophy of Science: An Encyclopedia, edited by Jessica Pfeifer and Sahotra Sarkar. New York: Routledge.
Task: Read the following article by Jonathan Haidt entitled See how your preferences in dogs, Internet browsers, and 10 other items predict your partisan leanings and take the quiz if you want to. Explain the sense in which the word “predict” is used in the title of Haidt’s article. What does it mean that specific preferences can “predict” political ideology?
Week 2 (28 Feb): Hume and the problem of induction
Preparatory reading:
- Ladyman, James. 2002. Understanding Philosophy of Science. Abingdon; New York: Routledge. Chapter 2: The Problem of Induction and Other Problems With Inductivism.
- Hume, David. 1999. An Enquiry Concerning Human Understanding (1748). Edited by Tom L. Beauchamp. Oxford: Oxford University Press. Section IV: Sceptical Doubts Concerning the Operations of the Understanding.
Complimentary reading:
- Hume, David. 2000. A Treatise of Human Nature (1739), edited by David Fate Norton and Mary J Norton. Oxford: Oxford University Press. Book I, Part 3, Sect. 1-6.
- Goodman, Nelson. 1983. Fact, Fiction, and Forecast (1954). Cambridge MA); London: Harvard University Press. Chapter III. The New Riddle of Induction.
Task: Many general statements are supported by their instances. For example, the fact that a given piece of copper conducts electricity supports the general statement that all pieces of copper conduct electricity. But this does not hold for all general statements. The fact that a given male in a room is a third son does not support the general statement that all males in that room a third sons. What do you think is the difference between these two general statements – “All pieces of copper conduct electricity” and “All males in this room are third sons” – and why is the former supported by its instances while the latter is not? (The example is taken from Nelson Goodman’s Fact, Fiction, and Forecast, 1954).
Week 3 (07 Mar): The relationship between prediction & explanation
Preparatory reading:
- Hempel, Carl G, and Paul Oppenheim. 1948. “Studies in the Logic of Explanation.” Philosophy of Science 15 (2).
- Scriven, Michael. 1959. “Explanation and Prediction in Evolutionary Theory.” Science 130 (3374): 477–82.
Complimentary reading:
- Cleland, Carol E. 2011. “Prediction and Explanation in Historical Natural Science.” British Journal for the Philosophy of Science 62 (3): 551–82.
Task: Read the famous last paragraph of Charles Darwin’s On the Origin of Species (1859; you are reading the version of the second edition from 1860). In that paragraph, Darwin gives a summary of his theory. What are the laws of Darwin’s theory of evolution? If there is anything else that you find remarkable about Darwin’s style or anything that is mentioned in the paragraph, briefly comment on that too.
Week 4 (14 Mar): The (un)predictability of history: Karl Popper’s “The Poverty of Historicism”
Preparatory reading:
- Popper, Karl R. 1961. The Poverty of Historicism. 3rd ed. London: Routledge & Kegan Paul. Introduction & Chapter 1: The Anti-Naturalistic Doctrines of Historicism.
Complementary reading:
- Popper, Karl R. 1961. The Poverty of Historicism. 3rd ed. London: Routledge & Kegan Paul. Chapter 2: The Pro-Naturalistic Doctrines of Historicism.
- Popper, Karl R. 1961. The Poverty of Historicism. 3rd ed. London: Routledge & Kegan Paul. Chapter 3: Criticism of the Anti-Naturalistic Doctrines
- Ladyman, James. 2002. Understanding Philosophy of Science. Abingdon; New York: Routledge. Chapter 3: Falsificationsism.
Task: Watch this interview with Popper, in which he describes Arthur Eddington’s and Frank Watson Dyson’s experiment that tested Einstein’s prediction that a light beam passing the sun will be deflected. Use the example to explain the difference between successful and failed experimental tests according to Popper. In other words: According to Popper, what follows from a successfully tested prediction, and what follows if the test fails?
Week 5 (21 Mar): Prediction in Economics: Friedman’s “Methodology of Positive Economics”
Preparatory reading:
- Friedman, Milton. 1953. “The Methodology of Positive Economics.” In Essays in Positive Economics:3–43. Chicago: University of Chicago Press.
Complementary reading:
- Paul Krugman. 2007. Who Was Milton Friedman? The New York Review of Books, 2007.
- Mäki, Uskali. 2003. “The Methodology of Positive Economics’ (1953) Does Not Give Us the Methodology of Positive Economics.” Journal of Economic Methodology 10 (4): 495–505.
Task: Produce a one to two page handout that summarizes Friedman 1953. You are free to structure the handout as you see fit. It does not have to be in continuous text, keywords are fine. Nevermind the 500 word limit either. Make sure that you capture the important concepts as well as the central idea(s) and arguments of the paper.
Week 6 (28 Mar): Wrap-up Session of Part I
Preparatory reading:
- none. (You are welcome to re-read Friedman 1953.)
Task: Read this article on ecnmy.org by Cambridge economist Ha-Joon Chang. In it, Chang makes the following statement:
“Many economists believe themselves, and tell other people, that economics is a ‘value-free’ science, like physics or chemistry. However, my book emphasises that economics is a fundamentally political and moral subject. Whereas the particles and compounds studied by scientists do not hold political and moral views, human beings who populate the economy do, and so we cannot fully understand the economy without understanding politics and ethics.
More to the point, even the boundary of the economy – and thus the scope of economics – is determined by ethical and political judgments. Think of child labour, which used to be a perfectly legitimate object of market transaction until the early 20th century, even in the richest countries. This means that the market itself is a political construct, rather than a natural order that should not be tampered with by ‘political’ intervention. Once we realise this, we begin to see how no economic argument can be free from politics.”
Semester Break
Part II — Book Discussions
(for details go to Instructions for reading groups)
Week 7 (18 Apr): Taleb, The Black Swan
Preparatory reading:
- Taleb, Nassim Nicholas. 2007. The Black Swan: The Impact of the Highly Improbable. New York, N.Y.: Random House. Chapter 6: The Narrative Fallacy.
Complimentary reading:
- Bschir, Karim (forthcoming). Prediction: A View from Philosophy. Chapter 4: The Limits of Predictability. (unpublished draft; please do not copy or disseminate).
- Lund, Robert. 2007. “Revenge of the White Swan.” American Statistician 61 (3): 189–92.
Task: In chapter 6 of The Black Swan, Taleb introduces what he calles “the narrative fallacy”. What is the narrative fallacy and what are, according to the author, the epistemic implications of the fallacy with regards to prediction?
Week 8 (25 Apr): Silver, The Signal and the Noise
Preparatory reading:
- Silver, Nate. 2012. The Signal and the Noise: Why so Many Predictions Fail, but Some Don’t. New York: Penguin Press. Chapter 2: Are You Smarter Than a Television Pundit?
Task: Silver introduces two types of forecasters in the Chapter 2, hedgehogs and foxes. He closes the chapter with the following statement: “In short, you will need to learn how to think like a fox. The foxy forecaster recognizes the limitations that human judgement imposes in predicting the world’s course.
1) What are the differences in the way hedgehogs and foxes use information and approach prediction? 2) Indicate what Silver means with the last statement with regard to forecasts in politics.
Week 9 (02 May):
Preparatory reading:
- Agrawal, Ajay, Joshua Gans, and Avi Goldfarb. 2018. Prediction Machines : The Simple Economics of Artificial Intelligence. Boston, Mass.: Harvard Business Review Press. Chapters 1, 2 & 7.
Task: One of the central premises of Prediction Machines is that developments in AI technology will make prediction cheaper and thus more readily available. The authors also claim that prediction is a central component of decision-making. But it is only one important component among others. Another important component is what the authors call judgment. Briefly describe the role of judgment in the decision-making process? Do you think that judment can also be improved by AI? Why/why not?
Week 10 (09 May): Tetlock & Gardner, Superforecasting
Preparatory reading:
- Tetlock, Philip E, and Gardner Dan. 2015. Superforecasting: The Art and Science of Prediction. New York: Crown Publishers. Chapter 3, pp. 72-96.
Complimentary reading:
- Lecture by Philip Tetlock at the American Enterprise Institute: https://www.youtube.com/watch?v=xBXDTQdmNyw.
Task: In the last part of chapter 3, Tetlock describes the “dragonfly’s eye”.
a) Shortly describe what is meant by “dragonfly’s eye” and what it has to do with the wisdom of the crowd.
b) If you want to apply the “dragonfly’s eye” optimally would you rather look for forecasts from a diverse set of forecasters (which may include superforecasters) or forecasts from a set solely composed of superforecasters?
Week 11 (16 May): Derman, Models Behaving Badly
Preparatory reading:
- Derman, Emanuel. 2011. Models. Behaving. Badly. Why Confusing Illusion with Reality Can Lead to Disaster on Wall Street and in Life. New York: Free Press. Chapter 2: Metaphors, Models, and Theories.
Task: In chapter 2, Derman explains the differences between metaphors, models and theories. In particular, he states that “models are analogies” while theories “are the real thing”. 1) How does the author distinguish between models and theories? 2) What does this imply for the validity of financial or economic theories?
Week 12 (23 May): Guest lecture by Benedikt Knuesel (ETH Zurich) “Model-based Predictions in Climate Science: Basics & Challenges”
Preparatory reading:
- Knutti, Reto. 2018. “Climate Model Confirmation: From Philosophy to Predicting Climate in the Real World.” In Climate Modelling: Philosophical and Conceptual Issues, edited by Elisabeth A. Lloyd and Eric Winsberg, 325–59. Cham: Palgrave Macmillan.
Task: In 2016, Warren Buffet wrote a letter to Berkshire Hathaway shareholders in which he claims that insurance businesses are likely to benefit from rising damages caused by the effects of climate change using an analogy of past increases in insurance loss costs. Read the following news article on Business Insider. Briefly summarize Buffet’s reasoning and discuss potential flaws in his argument. If you happen to think that the argument is flawless say why.