Abstract
A step towards theory development in the decision sciences will be taken in chapters 8-10 (Part III of the book). These closely intertwined chapters discuss challenges that the multiverse perspective (built up in chapters 2–4) might pose for that discipline. In a singular universe, a rational decision maker is supposed to choose the alternative with the highest expected utility. How could one translate this concept into the multiverse, is this straightforward, what are the required changes? Chapter 8 investigates this question for the general framework of normative decision theory as well as for the aspect of probability. Interestingly, not much has to be changed with respect to probability (partially addressed in a box), but the general framework is seriously affected by having to replace singular outcomes with vectorial outcomes. Indeed, the concept of vectorial choice, underlying the development in all remaining chapters of the book, will be introduced and discussed in this chapter. Normative decision theory will also be confronted with results from behavioral decision theory as well as the alternative framework of the effectuation principle (Sarasvathy 2001) that turns out to have some advantages for usage and further development in the multiverse.
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Notes
- 1.
Empirically, about 80% of individuals are risk averse and exhibit a concave utility function. About 20% are either risk neutral or risk taking exhibiting either a linear or a convex utility function. For an introduction into the relevant literature see Holt and Laury (2002), Harrison and Rutström (2015).
- 2.
A great introduction into normative and descriptive decision theory is to be found in Kleindorfer et al. (1993).
- 3.
Modifications of the normative benchmark applying weaker rationality assumptions within generalized utility models (e.g., Machina 1982, for the case of the independence axiom) will not be dealt with in this book.
- 4.
The ‘majority of cases’ exclude the rare, artificially constructed cases where a direct coupling of macro to quantum events (see, again, Box 8.1) is possible.
- 5.
The Oxford-School approach simply has a different purpose and does not allow for insights into actual decision making in the multiverse.
- 6.
The simplest case of a lottery is two different outcomes occurring with non-degenerate probabilities p and 1 − p; whereby a non-degenerate probability means that nothing occurs with certainty (p = 1) or not at all (p = 0).
- 7.
Multi-attribute versions of prospect theory will not be dealt with in this book.
- 8.
An overview and discussion of the different types of alternative theories and models that have been proposed in the literature are beyond the scope of this book. But it should be mentioned, here, that an approach somewhat opposed to Kahneman and Tversky’s type of reasoning has been quite successful, too, the approach by Gigerenzer and coauthors (see, e.g., Gigerenzer and Todd 1999). According to my reading, the recent book by Kahneman (2011) takes a middle position between his and Tversky’s older and Gigerenzer’s approaches. The last section of this chapter briefly touches upon Gigerenzer et al’s approach.
- 9.
I should also note that modelling both within quantum decision making and quantum social science is based on the Copenhagen-type and Born (1926) rule formalism and not on the multiverse interpretation of quantum mechanics.
- 10.
The classifications/comparisons would become far more complex if the same set of criteria were to be used for both purposes.
- 11.
It has already been mentioned that applying causation and effectuation may lead to a different decisional structure and to different decisional outcomes. However, some authors contributing to the effectuation literature would possibly argue that causation and effectuation are typically applied to different decision situations to start with. That might sometimes be correct. I am not so sure, however, whether it always makes sense to ‘allocate’ the two principles to different situations. I am also not sure whether there is such thing in practical decisions as a sole use of one or the other principle. Frankly, there might not be any decision without the (partial) application of effectuation.
- 12.
Another, somewhat casual and non-economic example for column four of Table 8.3, comparing the principles of effectuation and causation, is cooking a dinner for friends (see for this as well as the related example of “curry-in-a-hurry,” Sarasvathy 2001). A decision maker applying causation picks a meal from the cookbook, buys the ingredients at a grocer and prepares them according to the recipe. A person applying effectuation looks at what is in the fridge and in the drawers, tries to combine the possible ingredients to creative tasty dishes and cooks one of them.
- 13.
The problem is alleviated, not solved, given the fact that we do not know how smooth and thorough reallocations of consciousness are.
- 14.
Pushing it to the extreme, the market introduction of a novel, high-development-cost pharmaceutical, relevant for the global market, is probably a case where Sarasvathy and Faschingbauer would advise the usage of causation.
- 15.
Since those reallocations may or may not take place continuously (or rather from time to time) it is unclear whether overruns of the total amount of consciousness might temporarily be admitted.
- 16.
Answering this fairly complex question is beyond the scope of this book.
- 17.
I have no sound reason to suppose that EEG measurements might be the right way to go in the context analyzed here, but intuitively I felt that this is the closest to an appropriate measurement to try out that we currently possess. Although brain waves have never been quite understood, close to a study of consciousness, early results achieved with the EEG already indicated the following: “(…) [The] state of wakefulness and sleep of a normal individual (…) has been related successfully to changes in the EEG” (Simon and Emmons 1956, 1066). Moreover, depth of sleep has been related to certain patterns in EEG, and alpha waves are seen as an index of consciousness (Simon and Emmons 1956, 1066).
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Schade, C.D. (2018). General Framework, Objective Function, and Probability. In: Free Will and Consciousness in the Multiverse. Springer, Cham. https://doi.org/10.1007/978-3-030-03583-9_8
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