Abstract
Although widely investigated and used in psychology, the concept of randomness is beset with philosophical and practical difficulties. In this paper, I propose a resolution to a long-standing problem in psychological research by arguing that the inability to comprehend and produce random behavior is not caused by a defect on the part of the observer but is a consequence of conceptual confusion. Randomness describes a state of high complexity which defies analysis and understanding. The well-known biases in predictive behavior (e.g. hot-hand and gambler’s fallacy) are not caused by the observers’ inability to comprehend randomness but reflect a natural pattern-seeking response to high-complexity situations. Further, I address the circularity at the heart of the randomness debate. Replacing randomness with complexity in psychology and cognitive science would eliminate many of the current problems associated with defining, investigating and using this elusive term.
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Notes
Under a “single agent”, I broadly consider any agent that can be separated from the environment (e.g. steam engine, roulette, human observer etc.).
Here is von Mises’ definition of randomness requiring both infinity and equiprobability [from Eagle (2005, p. 756)]: an infinite sequence S of outcomes of types \( {\text{A}}_{1} , \ldots ,{\text{A}}_{\text{n}} , \) is vM-random iff (1) every outcome type Ai has a well-defined relative frequency \( {\text{relf}}_{\text{i}}^{\text{s}} \) in S; and (2) for every infinite subsequence S* chosen by an admissible place selection, the relative frequency of Ai remains the same as in the larger sequence: \( {\text{relf}}_{\text{i}}^{\text{s}} = {\text{relf}}_{\text{i}}^{{{\text{s}}^{*} }} . \)
Recent attempts to quantify the structure of random sequences ultimately represent a sophisticated incarnation of gambler’s fallacy (Aksentijevic 2015).
Cutting referred to invariance as “absence of change” and transformations as “ways of invoking a change” (1998, p. 79).
Similar problems can be found in other sciences but are outside the scope of this paper.
References
Adami C, Cerf NJ (2000) Physical complexity of symbolic sequences. Phys D 137:62–69
Aksentijevic A (2015a) Statistician, heal thyself: fighting statophobia at the source. Front Psychol. doi:10.3389/fpsyg.2015.01558
Aksentijevic A (2015b) No time for waiting: statistical structure reflects subjective complexity. Proc Natl Acad Sci USA 112:E3159. doi:10.1073/pnas.1507950112
Aksentijevic A, Gibson K (2012a) Complexity equals change. Cogn Syst Res 15–16:1–16
Aksentijevic A, Gibson K (2012b) Complexity and the cost of information processing. Theor Psychol 22:572–590
Alberoni F (1962) Contribution to the study of subjective probability: I. J Gen Psychol 66(2):261–264
Alter AL, Oppenheimer DM (2006) From a fixation on sports to an exploration of mechanism: the past, present and future of hot hand research. Think Reason 12(4):431–444
Attneave F (1959) Applications of information theory to psychology: a summary of basic concepts, methods, and results. Henry Holt, New York
Ayton P, Fischer J (2004) The hot hand fallacy and the gambler’s fallacy: the two faces of subjective randomness? Mem Cogn 32(8):1369–1378
Ayton P, Hunt A, Wright G (1989) Psychological conceptions of randomness. J Behav Decis Mak 2(4):221–238
Bar-Eli M, Avugos S, Raab M (2006) Twenty years of “hot hand” research: review and critique. Psychol Sport Exerc 7:525–553
Bar-Hillel M, Wagenaar W (1991) The perception of randomness. Adv Appl Math 12(4):428–454
Boynton DM (2003) Superstitious responding and frequency matching in the positive bias and gambler’s fallacy effects. Organ Behav Hum 91(2):119–127
Brown SG (1957) Probability and scientific inference. Longmans, Green, London
Burns BD (2004) Heuristics as beliefs and as behaviors: the adaptiveness of the “hot hand”. Cogn Psychol 48(3):295–331
Burns BD, Corpus B (2004) Randomness and inductions from streaks: “Gambler’s fallacy” versus “hot hand”. Psychon B Rev 11(1):179–184
Calude CS (2000) Who is afraid of randomness? Report of the Centre of Discrete Mathematics and Theoretical Computer Science, University of Auckland, New Zealand
Chaitin GJ (1969) On the length of the programs for computing finite binary sequences: statistical considerations. J Assoc Comput Mach 16:145–159
Chaitin GJ (1975) Randomness and mathematical proof. Sci Am 232(5):47–52
Chaitin GJ (2001) Exploring randomness. Springer, London
Copeland BJ (ed) (2004) The essential Turing: the ideas that gave birth to the computer age. Clarendon Press, Oxford
Coren RL (2002) Comments on “A law of information growth”. Entropy 4:32–34
Cowan N (2001) The magical number 4 in short-term memory: a reconsideration of mental storage capacity. Behav Brain Sci 24(1):87–114
Coward A (1990) Pattern thinking. Praeger, New York
Cutting JE (1998) Information from the world around us. In: Hochberg J (ed) Perception and cognition at century’s end: history, philosophy and theory. Academic Press, San Diego, pp 69–93
Dawes RM (1988) Rational choice in an uncertain world. Harcourt, Brace & Jovanovich, New York
Eagle A (2005) Randomness is unpredictability. Br J Philos Sci 56:749–790
Falk R (1991) Randomness—an ill-defined but much needed concept (commentary on “Psychological Conceptions of Randomness”). J Behav Decis Mak 4(3):215–218
Falk R (2010) The infinite challenge: levels of conceiving the endlessness of numbers. Cogn Instruct 28(1):1–38
Falk R, Konold C (1997) Making sense of randomness: implicit encoding as a basis for judgment. Psychol Rev 104(2):301–318
Feynman RP, Leighton RB, Sands M (1963) The Feynman lectures on physics. Addison-Wesley, Reading
Gardner M (1989) Mathematical carnival, chap 13—random numbers. The Mathematical Association of America, Washington, DC
Garner WR (1962) Uncertainty and structure as psychological concepts. Wiley, New York
Gell-Mann M (1994) The quark and the jaguar: adventures in the simple and the complex. Freeman, New York
Gell-Mann M (1995) What is complexity? Complexity 1(1):1–9
Gilden DL, Wilson SG (1995) On the nature of streaks in signal detection. Cogn Psychol 28(1):17–64
Gilovich T, Vallone R, Tversky A (1985) The hot hand in basketball: on the misperception of random sequences. Cogn Psychol 17:295–314
Glanzer M, Clark WH (1962) Accuracy of perceptual recall: an analysis of organization. J Verb Learn Verb Behav 1(4):289–299
Grassberger P (1986) How to measure self-generated complexity. Phys A 140(1–2):319–325
Hahn U, Warren P (2009) Perceptions of randomness: why three heads are better than four. Psychol Rev 116(2):454–461
Hammond KR, Householder JE (1962) A model of randomness. In: Hammond KR, Householder JE (eds) Introduction to the statistical method: foundations and use in the behavioral sciences. Alfred A. Knopf, New York, pp 238–286
Ichikawa S (1985) Quantitative and structural factors in the judgment of pattern complexity. Percept Psychophys 38(2):101–109
Jaditz T (2000) Are the digits of π an independent and identically distributed sequence? Am Stat 54(1):12–16
Kahneman D, Tversky A (1972) Subjective probability: a judgment of representativeness. Cogn Psychol 3(3):430–454
Keren G, Lewis C (1994) The two fallacies of gamblers: type I and type II. Organ Behav Hum 60(1):75–89
Koffka K (1935) Principles of Gestalt psychology. Lund Humphries, London
Kolmogorov AN (1965) Three approaches to the quantitative definition of information. Probl Inf Transm 1(1):1–7
Li M, Vitanyi P (1997) An introduction to Kolmogorov complexity and its applications. Springer, New York
Lopes LL (1982) Doing the impossible: a note on induction and the experience of randomness. J Exp Psychol Learn 8(6):626–636
Lordahl DS (1970) An hypothesis approach to sequential prediction of binary events. J Math Psychol 7(2):339–361
MacKay D (1950) Quantal aspects of scientific information. Philos Mag 41:289–311
Matthews WJ (2013) Relatively random: context effects on perceived randomness and predicted outcomes. J Exp Psychol Learn 39(5):1642–1648
Miller GA (1956) The magical number seven, plus or minus two: some limits on our capacity for processing information. Psychol Rev 63(2):81–97
Nickerson R (2002) The production and perception of randomness. Psychol Rev 109(2):330–357
Noether G (1987) Mental random numbers: perceived and real randomness. Teach Stat 9:68–70
Oskarsson AT, Van Boven L, McClelland G, Hastie R (2009) What’s next? Judging sequences of binary events. Psychol Bull 135(2):262–285
Péter R (1957/1976) Playing with infinity: mathematical explorations and excursions. Dover, London
Rapoport A, Budescu DV (1997) Randomization in individual choice behavior. Psychol Rev 104(3):603–617
Roney CJR, Trick LM (2003) Grouping and gambling: a Gestalt approach to gambler’s fallacy. Can J Exp Psychol 57(2):69–75
Shannon C (1948) A mathematical theory of communication. Bell Labs Tech J 27:623–656
Solomonoff RJ (1964) A formal theory of inductive inference, part 1 and part 2. Inform Control 7:224–254
Tune GS (1964) Response preferences: a review of some relevant literature. Psychol Bull 61(4):286–302
Tversky A, Kahneman D (1971) The belief in the law of small numbers. Psychol Bull 76(2):105–110
Tyzska T, Zielonka P, Dacey R, Sawicki P (2008) Perception of randomness and predicting uncertain events. Think Reason 14(1):83–110
Volchan SB (2002) What is a random sequence? Am Math Mon 109:46–63
Wagenaar WA (1991) Randomness and randomizers: maybe the problem is not so big. J Behav Decis Mak 4(3):220–222
Acknowledgments
The author wishes to thank Lisa Kainan for making available her unpublished doctoral dissertation and Ruma Falk for her encouragement and advice.
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Aksentijevic, A. Randomness: off with its heads (and tails). Mind Soc 16, 1–15 (2017). https://doi.org/10.1007/s11299-015-0187-7
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DOI: https://doi.org/10.1007/s11299-015-0187-7