THINKING FAST ISN'T SIMPLE: ON THE COMPLEXITIES OF IMPLICIT COGNITION. Jan De Houwer Ghent University, Belgium

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1 THINKING FAST ISN'T SIMPLE: ON THE COMPLEXITIES OF IMPLICIT COGNITION Jan De Houwer Ghent University, Belgium

2 Since the 1970 s: Thinking & behavior does not have to be rational, systematic, conscious, controlled It can also be irrational, heuristic, unconscious, unintentional, automatic, : implicit cognition => Important message: Nobel prizes Kahneman and Thaler => But that also led to caricatures 2

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6 OVERVIEW Good that implicit cognition is recognized But complexities also need to be recognized Not just for academic but also applied reasons Complexities at the conceptual level: What is the nature of the difference? Complexities at the empirical level: Evidence for implicit cognition is not as straightforward as might seem at first sight => brief overview of (mainly) research in my lab 6

7 Recent review papers that also question dual system/process models Melnikow & Bargh (2018, TiCS): general Stephens et al. (2018, Psych Rev): decision Hommel & Wiers (2017, TiCS): action Moors et al. (2017, ER): action & emotion Kruglanski (2013, PPS): general 7

8 CONCEPTUAL COMPLEXITIES 1. Dual Systems (sets of features)? Alignment problem: => Moors & DH (2006, Psych Inq): you can cut the cake in many ways but the resulting parts do not necessarily overlap (see also Keren & Schul, 09) => So how do you assign a process to a system? 8

9 2. Dual processes (one feature)?: Moors (2016) ARoP - Conscious and unconscious processing depends on quality of representation : 2 thresholds - Quality is determined by interplay between different features (stimulus intensity and duration, repetition, goals, expectations, attention) - The picture drawn so far suggests that the factors influencing current representational quality are cumulative: If one of the factors is low, other factors may compensate so that the quality nevertheless reaches the threshold required to trigger processing (Moors, 2016, p. 274). : Malleability of automaticity => How do you assign a process to a feature? 9

10 EMPIRICAL COMPLEXITIES Debunking Simplification 1: Little evidence for 2 systems Different features do not align Debunking Simplification 2: Overestimating implicit cogn. Evidence is often weak (wishful thinking) Today: overview of recent work in LIP lab on three phenomena that are often thought to be prototypical System 1 phenomena / processes: - Implicit evaluation - Conditioning - Habits 10

11 1. Implicit evaluation: spontaneous feelings 11

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13 - OK, IAT performance is fast and relatively difficult to control but - IAT scores do not reflect unconscious attitudes: IAT scores can be predicted (Hahn et al.,14, JEP:G) - IAT scores do not depend on slowly changing associations but on current beliefs Malleability: Michael Jordan as Black person vs. Basketball player (Blair, 2001) changing recently formed implicit evaluations => 1: BOB helps old ladies, is friendly to kids, => 2: BOB is a child molester Diagnosticity matters (Ferguson et al.,17, AESP) 13

14 Changes in deep-rooted, unambiguous implicit evaluations (Van Dessel et al., 2018, SPPS) 14

15 - Approach/avoid scores depends on beliefs, not hard-wired asso (Krieglmeyer et al., 2011, JESP) 15

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17 - Priming depends on attention (Spruyt et al., 09, JML) => 2 tasks intermixed Priming of naming responses + second task *Group 1: evaluative categorization *Group 2: semantic categorization => Results: No implicit evaluation in semantic group Implicit evaluation requires attention to evaluative properties => similar results for subliminal priming (Spruyt et al., 2012, Cognition), EEG responses (Everaert et al., 2014, SCAN), automatic allocation of attention to emotional stimuli (Everaert et al., 12, C&E) and effects of other goals (Spruyt et al., 2018, Emotion) 17

18 Conclusion: Unintentional & fast stimulus evaluation depends on beliefs, attention, and goals Maybe there is truly implicit evaluation? => But where is the evidence? => Does not appear to be default Stop thinking of implicit evaluation as a simple (system 1) process (by default) 18

19 2. Conditioning 19

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21 the prevalent modern view [is] that conditioning involves the learning of relations among events [this] is not a stupid process by which the organism willy-nilly forms associations between any two stimuli that happen to co-occur. Rather, the organism is better seen as an information seeker using logical and perceptual relations among events, along with its own preconceptions, to form a sophisticated representation of its world. Indeed, in teaching undergraduates, I favor an analogy between animals showing Pavlovian conditioning and scientists identifying the cause of a phenomenon. (Rescorla, 1988, pp ) 21

22 Fear conditioning in humans CS-Shock pairing leads to fear of CS Only if - awareness of CS-shock contingency (Shanks & Lovibond, 2002, JEP:ABP) - sufficient resources (Dawson & Schell, 1985) - attention + Instructions suffice (Cook & Harris, 1937) but uncontrollable 22

23 Evaluative conditioning: Impact of pairings on liking but little evidence for simple associative processes (Corneille & Stahl, in press, PSPR) 23

24 - Few (if any) clear instances of unaware EC: contingency awareness is (almost) always necessary - Contingency awareness is the main moderator (36% of variance in meta-analysis; Hofmann et al., 10, PB) - Contingency instructions produce similar effects * on various indices of liking (Gast & DH, 2013), even implicit evaluations (IAT, AMP, priming) and automatic parameters of multinomial processing * no added value of actual pairings (Kurdi et al., 17) and in kids, bigger effects of instructions than of pairings 24

25 Approach-Avoid learning: Impact of actions on liking (operant conditioning) 25

26 - Depends on awareness / memory Van Dessel et al. (2016, PSPB): Approach-avoid learning only if contingency memory Van Dessel et al. (2016, JPSP): failure to replicate and obtain AA effects with subliminal stimuli - Evaluative learning results from mere instructions Van Dessel et al. (2015, Exp Psy): for neutral stimuli but not for racial stimuli also on implicit liking Van Dessel et al. (2016, 2017, JESP): Impact on implicit evaluations even when no impact on explicit evaluations 26

27 Instruction 1: Niffites are good or Niffites are bad Luupites are bad Luupites are good Instruction 2 Approach Niffites or Avoid Niffites Avoid Luupites Approach Luupites Test Explicit evaluation: influenced only by Instruction 1 Implicit evaluation (IAT): influenced by both instructions => both explicit and implicit depend on beliefs but differ in which beliefs are important 27

28 Conclusion: Evidence for simple conditioning is weak Maybe there are some instances of real (System 1) conditioning? => But where is the evidence? => Not the default Stop thinking of conditioning as a simple (system 1) process (by default) 28

29 3. Habits 29

30 3. Habits Hommel & Wiers (2017, TiCS): dual-route models, distinguish between one system that is responsible for actions that can be considered to be intentional while the other system is responsible for actions that can be considered to be impulsive we show that there is no evidence for intention-independent action Moors et al. (2017, ER): Standard dual-process models in the action domain postulate that stimulusdriven processes are the default. We propose an alternative dual-process model in which goaldirected processes are the default instead. 30

31 KICKING THE HABIT: WHY EVIDENCE FOR HABITS IN HUMANS MIGHT BE OVERESTIMATED (2018; MOTIVATION SCIENCE) Jan De Houwer, Ayumi Tanaka, Agnes Moors, & Helen Tibboel

32 BACKGROUND Habits as backbone of human behavior (Wood & Runger, 2016, ARP) OK in non-technical sense: frequently or automatically emitted behavior But what about habits in technical sense?: behavior that is not goal-directed (i.e., under control of antecedents but not consequences: S-R) => Note that even frequent and automatic behavior can be goal-directed (Aarts & Dijksterhuis, 2000) 32

33 Two tests of habits in the technical sense: - Outcome revaluation: behavior unaffected by changes in outcomes - Contingency degradation: behavior unaffected by changes in impact of behavior on outcome => Both tests based on null effect: problematic not so much statistically but for inferring the reason of the null effect 1. Problematic if you change outcomes other than those that determine behavior 2. Problematic if your test of changes in behavior is not sensitive enough 33

34 Our proposal: Let s use two quality criteria in research on habits - Information criterion: check for knowledge about the relevant outcomes (i.e., the outcomes that actually guide behaviour) - Sensitivity criterion: do so in a sensitive way so that you capture all traces of this relevant knowledge Empirical data: Show that one of the most cited pieces of evidence for habits in humans (de Wit et al., 07, 13) is problematic because the test does not meet the information criterion 34

35 Worthwhile to revaluate also other evidence e.g. Neal et al. (2011): Popcorn study People who often eat popcorn when watching a movie in a cinema theatre will eat popcorn even when it is stale Might eat popcorn not for taste but for complete cinema experience 35

36 IMPLICATIONS For changing seemingly automatic / system 1 behavior, not just nudging (stimulus control) and extensive retraining are possible Policy makers and researchers need to move away from the idea that changing minds to motivate individuals to resist our unhealthy environments changes behaviour it doesn t. (Marteau, 2018) Also beliefs, attention, and goals matter: fast, implicit thinking is thinking, be it thinking under suboptimal conditions ( quick-and-dirty ) => also see Lovibond (2011) in psychotherapy => Hogarth et al. (2018) in addiction research 36

37 - For predicting behavior, automatic beliefs matter => e.g., I am good vs. I want to be good (Remue et al., 2013, 2014) => De Houwer et al. (2015, Frontiers): RRT => Rothermund (e.g., Wiswede et al., 2013, SCAN) 37

38 TAKE HOME MESSAGE Implicit cognition is important But we should embrace its full complexity Thinking fast is thinking under suboptimal conditions: 1 operating principle, different operating conditions Exploit this complexity to change implicit thinking and spontaneous behavior 38

39 ONE LINERS (Virtually) all behavior is operant behavior (Skinner, 1953) => change behavior by changes consequenses (Virtually) all behavior is goal-directed (Moors et al., 2017) => change behavior by changing expectancy (beliefs) and values (goals), taking into account goalhierarchies and complexities of changing beliefs Thinking fast is also thinking => not the principle but the operating conditions matter Irrational behavior can result from a rational (reasoning-based) system => examine quick-and-dirty reasoning 39

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41 THE END 41