Why Do We Start to Love Things We Used to Hate? What Exposure and Choice Research Actually Shows (2026)

TL;DR. Research has documented two main ways that “I can’t stand this” turns into “I like this”. The first is repeated exposure. In Robert Zajonc’s 1968 experiments, nonsense words shown 5, 10 or 25 times were rated as having better meanings than words shown 0, 1 or 2 times, and this held for all 12 words tested. The second is choice: once we pick something, we tend to value it more. Both effects have limits. A 2017 meta-analysis of 268 curve estimates from 81 articles found that liking follows an inverted U, rising with exposure and then falling. When the main methodological flaw in choice research was corrected, the effect fell from d = 0.61 to d = 0.26, about 43% of its earlier size (CEOtudent calculation). The CEO move is to treat your current dislikes and likes as data that can change, and to ask who benefits from the change. The student move is to use exposure on purpose, planning a set number of real attempts, so that you learn to like hard things that are worth liking.

How preferences form is close to how decisions form. Related reading: the decision stack for deciding well in the AI era, how AI feeds exploit cognitive biases and why being wrong faster is a competitive advantage.

Why was this article rewritten?

The 2021 version made a sound point, that familiarity shapes preference, but went beyond its sources. It claimed you might like something you hate “within a year”, that many friendships start with serious dislike, that children are less affected than adults, and that the effect grows as exposure time increases. None of this was cited, and the last claim runs against the research below. This version is rebuilt from primary papers, and every secondary summary is labelled.

What did Zajonc’s original experiments actually show?

Zajonc’s 1968 monograph, “Attitudinal Effects of Mere Exposure”, proposed a simple hypothesis: mere repeated exposure to a stimulus is a sufficient condition for a more positive attitude toward it. “Mere” means the stimulus is only made accessible to perception. There is no reward, no argument and no association with anything pleasant.

In Experiment I, 72 participants were tested one at a time. Twelve seven-letter “Turkish” words were rotated through six exposure frequencies (0, 1, 2, 5, 10 and 25) across six replications of 12 participants each. Each word card was shown for about 2 seconds, giving 86 trials in total. Participants then guessed, on a 0 to 6 good-bad scale, whether each “Turkish adjective” meant something good or bad. More frequent words were rated as better, and this was true for each of the 12 words. Zajonc put the chance probability of that result at .00024, which matches 0.5 to the 12th power (CEOtudent check in calc.py). Experiment II used Chinese-like characters that participants only looked at, with the same result. Zajonc also noted that the rating change was a linear function of the logarithm of frequency, so each extra exposure added less than the one before.

The monograph contains a qualification that popular summaries usually leave out. Zajonc discussed a study that found no exposure effect for meaningful English words. His explanation was that adding a few more exposures to a word already seen perhaps 1,000 times should hardly matter. Exposure moves preference most where experience is thin.

How big and how reliable is the mere exposure effect?

Robert Bornstein’s 1989 meta-analysis in Psychological Bulletin covered studies from 1968 to 1987. The full text was not accessible for this update, so its findings are reported here as later peer-reviewed papers summarize them:

• Szpunar, Schellenberg and Pliner (2004) summarize Bornstein’s conclusion that the effect is stronger for complex than for simple stimuli, for exposure to several stimuli than for one stimulus repeated, for brief stimuli (for example 1 second or less for visual stimuli) with relatively few repetitions, and when there is a delay between exposure and rating. They add that increases “often plateau after about 10 exposures”.
• Mrkva and Van Boven (2020) summarize Bornstein as finding a moderate effect when many stimuli appear in the same presentation, and no significant effect when each stimulus is presented on its own.

The most recent large synthesis is Montoya, Horton, Vevea, Citkowicz and Lauber (2017), also in Psychological Bulletin. They estimated parameters from 268 curve estimates drawn from 81 articles and found “a positive slope and negative quadratic effect consistent with an inverted-U shaped curve”. Liking rises, levels off, then declines. The inverted U appeared for all visual stimuli but not for auditory stimuli, and for exposures shorter than 10 seconds and longer than 1 minute. The authors also concluded that existing models of the effect “do not adequately account for the findings”. Mrkva and Van Boven, for example, argue that exposure works partly by making a stimulus stand out from competing ones.

Does it work for music and food, the classic “I hated it at first” cases?

Music. Szpunar, Schellenberg and Pliner (2004) ran a direct test. In their second experiment, participants heard 84 classical excerpts of 15 seconds each. Different excerpts were repeated 2, 8 or 32 times. The result depended on attention:

• Focused listening (identifying the lead instrument): liking rose from baseline to 2 exposures, rose marginally from 2 to 8, then fell from 8 to 32. After 32 exposures, liking was back at baseline.
• Incidental listening (music played quietly in the unattended ear): liking rose steadily all the way to 32 exposures, with no sign of satiation.

Background repetition, the kind a playlist, a store or a feed provides, can keep pushing liking up because you are not attending closely enough to get bored.

Food. The classic study is Birch and Marlin (1982), “I don’t like it; I never tried it”, on two-year-olds. Its full text could not be accessed, so its exposure counts are not quoted here. A peer-reviewed 2014 paper by Heath, Houston-Price and Kennedy summarizes that line of research, including Birch and Marlin, Sullivan and Birch, and Wardle and colleagues: without earlier visual exposure, “children need to taste a new food between 8 and 15 times” before accepting it. The same paper notes that parents typically offer a new food only three to five times before giving up. A randomized trial by Wardle and colleagues (2003) in three London primary schools, with 49 consenting children out of 72 eligible, gave the exposure group eight daily tastes of sweet red pepper. That group’s liking (P = 0.006) and consumption (P = 0.03) rose significantly compared with a no-treatment control.

Can our own choices change what we like?

The second route comes from Leon Festinger’s cognitive dissonance theory (1957) and Jack Brehm’s 1956 free-choice experiment with household objects: after a hard choice between similar options, people rate the chosen option higher and the rejected one lower. “I like it because I chose it.”

In 2010, Chen and Risen identified a serious flaw in this design. A choice partly reveals preferences that already existed, so later rating shifts can appear even if choosing changed nothing. The field responded with better controls, and the corrected evidence is more modest:

• Izuma and colleagues (2010, PNAS) used a proper control condition and brain imaging. They found that the act of choosing changed both self-reported preference and its neural representation in the striatum.
• Izuma and Murayama (2013) meta-analyzed four studies that addressed the flaw. The combined effect was significant but small: d = 0.26 (95% CI 0.10 to 0.42), against d = 0.61 (95% CI 0.55 to 0.66) in an earlier meta-analysis that did not correct for it. Their conclusion was that choice-induced preference change “does exist” but that past studies “substantially overestimated” it.
• Sharot and colleagues (2012) tested whether the change lasts. Thirty-nine students rated 80 vacation destinations, made hypothetical choices, and rated the destinations again immediately and 2.5 to 3 years later. Choices changed preferences at both points, and only when participants made the choices themselves, not when a computer chose for them. Only 18 participants completed the follow-up (46.2% of 39, CEOtudent calculation), so the long-term finding comes from a small sample.

The numbers side by side

Table 1. Exposure counts and effects as printed in the primary studies

Study	Who / what	Exposure or design	Reported result
Zajonc 1968, Exp. I	72 participants, 12 nonsense “Turkish” words	0, 1, 2, 5, 10, 25 exposures; about 2 s each; 86 trials	More frequent words rated better, for all 12 words; p = .00024
Zajonc 1968, Exp. II	Chinese-like characters, look only	Same frequencies	Same exposure-favorability relationship
Montoya et al. 2017	Meta-analysis	268 curve estimates, 81 articles	Inverted U: positive slope, negative quadratic
Szpunar et al. 2004, Exp. 2	Classical excerpts, 15 s each	2, 8, 32 exposures; 84 excerpts	Focused: up to 8, back to baseline by 32. Incidental: rising through 32
Wardle et al. 2003	49 children, sweet red pepper	8 daily tastes over 2 weeks	Liking up vs control (P = 0.006)
Heath et al. 2014 (summary statement)	Young children, new foods	Tastes needed	8 to 15 tastes; parents usually stop after 3 to 5 offers
Izuma and Murayama 2013	Meta-analysis, 4 corrected studies	Choice, not exposure	d = 0.26 vs d = 0.61 uncorrected
Sharot et al. 2012	39 students, 80 destinations	One round of choices	Change still present 2.5 to 3 years later (n = 18)

Sources: the papers named in each row; the full list is at the end.

Table 2. CEOtudent analysis of the studies above: what the numbers mean in practice

Comparison	Recomputed figure	Practical reading
Szpunar: listening time at the peak (8 x 15 s) vs at full satiation (32 x 15 s)	2 minutes vs 8 minutes	For focused attention, a short repeated dose was enough; four times more erased the gain
Food tastes needed (8 to 15) vs offers typically made (3 to 5)	Parents who stop at 5 deliver 62.5% of the lower bound; at 3, 20% of the upper bound	Many “I hate it” verdicts are reached before the test is complete
Corrected vs uncorrected choice effect	0.26 / 0.61 = 43%; a 57% reduction	“I like it because I chose it” is real but smaller than older textbooks imply
Zajonc: all 12 words in the predicted direction	0.5^12 = 0.00024	The original effect was very consistent, but only for novel, meaningless stimuli

Is a liking shift learning, or manipulation by repetition?

This is the decision question. Exposure works whether the repetition comes from your own plan or from someone else’s ad budget. Zajonc noted in 1968 that advertising was the “foremost proponent” of the exposure hypothesis. Today the repetition engine is the recommendation feed, as we covered in how AI feeds exploit cognitive biases. The incidental-listening result above is a warning: repetition you barely notice can raise liking without the boredom that would otherwise put a ceiling on it.

Table 3. CEOtudent editorial framework: the Preference Change Audit

Run these six questions when you notice “I used to dislike this, now I like it”, or the reverse.

#	Question	Points toward learning	Points toward repetition effect
1	Who chose the exposures?	You did, on purpose	A feed, ad schedule or default did
2	Were you paying attention?	Focused engagement	Background, incidental exposure
3	Can you name what you now notice that you missed before?	Yes: a structure, a flavor, a skill	No: “it just feels familiar”
4	Did your competence change?	You can do or judge more	Nothing new is possible
5	Would the liking survive a short break?	Yes, you seek it out	It fades when the repetition stops
6	Who profits from the shift?	Mainly you (health, skill, insight)	Mainly the party that paid for the repetition

Three or more right-hand answers: treat the new preference as a repetition effect until proven otherwise, and do not let it drive a large decision yet. This mirrors the base-rate discipline in the outside view for better predictions: ask what usually happens to preferences formed this way before trusting the feeling.

The choice research adds a check: if you like something more since choosing it, discount that when deciding whether to keep a tool, job or strategy you picked yourself.

How can you deliberately learn to like something worth liking?

The student side uses the same mechanism with intent: not to like everything, but to stop dropping valuable, difficult things (dense books, a language, a vegetable, a demanding skill) before a fair test is complete.

CEOtudent editorial framework: the Acquired Taste Protocol

1. Choose by value first, liking second. Decide on the target for reasons you can state: health, career or understanding. Exposure is the method, not the reason.
2. Plan a minimum number of real attempts before judging. For food, the research above suggests 8 to 15 tastes for children. No equivalent count exists for books or skills, so set your own number in advance (for example, 10 sessions) and do not deliver a verdict before you reach it. The aim is to avoid the parent pattern of quitting after 3 to 5 tries.
3. Keep each dose short and attentive. Brief, focused exposures performed well. In the music study, 2 minutes of total focused listening was enough to raise liking.
4. Vary within the target. Bornstein’s summarized finding favors several stimuli over one stimulus repeated. Read different authors in the same field, cook the vegetable different ways, or practice the skill on different problems.
5. Space the sessions and rate after a delay. Effects were stronger with a delay between exposure and rating. Score each session from 1 to 7 the next day, not immediately afterwards.
6. Watch for the turn. If ratings rise and then fall across three sessions, you have probably reached the satiation side of the inverted U. Change the variety or take a break. Do not push more of the same.
7. Close with an audit. At the planned count, run the Preference Change Audit. If you can name something you now notice that you missed before, the taste was learned and not just installed.

Planning sheet (CEOtudent editorial heuristic, not a research finding)

Target	Unit of exposure	Planned minimum before verdict	Variety lever	Stop or pause signal
A rejected vegetable	One tasting	10	Raw, roasted, in a sauce	Three falling scores in a row
A difficult genre of books	One 20-minute session	10	Different authors, essays vs books	Dread before sessions, falling scores
A new skill (for example SQL or drawing)	One focused practice block	10	Different problem types	Scores fall while competence stalls
An unfamiliar music style	One focused listen	8	Different artists	Liking drops after repeated plays

These are planning defaults loosely drawn from the ranges above; no study has set a universal count for books or skills. Committing in advance also protects against the tired late-day “never mind” covered in decision fatigue research.

What this does not mean

• It does not mean familiarity always wins. Liking follows an inverted U. Focused overexposure brought liking back to baseline in the music study, and a snack-monotony study cited by Heath and colleagues found children’s desire for a snack they ate every day for 3 weeks declined over time.
• It does not mean exposure fixes strong dislikes. Most exposure studies use novel, neutral stimuli. Zajonc himself noted no effect for well-known words. A long-standing aversion is a different starting point from a new taste.
• It does not prove the friendship story. Nothing in these sources supports “many friendships start with serious dislike”.
• It does not mean the choice effect is large. After correction it is small (d = 0.26) and comes from a few studies with modest samples.
• It does not settle the mechanism. Treat any single-cause explanation, such as fluency, safety or salience, with caution.

Frequently asked questions

What is the mere exposure effect?
It is the tendency to like a stimulus more after being exposed to it repeatedly, with no reward or argument involved. Zajonc formalized it in 1968. A 2017 meta-analysis found it follows an inverted U rather than a straight line.

How many exposures does it take to like something?
There is no universal number. In Zajonc’s experiments, 5 to 25 exposures beat 0 to 2. Summaries of Bornstein’s meta-analysis note increases often plateau after about 10 exposures. For children and new foods, research summaries cite 8 to 15 tastes.

Can you get tired of something because you have seen it too often?
Yes. In the 2004 music study, focused listeners’ liking was highest at 8 exposures and was back at baseline by 32. Incidental listeners did not show this drop.

Do we like things more after choosing them?
Yes, but less than older studies suggested. Once the free-choice paradigm’s flaw was corrected, the pooled effect was d = 0.26. One study found the change still visible 2.5 to 3 years later in a small follow-up sample.

Is liking something because of ads a real preference?
The feeling is real, but it may be a repetition effect rather than learning. The Preference Change Audit above helps separate the two.

Sources

1. Zajonc RB. Attitudinal Effects of Mere Exposure. Journal of Personality and Social Psychology Monograph Supplement. 1968;9(2, Part 2):1-27.
2. Bornstein RF. Exposure and Affect: Overview and Meta-Analysis of Research, 1968-1987. Psychological Bulletin. 1989;106(2):265-289. Findings cited as summarized in sources 3 and 4; full text not accessed.
3. Szpunar KK, Schellenberg EG, Pliner P. Liking and Memory for Musical Stimuli as a Function of Exposure. Journal of Experimental Psychology: Learning, Memory, and Cognition. 2004;30(2):370-381.
4. Mrkva K, Van Boven L. Salience Theory of Mere Exposure: Relative Exposure Increases Liking, Extremity, and Emotional Intensity. Journal of Personality and Social Psychology. 2020 (online first, 23 January 2020).
5. Montoya RM, Horton RS, Vevea JL, Citkowicz M, Lauber EA. A Re-examination of the Mere Exposure Effect: The Influence of Repeated Exposure on Recognition, Familiarity, and Liking. Psychological Bulletin. 2017;143(5):459-498. Abstract.
6. Birch LL, Marlin DW. I Don’t Like It; I Never Tried It: Effects of Exposure on Two-Year-Old Children’s Food Preferences. Appetite. 1982;3(4):353-360. Cited as summarized in source 7; full text not accessed.
7. Heath P, Houston-Price C, Kennedy OB. Let’s Look at Leeks! Picture Books Increase Toddlers’ Willingness to Look at, Taste and Consume Unfamiliar Vegetables. Frontiers in Psychology. 2014;5:191.
8. Wardle J, Herrera ML, Cooke L, Gibson EL. Modifying Children’s Food Preferences: The Effects of Exposure and Reward on Acceptance of an Unfamiliar Vegetable. European Journal of Clinical Nutrition. 2003;57(2):341-348. Abstract.
9. Festinger L. A Theory of Cognitive Dissonance. Stanford University Press, 1957. Cited as described in sources 11 and 13.
10. Brehm JW. Post-Decision Changes in the Desirability of Choice Alternatives. Journal of Abnormal and Social Psychology. 1956;52:384-389. Cited as described in sources 11 and 13.
11. Izuma K, Murayama K. Choice-Induced Preference Change in the Free-Choice Paradigm: A Critical Methodological Review. Frontiers in Psychology. 2013;4:41.
12. Chen MK, Risen JL. How Choice Affects and Reflects Preferences: Revisiting the Free-Choice Paradigm. Journal of Personality and Social Psychology. 2010;99:573-594. Cited as described in sources 11, 13 and 14.
13. Izuma K, Matsumoto M, Murayama K, Samejima K, Sadato N, Matsumoto K. Neural Correlates of Cognitive Dissonance and Choice-Induced Preference Change. Proceedings of the National Academy of Sciences. 2010;107(51):22014-22019. Abstract.
14. Sharot T, Fleming SM, Yu X, Koster R, Dolan RJ. Is Choice-Induced Preference Change Long Lasting? Psychological Science. 2012;23(10):1123-1129.

Table 2, the Preference Change Audit, the Acquired Taste Protocol and its planning sheet are CEOtudent analyses and editorial frameworks built on the sources above; all other figures are quoted as printed. Sources read only as abstracts or through other papers are marked. Two widely repeated figures were left out because their primary texts could not be checked: the experiment count and overall effect size of Bornstein (1989), and the exposure counts of Birch and Marlin (1982).

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This content was compiled with the support of AI following in-depth research, then written and prepared for publication by the CEOtudent editorial team.

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